vivien szabo optogénétique chez la souris éveillée et ... · acknowledgements i could not have...

Thèse de doctorat de l’Université Paris Descartes

SpécialitéNeurosciences

École Doctorale n°474 Interdisciplinaire Européenne Frontières du Vivant

Préparée au Laboratoire de neurophysiologie et nouvelles microscopies

Microscopie à modulation de front d’onde

Présentée par

Vivien Szabo

Pour obtenir le grade deDocteur de l’Université Paris Descartes

Sujet de la thèse :

Optogénétique chez la souris éveillée et mobile àl’aide d’un fibroscope

Optogenetics in freely behaving mice with afiberscope

Soutenue le 19 décembre 2013

Membres du jury :

Dr. Valentina Emiliani (directrice de thèse)

Dr. Cathie Ventalon (co-directrice de thèse)

Pr. Claude Boccara (président)

Pr. Fritjof Helmchen (rapporteur)

Dr. Jason Kerr (rapporteur)

Acknowledgements

I could not have undertaken and gone through this PhD project all by myself. There-fore, there are many people I am grateful to and wish to acknowledge.

First of all, I thank Valentina Emilani for allowing me to work on a project of mypassion in an ideal environment, introducing me to the optogenetics community andgiving me the opportunity to discover how optics can apply to biology. I thank CathieVentalon for teaching me so much in optics, and spending so much time with me inexperiments and discussions. I thank Jonathan Bradley for his teaching in neurobiology,molecular biology, virology, for sharing technical experience, and for joining this project.I thank Vincent de Sars for on demand custom software development.

I thank Serge Charpak and all the members of the Neurophysiology and new mi-croscopies laboratory, especially Francesca Anselmi, Aurélien Bègue, Elke Schmidt, De-clan Lyons, Francoise Levavasseur and Christophe Tourain for technical expertise, usefuldiscussions and insights. I thank Patrice Jeguzo for manufacturing various laboratoryequipment items.

I would like to thank many members of the Brain physiology laboratory, in particularIsabel Llano for discussions and for providing transgenic mice, Ali Jalil for technical ad-vices and experimental work, Pepe Alcami for discussions and expertise. I warmly thankPhilippe Ascher, for his infinite patience, hours of discussions and invaluable advices andinsights.

I thank the members of my thesis advisory committee, Clément Léna and ClaudeBoccara, for their relevant and useful inputs to this project.

I thank the Inserm School and the Frontières du Vivant (FdV) PhD program forallowing me to undertake and see through the MD-PhD program I joined 6 years ago. Ithank the Fondation Bettencourt-Schueller for financial support.

Finally, I thank the members of my thesis committee, Claude Boccara, Jason Kerrand Fritjof Helmchen for kindly accepting to review this manuscript and attending thedefense.

Je tiens à remercier mes parents, qui ont su cultiver la curiosité et l’enthousiasmechez leurs enfants.

Je remercie ma compagne, Ombeline Hoa, de m’avoir soutenu, et de continuer à mesoutenir, tout au long de ce parcours.

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Acronyms and abbreviations

3D: three-dimensional

AP: action potential

BBB: blood-brain barrier

BR: bacteriorhosopin

ChR: channelrhodopsin

CGH: computer generated holography

D1/D2: dopamine D1/D2 receptor

DMD: digital micromirror device

cpEGFP: circularly permutated enhanced green fluorescent protein

fMRI: functional magnetic resonance imaging

FRET: Förster resonance energy transfer

GECI: genetically encoded calcium indicator

GFP: green fluorescent protein

HR: halorhodopsin

LED: light-emitting diode

MSN: medium spiny neuron

NA: numerical aperture

NpHR: Natromonas pharaonis halorhodopsin

PD: Parkinson’s disease

SIM: structured illumination microscopy

TM: transmembrane domain

VSD: voltage sensing domain

VSFP: voltage-sensitive fluorescent proteins

WD: working distance

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Résumé

Les techniques optogénétiques ont laissé entrevoir un potentiel exceptionnel dansl’étude des mécanismes gouvernant l’intégration de l’information dans le système nerveux.Afin d’établir les relations existant entre des séquences d’activité neuronale définies etle comportement, les techniques optiques doivent permettre d’appréhender des groupesde neurones avec une résolution cellulaire chez l’animal éveillé et mobile. Jusqu’alors,l’activité neuronale chez l’animal vigile non contraint n’a été contrôlée que via l’illuminationen champs large. Dans ce travail, nous démontrons une résolution proche de la celluleunique pour la photoactivation, chez l’animal éveillé et mobile, à l’aide d’un fibroscope.

Les motifs de photoactivation, produits par holographie, sont transmis jusqu’à lasouris par un guide d’image couplé à un micro-objectif. Une imagerie de fluorescencepermet de localiser les cellules d’intérêt et d’enregistrer l’activité neuronale, par épi-fluorescence, illumination structurée, ou encore microscopie confocale multi-point sansbalayage. Le fibroscope est testé chez l’animal anesthésié et chez l’animal éveillé et mo-bile, dont les interneurones de la couche moléculaire du cervelet expriment les protéinesChR2-tdTomato et GCaMP. Nous avons généré des signaux calciques somatiques enciblant les corps cellulaires avec des spots de photoactivation de 5µm de diamètre.

Chez l’animal anesthésié, nous avons démontré que la photoactivation pouvait êtreréalisée avec une résolution latérale de 10µm et une résolution axiale de 40µm, en con-sidérant la demi-largeur à mi-hauteur de la courbe de résolution. Nous avons montréqu’un ou plusieurs soma pouvaient être ciblés sélectivement. Chez l’animal éveillé etmobile, le champs de vue est resté stable au cours des acquisitions. Nous avons trouvéune résolution latérale pour la photoactivation égale à 10µm, démontrant une résolutionde photoactivation proche de la cellule unique chez l’animal vigile non contraint.

Mots-clés : photoactivation, imagerie calcique, microscopie, neurosciences, in vivo,souris éveillée et mobile

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Abstract

Optogenetics has shown great potential to study the mechanisms governing infor-mation integration in the brain. To link specific spatiotemporal activity patterns andbehaviours, optical methods should provide simultaneous access to a group of neuronswith single cell resolution in freely behaving animals. So far, however, optogenetic controlof neural activity in freely behaving rodents has been performed with widefield illumina-tion only. Here, we demonstrate photoactivation with near-cellular resolution in freelybehaving mice using a fiberscope.

Photoactivation patterns, produced with computer-generated holography, were trans-mitted to the mouse using a fiber bundle coupled to a micro-objective. Fluorescenceimaging allowed locating cells and recording neuronal activity, via either epifluorescence,structured illumination, or scanless multi-point confocal microscopy. The fiberscope wastested both in anesthetized and freely-behaving mice co-expressing ChR2-tdTomato andGCaMP proteins in cerebellar molecular layer interneurons. By targeting an interneuronsoma with a 5µm diameter photoactivation spot, we could elicit a calcium transient.

In anesthetized animals, we demonstrated that photoactivation could be performedwith 10µm and 40µm lateral and axial resolution, half-width at half maximum, respec-tively. We showed that either a single or multiple somata could be selectively targeted.In awake unrestrained animals, the field of view remained stable during our acquisitions.We found that photoactivation lateral resolution remained equal to 10µm, demonstratingphotoactivation with near-cellular resolution in freely behaving mice.

Keywords : photoactivation, calcium imaging, microscopy, neuroscience, in vivo,freely behaving mice

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Contents

I Introduction 13I. A The neural organization of behaviour . . . . . . . . . . . . . . . . . . . . 13I. B Optogenetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

I. B.1 Key features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16I. B.2 Optogenetic actuators . . . . . . . . . . . . . . . . . . . . . . . . . 17I. B.3 Microbial opsins and behaviour . . . . . . . . . . . . . . . . . . . . 23I. B.4 Optogenetic indicators . . . . . . . . . . . . . . . . . . . . . . . . 25

I. C Imaging in freely behaving rodents . . . . . . . . . . . . . . . . . . . . . 32I. C.1 Single-photon microscopy . . . . . . . . . . . . . . . . . . . . . . . 32I. C.2 Two-photon microscopy . . . . . . . . . . . . . . . . . . . . . . . . 37I. C.3 The need for further technical development... . . . . . . . . . . . . 40

I. D Motivations summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

II Experimental study : Optogenetics in living mice with a fiberscope 43II. A Experimental conditions . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

II. A.1 Fiberscope setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43II. A.2 Photoactivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48II. A.3 Fluorescence imaging . . . . . . . . . . . . . . . . . . . . . . . . . 55II. A.4 Setup transmission and power adjustment . . . . . . . . . . . . . . 61II. A.5 Biological model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64

II. B In vivo experimental results . . . . . . . . . . . . . . . . . . . . . . . . . 70II. B.1 Experiments in anesthetized mice - ChR2 and GCaMP3.3 . . . . . 70II. B.2 Experiments in anesthetized mice - ChR2 and GCaMP5-G . . . . 77II. B.3 Experiments in awake, freely behaving mice . . . . . . . . . . . . . 85II. B.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

IIIDiscussion 97III. A Optogenetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

III. A.1 Optogenetics side-effects . . . . . . . . . . . . . . . . . . . . . . . 97III. B Optogenetics in freely moving mice with a fiberscope . . . . . . . . . . . 100

III. B.1 Experimental design . . . . . . . . . . . . . . . . . . . . . . . . . . 100III. B.2 Setup development . . . . . . . . . . . . . . . . . . . . . . . . . . . 101III. B.3 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

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Chapter I

Introduction

Contents

I. A The neural organization of behaviour . . . . . . . . . . . . . . . . . . 13

I. B Optogenetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

I. B.1 Key features . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

I. B.2 Optogenetic actuators . . . . . . . . . . . . . . . . . . . . . . 17

I. B.3 Microbial opsins and behaviour . . . . . . . . . . . . . . . . . 23

I. B.4 Optogenetic indicators . . . . . . . . . . . . . . . . . . . . . . 25

I. C Imaging in freely behaving rodents . . . . . . . . . . . . . . . . . . . 32

I. C.1 Single-photon microscopy . . . . . . . . . . . . . . . . . . . . 32

I. C.2 Two-photon microscopy . . . . . . . . . . . . . . . . . . . . . 37

I. C.3 The need for further technical development... . . . . . . . . . 40

I. D Motivations summary . . . . . . . . . . . . . . . . . . . . . . . . . . 40

I. A The neural organization of behaviour

In the late 1940’s, D.O. Hebb proposed a theory for the neural organization of behaviourand cognition [Hebb, 2002]. At that time, available experimental procedures were farfrom able to confirm or infirm it. D. O. Hebb proposed two basic hypotheses. The firstone states that two connected neurons strenghten their functional connectivity whenactive together. Cellular neurobiology has (at least partly) confirmed this by describingso called Hebb’s synapses and their mechanisms. Further discussion of these phenomenais beyond the scope of this manuscript, and I will now turn to the second hypothesis.It states that although the neuron is the fundamental histological unit in the brain, thefundamental functional unit responsible for representative processes is composed of a"cell assembly". An assembly would be a functional, incidental, probabilistic cluster ofneurons. "Functional" means here that only joint activity includes cells in an assembly,physical distance in the brain or direct connections being disregarded. "Incidental"

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implies a context dependent activity, the context being here the environmental stimuliand ongoing neural processes. Finally, the "probabilistic" nature of the assembly refersto the non deterministic recruitment of neurons in the ensemble. From a defined neuronalpopulation belonging to an assembly, only a fraction of it would be effectively enrolled at agiven moment. This subpopulation would comprise the cells with the highest probabilityof recruitment based on previous learning. Therefore, an assembly might be defined bythe evoked activity in downstream units rather than by the identity of the cells it is madeof. At this point, it is important to note that a single cell can, at different times, be part ofdifferent assemblies. During a behavioural or cognitive process, several assemblies wouldbe sequentially recruited, each of them generating some activity in a subsequent neuronalensemble (inhibitory synapses were not a common idea at that time). This putativephenomenon was called a "phase-sequence", and would be responsible for associativeprocesses (such as conditioned learning). Overall, the experimental constraints to test D.O. Hebb’s second hypothesis are quite strong, as discussed in the next paragraph, suchthat it has been difficult to test it properly until now. During my PhD, the goal of mywork was to design and assess a technique able to overcome these contraints.

The different features of the cell assembly are listed again here with the aim ofdiscussing experimental constraints that they impose.

1) First of all, the functional activation of a neuronal cluster depends on the inputsit receives. Hence, a full characterization of an ensemble needs intact structures, withpreserved short and long range projections. Studies would therefore be preferentiallyundertaken using an in vivo animal model. We will focus on rodents (rats and mice) inthis manuscript, because they are the only mammal model in which genetic tools havebeen extensively developed (see Section I. B for justification of the interest of this point).Besides, nerve influx, synaptic transmission, intracellular signaling and metabolism mustbe unimpaired. This causes harsh constraints on the entire experimental procedure, sincethe use of anaesthetics can compromise results relevance by altering synaptic transmis-sion, sensory and motor integration, and behaviour [Arhem et al., 2003, Autry et al.,2011, Haider et al., 2012, Ferezou et al., 2006, Greenberg et al., 2008].

2) Second, the assembly is incidental. Since the ultimate goal is to understand how abehaviour is driven by neural activity, neuronal ensemble should be studied in a relevantcontext. Then, the animal must display a behaviour, and therefore be awake, which addsa supplementary experimental difficulty. With this in mind, two approaches have beenadopted in microscopy (the choice of microscopy is explained in Section I. B). One isto physically restrain the animal, so that the fixed brain position leaves the proceduresomehow similar to those in anaesthetized animals. The major issues I can see here are,first, that the range of accessible behaviours is limited, second, that fixing the head isstressful for the animal (in practice, repeated training sessions are needed to get theanimal habituated) and is likely to modify sensory and motor processing. In order toreproduce "normal" motor behaviours, head-fixed mice have been trained to run on aspherical treadmill [Dombeck et al., 2007]. To extend the experimental possibilities,virtual navigation in a visual environment has also been implemented [Dombeck et al.,2010]. These inventions aim at re-creating an environment necessary for behavioural

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investigations. The other approach is to let the animal freely behave, with an adaptedmicroscope mounted on its head. This promising approach, chosen in this work, isdiscussed in more details in Section I. C.

3) The third feature mentioned is the probabilistic nature of the assembly. Recallthat the cluster is functional, and therefore not necessarily anatomicaly confined. Then,the odds of detecting active cells depends directly on the number of monitored cells. Inpractice, it means that recording must be performed across "large" populations, fromtens to thousands of neurons.

From these three cell assembly features, we can already conclude that the meansof investigation must allow studies in awake, freely behaving animals, in populations ofneurons. Focusing on neuronal populations, there are at least two characteristics thatmust be emphasized. First, single neurons activity must be accessible, and distinguishedfrom that of surrounding cells. This is indeed necessary to define membership to anassembly comprising, by definition, several cells. From a technical point of view, thismeans that the system spatial resolution must be no more than a few micrometers toclearly discern somata (roughly 10µm in diameter) and ideally submicrometric to discernprocesses. Besides, activity in neurons may last for no more than a few milliseconds. Thesystem temporal resolution must be able to follow this activity. Second, since the cellassembly hypothesis must be testable, cell activity must be tunable (triggered, enhanced,suppressed) according to the experimentator needs to directly test previously identifiedputative functional ensembles. Regarding this last aspect, the recent development ofoptogenetic tools provides means for both perturbing and monitoring neuronal activ-ity. The remainder of this introduction presents these molecular tools and microscopytechniques allowing to take advantage of them. Section I. B aims to discuss the gen-eral principles of optogenetics, focusing first on optogenetic actuators (subsection I. B.2)and their usefulness to prove causal relationships between neurons population activityand specific behaviours (subsection I. B.3), and then on optogenetic indicators used torecord neuronal activity (subsection I. B.4). Section I. C specifically deals with techni-cal achievements in the relatively recent field of functional imaging in freely behavingrodents.

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I. B Optogenetics

I. B.1 Key features

Optogenetics is the field bringing together various tools allowing to use light (opto-) forfunctional biological investigations, via genetically engineered proteins (-genetics) (ref).Two categories of optogenetic tools can be distinguished, one (optogenetic actuators)dedicated to manipulation of some cellular activity by acting on a protein properties, theother (optogenetic indicators) being used to monitor cellular phenomena by recording asignal from a protein.

Part of the great interest generated by optogenetics can be explained by a few keycharacteristics of light as an investigation tool in Neuroscience. First of all, the po-tentially achievable spatial resolution can clearly be good enough (on the micrometerscale) to distinguish single somata and even thinner sub-cellular compartments such asdendrites, although this depends on the excitation system (either single- or two-photonexcitation) [Denk et al., 1990]. Second, temporal resolution can, in theory, follow fastneuronal events. In practice, although it is limited by the optical reporter and/or the exci-tation/acquisition system, technical implementations have enabled successful recordingsof functional signals from optogenetic indicators [Tian et al., 2009, Lütcke et al., 2010,Dombeck et al., 2010, Ziv et al., 2013] (see Section I. C for examples). Finally, relativelylarge field of views (in the mm2 range) provide access to large neuronal populations. Notethat light scattering in brain tissue limits imaging to superficial structures, from tens ofmicrometers depth with single-photon excitation to a few hundreds of micrometers (andup to a millimeter) with two-photon excitation [Mittmann et al., 2011].

In comparison, electrophysiological approaches benefit from excellent temporal reso-lution. However, there is a tradeoff between spatial resolution and the number of targetcells. The use of intracellular electrodes in vivo provides single neuron resolution bothfor activity manipulation and recording, but is limited to very few neurons (1 or 2, upto 4 in vitro [Ko et al., 2011]). On the other hand, extracellular recordings with elec-trode arrays allow population monitoring, but stimulating a single neuron, for example,is not an option. A final point is the potential low invasiveness of light compared tointracerebral electrodes. Indeed, shining light inside the brain can certainly heat up neu-rons and harm them at very high power densities, but is unlikely to damage histologicalstructures the way an electrode can do. As a consequence of all these characteristics,namely potential subcellular spatial resolution, submillisecond temporal resolution, ac-cess to wide areas/volumes, and minimal invasiveness, microscopy is definitely a tool ofchoice in neuroscience (see Section I. C for some key technical achievements).

Since the interest of light in functional neuroscience has been discussed, it remains todescribe how a neuron can become, somehow, photosensitive. The concept is relativelyold, and chemical tools have been successfully developed in the past [Stosiek et al., 2003].The major point of optogenetics, responsible for the main part of the enthusiasm of theNeuroscience community, is to target photosensitivity to a genetically specified cell pop-ulation. The basic idea is to express an exogeneous, genetically encoded, photosensitiveprotein. Then, involvement of defined populations in a behaviour, for example, can be

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distinctly studied, based on the cell-type. This important feature provides optogenet-ics with a great advantage over chemical indicators and electrophysiological recordings,which do not allow cell-type specific activity stimulation, inhibition or monitoring. Thislater point is crucial for deciphering the functional organization of neural networks, madeof several genetically distinct populations. Optogenetic tools provide transduced neuronswith some light-related properties, the major ones being light-dependent electrical activ-ity due to optogenetic actuator expression at the cell membrane, and activity-dependentfluorescence (excitation/emission wavelengths or intensity) owed to optogenetic indicatorexpression. Optogenetic actuators’ principle mainly relies on a light-induced conforma-tional change of the protein structure, causing a change in its properties. They canbe used to establish causal relationships between cellular activity and behaviour. It isimportant to recall that specific perturbation of neuronal activity with single neuronprecision was, so far, possible only when targeting very few neurons, using electrophysi-ological approaches or neurotransmitter photo-release. The population level was accessi-ble with non specific electrophysiological stimulation and anatomical lesions, or receptorspecific pharmacological approaches. Optogenetic actuators add the possibility to targetgenetically defined neurons, and represent a major advance to test cellular activity in-volvement in a defined behaviour. Next Subsection I. B.2 describes some of these tools,used to evoke or suppress action potentials in neurons, with particular emphasis on theChannelrhodopsin2 protein (ChR2). It is followed in Subsection I. B.3 by examplesof the use of optogenetic actuators in the field of behavioural neurophysiology. ThenSubsection I. B.4 portrays optogenetic indicators used to infer action potential firing.These are the successors of chemical indicators, developed to record activity from neu-ronal populations with single cell spatial resolution. Indeed, although these latter toolswork reasonably well and have been successfully used, cell-type specific labelling bringsmuch more valuable information on the functional organization of neural networks thatchemical indicators start being disused. The intention in this manuscript is to focus onwidely used fluorescent calcium chelator proteins, usually referred to in the littereatureas genetically encoded calcium indicators (GECI). It is worth mentioning that optimaluse of optogenetic tools is permitted by well-designed microscopes, some of them beingdescribed in section I. C.

I. B.2 Optogenetic actuators

I. B.2.1 General principles

Optogenetic actuators have been developed to evoke or suppress electrical activity inneurons [Zemelman et al., 2002, 2003, Nagel et al., 2003, Boyden et al., 2005] or mimickreceptor activation [Banghart et al., 2004, Volgraf et al., 2006]. We will focus on themost successful class, the microbial opsins used to directly depolarize cell membranesand evoke action potentials in neurons. The impact of these tools in neuroscience isso important that the pioneer researchers Ernst Bamberg, Edward Boyden, Karl Deis-seroth, Peter Hegemann and Georg Nagel, responsible for the characterization of theirarchetype, channelrhodopsin2, have been awarded the Brain Prize 2013 (also awarded

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to Gero Miesenböck for its early work on chARGe providing a solid basis for furtherdevelopment of optogenetics).

Before going into the details of the microbial opsin channelrhodopsin2 characteristics,it is worth mentioning that so called chemical optogenetics are of interest to investigateneurotransmission and plasticity. Their mechanisms rely on molecular engineering ofreceptors, for example the light-activated ionotropic glutamate receptor LiGluR [Volgrafet al., 2006] (Figure I.1). The expression system works in two steps. First, the receptoris genetically modified to present a ligand binding domain, and is expressed in trans-duced neurons, where it can even replace the wild-type protein. Second, an exogeneousphotoswitch-ligand is supplied. This small synthetic molecule comprises the ligand (anagonist, for example) and a linker (a maleimide-azobenzene-glutamate analog (MAG), forexample) which covalently binds the engineered receptor near the ligand binding domain.As a consequence, the receptor is tethered to a photoactivatable ligand. The tetheredligand position relative to the receptor depends on the ligand conformation. The receptorcan be in one of two states, deactivated when the ligand is far from its binding pocketin the receptor, or activated when it is in there. The switch between these two statesdepends on photoisomerization of the MAG linking the ligand to the receptor. In the caseof LiGluR, photoactivation is effective at 380nm, and deactivation at 500nm. This on-offsystem has been used in vitro [Szobota et al., 2007] and in vivo in zebrafish [Szobotaet al., 2007, Wyart et al., 2009], and supposedly acts similarly to endogenous receptors.However, it suffers from the mandatory exogenous supply of photoswitch-ligand. In fact,photoswitch-ligand diffusion in large volumes of intact mammalian brain tissue still hasto be demonstrated, and no application in behaving mammals has been published so far.

Figure I.1: Schematic of LiGluR principle. An agonist (orange) is tethered to the ligandbinding domain of an engineered receptor through an optical switch (MAG) (red) vialinkers (black). In the deactivated state (left) the ligand cannot reach the binding pocket.After photoisomerization, the ligand docks and stabilizes the activated state (right).From [Volgraf et al., 2006].

Besides microbial opsins and chemical optogenetic tools, a very large range of optoge-netics tools is being developed, addressing various cellular events ranging from intracel-lular signaling, phosphorylation [Wend et al., 2013] and synaptic release [Lin et al., 2013]

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to transcription and epigenetic modifications [Konermann et al., 2013]. Although suchtools are certainly promising, they are not reviewed in this manuscript. As mentionedearlier, the center of attention is on microbial opsins, taking channelrhodopsin2 as anexample.

I. B.2.2 Microbial opsins, channelrhodopsin2

Opsins are found in a wide range of organisms ranging from archaebacteria to mammals.These proteins comprise a seven-transmembrane-helix-domain (7TM) where a retinalmolecule covalently binds, forming a Schiff base 1. Opsins are divided into two groups,based on their primary sequence, type I (microbial) and type II (animal). Type I opsinsare found in archaea, eubacteria, fungi and algae, but are normally not expressed inanimals, while type II are, for example in the mammalian retina photoreceptor cells.Optogenetics takes advantage of this segregation by expressing de novo microbial opsins,for example in mammalian cells, confering them new light sensitivity. A major feature ofmicrobial opsins is that, once expressed in mammals, they bind endogenous retinal (natu-rally present) and confer light sensitivity in one step (as opposed to chemical optogenetictools).

Two classes of microbial opsins have been described: light-driven ion pumps, includ-ing the proton pumps bacteriorhodopsins (BR) and the chloride pumps halorhodopsins(HR), and the light-driven ion channels channelrhodopsins (ChR) (Figure I.2 and I.3).Both BR and HR have been succesfully used to silence mammalian neurons, via anoutward proton flux with Arch [Chow et al., 2010] and an inward chloride flux withNpHR [Zhang et al., 2007b]. Examples of their use in behavioural studies are given inSubsection I. B.3. ChR coming from the green algae C. reinhardtii, and in particularchannelrhodopsin2 (ChR2) and variants derived from mutagenesis are by far the mostwidely used optogenetic actuators. ChR2 was described in 2002 [Nagel et al., 2003] andits ability to reliably evoke action potentials in mammalian neurons has been demon-strated in 2005 [Boyden et al., 2005]. Since then, it has been extensively employed bothin vitro and in vivo (see section I. B.3).

The ChR crystal structure at 2.3 Å resolution2 revealed a 3D structure with an extra-cellular N-terminal domain, 7 transmembrane-helix domains (TM) linked by 3 intracel-lular loops (ICL1-3) and 3 extracellular loops (ECL1-3), and an intracellular C-terminaldomain [Kato et al., 2012] (Figure I.4). Interestingly, ChR was found to form dimers,confirming previous investigations [Müller et al., 2011]. Interactions between the pro-tomers occured between the N-Terminal domains, where 3 disulphide bonds formed, andbetween ECL1, TM3 and TM4 of each protomer. The 7TMs arranged in a cylindrical

1A Schiff base is a compound of general formula R1R

2C = NR

3. It forms a coordination complexinvolved in the rhodopsin photocycle.

2In [Kato et al., 2012] work, a chimaera of ChR1 and ChR2, named C1C2, was generated andcrystallized (Figure I.4). The N-terminus sequence originated from ChR1, the last two TM domainsfrom ChR2, and the C-terminus was truncated after residue 356. The native ChR2 consists of 737 aminoacids, with an intracellular C-terminus thought to be involved in protein interactions in C. reinhardtii.The C1C2 chimaera protein crystallized in the dark (closed) state. It is referred to as ChR in thismanuscript.

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b c

K+

Na+ Cl–

Blue light Yellow lightChR2 NpHR

a

p!

Figure I.2: Schematic of ChR2 (left) and NpHR (right). Following blue light illumination,ChR2 opening allows passive cations flux. Following yellow light illumination, NpHRactively pumps chloride ions. See Figure I.3 for action spectra of ChR2 and NpHR.Extracellular side is up. From [Zhang et al., 2007a]

c d

a b

325 425 525 625 725

Activatio

n

0

0.2

0.4

0.6

0.8

1.0 ChR2NpHR

Wavelength (nm)

Figure I.3: Action spectra of ChR2 (blue) and NpHR (yellow). From [Zhang et al.,2007b]

pore-like structure, where the retinal molecule placed in a hydrophobic pocket and cova-lently bound a Lysine, as in other microbial opsins. Photoactivation of the ChR allowsa change from all-trans to 11-cis retinal conformation, followed by relative movement ofthe opsin domains and opening of an electronegative pore supposedly formed by TM1,2, 3 and 7.

In its open-state, the ChR2 protein is responsible for photocurrents of a few tensof pA in Xenopus oocytes [Nagel et al., 2003]. Nagel et al. demonstrated a reversalpotential around 0 mV, a sign of passive ion conductance, and established a permeabilityfor H+, Na+, K+, and Ca2+, but not to Mg2+. Monovalent cations relative permeabilityis summarized in Table I.1. A photocycle model has been hypothesized to representChR2 activation [Nagel et al., 2003]. In this model, the channel can exist in a closed

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ba c

N

C

N domain

TM1

TM6

TM7

TM5TM2

TM4

TM3

ECL1

ECL2

ICL2

ICL3ICL1

Intracellular

90°

C domain

e

ECL3

Extracellular

ATR 90°

Figure I.4: Crystal structure of ChR. From [Kato et al., 2012].

Ion x Px/PNa

H+ 106

Na+ 1K+ 0.5± 0.3

Table I.1: Ratio permeability of the most relevant monovalent cations through ChR2 inits open-state. Note that ChR2 is also permeable to Ca2+. Adapted from [Nagel et al.,2003].

ground state. A fast (< 1ns) step following light absorption leads to an excited statefollowed by a slower reaction leading to an open state. This entire process has beenassociated with a time constant of 0.2 ms. After ChR2 opening, a dark reaction leads toa closed desensitized state with a time consant of 20 ms at intracellular pH=7.3, beforereturning to the initial closed ground state with a predicted time constant of 2 s and aneffective time constant of 60 ms, indicating that this model is too simple. More complexphotocycle models, involving several open and closed states, absorption of more than onephoton, have been considered and still need to be validated [Kato et al., 2012].

The original article reporting expression of ChR2 in neurons established its basic elec-trophysiological properties under blue light illumination (bandwidth 450-490 nm) [Boy-den et al., 2005]. First of all, ChR2 photoactivation led to a peak photocurrent of afew hundreds of pA, followed by a steady state current of a hundred of pA in culturedhippocampal neurons. A recovery time of a few seconds was necessary to reproduce thepeak current after a first activation. Then, the authors showed reliable spike generationwith a few ms (up to 10ms) latency, using either long steady illumination or trains oflight pulses of 10 or 15ms duration at up to 10Hz. Stimulation at higher frequencies wasless reliable. Finally, they confirmed that APs evoked by ChR2 photoactivation could

21

trigger synaptic transmission. The authors also stated that ChR2 expression and acti-vation did not degrade membrane resistance, resting potential, cell survival or electricaldynamic properties. Figure I.5 displays an example of evoked trains of action potentialsin cultured neurons. This work was the starting point of the rapid and prolific develop-ment of optogenetic actuators, leading to a variety of mutants, including CatCh havingenhanced Ca2+permeability [Kleinlogel et al., 2011] and C1V1 having a red-shifted actionspectrum [Yizhar et al., 2011]. The recent determination of ChR 3D structure shouldallow optimization of molecular engineering processes and provide even more powerfultools for neuronal activity manipulation. That being said, native and slightly modifiedmicrobial opsins have already been used in vivo in behavioural studies.

Three different neurons:same pulse series

1 s

60 mV

One neuron: repeated pulse seriesa

f

g h

b c

d e

Figure I.5: Action potential generation with ChR2. From [Boyden et al., 2005].

22

I. B.3 Microbial opsins and behaviour

As discussed in subsection I. B.2, microbial opsins are attractive optogenetic actuatorsdue to their relative ease of use. Indeed, expression in the desired cell-type 3 and alight source are all is needed to gain control over membrane voltage. Therefore, a greatquantity of studies have used these tools to investigate potential involvement of neuronalpopulations in specific behaviours. Since reviewing all of them would be titanic andsomehow pointless, we will only describe the different types of studies and illustratethem with a few examples.

So far, studies in freely behaving rodents have addressed the neuronal populationlevel, relying entirely on the specific expression of the optogenetic actuator in the neu-rons of interest and not on selective illumination of cellular targets. A successful protocolfor wide-field light delivery was published in 2007 [Aravanis et al., 2007]. It relied onstraightforward insertion of a thin optical fiber (200µm diameter) in the motor cortex ofrats and mice, transduced with ChR2. The optical fiber was mounted on a holder ce-mented on the skull at one end, and was coupled to a 473nm laser at the other. Figure I.6shows a picture of the so called "optical neural interface" used to photoactivate pyramidalneurons and evoke whisker deflection in vivo . Since then, this experimental approachhas been largely re-utilized, with virtually no modification except the addition of an elec-trode for extracellular recording, this combination being called an "optrode" [Gradinaruet al., 2007].

Chemicon),

anti-

cells

(a) (b)

Figure I.6: Optical fiber based in vivo photoactivation. From [Aravanis et al., 2007].

The first category of studies taking advantage of photoactivation of microbial opsinsin freely behaving rats and mice focused on identification of neuronal populations, eitherprojection neurons or interneurons, involved in cognitive, behavioural, pathological ortherapeutic processes. The neuronal population of interest is genetically targeted withan excitatory or an inhibitory opsin, so that its activity can be controlled during a be-havioural task. This way, the involvement of this population in the defined behaviour canbe assessed. For example, Gradinaru et al. investigated the neural mechanisms respon-

3Expression systems are discussed in Subsection III. A.1.1.

23

sible for symptoms improvement in a treatment of Parkinson disease (PD) by deep brainstimulation [Gradinaru et al., 2009]. Their results provided great insight into both theneuronal populations involved and their activity (stimulation versus inhibition). Sim-ilarly, Kravitz et al. studied the effects of striatal D1 and D2 medium spiny neurons(MSNs) photoactivation in a PD model [Kravitz et al., 2010]. Specific expression inone of these populations allowed to differentiate between symptoms amelioration withD1-MSNs activation and symptoms worsening with D2-MSNs activation. Other worksfocused on fear and conditioned behaviours [Ciocchi et al., 2010, Witten et al., 2010,Goshen et al., 2011]. For instance, Goshen et al. nicely investigated the role of thehippocampus (CA1), basolateral amygdala and anterior cingulate cortex in fear con-ditioning. Through optogenetic actuator manipulation, they were able to differentiatebetween different neuronal populations involved either in contextual conditioning andinitial recall, or deferred recall [Goshen et al., 2011]. The ability to transiently shapea defined cell population activity, which has been made possible by optogenetics, wascrucial to successfully complete this kind of behavioural study.

A second category of experiments addressed the temporal pattern of activity of adefined population necessary to evoke a behaviour. Photoactivation protocols were de-signed to evoke either continuous tonic or bursty phasic activity in the target neurons.Tsai, Zhang et al. demonstrated that only phasic firing of dopaminergic ventral tegmen-tal area neurons generated conditioned place preference [Tsai et al., 2009]. Ciocchi, Herryet al., showed that fear generalization depended on firing temporal patterns in centralamygdala neuron subpopulations [Ciocchi et al., 2010].

Finally, Huber et al. used a different approach to look into neuronal activity syn-chronicity. Instead of using an implanted optical fiber, they delivered light with a LEDplaced at the surface of the barrel cortex [Huber et al., 2008]. Freely moving mice weretrained to detect layer 2/3 pyramidal neurons photoactivation. The authors’ results sug-gest that successful detection was performed when 1) as few as about 300 neurons fireda single AP together, and 2) about 60 neurons fired 5 APs synchronously. Then, sparseactivity in a limited number of cortical cells would be enough to drive learning, decisionmaking and behaviour.

Interesting as they are, all these studies were about entire cell populations. They arevery informative at the mesoscopic scale, and allow to establish the genetic identity andpattern of activity of neurons involved in a causal relationship with a characterized be-haviour. However, the experimental approach prevents investigation of the cell assembly,since single neurons cannot be selectively activated 4. That is why innovative technolo-

4Three publications reported implementations for spatially resolved in vivo photoactivation in anaes-thetized mice. Dhawale et al. used a digital micromirror device to target single glomeruli in the olfactorybulb [Dhawale et al., 2010], and Wilson et al. focused a laser beam to be even more selective [Wilsonet al., 2012]. However, these approaches necessitate a restrained, head-fixed animal. Alternatively,Hayashi et al. developed a fiber bundle-based probe for targeted photoactivation [Hayashi et al., 2012].A laser beam was scanned at the bundle entrance so that ChR2 expressing neurons were excited inanaesthetized mice. An electrode array was used to record neuronal activity. The main limitations werethe absence of objective, limiting targeted photoactivation to the structures at the fiber bundle tip, andthe inability to target several structures simultaneously. To our knowledge, this system has not been

24

gies allowing photoactivation in freely behaving mice with good spatial resolution areneeded.

I. B.4 Optogenetic indicators

I. B.4.1 Generalities

Optogenetic indicators are genetically encoded sensors of "cellular activity". As cellularactivity is not by any way a unique entity, a multitude of sensors have been developed todetect gene expression, intracellular signaling pathways activation, membrane potentialchanges, and so on. The development of optogenetic indicators started to grow whenthe crystal structure of the jellyfish Aequorius victoria green fluorescent protein (GFP)was determined in 1996 [Ormö et al., 1996] (Figure I.7)5. GFP found so many uses inbiology that Osamu Shimomura, Martin Chalfie and Roger Tsien were awarded the 2008Nobel Prize in Chemistry for its discovery and development. In particular, GFP can befused to another protein. Then, this tagged protein can be detected by GFP fluorescencecollection or imaged in living cells. Optogenetic indicators are often based on this ap-proach, using a judiciously chosen tagged protein playing the role of the sensor. Försterresonance energy transfer (FRET) based indicators and single fluorophore indicators arebriefly described in following paragraphs.

Crystal Structure of the Aequorea victoriaGreen Fluorescent Protein

Mats Ormo, Andrew B. Cubitt, Karen Kallio, Larry A. Gross,Roger Y. Tsien,* S. James Remingtont

The green fluorescent protein (GFP) from the Pacific Northwest jellyfish Aequorea victoriahas generated intense interest as a marker for gene expression and localization of geneproducts. The chromophore, resulting from the spontaneous cyclization and oxidationof the sequence -Ser65 (or Thr65)-Tyr66-Gly67-, requires the native protein fold for bothformation and fluorescence emission. The structure of Thr65 GFP has been determinedat 1.9 angstrom resolution. The protein fold consists of an 11-stranded barrel with a

coaxial helix, with the chromophore forming from the central helix. Directed mutagenesisof one residue adjacent to the chromophore, Thr203, to Tyr or His results in significantlyred-shifted excitation and emission maxima.

Although the GFP of the Pacific North-west jellyfish Aequoria victoria was discov-ered some time ago (1), the cloning (2) andheterologous expression (3) of its cDNAwere the crucial steps that triggered thewidespread and growing use of GFP as areporter for gene expression and proteinlocalization in a broad variety of organisms(4, 5). Wild-type GFP is a stable, proteoly-sis-resistant single chain of 238 residues andhas two absorption maxima at about 395and 475 nm. The relative amplitudes ofthese two peaks are sensitive to environ-mental factors (6) and illumination history(4), presumably reflecting two or moreground states. Excitation at the primaryabsorption peak of 395 nm yields an emis-sion maximum at 508 nm with a quantumyield of 0.72 to 0.85 (1, 4-6). The fluoro-phore results from the autocatalytic cycliza-tion of the polypeptide backbone betweenresidues Ser65 and Gly67 and oxidation ofthe ox-3 bond of Tyr66 (4, 7, 8). Mutation ofSer65 to Thr (S65T) (9) simplifies the ex-citation spectrum to a single peak at 488nm of enhanced amplitude (10), which nolonger shows signs of conformational iso-mers (4). As a step in understanding theseproperties, and to aid in the tailoring ofGFPs with altered characteristics, we havedetermined the three-dimensional structureat 1.9 A resolution of the S65T mutant (10)of A. victoria GFP (11).

The structure of GFP was determined by

M. Ormo, K. Kallio, S. J. Remington, Institute of MolecularBiology and Department of Physics, University of Oregon,Eugene, OR 97403-1226, USA.A. B. Cubitt, Aurora Biosciences, 11149 North TorreyPines Road, La Jolla, CA 92037, USA.L. A. Gross and R. Y. Tsien, Department of Pharmacolo-gy and Howard Hughes Medical Institute 0647, Universityof California, San Diego, La Jolla, CA 92093-0647, USA.

*To whom requests for mutants should be addressed.Fax: (619) 534-5270.tTo whom correspondence regarding crystallographyshould be addressed. E-mail: [email protected]

multiple isomorphous replacement and anom-alous scattering (1 1 ) (Table 1), solvent flat-tening, phase combination, and crystallo-graphic refinement. The most distinctive fea-ture of the fold of GFP is an 11-stranded 1barrel wrapped around a single central helix(Fig. 1, A and B), where each strand consistsof approximately 9 to 13 residues. The barrelforms a nearly perfect cylinder 42 A long and24 A in diameter. The NH2-terminal half ofthe polypeptide comprises three antiparallelstrands, the central helix, and then anotherthree antiparallel strands, the third of which(residues 118 to 123) is parallel to the NH2-terminal strand (residues 11 to 23). Thepolypeptide backbone then crosses the "bot-tom" of the molecule to form the second halfof the barrel in a five-strand Greek key motif.The top end of the cylinder is capped by threeshort, distorted helical segments, and one

short, very distorted helical segment caps thebottom of the cylinder. The main chain hy-drogen bonding lacing the surface of the cyl-inder likely accounts for the unusual stabilityof the protein toward denaturation and pro-teolysis. There are no large segments of thepolypeptide that could be excised while pre-serving the intactness of the shell around thechromophore. Thus, it would seem difficult tore-engineer GFP to reduce its molecular size(12) by a large percentage.

The p-hydroxybenzylideneimidazolidinonechromophore (7) is completely protectedfrom bulk solvent and is centrally located inthe molecule. The total and presumably rigidencapsulation is probably responsible for thesmall Stokes' shift (that is, wavelength differ-ence between excitation and emission maxi-ma), high quantum yield of fluorescence, in-ability of 02 to quench the excited state (13),and resistance of the chromophore to titrationof the external pH (6). It also allows one torationalize why fluorophore formation shouldbe a spontaneous intramolecular process (8),because it is difficult to imagine how an en-zyme could gain access to the substrate. Theplane of the chromophore is roughly perpen-dicular (600) to the symmetry axis of thesurrounding barrel. One side of the chro-mophore faces an unexpectedly large cavitythat occupies a volume of -135 A3 (14). Thecavity does not open out to bulk solvent. Fourwater molecules are located in the cavity,forming a chain of hydrogen bonds linkingthe buried side chains of Glu222 and Gln69.Unless occupied, such a large cavity would beexpected to destabilize the protein by severalkilocalories per mole ( 15). Part of the volumeof the cavity might be the consequence of thecompaction resulting from cyclization and de-

A

Fig. 1. (A) Schematic drawing of the backbone of GFP produced by the program MOLSCRIPT (32). Thechromophore is shown as a ball and stick model. (B) Schematic drawing of the overall fold of GFP. Approx-imate residue numbers mark the beginning and ending of the secondary structure elements. N, NH2-terminus; C, COOH-terminus.

SCIENCE * VOL. 273 * 6 SEPTEMBER 1996

FAMEMM FAi fleg 151 .'r w I., I!k....4.,..,4,.RO.4.........,.,,Q.§ 'p, .. .,r,i. 4,,, WMIVWM.!u 0H. .-- K,w,.ill ..- lk.R!M

1392

Do

wn

loa

de

d f

rom

Figure I.7: Schematics of the GFP (S65T) backbone and fold. Arrows represent β-strandsand cylinders helices. From [Ormö et al., 1996].

used in awake animals.5Osamu Shimomura played a key role in GFP discovery in 1962, and Martin Chalfie demonstrated

its use in detection of gene expression in 1992. The determination of its 3D structure in 1996 allowedmolecular engineering towards optimization of the protein fluorescence properties and fusion to otherproteins to "tag" them in living cells. Roger Tsien role in this development was of first importance.

25

The GFP protein6 is composed of a single chain of 238 amino acid residues, arrangedin a cylindrical barrel containing the chromophore (Figure I.7). The wall of the barrelconsists of 11 β-strands, capped by three helical segments at the top and one at thebottom. Protected from solvent and proteolysis, the inner helix is buried inside themolecule, where it forms the chromophore. As displayed in Figure I.8, peak fluores-cence excitation is around 488nm, and fluorescence emission is maximum around 509nm.After GFP(S65T) crystal structure had been determined, a great quantity of mutantswere developed [Cubitt et al., 1995], with the aim of providing a wide variety of fluores-cence proteins covering the entire colour spectrum. Then, red, orange, yellow, green andblue fluorescent proteins were soon available [Shaner et al., 2004, 2005], and have beencombined to tag simultaneously different proteins or to perform FRET measurements.

Figure I.8: Fluorescence excitation and emission spectra of wild-type GFP (- - -), S65A(- ·· -), S65C (– –) and S65t (—) mutants. From [Heim et al., 1995].

FRET is a quantum mechanism describing non radiative energy transfert between twofluorophores. When one of the two fluorophores, the donor, is excited, FRET results influorescence emission from the second one, the acceptor. Briefly, FRET efficiency dependson the overlap between the donor emission and the acceptor excitation spectra (the donorenergy must roughly correspond to the energy needed to excite the acceptor), and thedistance7 and relative orientation of the two fluorophores. FRET-based indicators usea sensor protein that modifies the distance (and orientation) of two fused fluorophores

6The wild-type GFP displays two absorption maxima at 395 and 475nm. GFP mutants (such asGFP(S65T)) show a simplified excitation spectrum with a single peak at 488nm.

7FRET efficiency is a function of 1

r6, where r is the distance between the donor and the acceptor.

26

depending on a sensed parameter [Tsien, 2009]. A change in this parameter leads toa change in FRET efficiency, and therefore a change in the FRET signal processed asthe FRET ratio acceptor fluorescence

donor fluorescence. For example, a FRET-based indicator making use

of the calcium chelator calmodulin (CaM) has been developed to estimate intracellularCa2+concentration changes [Miyawaki et al., 1997] (Figure I.9). When the CaM-derivedpart of the protein is Ca2+free, the two fluorophores are too far for FRET to occur (a fewÅ). Then, fluorescence signal from the donor only is recorded. Following Ca2+chelation,CaM binds the M13 peptide, derived from myosin light chain kinase, which brings thedonor close enough to the acceptor for FRET to happen. The resulting signals area decrease in the donor fluorescence (since the energy is no more lost as photons buttransfered to the acceptor) and an increase in the acceptor fluorescence emission, resultingin an increase in FRET ratio.

Figure I.9: Scheme of a FRET-based calcium indicator. The calmodulin (CaM) domainand M13 CaM-binding peptide act as a Ca2+sensor. When it chelates Ca2+, CaM binds toM13 and the two fluorescent proteins come closer to each other, resulting in an increasedFRET ratio. From [Miyawaki et al., 1997].

Besides FRET-based indicators, single fluorophore indicators have also been devel-oped. An example is the GCaMP protein and its variants, used to monitor intracellularCa2+concentration changes. First reported in 2001 [Nakai et al., 2001], the GCaMP pro-tein is derived from a circularly permutated enhanced GFP (cpEGFP) fused to the M13peptide at its N-terminus and to the CaM at its C-terminus (Figure I.10). Ca2+chelationinduces a conformational change via interaction between CaM and M13. A subsequentconformational change in cpEFGP results in fluorescence intensity increase.

Optogenetic indicators are widely used in cellular biology, for instance to report geneexpression, to follow protein intracellular and extracellular trafficking, membrane re-ceptor oligomerization [Maurel et al., 2008] and activation [Lohse et al., 2007], enzymeactivity [Ouyang et al., 2010], intracellular signaling pathways (cAMP) [Lohse et al.,2007], and so on. Most of these signaling and metabolism reporters are reviewed byTantama et al. [Tantama et al., 2012]. For the study of neuronal ensembles, two classes

27

Figure I.10: Scheme of GCaMP, a single fluorophore calcium indicator. The calmodulin(CaM) domain and M13 CaM-binding peptide act as a Ca2+sensor, as in the FRET-basedindicator shown in Figure I.9. When it chelates Ca2+, CaM binds to M13, inducing aconformational change in cpEGFP resulting in fluorescence increase. From [Nakai et al.,2001].

of indicators are of particular interest, membrane voltage and calcium indicators [Man-cuso et al., 2011]. Membrane voltage indicators, often referred to as voltage-sensitivefluorescent proteins (VSFP), are mainly FRET-based sensors, with the exception of thearchaerhodopsin, a microbial opsin [Kralj et al., 2012]. FRET-based VSFP comprise avoltage-sensing domain (VSD) fused to two fluorophores [Akemann et al., 2012] (FigureI.11). The VSD is inserted into the cytoplasmic membrane, its conformation dependson the transmembrane voltage so that voltage variations are detected as changes inFRET ratio. The main limitations of VSFP are on one hand the increased membranecapacitance, and on the other hand the impossibility to increase fluorescence signal byincreasing protein expression level. Indeed, membrane insertion and capacitance modifi-cation set an upper limit to protein expression, impairing signal-to-noise-ratio. Recently,archaerhodopsin has been demonstrated to reliably report membrane voltage in culturedneurons [Kralj et al., 2012, Gong et al., 2013]. It is possible that microbial opsins, besidesbeing optogenetic actuators of choice, also represent the future of VSFP. In any case, al-though optogenetic voltage indicators allow direct reading of membrane potential, whichis the main information needed in these studies, they do not yet display sufficient signalto noise ratio for in vivo exploration of the cell assembly. Therefore, most studies makeuse of calcium indicators.

I. B.4.2 Genetically encoded calcium indicators

Optogenetic calcium indicators, called genetically encoded calcium indicators (GECIs),are used in neuroscience as indirect sensors of action potentials (AP). Indeed, AP firingleads to cytosolic Ca2+increase by various mechanisms, such as activation of voltage-gatedcalcium channels or calcium-induced calcium-release. Then, fluorescent Ca2+chelators,which fluorescence intensity depends on ion chelation, have been widely used to inferneuronal electrical activity. Initially, synthetic chemical indicators were successfully de-

28

Figure I.11: Scheme of the VSFP Butterfly. The VSD is composed of 4TM inserted inthe plasmic membrane (PM). The two fluorophores mCitrine (the donor) and mKate2(the acceptor) are fused to the intracellular N and C-terminus domains. Changes intransmembrane voltage induce conformational changes in the VSD, detected as FRETratio changes. From [Akemann et al., 2012].

veloped and used, both in vitro and in vivo . However, the advent and importantdevelopement of GECIs are making chemical indicators less and less interesting in be-havioural neuroscience [Mancuso et al., 2011, Chen et al., 2013b]. I will focus on theGCaMP protein (Figure I.10), because of its broad use in the neuroscience communityand in this work in particular.

The first GCaMP protein was reported in 2001 [Nakai et al., 2001]. The authorsmeasured its excitation and emission spectra, which peaked around 490 and 510nm re-spectively, similarly to EGFP (Figure I.12). Apparent dissociation constant Kd wasestimated around 230nM. The association time constant varied between 230ms at 0.2µMCa2+and 2.5ms at 1µM Ca2+. The dissociation time constant was independent fromCa2+concentration and found to be τoff ≈ 200ms. All these characteristics were intheory compatible with intracellular Ca2+monitoring in excitable cells. However, smallfluorescence increase upon Ca2+binding prevented the use of this first GCaMP in awakerodent.

Until now, 6 GCaMP variants have been engineered, and several slightly differentversions of each of them exist. The latest one, GCaMP6, is surpassing the gold-standardchemical indicator OGB1 [Chen et al., 2013b]. Until then, OGB1 displayed the high-est fluorescence increase and sensitivity, and the fastest kinetics. It was therefore theCa2+indicator of predilection to detect small, rapid Ca2+events, i.e. single APs. Asillustrated in Figure I.13, GECI have started to catch up with chemical indicators. In-deed, GCaMP6f displayed almost 20% ∆F/F increase in response to a single AP, whenrecorded with a two-photon laser scanning microscope in the neocortex of anaesthetizedmice [Chen et al., 2013b]. In these conditions, the measured rise and decay times wereτpeak ≈ 45 ms and τ1/2 ≈ 140 ms respectively. In practice, GCaMP6 seemed to reliablyreport AP firing, with single spike resolution, in single neurons of anaesthetized mice(Figure I.14).

29

A B

Figure I.12: GCaMP excitation and emission spectra, in the presence of 1mM Ca2+or5mM ethyleneglycol tetracetic acid (EGTA), a Ca2+chelator. From [Nakai et al., 2001].

0 1 2 3

0

5

b

0

0.3

1 action potential

10 actionpotentials

5G

OGB1

6f6m6s

GCaMP3

ΔF/F

0ΔF/F

0

Time (s)

Figure I.13: Various calcium indicators fluorescence response averaged across multiplecultured neurons for GCaMP3, 5G, 6f, 6m,6s, and OGB1-AM. Top, fluorescence changein response to 1 AP; bottom, 10APs. In the present work, GCaMP3 and GCaMP5-Gwere used. Note that they are not good candidates for single AP detection, but readilyreport 10 APs. From [Chen et al., 2013b].

Optical recording of neuronal populations can then be considered for investigatingthe cell assembly. Unlike photoactivation, in vivo functional microscopy benefits from

30

6s

6f

100%

20%

200 ms

* 1 action potential events

b

* * * * * ***

5 s

ca

* *2 * * * * * * * * *6 22 2

2 2 4 5 2 3 3

10 μm

500 ms

25%* *

* ***

Figure I.14: GCaMP6 AP detection in the visual cortex of anaesthetized mice. APswere evoked by visual stimulus. a. Simultaneous electrophysiological recording in thecell-attached configuration and two-photon fluorescence imaging in a GCaMP6s (top)and GCaMP6f (bottom) expressing neuron (left inset. neuron with the pipette schemat-ically indicated). Single APs are indicated by asterisks, the number of spikes for eachburst is indicated below the trace. b. Enlarged view of bursts of APs squared in a. c.Fluorescence change in response to a single AP. Top, GCaMP6s; bottom, GCaMP6f.From [Chen et al., 2013b].

a few decades of technical developments. Optical monitoring of neuronal activity wasalready demonstrated in the early 1980’s [Orbach and Cohen, 1983, Orbach et al., 1985],and that field kept growing until now. Because of the various technical approachesimplemented, functional fluorescence imaging in freely behaving rodent deserves a fullydedicated section (section I. C).

31

I. C Imaging in freely behaving rodents

The two general approaches used in microscopy to study the cell assembly in rodents,based either on head-restrained or freely behaving animals, have been presented in Sec-tion I. A. Using awake, head-restrained animals certainly has the great advantage ofbeing compatible with regular upright microscopes. Thus, optical implementations andcoupling to electrophysiological recording are significantly easier than with the otheroption, since they are similar to those for experiments in anaesthetized animals. How-ever, with the development of optogenetic tools, electrophysiological recordings probablywon’t be absolutely necessary in the near future (see Section I. B). Besides, access to nor-mal behaviour of the studied animal might be of importance to ensure that the observedmechanisms are relevant in physiology; the range of accessible behaviour in restrained an-imals might be limited. The second approach, implementation of microscopy techniquesin freely moving rodents, is then justified by the need for physiological sensory-motorprocessing and normal environment exploration. This section focuses on this secondstrategy, that we consider to be the most promising for exploration of neural mecha-nisms underlying behaviour.

Two different classes of techniques, single-photon and two-photon fluorescence mi-croscopy, arise from the fluorescence excitation mechanism.

I. C.1 Single-photon microscopy

Single-photon microscopy is by far easier to implement than two-photon microscopy.Indeed, it only requires a conventional light source, such as a lamp, a LED, or a laser, toexcite the fluorophore, and a detector to record fluorescence. Two strategies have beendeveloped for single-photon functional imaging in freely behaving rodents. The first oneis to design miniaturized, compact microscopes integrating both the light source and thedetector, the device being light enough to be carried by the animal [Murari et al., 2010,Ghosh et al., 2011, Ziv et al., 2013]. The second one is to make use of a fiber bundle,relaying excitation and fluorescence light between the animal and the light source anddetector; this implementation is called a fiberscope in this manuscript [Ferezou et al.,2006, 2007, Murayama et al., 2007, Murayama and Larkum, 2009b,a, Flusberg et al.,2008].

A good example of an integrated microscope is the one reported by Gosh et al. in2011 [Ghosh et al., 2011] (Figure I.15). The whole device was about 8.4 mm × 13mm × 22 mm and weighted 1.9 g. In this system, optimized for OGB-1 and GCaMPimaging, illumination was ensured by a small blue LED (470nm central peak) locatedon a 6mm × 6 mm printed circuit board. A lens collected excitation light, which passedthrough an excitation filter (480/40nm bandpass filter) and was deflected towards theobjective with a dichroic beamsplitter. A 2 mm diameter GRIN objective (0.45 numericalaperture (NA), GRINTech) was used to focus illumination light onto the sample andcollect fluorescence signal. Emitted fluorescence passed through the dichroic mirror andan emission filter (535/50nm bandpass filter) before being focused by a doublet lens ontoa CMOS sensor. The 5.8 mm × 5.6 mm camera chip had 640 × 480 pixels of 5.6 × 5.6

32

µm2 dimensions. Adjustement of the sensor position allowed choosing the plane of focus.Depending on the focal position, the magnification ranged from 4.5× to 5.5×, the workingdistance from 150 to 200µm and the field of view area from 650 × 490 µm2 to 800 × 600µm2. Although the estimated lateral spatial resolution was 1.2 µm on-axis and 1.6 µm atthe field of view periphery, the CMOS pixel size limited it to 2.5-2.8 µm, still sufficient forsomata imaging. In addition to acute experiments, this device could be adapted for time-lapse imaging [Ziv et al., 2013] via implantation of a guide tube in which the objectivewas chronically placed. The microscope body could then be attached and detached froma cemented head-plate, while keeping the same imaged area. This integrated microscopewas used in freely behaving mice and allowed acute recording of microcirculation (100Hzfull-frame acquisition rate) [Ghosh et al., 2011] and Purkinje cells activity (36 Hz) [Ghoshet al., 2011], and chronic Ca2+imaging in hippocampus pyramidal cells (20Hz) [Ziv et al.,2013]. The main advantage of this implementation is its ease of use. Once the microscopebody has ben built, it necessitates no optical alignment. During an experimental session,the animal is only tethered via a floppy cable which should not apply much mechanicalstress; all the optics move with the animal so that there is no rotation of the field of view(see next paragraphs) alleviating post-processing. Movement of the field of view wasas small as about 1 µm. Finally, chronic experimentation is straightforward. However,these features have been gained at the expense of extremely simplified optics. Imaging isrestricted to epifluorescence, and the microscope cannot provide any optical sectioning. Inthese conditions, functional imaging of a layer of fluorescent neurons like CA1 pyramidalcells is just fine, but might be impaired by out-of-focus fluorescence in a structure with3D neuronal arrangement. Besides, adding a second illumination pathway or/and lightsculpting technique for targeted photoactivation would be hard to implement. For thesereasons, the fiberscope approach has been preferred in this work.

Several fiberscopes have been developed to perform functional imaging in freely mov-ing rodents. The one reported by Ferezou et al. in 2006 [Ferezou et al., 2006] is illustratedin Figure I.16. The device was tuned for voltage sensitive dye imaging. It made use ofa 50 cm long fiber bundle of 3 × 3 mm section, composed of a layout of 6 × 6 smallerbundles of 50 cores each, yielding a 600 × 600 cores fiber bundle. Each core has a di-ameter of 8 µm and a NA of 0.6. The fiber bundle tip was directly placed on the brain,without using an objective, so that the focal plane was at the bundle end. The authorsimaged cells located a hundred micrometers from the bundle tip, hence out of focus. Asa consequence, only blurred images were acquired. Illumination and fluorescence lightwere both transmitted from the light source and detector, respectively, to the samplethrough the fiber bundle. A halogen lamp was coupled to the fiber bundle with a lensfor sample illumination at 630 nm. Fluorescence was collected and transmitted via thesame optical pathway, passed through a dichroic mirror and was imaged on a camera.To perform experiments in awake behaving mice, the fiberscope tip was cemented to anU-shaped aluminum plate previously fixed on the skull. During experimentation, theanimal behaviour was recorded on a camera. Using this strategy, the authors comparedsomatosensory cortex activity in anaesthetized and awake mice, by recording membranepotential variations at 500 Hz. However, the relatively low lateral spatial resolution,

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Figure I.15: Schematic of single-photon integrated microscope. The illumination pathwaycomprises a LED, a collector lens, an excitation filter and a dichroic mirror. Illuminationlight is coupled to the sample with an objective. Fluorescence emitted at the sampleis collected by the objective, transmitted through the dichroic mirror and an emissionfilter, and imaged on a CMOS sensor via a doublet lens. From [Ghosh et al., 2011].

which did not allow single cell imaging, the absence of objective and incompatibilitywith chronic experiments surely limited this fiberscope applications.

Then, other fiberscope implementations, such as those reported by Murayama et al.in 2007 [Murayama et al., 2007] and Flusberg et al. in 2008 [Flusberg et al., 2008],included a miniaturized objective. Murayama et al. proposed two different approachesof fluorescence imaging (Figure I.17). The first one is based on a single-fiber bundle forexcitation and fluorescence light transmission, similar to the system presented by Ferezouet al., but making use of a small objective and a miniature prism. The second one includesa fiber bundle and an objective for imaging, and a single core optical fiber for excitation.In both cases, a xenon lamp was used for fluorescence excitation, coupled to either thefiber bundle or the single fiber with a lens and an objective (6.3× or 10× respectively).Fluorescence was collected with the miniaturized objective, transmitted through the fiberbundle, and focused on a CCD camera with a microscope objective (6.3×) and a tubelens. The single-fiber bundle based system comprised a 2 meters long, 0.68mm diameterfiber bundle consisting of 17,000 cores of 2.5 µm diameter and 0.35 NA (Figure I.17a).The fiber bundle imaging area had a diameter of 0.54 mm, and the fiber bundle distaltip was coupled to a prism-lens assembly forming a periscope. A GRIN-lens (GrinTech)of 0.5 mm diameter and 0.5 NA was glued to a right angled prism of dimensions 0.5× 0.5 × 0.5 mm (GrinTech). The resulting working distance (WD) was 100 µm. The0.73× magnification yielded a field of view of 685 µm diameter. The prismatic part of theperiscope was inserted inside the brain, providing a lateral view of the apical dendritesof pyramidal neurons in this case. In the second approach, the authors used a 2-meterlong, 0.96 mm outer diameter fiber bundle, composed of 30,000 fiber cores. The distalend of the bundle was connected to a 4.4× miniaturized objectif of 300µm WD, made

34

Figure I.16: Schematic of single-photon fiberscope setup, with no objective. A fiberbundle transmits illumination light and fluorescence, the latter being imaged on a camera.The animal evolves in a behaviour chamber illuminated with an infrared LED. Animalbehaviour is recorded on a camera. VSD: voltage sensitive dye. From [Ferezou et al.,2006].

of two GRIN lenses (GrinTech) of respective length 2 mm and 11.12mm, diameter 1mm for both and NA 0.5 and 0.11; the resulting field of view was 155 µm. Illuminationwas performed using a single core optical fiber of 440 µm diameter (470 µm includingcladding) and 0.22 NA, with either one of the two following possibilities. One option wasto glue a prism at the distal end of the single core fiber, so that insertion of this prisminside the brain would result in lateral illumination of the sample while the objectivewould provide a top-down view (Figure I.17b). The second option was to keep the singlecore fiber at the brain surface, to keep the brain undamaged (Figure I.17c).

In order to perform experiments in freely moving rats, Murayama et al. designed atwo-component periscope holder. A drilled base plate was anchored with three screwsand cemented to the skull (Figure I.18), centered on a craniotomy. A hollow tube-likepiece was then cemented on the base, and the fiberscope was inserted through it insidethe brain, and fixed with a screw. The authors used this strategy to record dendriticCa2+dynamics in awake behaving rats. The main advantage of both the periscope and the

35

Figure I.17: Schematics of single-photon fiberscope setups using a periscope. From [Mu-rayama et al., 2007].

two-fiber based fiberscopes is the reduced out-of-focus background fluorescence. Indeed,detection of the fluorescence resulting from side-illumination is confined to a small sliceof excited fluorophores, so that there is no signal from deeper layers. In the case ofMurayama et al., this was critical to ensure that Ca2+signals originated from apicaldendrites, and not from somata located below. However, physical insertion of the prism isrequired, resulting in damages of unknown consequences near the explored area, althoughthe authors did not see obvious effects on Ca2+signals (the third, less invasive option,with side illumination without prism insertion, was not tested in vivo ). The periscopehad the advantage of providing information on the Ca2+signal depth in the corticalcolumn, which can be of interest depending on the biological question. All in all, theseapproaches allowed to resolve Ca2+events in pyramidal cell dendrites, but suffered fromlack of optical sectioning, somehow compensated in the case of side-illumination.

Flusberg et al. [Flusberg et al., 2008] used a very similar approach in their fiberscopeimplementation. A 1.5 meter long fiber bundle transmitted excitation and emission lightthrough its 30,000 fiber cores of 2.2 µm diameter. The imaging area was 0.72 mm diam-eter, the inter-core distance was 3.7 µm. Because displacement of freely moving animalsare likely to coil the fiber, the proximal end of the bundle was fixed in a commutator torelieve torsional strength. A mercury lamp was used for illumination, and a EM-CCDdetected fluorescence signal. A miniaturized objective was mounted at the distal tip ofthe fiber bundle. It was made of a 2 mm diameter spherical lens, a 2 mm GRIN lens, and

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Figure I.18: Schematic of a periscope holder. From [Murayama et al., 2007].

a 1 mm GRIN lens objective of 0.47 NA. The second lens position could be controlledby a motor, allowing focus adjustment over 110 µm in the sample (Figure I.19). The mi-croscope magnification ranged, depending on focus position, between 1.9-2.7×, the fieldof view was 240-370 µm and the working distance 300-400 µm. The fiberscope lateralresolution was 2.8-3.9 µm, limited by inter-core distance and microscope magnification.The microscope was mounted either on the skull or a metal head plate. It weighed 1.8g including adhesive and head plate. The focusing motor added 1.7 g to the device,and was usually used in anesthetized mice only. This fiberscope was used to investigateneocortex and CA1 hippocampus microcirculation, and Purkinje’s cells Ca2+dynamicsin freely behaving mice. An interesting feature of this implementation is the possibilityto use either a short objective lens for surface imaging, or a longer version that can beinserted inside the brain for deep structure imaging. A noticeable constraint was thenecessity for image realignement due to rotation in the commutator. Indeed, high ac-quisition rates were needed for correct post-processing and realignement. In this case,up to 100Hz acquistion rate was necessary and achieved through pixel binning, at theexpense of lateral resolution. Besides, limitations for functional imaging were a lack ofoptical sectioning, inherent to epifluorescence microscopy, and a limited minimal lateralresolution of about 3 µm.

The reader is referred to [Flusberg et al., 2005a] for a more extensive review offiberscopy, describing, among others, approaches not demonstrated for functional flu-orescence imaging in freely behaving rodents.

I. C.2 Two-photon microscopy

So far, single photon fiberscopes lacked optical sectioning, impairing the ability to performfunctional imaging in complex 3D neuronal networks. In order to overcome this mainlimitation, fiberscopes designed for two-photon fluorescence imaging have been developed.Indeed, two-photon fluorescence imaging benefits from intrinsic optical sectioning8.

8Two-photon excitation scales quadratically with the illumination intensity, such that fluorescenceemission is restricted to the illumination focal spot.

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Figure I.19: Distal part of the fiberscope reported by Flusberg et al, showing the remov-able focusing motor and the miniaturized objective. From [Flusberg et al., 2008].

Several two-photon fiberscopes have been developed since 2001 [Helmchen et al., 2001,Göbel et al., 2004, Flusberg et al., 2005b, Lelek et al., 2007, Engelbrecht et al., 2008,Piyawattanametha et al., 2009], but only one succeded in functional fluorescence imagingin freely moving rodent [Sawinski et al., 2009]. This manuscript describes this last workin more details than the others, the reader being referred to [Helmchen et al., 2013] fora more extensive review of this field. Briefly, two-photon fiberscopes can be classifiedaccording to the laser beam scanning approach and the fluorescence detection strategy.Laser beam scanning can be performed at the fiber entrance (proximal scanning) or atthe fiber end, at the sample (distal scanning). Similarly, fluorescence detection can beeither distal or proximal.

In proximal scanning approaches, a fiber bundle is used to transmit both excitationand emission light. A scanning unit is used to couple the laser beam to individual cores.This strategy has been adopted by Göbel et al. for fluorescence imaging in anaesthetizedanimal [Göbel et al., 2004]. Distal scanning makes use of a single core optical fiber, andcan be performed via laser beam deflection [Piyawattanametha et al., 2009] or fiber tipdisplacement [Helmchen et al., 2001, Flusberg et al., 2005a, Engelbrecht et al., 2008,Sawinski et al., 2009]. Piyawattanametha et al. used a microelectromechanical systemto perform lateral scanning of the laser beam with a scanning mirror [Piyawattanamethaet al., 2009]. Fiber tip deflection has been performed using piezoelectric bending elementsto accomplish either resonant scanning, producing complex harmonic Lissajoust [Helm-chen et al., 2001] or spiral [Engelbrecht et al., 2008] patterns, or nonresonant raster orrandom access scanning [Sawinski et al., 2009].

Fluorescence emission can be detected at the distal end of the fiber by means ofa small detector, such as a photomultiplier tube [Helmchen et al., 2001]. The mainadvantage of this strategy is the reduced transmission losses. However, it increases thesize and weight of the element mounted on the animal. Proximal detection through largecore optical fiber [Flusberg et al., 2005b, Engelbrecht et al., 2008, Sawinski et al., 2009],on the other hand, can work with any sensitive detector and allows multi-color imagingby spectral separation at the end of the collection fiber.

Sawinski et al. provided the first, and so far the only report of functional fluorescence

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imaging in freely behaving rodents with a two-photon fiberscope [Sawinski et al., 2009](Figure I.20). 925 nm pulses were delivered by a Ti:Sapphire laser and pre-chirped tocompensate group velocity dispersion. The head-mounted piece, excluding the head plateand optical fiber, weighted 5.5 grams and could be carried by adult rats. It included asmall microscope objective (Throl Optical Systems) of 0.9 NA and 0.7 mm WD usedfor laser beam focusing and fluorescence collection, a tube lens for coupling it to theexcitation fiber, a dichroic beam splitter, and a condenser lens focusing fluorescence ontoa collection plastic optical fiber of 0.63 NA. Fluorescence was transmitted to photomul-tipliers, in a green and a red channel. Functional recordings were performed at about10Hz in 63× 63 pixel frames with submicrometer spatial lateral resolution.

1cm

4

5

3

6

2

7

81A

Figure I.20: Two-photon fiberscope. Left. Schematic of the two-photon fiberscope. 1.Excitation optical fiber; 2. Mirror; 3. Tube lens; 4. Objective; 5. Focusing flange; 6.Dichroic beamsplitter; 7. Condenser lens; 8. Collection optical fiber. Center and right.Photographs of the fiberscope. From [Sawinski et al., 2009].

This two-photon fiberscope allowed to detect single somata in the layer 2/3 of thevisual cortex (Figure I.21). The authors could perform functional recordings from singleneurons in freely behaving rats with small movement artifacts. The strongest image shiftdue to brain displacement was estimated to less than 3 µm. The main advantages ofthe approach are the optical sectioning inherent to two-photon fluorescence imaging, therelatively important imaging depth (here about 200 µm) and the multi-color imaging,which allowed the author to differentiate neurons from astrocytes and compensate formovement artifact. However, a difficulty here lies in the tradeoff between the size of thefield of view and the acquisition rate. In this case, to achieve reasonable repetition rate(about 10Hz), authors were limited to areas of about 100× 100µm2 or less comprising afew neurons only. Besides, scanning approaches have the disadvantage of providing non-simultaneous information from different points. In some experimental contexts, whenrelative timing between different neurons is important, this might be a limitation of thisfiberscope. Finally, the fiberscope is too heavy to be carried by mice, which prevents theuse of many optogenetic tools.

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20 µm

E

50 µm

D

Figure I.21: Fluorescence images of a mouse visual cortex acquired with the head-mounted two-photon fiberscope (left and right). Right. Two-colour image of the squaredregion from the left panel. Green channel: OGB1 (neurons and astrocytes) Red channel:sulfurhodamine 101 (astrocytes). From [Sawinski et al., 2009].

I. C.3 The need for further technical development...

The microscopy strategies presented in the previous section can be used to correlateneuronal activity and behaviour, and establish putative cell assemblies. The latest im-plementations provide spatial resolution of a few micrometers in single-photon and lessthan 1 micrometer in two-photon microscopy, compatible with single somata detection.All of them should allow acquisition rates high enough to follow Ca2+dynamics. However,two points are to be mentioned.

The first one relates to imaging itself. So far, single-photon implementations did notallow fluorescence imaging with optical sectionning. This limits investigations of com-plex 3D fluorescent structures, since out-of-focus signal can affect functional recordings.Regarding two-photon fiberscopy, simultaneous recordings at different locations in thesample are not possible. This limits its use in studies where relative timing betweenseveral neurons’ activity (in the range of 1-10 ms) is essential.

The second point concerns the inability of all these approaches to easily photoactivateoptogenetic tools in real-time with single neuron precision. Thus, direct test of theputative cell assemblies estimated from functional fluorescence imaging is unconceivable.

So in spite of important technical development, there is still a need for further inno-vation to investigate properly the cell assembly hypothesis.

I. D Motivations summary

This work was motivated by the following question: how can the cell assembly hypoth-esis be experimentally tested? A general experimental design could be, first, to findputative cell assemblies using functional fluorescence imaging; then to excite/inhibit thewhole/part of the ensemble and record the consequences on local neuronal activity or/andon behaviour. Here, optogenetics is of great interest, since it provides genetically encodedactuators and indicators of neuronal activity. Hence, microscopy techniques are needed

40

to take full advantage of these tools in behaving animals. Some experimental conceptsrequiring both optogenetics and advanced microscopy methods are discussed below.

D. O. Hebb’s cell assembly forms through activity dependent learning mechanisms.Simultaneous targeted photoactivation and functional imaging could be used to investi-gate the processes of neurons integration in an ensemble using at least two experimentaldesigns. 1) It has been suggested that single neuron activity can impact on rodentsbehaviour [Houweling and Brecht, 2008, Arduin et al., 2013]. This neuron is probablyintegrated in a cell assembly involved in the observed behaviour. Targeted excitationof single neurons during a defined behaviour could be used to determine the importantparameters (timing, pattern of activity) for these neurons recruitment in an ensemble.Then, functional imaging would confirm effective enrollment in the assembly during be-haviour. 2) At a given instant, the cell assembly is composed of neurons with high recruit-ment probablility. It has been proposed that neurons with low level of activity duringa given task could be recruited during learning processes [Margolis et al., 2012], whichwould correspond to a change in cell assembly constitution. Direct assay of neuronalenrolement during cell assembly remodeling could be performed by targeted inhibitionof a subset of cells. Functional imaging would then be used to detect the emergence ofnew memberships.

According to D. O. Hebb theory, the cell assembly is the fundamental unit of be-haviour. This could be testable using functional imaging to find putative ensembles andtargeted photoactivation to either excite or inhibit the neuronal members. Ziv et al.showed that CA1 hippocampus place cells are activated in unique patterns depending onthe mouse location [Ziv et al., 2013]. We could propose a conditioned place preferenceparadigm where the animal learns to avoid a location and prefer another. Then, theimportance of putative assemblies activity could be tested. Does excitation or inhibitionof the ensemble members affect the mouse behaviour, during and after learning? An-other example, inspired by Chen et al., would focus on cortical neurons subpopulations,projecting either to sensory or motor areas [Chen et al., 2013a]. It has been suggestedthat sensory and motor projecting neurons are of distinct importance in a sensory dis-crimination task. Does selective inhibition of one of these populations have any effect ondecision making?

From a technical point of view, all these experiments share common features. First,they necessitate targeted photoactivation, down to the single neuron level. So far, thishas not been reported in freely behaving rodent. However, some implementations have al-ready been developed and used in cultured cells and brain slices. In particular, ValentinaEmiliani’s group (among others [Shoham et al., 2005, Packer et al., 2012]) has beenusing phase modulation techniques to shape an excitation beam and precisely targetneurons [Lutz et al., 2008, Zahid et al., 2010, Yang et al., 2011, Anselmi et al., 2011,Papagiakoumou et al., 2010]. In this work, this approach has been extended to in vivoapplications with a fiberscope. The second requirement to perform the above mentionedexperiments is to record neuronal activity. Although this field is much more developedthan the one of in vivo targeted photoactivation, there is still a need for technical im-provement. This work is based on a fiberscope making use of structured illumination

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microscopy (SIM) [Bozinovic et al., 2008]. It has been further developed to allow multi-point confocal imaging. Finally, taking advantage of optogenetic tools, the fiberscopehas been tested for simultaneous targeted photoactivation and fonctional fluorescenceimaging in freely behaving mice.

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Chapter II

Experimental study : Optogenetics in living

mice with a fiberscope

Contents

II. A Experimental conditions . . . . . . . . . . . . . . . . . . . . . . . . . 43

II. A.1 Fiberscope setup . . . . . . . . . . . . . . . . . . . . . . . . . 43

II. A.2 Photoactivation . . . . . . . . . . . . . . . . . . . . . . . . . 48

II. A.3 Fluorescence imaging . . . . . . . . . . . . . . . . . . . . . . 55

II. A.4 Setup transmission and power adjustment . . . . . . . . . . . 61

II. A.5 Biological model . . . . . . . . . . . . . . . . . . . . . . . . . 64

II. B In vivo experimental results . . . . . . . . . . . . . . . . . . . . . . . 70

II. B.1 Experiments in anesthetized mice - ChR2 and GCaMP3.3 . . 70

II. B.2 Experiments in anesthetized mice - ChR2 and GCaMP5-G . 77

II. B.3 Experiments in awake, freely behaving mice . . . . . . . . . . 85

II. B.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

II. A Experimental conditions

II. A.1 Fiberscope setup

The development of a microscope for photoactivation and functional imaging with micro-metric and millisecond resolutions in behaving animals has been motivated by section I.A. Two opposing constraints arise when designing such a device. First, optics must pro-vide spatial resolution at the micrometer scale to resolve single neurons, in a field of viewof several tens of micrometers to provide access to several cells. Besides, photoactivationpatterns size and shape must adapt to experimental needs. Second, the device must betolerated by the animal so that behaviour is not hindered. To address these two limi-tations concurrently, we designed a fiberscope composed, for one part, of a microscope

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handling light patterning both for photoactivation and fluorescence functional imagingand, for the other part, of a fiberscopic probe acting as a relay between the microscopeand the animal (Figure II.1).

Figure II.1: Diagram of the fiberscope setup. The photoactivation path is depictedin light blue, and described in II. A.2. The imaging path is depicted in green, anddescribed in II. A.3. L: lens; LC-SLM: liquid-crystal spatial light modulator; DMD:digital micromirror device; BS: dichroic beamsplitter.

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II. A.1.1 Fiberscopic probe : fiber bundle and micro-objective

The fiberscopic probe is composed of a 2-meter long fiber bundle attached to an imagingmicro-objective (Ultra Mini O probe, Maunakea Technologies, Paris, France).

The fiber bundle (Figure II.2) is made of 30,000 cores of about 2 µm diameter each,distributed in a 600µm diameter imaging area with an intercore distance dic,b ≈ 3.3µm.Note that the fiber cores are multimode and transmit light intensity but not phase. Themicro-objective (Figure II.3) has an external diameter of 2.6mm, a numerical apertureNA=0.8 and a magnification of 2.5 yielding a field-of-view of 240µm diameter and anintercore distance at the sample dic,s ≈ 1.3µm. The micro-objective imaging field isspherical, with a working distance of 60 µm at the center, and approximately 11 µmshorter at the border.

Based on the micro-objective NA, lateral resolution should be close to ∆ρ = λ2NA ≈

0.52×0.8 ≈ 0.3µm. However, fluorescence signal is sampled by the fiber bundle cores. Asa consequence, the lateral resolution, according to Shannon-Nyquist theorem, cannotbe better than ∆ρ = 2dic,s = 2.6µm. In our experimental context, this is neverthelesssufficient for detection of single somata of about 10µm diameter.

To sum up, the fiberscopic probe gives acces to the sample through circular imagesof 240µm diameter of 30,000 pixels with a lateral resolution of 2.6µm.

Figure II.2: Cross section of the fiber bundle, showing the 30,000 fiber cores randomlydistributed in a 600µm diameter imaging area.

II. A.1.2 Home-made microscope

The home-made microscope is composed of two optical paths (Figure II.1 and II.4). Oneis dedicated to photoactivation and makes use of computer generated holography) [Lutzet al., 2008], a phase modulation technique implemented with a Liquid-Crystal SpatialLight Modulator (LC-SLM). A home-made software is used to control the LC-SLM anddesign the photoactivation patterns based on fluorescence images. The second path isdevoted to fluorescence imaging and includes a Digital Micromirror Device (DMD). TheDMD modulates the amplitude of the excitation beam to perform alternatively widefieldepifluorescence imaging with either uniform or structured illumination [Bozinovic et al.,

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Figure II.3: Picture of the micro-objective, of 2.6mm outer diameter, 60µm workingdistance, and 0.8 numerical aperture. From www.maunakeatech.com

2008] and scanless multipoint confocal microscopy. A home-made software allows tochoose between these three different configurations and record fluorescence images.

Figure II.4: The fiberscope setup. The photoactivation path is depicted in light blue,and described in II. A.2. The imaging path is depicted in green, and described in II.A.3. Dashed green lines indicate the path used for aligning the imaging path optics. L:lens; LC-SLM: liquid-crystal spatial light modulator; DMD: digital micromirror device;BS: dichroic beamsplitter; 10X obj.: microscope objective; M: flip mirror.

Illumination patterns for photoactivation and fluorescence imaging are projected atthe focal plane of the microscope objective (Olympus UPlanSApo, 10X, 0.4 N.A.), wherethe proximal end of the imaging bundle is positioned. Intensity patterns are then trans-mitted through the bundle and imaged onto the sample with the micro-objective. Sim-

46

ilarly, fluorescence from the sample is imaged onto the distal end of the fiber bundle,transmitted through the bundle, and reimaged on a scientific CMOS camera (Orca Flash4.0, Hamamatsu) using the microscope objective and a tube lens (L8, f8 = 100mm)leading to a magnification of ftube

fobj= 100

18 ≈ 5, 6. The resulting field of view and intercoredistance at the camera are then 3, 4mm and 18.5µm respectively. The size of the field ofview at the camera was chosen to optimize both the frame rate, which depends on thenumber of lines acquired by the camera (see below), and the resolution, limited by thefiber bundle if the intercore distance at the camera is smaller than a camera pixel.

The scientific CMOS camera sensor (13, 3 × 13, 3mm2) is composed of 2048 × 2048pixels of dimensions 6.5 × 6.5µm2. This camera was chosen to optimize both temporalresolution and signal to noise ratio (SNR). The frame rate at which the camera operatesdepends on the number of vertical lines acquired. It can be as high as 100 frames/s at 2048lines or 400 frames/s at 512 lines, sufficient for somatic calcium signal oversampling [Tianet al., 2009, Akerboom et al., 2012]. Here, our field of view corresponds to a regionof interest of 528 × 528 pixels, and even smaller regions of interest were used in thescanless confocal configuration (see Section II. A.3.4). Second, read noise is very low (1.9electron, root mean square), ensuring good SNR even at low photon count. Finally, highquantum efficiency (about 70% at 530nm) provides efficient photon detection. Becauseall experiments were performed in low light conditions (see II. B.1.2 and II. B.2.1), theselast two parameters were critical in recording functional fluorescence signals.

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II. A.2 Photoactivation

In order to photoactivate defined structures, e.g. neuronal cell bodies, we controlledlight intensity distribution in the sample using a wavefront modulation method calledcomputer generated holography (CGH) [Lutz et al., 2008, Zahid et al., 2010, Yang et al.,2011, Anselmi et al., 2011].

II. A.2.1 Computer generated holography principle

To understand CGH principle, let us first consider the propagation of an electric field−→E (−→ρ , z), where −→ρ and z are the lateral and the axial coordinates respectively, througha lens of focal length f . Following the laws of Fourier optics, the field distributions atthe planes located at z0 = −f and z1 = f , called Fourier planes, are related by a scaledFourier Transform [Mertz, 2010] :

E(−→ρ1, z1) ∝

∫

E(−→ρ0, z0)e−i2π k

f−→ρ 0·

−→ρ 1d2−→ρ 0 (II.1)

where k = nλ is the wavenumber, n the refractive index and λ the wavelength.

The Fourier planes of the microscope objective will be called the front focal plane inthe sample, and the back focal plane inside the microscope. Knowing the field distributionat one of these planes allows calculating it at the other plane.

CGH allows to generate a user-defined intensity pattern at the front focal plane byadressing a suitable phase pattern at the back focal plane. The phase pattern is calculatedwith an iterative Fourier transform algorithm, described in the next paragraph, and isadressed to the LC-SLM placed in a conjugated plane from the back focal plane. Thecorresponding intensity pattern is then generated at the front focal plane, and can beused to target photosensitive structures. CGH is a phase-only modulation technique. Asa consequence, there is little power loss compared to amplitude modulation techniques,and therefore higher excitation densities can be achieved.

The Iterative Fourier Transforms Algorithm (IFTA), implemented into a custom-designed software, computes the phase addressed to the LC-SLM [Lutz et al., 2008].As depicted on Figure II.5, the IFTA operates in steps, constituting a loop describedthereafter. A target intensity pattern at the sample plane |U(x0, y0) |

2 is first defined,the phase at the sample being the free parameter of the algorithm. An initial randomphase Φ (x0, y0) is associated with the corresponding amplitude, resulting in the fieldg (x0, y0) = |U(x0, y0) | exp (iΦ (x0, y0)). The field g (x0, y0) is then propagated from thefront focal plane to the LC-SLM plane with an inverse Fourier transform (FT−1), re-sulting in G(x1, y1) = |G(x1, y1) | exp (iΦ (x1, y1)). Then, constraints on the amplitudeat the LC-SLM are imposed, so that the impinging beam has a Gaussian distributionand an area corresponding to the LC-SLM surface, resulting in G′ (x1, y1) = |U(x1, y1) |exp (iΦ (x1, y1)). This field is propagated back to the sample plane with a Fourier trans-form (FT), resulting in g′ (x0, y0). The calculated amplitude |g′ (x0, y0) | is then replacedby the target amplitude |U(x0, y0) | while keeping the calculated phase. This constitutes

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an iteration loop. After eight loops, the difference between calculated and target ampli-tudes, measured as E′2 =

∑

x0,y0[|g′ (x0, y0) | − |U(x0, y0) |]

2, is minimized and the phaseΦ (x1, y1) is adressed to the LC-SLM.

Figure II.5: Block diagram of the iterative Fourier Transform algorithm used to calculatethe phase-holograms addressed to the LC-SLM.

This technique has been developed for neuroscience applications in the wavefront en-gineering microscopy group since 2008. Implementation was first designed for neuronalexcitation in brain slices, either through photorelease of caged-neurotransmitters or pho-toactivation of optogenetic tools [Lutz et al., 2008, Zahid et al., 2010, Yang et al., 2011,Anselmi et al., 2011]. In our work, the use of this technique was extended to in vivophotoactivation of optogenetic tools.

II. A.2.2 Implementation in the fiberscope setup

Computer generated holography is implemented with a Liquid-Crystal Spatial LightModulator (LC-SLM) (Hamamatsu X10468) used to modulate the spatial phase of alaser beam (473nm, Ciel, Laser Quantum). This device is composed of an array of800 × 600 pixels, made of nematic liquid crystal, of dimensions a0 × a0 = 20 × 20µm2,and arranged in a 16 × 12mm2 area (diagonal = 20mm). The refractive index of eachpixel is determined by the orientation of the birefringent nematics, which depends on an

49

applied voltage. This LC-SLM can achieve 0 to 3π phase shifts and accepts 256 inputslevels.

The CGH optical path implementation in the microscope is depicted on Figure II.1and II.4. The laser beam is expanded by a telescope (L1 and L2, of respective focallengths f1 = 19mm and f2 = 200mm) to cover the entire surface of the LC-SLM. TheLC-SLM is then imaged onto the back focal plane of the microscope objective (OlympusUPlanSApo, 10X, 0.4 N.A. and fobj = 18mm) through a 4f telescope (L3-L4, f3 =300mm, f4 = 150mm).

Because the LC-SLM is composed of discrete diffractive elements, e.g. the pixels, theintensity of patterns generated with phase-holograms varies with the distance from theexcitation field center, corresponding to the optical axis. Diffraction efficiency, definedas the intensity ratio between a holographic spot of coordinates (x, y) in the sample anda focused spot obtained with the LC-SLM off, is given by [Yang et al., 2011]:

IspotI0

=

(

sinX

X

)2(sinY

Y

)2

(II.2)

where X = nπaλfobj

x, Y = nπaλfobj

y, n = 1 is the refractive index at the front focal plane,

a = a0f4f3 = 10µm is the demagnified LC-SLM pixel size at the objective back focal plane,

and λ = 473nm is the laser wavelength.The maximum diffraction angle at the LC-SLM is Xmax = π

2 . Then, xmax =

Xmaxλfobjnπa = 426µm. Diffraction efficiency is then Ispot

I0= 1 at the center of the ex-

citation field, and IspotI0

≈ 0.41 at 426 µm from the optical axis, which sets the fieldof excitation radius at the microscope objective front focal plane. The fiber bundle ispositioned at the center of this 852µm diameter excitation field. The lowest diffractionefficiency within the 600µm diameter fiber bundle imaging area is obtained for a spotplaced at the border of the bundle, on the x or y axis at 300µm from the field center,and is

(

IspotI0

)

min≈ 65%.

We can estimate the diffraction-limited lateral resolution at the front focal planeof the objective. Given the LC-SLM dimensions at the back focal plane of the objec-tive, xLC−SLM = 6mm and yLC−SLM = 8mm, we can calculate the effective numericalaperture NAeff in both x and y directions :

NAeff,x =xLC−SLM

2fobj= 0.17 NAeff,y =

yLC−SLM

2fobj= 0.22 (II.3)

The diffraction-limited lateral resolution of a holographic spot is then given by :

xmin =λ

2NAeff,x= 1.4µm ymin =

λ

2NAeff,y= 1.1µm (II.4)

We recall the intercore distance in the fiber bundle dic,b ≈ 3.3µm. This result statesthat lateral resolution in the bundle imaging area is not limited by the microscope butrather by the intercore distance. Besides, we did not address holographic spots to indi-viual cores. As a consequence, the holographic spots minimum diameter at the imaging

50

plane of the micro-objective was approximately 3µm, corresponding roughly to 2 coresin the sample.

Part of the laser beam remains unmodulated by the LC-SLM, and generates anundesired "zero-order" spot, removed using the following approach [Polin et al., 2005,Zahid et al., 2010]. The distance between L1 and L2 is increased to 235mm (instead of219 for a regular 4f telescope), so that the beam is slightly convergent at the LC-SLM.A defocus phase is added to the phase profiles addressed to the LC-SLM, so that theconvergence of the input beam is compensated for the modulated light. The unmodulatedcomponent forms a small spot out of the focal plane of L3, where it is removed from theexcitation field by the beam block B1.

The photoactivation laser beam is combined with the imaging laser beam using adichroic beam splitter (BS1) (LM01-480-25x36, Semrock). A second dichroic beam split-ter (BS2) (FF505-606 Di01, Semrock) is placed right before the microscope objective toseparate the illumination laser beams from the emitted fluorescence. These two dichroicbeam splitters introduce astigmatism on the photoactivation beam that is compensatedby introducing the appropriate phase at the LC-SLM with the computer generated holog-raphy software.

II. A.2.3 Results

CGH allowed generation of patterns of various sizes and shapes in the entire micro-objective field of view, as illustrated on Figure II.6. Note the curvature of the excitationand imaging field, with a working distance 11µm shorter at the edges compared to thecenter (see II. A.1.1).

Intensity patterns obtained with computer generated holography were characterizedwith a custom-made transmission microscope (Figure II.7). A thin fluorescent layerof Rhodamine spin-coated on a microscope coverslip was placed near the fiberscopeimaging plane and imaged onto a CCD camera (Orca 05G, Hamamatsu) using a high-NA coverslip-corrected microscope objective (UPlanSApo, Olympus, water immersion,NA = 1.2, 60x) and a tube lens (f = 100mm). The fiberscope probe was mounted ona piezoelectric device (MIPOS100PLSG, Piezosystems Jena) to modify the distance be-tween the imaging plane of the micro-objective and the fluorescent layer. 100 z-sectionsof the computer generated holography laser beam were then obtained, with ∆z = 1µm.The signal was integrated on a ROI covering the spot in focus (z = 0) and plotted alongthe z-axis.

The lateral size and shape of the illumination beam determine its axial extent, whichis defined as the full-width at half maximum (FWHM) of the intensity profile along theoptical axis. For circular shapes of diameter D, the axial extent is approximately equalto 3D (Figure II.8). Therefore, to reach cellular resolution photoactivation spots of 5µmdiameter and 19µm axial extent (in average) were used (Figure II.9).

51

Figure II.6: Illumination patterns generated with computer generated holography andrecorded with the fiberscope from a fluorescent layer of rhodamine, showing that the fullfiberscope field-of-view (240µm) is accessible for photoactivation. Inhomogeneities in theintensity are partly due to the hologram and to the inequal core transmission, but mainlyto the fluorescent layer. The curvature of the imaging and photoactivation fields is alsoapparent. Indeed, the photoactivation and imaging points are located on a spherical cap,resulting in a working distance shorter by approximately 11µm at the edge of the fieldcompared to the center. Top: Fluorescence image with the center of the field placed infocus. Bottom: The fluorescent layer is moved 8µm (left) or 11µm (right) closer to thefiberscope probe to place the edge of the pattern in-focus. Scale bars: 20µm.

52

Figure II.7: Diagram of the setup used for computer generated holography characteriza-tion, showing the photoactivation path of the fiberscope and the transmission microscope.

Figure II.8: Axial resolution (∆zFWHM, FWHM of the axial profile) of the photoacti-vation beams generated with computer generated holography as a function of the spotdiameter D. Squares: experimental data, average of several measurements (n). 3.7µm,n = 5; 5µm, n = 8; 7.5µm, n = 5; 10µm, n = 5; 15µm, n = 3; 20µm, n = 3; 25µm,n = 3; 30µm, n = 3. Solid line: linear fit of equation ∆zFWHM = 3D.

53

Figure II.9: a. Sections of the photoactivation beam along the (x − z) plane (left),(y − z) plane (right), (x − y) plane (inset), for a 5µm diameter spot generated withcomputer generated holography. b. Integrated intensity along the z axis for the samespot, ∆zFWHM = 18µm in this example.

54

II. A.3 Fluorescence imaging

In order to locate target neurons and record their activity, we combined CGH withfluorescence imaging. As depicted on Figure II.1, the optical path includes a DigitalMicromirror Device (DMD) (Texas Instruments, ALP discovery 4100 basic, 0.55” XGAchip, Vialux, Germany) used to modulate the spatial intensity of a 491 nm laser beam(Cobolt, Calypso 50).

II. A.3.1 Implementation of fluorescence imaging with intensity modulation

The DMD is composed of a two-dimensional array of 1024 × 768 individual pixels ar-ranged in a 11.2×8.8mm2 area (14mm diagonal). Each pixel comprises a 10.8×10.8µm2

aluminum micromirror with two stable states. Each state corresponds to a discrete mi-cromirror angular position, +12 degrees and -12 degrees relative to a plane parallel to thearray. Figure II.10 shows a schematic of two mirrors, and indicates the electro-mechanicalcomponents responsible for position switch and stabilization. The tilt direction is per-pendicular to the hinge axis, positioned in the micromirror diagonal. Each micromirroris positioned over a CMOS memory cell, which is in a binary state 1, corresponding to a+12 degrees position, or 0, corresponding to a -12 degrees position. A "clocking pulse"synchronizes all the micromirrors, switching them from their previous state to the onecorresponding to the logic written in their respective CMOS memory cell. Dependingon the micromirror angular position, the impinging light is deflected either towards thesample or towards a block.

Figure II.10: Diagram of two pixels of the DMD. A via attaches the mirror to a yoke.A hinge allows the yoke to switch between two positions, where it makes contact with aspring tip. The electrodes stabilize the mirror position. From Texas Instrument Incor-porated.

The imaging laser beam is expanded to cover the DMD surface with a telescope (L5and L6, of respective focal lenghts f5 = 19mm and f6 = 250mm) (Figure II.1 andII.4)1. The DMD is then imaged onto the proximal tip of the fiber bundle using a lens

1To align properly the imaging path optics, we directed the laser beam to the DMD in the reversedirection using a flip mirror, as depicted by the dashed lines on Figure II.4. The DMD and the mirrors

55

(L7, f7 = 150mm) and the microscope objective (Olympus UPlanSApo, 10X, 0.4 N.A.and fobj = 18mm) (Figure II.1), yielding a magnification of fobj

f7 = 18150 = 0.12. The

resulting field of excitation is 1.3 × 1.1mm2, covering the fiber bundle imaging area.The DMD pixel size at the bundle entrance is then 1.3 × 1.3µm2. DMD pixels areimaged at the microscope objective imaging plane with a diffraction-limited resolutionλ

2NA = 4912×0.4 ≈ 0.6µm. Recalling the intercore distance dic,b = 3.3µm, we conclude that

excitation resolution at the sample is not limited by our implementation of the DMD,but rather by the fiber bundle.

Depending on the mirror pattern displayed on the DMD, we could achieve conven-tional widefield epifluorescence imaging, Structured Illumination Microscopy (SIM) orscanless multipoint confocal imaging.

II. A.3.2 Conventional widefield epifluorescence imaging

Conventional widefield epifluorescence imaging is performed when displaying a uniformpattern on the DMD. This straightforward technique simply consists in uniformly illu-minating the sample to excite the fluorophores, and recording the resulting fluorescencesignal on the sCMOS camera. The detected signal is then the convolution of the detectionpoint spread function (PSF) and the fluorophore distribution C [Mertz, 2010]:

IWF(−→ρ 1) ∝

∫∫

PSF (−→ρ 1 −−→ρ 0,−z0)C (−→ρ 0, z0)d

2−→ρ 0dz0 (II.5)

where −→ρ 0 and −→ρ 1 are the two-dimensional coordinates and z0 is the axial coordinatein the sample.

This modality provides optical recording from the entire field-of-view, but has nooptical sectioning. Indeed, the signal recorded from a uniform fluorescent plane followsthe relationship [Mertz, 2010]:

IWF(−→ρ ) ∝

∫

PSF (−−→ρ 0,−zs)d2−→ρ 0 (II.6)

where zs is the axial position of the sample. Since [Mertz, 2010]:∫

PSF (−→ρ , z)d2−→ρ = 1 ∀z (II.7)

IWF does not depend on the axial position of the uniform plane, and conventionalwidefield epifuorescence imaging does not provide optical sectioning.

All the same, this simple technique was used to position the fiberscopic probe abovea brain region of interest. In order to remove the fiber cores artifacts from the finalimages, raw images were processed with a low-pass Gaussian filter. Figure II.11 displaysa sample image acquired in this configuration. As discussed in sections II. B.1.2 andII. B.2.1, conventional widefield epifuorescence imaging could not be used for functionalrecordings.

proximal to the DMD were aligned by superimposing the two counterpropagating beams.

56

Figure II.11: GCaMP5-G fluorescence recorded in an anesthetized mouse with conven-tional epifluorescence imaging (a) and SIM (b). SIM was performed with a grid periodof 43µm, yielding an axial resolution of 34µm FWHM. Exposure time is 40ms for epiflu-orescence and 3x40ms for SIM.

II. A.3.3 Structured Illumination Microscopy (SIM)

II. A.3.3.1 Principle As mentionned above in section II. A.3.2, conventional widefieldepifluorescence does not provide optical sectioning. Stated differently, low spatial frequen-cies are equally transmitted independently from the object axial position. This leads toan important drawback of conventional widefield epifluorescence imaging, namely out-of-focus background. Indeed, fluorescence emitted from above and below the focal planegenerate a quasi-homogeneous (low-fequency) signal in the recorded images, reducing in-focus contrast. In order to readily target neurons, we needed the best contrast available.Therefore, we removed out-of-focus background by implementing structured illuminationmicroscopy (SIM) [Neil et al., 1997].

SIM is based on illumination of the sample with spatially modulated light, in our casewith a periodic monodimensional grid pattern. In the case of a sinusoidal modulationof an incoherent source and assuming symmetry of the PSF around the z axis, thedistribution of illumination intensity in the sample is given by [Mertz, 2010]:

Ii(−→ρ , z) = Ii(1 + OTFi(νg, 0, z) cos(2πνgx0 +Φ)) (II.8)

where −→ρ is the 2D lateral coordinate and z is the axial coordinate at the sample, Ii isthe illumination source intensity, OTFi the illumination optical transfer function in themixed representation, νg the spatial frequency of the modulation along the x directionand Φ the phase of the modulation.

A phase stepping algorithm is applied. A fluorescence image is acquired at threedifferent phase steps, corresponding to three different grid positions. The processed SIMimage intensity distribution is given by [Mertz, 2010]:

57

ISIM(−→ρ 1) =1

2ΩdσfIi

∣

∣

∣

∣

∫∫

PSFd(−→ρ 1 −

−→ρ 0,−z)OTFi(νg, 0, z) exp(−i2πνgx0)C(−→ρ 0, z)d2−→ρ 0dz

∣

∣

∣

∣

(II.9)

where Ωd is the detection solid angle, σf is the fluorophore cross-section PSFd is thedetection point spread function and C is the fluorophore concentration.

SIM optical sectioning can be evaluated by calculating the SIM intensity from afluorescent plane [Mertz, 2010]:

ISIM(νg, zs) ∝ C |OTFd(−νg, 0,−zs)| |OTFi(νg, 0, zs)| (II.10)

where zs is the position of the fluorescent plane and OTFd is the detection OTF.Assuming the illumination and detection OTFs are identical, normalizing to the intensityobtained when the plane is in focus, and using the Stockseth approximation of the OTFfor a circular pupil, we finally obtain [Chasles et al., 2007]:

ISIM, norm(ν ′g, u) =

∣

∣

∣

∣

∣

∣

2J1

(

uν ′g

(

1−ν′g2

))

(

uν ′g

(

1−ν′g2

))

∣

∣

∣

∣

∣

∣

2

(II.11)

where J1 is the cylindrical Bessel function of order 1, u = 4knzs sin2 α

2 is the nor-malized sample axial position, k = 2π

λ is the wavenumber, n is the refractive index inthe sample, α is the objective semi-aperture angle, and ν ′g = νg

NAλ the normalized grid

frequency in the sample.To evaluate the theoretical axial resolution of SIM imaging, we calculated the full

width at half maximum ∆zFWHM of the normalized SIM intensity as function of thesample axial position z. We calculated that ISIM, norm = 1

2 when uHWHMν ′g

(

1−ν′g2

)

=

1.6. Then, with NA = 0.8 and n = 1.33, we found ∆zFWHM = 0.79Λ, where Λ is thegrid period in the sample. Hence, optical section thickness of fluorescence images can beadapted by changing the grid period.

II. A.3.3.2 Implementation in the fiberscope setup Spatial intensity modulation can beperformed in various ways, and was originally generated by physically moving a metalgrid placed in the illumination pathway, in a plane conjugated to the sample plane.In our implementation, a monodimensional grid pattern is displayed on the DMD. Inthis way, the grid spatial frequency is easily tunable, allowing to adjust optical sectionsthickness during the experiment. Besides, the high refresh rate of the DMD (up to 10kHz) ensures high temporal modulation frequency capability, so that SIM acquisitiontime is not limited by our implementation but rather by exposure time, depending onthe sample fluorescence signal. Prior to image reconstruction, we performed waveletprefiltering to remove potential grid artifacts [Bozinovic et al., 2008].

58

II. A.3.3.3 Results Optical sectioning of the structured illumination microscope wascharacterized by measuring the fluorescence back-propagating from a layer of rhodamine,as the micro-objective was moved along the axial direction of a distance z between thefluorescent and imaging planes.

The axial resolution, defined as the FWHM of the SIM intensity as a function ofz, varied linearly with the grid period (Figure II.12) and was adjusted online accordingto the experimental needs. We found that theoretical results fitted relatively well withexperimental data.

Wavelet prefiltering did not affect axial resolution (Figure II.13), and therefore, theaxial resolution shown in Figure II.12 as a function of the grid period has been calculatedwithout wavelet prefiltering.

Figure II.12: Axial resolution of SIM (FWHM of optical sectioning curves) as a function ofthe grid period. Square: experimental data. Solid line: theoretical results correspondingto NA=0.78, and yielding ∆zFWHM = 0.79Λ.

Figure II.11 displays fluorescence images of the same field of view, acquired withwidefield epifluorescence and SIM, showing contrast improvement with SIM. Contrastwas defined as Isoma−Ibg

Ibg, where Isoma is the soma fluorescence intensity and Ibg is the

background fluorescence intensity. Fluroescence intensity was measured along a 20 µmline crossing the cell. Soma fluorescence intensity was defined as the mean fluorescence inthe soma. Background fluorescence was defined as the mean intensity outside the soma.In this particular example, contrast of the cells was improved by a factor 14 (n = 10somata), confirming that background rejection has a clear impact on image quality.

II. A.3.4 Scanless multipoint confocal imaging

II. A.3.4.1 Principle We have just described a method in section II. A.3.3, SIM, thatovercomes the lack of optical sectioning in widefield epifluorescence microscopy. However,

59

Figure II.13: SIM intensity measured with the fiberscope from a fluorescence plane as afunction of its axial position z (z = 0 at the imaging plane of the micro-objective), for agrid period of 43µm, with (grey triangles) or without (black squares) wavelet prefiltering.Axial resolution is defined as the FWHM of this optical sectioning curve and is equal to33µm or 34µm respectively.

strong temporal intensity variations between raw images ultimately leads to artifacts, notcompensated by the wavelet filter. Finally, it was important to keep illumination poweras low as possible to keep the sample unaffected by illumination. Hence, we implementeda third imaging modality to perform fast recording with optical sectioning, called scanlessmultipoint confocal imaging.

Fluorescence confocal imaging relies on confinement of both illumination and de-tection so that the recorded signal comes only from a small probe volume. Focusedillumination can be performed by placing in the illumination pathway a small circularaperture, called pinhole, in a plane conjugated to the sample, or by directly focusinga laser beam in the sample. In either case, detection is done through a pinhole. Thedetected signal follows the relationship [Mertz, 2010]:

Iconf(−→ρ s, zs) ∝

∫∫

PSFi (−→ρ 0, z0) PSFd (−

−→ρ 0, z0)C (−→ρ 0 −−→ρ s, z0 − zs)d

2−→ρ 0dz0

(II.12)where PSFi and PSFd are the microscope illumination and detection point spread

function respectively, −→ρ 0 and −→ρ s are lateral coordinates in the image and the sampleplanes respectively, and z0 and zs are axial coordinates in the image and sample planesrespectively.

This configuration leads to out-of-focus fluorescence rejection. Indeed, since the sameobjective is used for both illumination and detection, PSFi and PSFd are similar (the

60

only variation coming from the difference beteen excitation and fluorescence wavelength).Then, in the case of a circular pupil, the fluorescence signal recorded from a uniformfluorescent plane follows the relationship [Mertz, 2010]:

Iconf(−→ρ s, zs) ∝

∫

PSF2 (−→ρ 0, zs)d2−→ρ 0 ∝

1

z2s(II.13)

Hence, the confocal image intensity indeed decays with z, confirming that confocalimaging does provide optical sectioning.

II. A.3.4.2 Implementation in the fiberscope setup In our implementation (Figure II.14),the DMD is used to create a pattern of one or several spot(s), constituting a set of virtualillumination pinhole(s). Fluorescence signal is recorded on the sCMOS camera, where itis integrated on regions of interest (ROIs) acting as virtual detection pinholes. Insteadof scanning one or several focused illumination spot(s), as in laser scanning or spinningdisk confocal microscopy respectively, a fixed set of DMD-generated spots, centered onstructures of interest, is imaged in the sample. Fluorescence signals are then continuouslyrecorded in this scanless configuration. In this way, we get simultaneous optical recordingfrom various locations with optical sectioning, with a low amount of light delivered tothe sample.

II. A.3.4.3 Results The confocal microscope point-spread-function was measured byimaging fluorescent beads (2.5µm diameter, Green (505/515), Molecular Probes) de-posited on a coverslip coated with poly-L-lysine. The sample was kept at the sameposition while the illumination beam was scanned by changing the virtual illuminationand detection pinholes position. Axial displacement was obtained by moving the fiber-scope probe, mounted on a piezo-electric actuator, and lateral displacement was obtainedby simultaneously moving the illumination spot and the detection ROI.

The confocal point-spread function (PSF) could be easily tuned by modifying thesize of the virtual illumination and detection pinholes. We chose a PSF sufficient forsingle-cell resolution with ∆ρFWHM = 4µm and ∆zFWHM = 10µm(Figure II.15).

II. A.4 Setup transmission and power adjustment

The fiber bundle transmission was about 40%, mostly imposed by the filling factor of thecores within the bundle imaging area.

The LC-SLM transmitted 56% of the impinging laser beam, due to overfilling ofthe LC-SLM. Only 4% of the transmitted light was diffracted in the zero order. Fora 5µm diameter holographic spot near the field center, transmission was 6.9% betweenthe setup entrance (just before L1) and the micro-objective output. In order to adjustphotoactivation power density (P ) during the experiments, we adjusted the laser outputusing its controler.

The DMD (overfilled) transmitted 20% of the light intensity to the fiber bundle.It is worth noting that up to 60% transmission could be achieved if the DMD was not

61

Figure II.14: Optical layout of the scanless multi-point confocal microscope, for fluores-cence recording from three somata (1, 2, 3). a. SIM image showing location of cells. b.Illumination mask displayed by the DMD and acting as virtual illumination pinholes. c.Image registered on the camera with the illumination mask displayed in (b) and show-ing ROIs acting as virtual detection pinholes. For each cell, the fluorescence signal isintegrated in the corresponding ROI.

overfilled. With uniform illumination, transmission was 4.3% between the setup entrance(just before L5) and the microobjective output, and about 1.8 × 10−5 for a spot of 5µm diameter. Losses were mostly due to the DMD image overfilling the bundle imagingarea. In order to adjust imaging power density (Pi) during the experiment, we rotated ahalf-wave plate placed in front of a cube polarizer, at the laser output.

Available laser power (300 mW at 473 nm and 50 mW at 491 nm) was orders ofmagnitude larger than that required in our experiments. Therefore, the setup was tunedto optimize photoactivation and imaging resolution and homogeneity within the fields ofexcitation and illumination rather than transmission efficiency.

62

Figure II.15: Characterization of scanless confocal imaging. Left : (x-z) profile of theconfocal PSF for 4µm diameter illumination and detection “pinholes”. Center and right :lateral and axial profiles of the PSF. Lateral resolution, 4.2µm FWHM; axial resolution,10.3µm FWHM. Scale bar 10µm.

63

II. A.5 Biological model

In order to readily test the fiberscope performances in manipulating optogenetic tools inliving animal, we developed a convenient biological model. We chose to work in a mousemodel, largely because of the profuse genetic backgrounds available making optogenetictools easy to implement. Since no mice line providing both a photoactivable actuatorand a fluorescent reporter was available at that time, we developed an expression systembased on intracerebral injection of viral vectors. Because the accessible structures werelimited by the micro-objective 60µm working distance, we targeted cerebellum molecularlayer interneurons (MLIs), so that we would have easy access to numerous neuronal cellbodies in vivo . However, getting specific protein expression in these cells required acombination of molecular tools including virus vector serotype, a Cre-lox system and atransgenic mice line, described in the following sections.

All experiments followed European Union and institutional guidelines of the careand use of laboratory animals (Council directive 86/609 EEC). They were approved bythe Paris Descartes Ethics Committee for Animal Research with the registered numberCEEA34.EV.118.12.

II. A.5.1 AdenoAssociated Virus vectors

We chose to use virus vectors for in vivo delivery of optogenetic tools. Indeed, this methodallows great flexibility in the target brain area, through stereotactic injection (describedin Section II. A.5.4), the targeted cell type, depending on the serotype and promoter, andthe genes of interest, by chosing the appropriate transgene cassette. This approach canlead to high level of protein expression within short periods of time (week(s)). Therefore,it allows relatively easy adaptation of the transgenes to the experimental needs.

We used vectors derived from AdenoAssociated Virus (AAVv), for reasons explainedbelow. We will first introduce AdenoAssociated Virus (AAV), and then briefly describeAAVv. AAV belong to the Parvoviridae family, the smallest and most simple DNA animalviruses. The viruses from which AAVv are derived belong to the Dependovirus family.Virus life cycle can schematically be described in two phases, infection and replication.AAV are naturally replication defective, in a sense that they need to coinfect their hostwith an Adenovirus or a Herpes Simplex Virus to effectively replicate. AAV virions are20-22nm diameter non-enveloped particles. The icosahedral capsid, composed of the 3structural proteins VP1, VP2 and VP3, contains a 4.7kB single-stranded DNA genome.The genome is flanked by two 145b Inverted Terminal Repeats (ITR), with palindromicterminal 125b. These regions are the only cis-acting elements necessary and sufficientfor encapsidation and replication, and are used in vector preparation (rescue) [Hermensand Verhaagen, 1998, Papale et al., 2009].

AAV2 has never been associated with any disease, and can be concentrated to hightiter (1010 - 1011) [Hermens and Verhaagen, 1998]. It was therefore a good vector can-didate. Indeed, AAV2v production has been successfully performed. The viral genomesequence (except the ITRs) is replaced by a promoter-gene sequence, so that virus pro-teins are no longer carried by the AAVv, which will instead lead to designed protein

64

expression. Various serotypes, noted from AAV2.1 to AAV2.9, expressing diverse cap-sid proteins, have various tropisms, so that many cell-types can be infected, includingneurons. The AAVv genome mainly remains episomal, with an integration frequencyrelatively low (about 5% of the infected cells) [Russell and Kay, 1999]. in vivo proteinexpression is noticeable from one week to more than six months after infection. Fi-nally, since there is no virus protein expression (except the capsid proteins), the reactiveimmune response is relatively weak [Papale et al., 2009].

AAVv infection and expression mechanisms are illustrated in Figure II.16. Once theAAVv has been introduced in the organism, it can bind to the target cell membrane,through interaction between the capsid and membrane receptors, which leads to vectorinternalization. The vector DNA is then released in the cytosol and translocated to thenucleus. There, vector gene expression is effective after hybridization or integration inthe host genome [Russell and Kay, 1999].

Figure II.16: Diagram of transduction by AAV vectors. From [Russell and Kay, 1999].

II. A.5.2 Cre-lox system

Vector gene expression is dependent on the transgene promoter. However, we did nothave access to any promoter leading to specific expression in MLIs. We hence had touse another approach to confine expression in the cells of interest, and used the Cre-loxsystem.

The Cre is a 38 kDa protein derived from the virus bacteriophage P1. This enzymecatalyzes DNA recombination between two lox sites of 34 bp each. Depending on the loxsites arrangement, the recombination is either an excision (when the two lox sites are

65

repeated) or an inversion (when the sites are inverted) of the intervening DNA segment.The Cre protein catalyzes intra and intermolecular recombination with either linear orsupercoiled DNA [Sauer and Henderson, 1988].

Genetic engineering has allowed optimization of the Cre-lox system, through the useof two pairs of lox sites, for example loxP and lox511 [Schnütgen et al., 2003]. TheCre efficiently recombines DNA between identical sites, either loxP or lox511 , but notbetween different sites. Therefore, using the sequence depicted on Figure II.17 results inthe following gene expression scenarios. If Cre is absent, then the reversed gene sequenceprevents gene expression. If Cre is present, a first recombination between identical andinverted lox sites can occur, leading to reversal of the gene sequence. Then, a secondrecombination between identical and repeated lox sites can happen and lead to excisionof the intervening lox site, preventing any further DNA inversion. Gene expression isnow allowed by correct DNA orientation.

Figure II.17: Diagram of the Cre-lox system.

We made use of this conditional expression system, called FLEx switch, to restrictoptogenetic tools expression to Parvalbumin positive neurons. The ChR2 and GCaMPgenes, carried by a AAVv, were flanked by loxP and lox511 sites. We used a mice lineexpressing the Cre protein under the control of the parvalbumin, expressed in MLIs.

II. A.5.3 PV-Cre mice line

Genetically engineered mice carry induced mutations, allowing the experimenter to gaincontrol over gene expression. The genetic manipulation panel includes transgenes, tar-geted mutations (knockins and knockouts), and retroviral, proviral or chemically-inducedmutations. To control optogenetic tools expression, we used a commercially availableparvalbumin-Cre (PV-Cre) targeted mutant mice line from Jackson Laboratory.

Targeted mutant mice are generated in four steps. First, gene disruption, replacementor duplication is achieved in mice embryonic stem cells (ESc) by homologous recombi-nation between the exogenous and the endogeneous DNA. The genetically-modified EScare then injected into host mice blastocysts, which are then injected in host females.The line is finally established by breeding the chimeric progeny carrying the targetedmutation in their germ cells. Note that homologous recombination almost never happensin model mammals, except in mice.

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We used a PV-Cre mutant carrying the Pvalbtm1(cre)Arbr allele, produced by insertingan IRES-Cre-pA targeting cassette into the 3’ UTR of parvalbumin exon 5 [Hippenmeyeret al., 2005]. Hence, the endogeneous parvalbumin promoter drives transcription of anadditional mRNA sequence, coding for the Cre recombinase, at the endogenous parval-bumin locus (Chr15:78191114-78206400 bp, - strand; genetic position: Chr15, 36.93 cM,cytoband E). The IRES (internal ribosome entry site) sequence promotes translationinitiation, leading to expression of the Cre recombinase protein. The ESc used werederived from 129P2/OlaHsd mice line, and the resulting heterozygote chimeric animalswere crossed to C57BL/6 mice. Homozygotes were produced by intercrossing these het-erozygote animals.

II. A.5.4 Intracerebral stereotactic injection

Gene delivery in the mammalian central nervous system can be a limiting step in exoge-nous protein expression. Indeed, the vector must enter the animal, and, if it is deliveredin the periphery, go through the blood-brain barrier and reach the target area at a titersufficient for efficient transduction. To overcome this difficulty, we directly injected thevirus vector inside the brain, in the target area located with stereotactic coordinates.

Stereotactic injection of viral vectors was performed in heterozygous PV-Cre F1 malemice (B6;129P2-Pvalb<tm1(cre)Arbr>/J (male) X Swiss (female)). Animals were anes-thetized at P29-39 (24-28g) by intraperitoneal (IP) injection of ketamine (52-120mg/kg)and xylazine (4.7-10.7mg/kg) after induction with isoflurane, then placed in a stereotac-tic apparatus (Kopf) with eyecream and opaque paper on the eyes to prevent dessicationand potential damage caused by high light intensities used during surgery. The micewere covered with one layer of "survival blanket", and shaved. After ethanol applicationon the skin, lidocaïne (2%) was injected subcutaneously, and the scalp incised. Perios-teum was gently removed from the part of the inter-parietal bone where a small (<1mm)craniotomy was made (0.5mm mediolateral, -6.2mm anteroposterior (from Bregma)) bydrilling the bone down to the second tablet (Foredom, spherical bit, 0.5mm diameter).The remaining bone was cut with a 27 gauge needle. A small incision was then made inthe dura before placing the injection cannula (36 gauge with 45°bevel, Coopers NeedleWorks Ltd.) so that the upper edge of the bevel was at the cerebellum surface. Thecannula was then lowered 100µm inside the cerebellum, left there for 2 minutes, andretracted 100µm. 1 to 1.5µL of the vector suspension was then infused at 0.1µL/mn. 10minutes after the end of the injection, the cannula was removed, lidocaine applied on thewound, and the scalp sutured. Animals were given 0.5mL of warm saline subcutaneously,0.05mL of Antisedan (0.2mg/kg) by IP injection, and placed under a heating lamp untilrecovery.

The following adeno-associated virus vectors were used: AAV2/1.hSynap.Flex.GCa-MP3.3.SV40 (5.57×1013GC/mL; catalog number: AV-1-PV1627, sequence: PennVectorP1627, University of Pennsylvania School of Medicine, Vector Core), AAV2/1.hSynap-.Flex.GCaMP5-G(GCaMP3(T302L).R303P.D380Y).WPRE.SV40 (1.47 × 1013GC/mL;catalog number: AV-1-PV2540, sequence: PennVector P2540, University of Pennsyl-vania School of Medicine, Vector Core) and AAV2/1.CAGGS.flex.ChR2.tdTomato.SV40

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(8.4×1012GC/mL; catalog number: AV-1-18917P, sequence: Addgene 18917, Universityof Pennsylvania School of Medicine, Vector Core). For GCaMP5-G/ChR2-tdTomato co-expression, 1.2 to 1.75µL of each vector suspension was mixed with 0.5µL of MethyleneBlue (1%), and 1.5µL of this mixture was injected. For GCaMP expression only (controlexperiments), 1 to 1.5µL of either AAV2/1.hSynap.Flex.GCaMP3.3.SV40 or AAV2/1-.hSynap.Flex.GCaMP5-G.SV40 was mixed with 0.5µL of Methylene Blue (1%), and 1to 1.2µL of this mixture was injected. Methylene blue served as a positive control forinjection of the suspension inside the parenchyma.

II. A.5.5 Cerebellar molecular layer interneurons (MLIs)

In order to test the fiberscope performances in vivo , we needed to access a reasonablenumber of neurons. We decided to keep the brain as intact as possible, and thereforechose a brain area where somata were accessible in the first tens of micrometers. Thecerebellum molecular layer interneurons were, due to their location, ideal.

Cerebellum anatomy, architectony, and physiology description is beyond the scopeof this work and can be found in textbooks and reviews [Ito, 2006, Apps and Garwicz,2005]. We will focus on the cerebellar cortex, comprising three layers, the granule layer,the Purkinje cells layer, and the molecular layer (Figure II.18).

Figure II.18: Diagram of the cerebellar cortex.

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II. A.5.5.1 Molecular layer interneurons : stellate and basket cells MLIs are small GABAer-gic neurons located in the cerebellar molecular layer. Their soma is about 5 − 10µm indiameter, and their dendritic arborization is remarkably planar. Indeed, dendritic pro-cesses are confined in a para-sagittal disk, of radius close to 50µm.

Stellate cells (SCs) are located in the outer region of the molecular layer, and givean axon targeting the Purkinje cells dendrites. Basket cells (BCs) are found deeper, andgive an axon terminal enwrapping Purjkinje cells soma and axon initial segment.

SCs and BCs form a network, coupled by inhibitory chemical synapses, and excita-tory gap junctions. However, electrical coupling via gap juntions is mainly limited todendrites, and therefore limited to a single para-sagittal plane.

II. A.5.6 AAVv injection : MLIs expression

AAVv-induced expression was characterized in slices of fixed cerebella, observed with aconfocal laser scanning microscope (Zeiss LSM510).

In PVCre+/- male mice injected with AAV2.1 vectors, co-expression of ChR2-td-Tomato and GCaMP5-G was complete in MLIs (513 cells from 5 mice) and reliable(Figure II.19). In these conditions, we considered that expression was largely specific toMLIs.

Figure II.19: Confocal laser scanning microscopy (Zeiss LSM 510) fluorescence imaging offixed cerebellar brain slices (molecular layer) from mice injected with AAV2.1-CAGGS-flex-ChR2-tdTomato and AAV2.1-hSyn-flex-GCaMP5-G. Left. Membrane localization ofChR2-tdTomato. Center. Cytosolic expression of GCaMP5-G in the same region. Right.Merged image showing co-expression of the two proteins in MLIs. Similar results wereobtained in 7 other mice. Cell counting gave 100% co-expression (n=513 cells from 5mice).

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II. B In vivo experimental results

The fiberscope presented in the previous section was tested in in vivo experimentalconditions. Indeed, its main purpose is to enable functional studies in the living animal atthe single cell scale, taking advantages of optogenetic tools. Therefore, the photoactivablecationic channel ChR2 and the fluorescent genetically encoded calcium indicator GCaMPwere coexpressed in cerebellar molecular layer interneurons (see Section II. A.5). Targetedphotoactivation and functional fluorescence imaging were simultaneously performed inliving mice, either anesthetized or awake.

II. B.1 Experiments in anesthetized mice - ChR2 and GCaMP3.3

Experiments were first conducted in mice co-expressing ChR2 and GCaMP3.3 in cere-bellar MLIs, under ketamine-xylazine anesthesia (Figure II.20).

II. B.1.1 Protocol for experiments in anesthetized mice.

Anesthesia was induced with isoflurane 5% saturated with O2 and an initial dose ofKetamine (77 − 120mg/kg) and xylazine (6.8 − 10.7mg/kg), and maintained with 25-33% of the initial dose administered every 30-45 minutes. The mice were held in arestraining frame (SG4N, Narishige) (Figure II.20) with eyecream and opaque paper onthe eyes to prevent dessication and potential damage caused by high light intensities usedduring surgery. Temperature was monitored with a rectal probe and kept close to 36°Cwith a homeothermic blanket (50-7221-R/F, Harvard Apparatus). SpO2 was monitoredwith an oxymeter (V3304, SurgiVet) and maintained above 90% with O2. After shaving,the scalp was incised, and the periosteum gently removed from the inter-parietal bone.A 2.7mm diameter craniotomy was performed with a trephine and a 26G needle to scorethe final second tablet. Meninges were kept intact, and moistened with HEPES bufferedartificial cerebrospinal fluid (in mM : NaCl 132 ; KCl 4 ; MgCl2 1 ; CaCl2 2.5 ; NaHCO3

2 ; HEPES 10 ; Glucose 25 ; pH adjusted to 7.3 with NaOH). The fiberscope was placedon the brain surface using a micropositioner. At the end of the experiments, cerebellawere fixed in 4% PFA for post-hoc analysis.

II. B.1.2 Imaging protocol

Functional imaging relied on fluorescence recording of GCaMP3.3 signal. In order tomaximize GCaMP3.3 excitation, we used a 491nm laser (Tian 2009).

At that point, our three imaging modalities, relying on different mirrors patterns dis-played on the DMD, were candidates for functional fluorescence recordings. Epifluores-cence provides fast and simultaneous imaging of the entire field-of-view. In comparison,structured illumination microscopy provides optical sectioning, but artifacts would resultfrom activity-related fluorescence changes. Finally, scanless multi-point confocal imagingcombines advantages of the two latter modalities, since it allows fast simultaneous multi-ple sites recording with optical sectioning. Nonetheless, the number of regions of interestis limited compared to widefield epifluorescence imaging. We decided to use SIM images

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Figure II.20: Picture of a mouse anesthetized with ketamine-xylazine, placed in therestraining frame, with the fiberscopic probe placed on the brain surface.

to locate target neurons, and to test epifluorescence and scanless confocal microscopy forfunctional fluorescence recording.

We first attempted to perform functional imaging using the widefield epifluorencemodality. However, even at relativeley low light power densities (Pi = 0.5mW/mm2),this approach resulted in a dramatic signal increase in single somatas (Figure II.21).Since 491nm light also activates ChR2 (Nagel), we interpreted this "unstable baselinefluorescence" as a result of photoactivation with the imaging laser.

Because stable baseline fluorescence would correspond to undetectable perturbationof neuronal activity, we aimed at decreasing the total amount of photons reaching thesample so that the imaging protocol would not affect the functional response of thesystem. We used the scanless confocal configuration to restrict illumination to the somataof interest. In these conditions, using the same power density than previously, the baselinefluorescence was stable from imaging onset to the end of acquisition (Figure II.21).

In order to minimise the effects of fluorescence imaging on ChR2 expressing neuorns,we performed all functional recordings in the scanless confocal configuration.

II. B.1.3 Photoactivation protocol

In ChR2 expressing MLIs, photoactivation was performed using a 473nm laser [Nagelet al., 2003], phase-modulated to generate 5µm diameter spots targeting single somata(see Section II. A.2). We illuminated cells for various periods of time, to evaluate thesomatic calcium signals amplitude. We found that relatively long pulses, of about 1s du-ration, produced a detectable fluorescence increase in single trials. Baseline was estimatedas the average ∆F/F before photoactivation. Figure II.22 shows that fluorescence signalfollowing a 1200ms photoactivation pulse increased, in this case yielding a fluorescenceincrease of more than 20%. The decay phase was approximated with the monoexponen-tial ∆F/Fp exp

−(t−tp)τ of decay time τ = 1s (see below), in red in Figure II.22, similar to

Tian 2009. ∆F/Fp is defined as the signal amplitude. Note that GCaMP3.3 is excitedby the photoactivation laser. Hence, fluorescence increase during photoactivation cannotbe used to infer neuronal activity, and was not recorded.

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Figure II.21: ChR2 and GCaMP3.3: imaging protocol. ∆F/F traces measured from a4.2µm region of interest placed on a cell body, for widefield epifluorescence (top trace)and scanless confocal (bottom trace) configurations (Pi = 0.5mW/mm2, exposure time= 40ms). In this experiment, the photoactivation laser was off. In the widefield config-uration, a dramatic increase of the fluorescence signal was observed after imaging onset.This was interpreted as a result of widefield photoactivation of ChR2 with the imaginglight. Keeping the same imaging power density and limiting imaging illumination to thesoma with a 4µm diameter spot (scanless confocal configuration) gave a stable baseline.This was taken as an unaffected neuron baseline activity. Traces shown are single trials.

No signal increase was observed in mice expressing only GCaMP3.3. (Figure II.22,bottom). Therefore, we interpreted the evoked fluorescence increase observed in ChR2-expressing mice as a consequence of light-induced ChR2 photocurrent leading to cytosoliccalcium increase, detected via GCaMP3.3 fluorescence changes.

Using our fiberscope, it was not possible to record electrically from MLIs during pho-toactivation and functional imaging. Hence, we were neither able to correlate GCaMP3.3fluorescence changes with spiking nor with firing rate. However, Franconville et al. haveperformed simultaneous in vivo electrophysiological recordings and calcium imaging, andreported that calcium signal rising phases corresponded to periodes of increased firingrates, while decay phases corresponded to silent periods [Franconville et al., 2011]. Intheir case, fluroescence calcium transients reported AP firing. We hypothesized that asimilar phenomenon occurred in our experiments.

Assuming that firing rate increased during photoactivation, we suggested that infor-

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Figure II.22: ChR2 and GCaMP3.3: photoactivation with a long pulse. Photoactiva-tion protocol (blue line) was a 1.2s light pulse with a 5µm diameter computer generatedholography spot, at a power density P = 100mW/mm2. Imaging was performed in thescanless confocal configuration, with a power density Pi = 0.5mW/mm2 and an exposuretime of 40ms, yielding a 18-20Hz acquisition rate. Acquisition is stopped during photoac-tivation. Signal traces shown are single trials. Top. Single cell somatic calcium signaltriggered by photoactivation between t = 0 and t = tp. Red, fit with a monoexponentialfunction of decay time τ = 1s. Bottom. The same experiment is repeated in a controlmouse expressing GCaMP3.3 only.

mation from this rising phase could be obtained by fractionating the single long pulse intoa train of short pulses and by acquiring an image between two photoactivation pulses.We targeted again single somatas with 5µm photoactivation spots, but the 1200ms lightpulse was replaced by either 20 pulses of 40ms or 24 pulses of 60ms. Figure II.23 showsthat fluorescence increase could be obtained with similar light power density. The decayphase was approximated with the same function, using the decay time τ = 1s, estimatedby averaging the τ extracted from 3 cells. The rising phase during photoactivation waslinear with the number of pulses, indicating that each photoactivation pulse drove ef-fective photocurrent. The overall shape of the evoked signal was very similar to whatwas observed by others [Franconville et al., 2011], suggesting once again that photoac-tivation evoked neuronal firing. We quantified the calcium signals by fitting them witha piecewise-defined function (in red in Figure II.23), composed of a linear rising phaseand a monoexponential decay phase defined by ∆F/F = ∆F/Fp exp

−(t−tp)τ with τ = 1s.

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Baseline was estimated as the mean value before photoactivation. The signal amplitude∆F/Fp was defined as the peak of the fit function.

These trains of light pulses had no detectable effect in mice expressing only GCaMP3.3(note the smaller sampling rate during photoactivation). Therefore, we assumed that thisphotoactivation/imaging protocol could successfully photoactivate MLIs and detect theresulting change in activity in anesthetized mice.

Figure II.23: ChR2 and GCaMP3.3: photoactivation with a train of pulses. Photoacti-vation protocol (blue line) was a 9Hz train of light pulses (24 pulses of 60ms duration)with a 5 micrometers diameter computer generated holography spot. Imaging was per-formed in the scanless confocal configuration, with a power density Pi = 0.5mW/mm2

and an exposure time of 40ms, yielding a 18-20Hz acquisition rate. Acquisition rate waslowered to 9Hz during photoactivation because imaging is only performed between thephotoactivation pulses. Signal traces shown are single trials. Top. Single cell somaticcalcium signal triggered by photoactivation between t = 0 and t = tp. Red, fit with apiecewise-defined function (linear rising phase and monoexponential decay of decreasetime τ = 1s). Calcium signal amplitude (∆F/Fp ) is the fit function amplitude attp. P = 75mW/mm2. Bottom. The same experiment is repeated in a control mouseexpressing GCaMP3.3 only. P = 100mW/mm2.

II. B.1.4 Photoactivation lateral resolution

Targeting a subset of cells in a homogeneous population is the main interest of a photoac-tivation light patterning technique. In order to characterize the lateral resolution really

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achieved in our anesthetized mouse model, we used the following protocol. A photoactiva-tion spot was placed on a MLI soma, and evoked a somatic calcium signal ∆F/Fp,on−cell .This photoactivation spot was then displaced from a distance d ∈ [0; 25µm] between thespot and the soma centrers by steps of 5µm from its original location, resulting in asomatic calcium signal ∆F/Fp,d . The displacement direction was in a plane orthogonalto the dendrites so that processes or coupling to other neurons via gap-junctions (Ref)would not confound our measurements. We calculated the remaining somatic calciumsignal R =

∆F/Fp,d

∆F/Fp,on−cell. Figure II.24 shows that signal amplitude was maximum when

somata were directly targeted. R decreased with d, and reached a plateau of about 0.15at 15µm. We evaluated the half-width at half-maximum of the curve d1/2 < 10µm;however, R did not reach 0 for any distance d. These results indicate that, first, ourphotoactivation protocol using 5µm spots provided reasonable spatial resolution; second,photoactivation light power density (P ) was probably too high to obtain complete signalextinction. We supposed that out-of-focus excitation was strong enough to drive somaticcalcium signals. However, when we then decreased P , the evoked signals became sosmall that we could not discern ∆F/Fp from noise. Indeed, in order to readily detectthe response to photoactivation, only cells displaying ∆F/Fp ≥ 10% were included. Wefound that only relatively high power densities (P = 50− 100mW/mm2) achieved theseamplitudes. In order to increase the response amplitude, we exchanged GCaMP3.3 forGCaMP5-G [Akerboom et al., 2012].

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Figure II.24: ChR2 and GCaMP3.3 : photoactivation lateral resolution. Ratio R =∆F/Fp,d

∆F/Fp,on−cellas a function of the distance d between the spot and the soma center in

the coronal plane. For each cell, the first and last measurements were performed with aphotoactivation spot on-cell. The first measurement was taken as ∆F/Fp,on−cell . Notethat R varied from 0.6 to 1.6 when the spot was placed back on-cell. Grey squares: datafrom n=5 cells from 3 mice. Black squares: mean of all data. Error bars represent 95%confidence intervals of the mean (CI95). Photoactivation protocols used were 20× 40msor 24 × 60ms; P = 50 − 100mW/mm2 depending on the cell. Imaging was performedin the scanless confocal configuration, with spots of 4 − 5µm diameter; Pi = 0.47 −0.67mW/mm2; Exposure time = 40ms

.

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II. B.2 Experiments in anesthetized mice - ChR2 and GCaMP5-G

In order to evoke large fluorescence signals (∆F/Fp ≥ 10%) with low photoactivationdensities (P ≤ 75mW/mm2), we exchanged GCaMP3.3 for GCaMP5-G [Akerboom et al.,2012]. Taking advantage of higher signal to noise ratio, we further characterized photoac-tivation lateral selectivity, studied photoactivation axial selectivity, and assessed lateralselectivity in groups of neurons Experiments were conducted in mice co-expressing ChR2and GCaMP5-G in cerebellar MLIs, under ketamine-xylazine anesthesia.

II. B.2.1 Imaging protocol

In anesthetized animals co-expressing ChR2 and GCaMP5-G in cerebellar MLIs, we con-firmed that baseline fluorescence stability at imaging onset depended on the amount oflight received by the cells. Indeed, at low imaging power density (Pi = 0.5mW/mm2)widefield uniform illumination resulted in an important fluorescence increase, not ob-served when reducing the illuminated area to one soma in the scanless confocal configu-ration (Figure II.25). Unstable baselines were also obtained using the latter modality byraising the power density above 1mW/mm2. Hence, functional recordings were performedusing the scanless confocal configuration at low power densities (Pi ≤ 0.5mW/mm2) inorder to keep the neurons unaffected by the imaging protocol.

II. B.2.2 Photoactivation protocol

We used trains of 24×60ms light pulses at 9Hz to elicit GCaMP5G fluorescence increasesin MLIs somata targeted with a 5µm photoactivation spot (Figure II.26, top trace).We observed a linear rising phase, followed by a decay phase when the photoactivationstopped, similar to the results obtained in ChR2-GCaMP3.3 animals. Again, this signalwas fitted with a piecewise-defined function of equation ∆F/F = ∆F/Fp exp

−(t−tp)τ ,

and ∆F/Fp was defined as the signal amplitude. The decay phase was approximatedwith a monoexponential of decay time τ = 0.96s, estimated as the average of singularτ extracted from 7 cells from 5 mice. This result was close to what Akerboom et alobserved [Akerboom et al., 2012]. As previously, we interpreted these evoked CGaMP5-G fluorescence increases as ChR2-photocurrent-dependent cytosolic calcium rises, andsuggested that they corresponded to increases in firing rates [Franconville et al., 2011].

Again, these evoked transients were not observed in the absence of ChR2 transduction(mean ∆F/Fp = 0.1%; CI95 = [−0.7; 0.9]; n = 48 cells from 3 mice, Figure II.26, bottomtrace).

Compared to signals obtained with GCaMP3.3, ∆F/Fp were much higher, which al-lowed us to decrease photoactivation power densities and still clearly detect the evokedresponses (Power densities range = 8 − 60mW/mm2). Overall, we used power den-sities similar to those reported in the literature for photoactivation of populations ofneurons [Aravanis et al., 2007, Huber et al., 2008].

Single spike generation with short photoactivation pulses (in the ms range) has beenreported many times [Boyden et al., 2005, Arenkiel et al., 2007, Tsai et al., 2009, Witten

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Figure II.25: ChR2 and GCaMP5-G: imaging protocol. ∆F/F traces measured froma 4.2µm region of interest placed on a cell body, for various configurations and powerdensities (Pi) of the imaging illumination beam. In this experiment, the photoactivationlaser was off. In the widefield configuration (top curve), at low power density (Pi =0.5mW/mm2), a dramatic increase of the fluorescence signal was observed after imagingonset. This was interpreted as a result of widefield photoactivation with the imaginglight. Keeping the same imaging power density and limiting imaging illumination tothe soma with a 4.2µm diameter spot (scanless confocal configuration) gave a stablebaseline (bottom trace). This was taken as an unaffected neuron baseline activity. ForPi ≥ 1mW/mm2, a small increase of the baseline was observed following imaging onset.Therefore, functional imaging was performed in the scanless confocal configuration withPi ≤ 0.5mW/mm2. The turquoise horizontal bar shows sample illumination with theimaging beam. Widefield ∆F/F trace is single trial. Confocal ∆F/F traces are obtainedby averaging 2 trials (1mW/mm2, 1.5mW/mm2, and 3mW/mm2), 3 trials (2mW/mm2)or 5 trials (0.5mW/mm2).

et al., 2010]. In order to test the fiberscope ability to evoke activity with such shortpulses, we targeted single somata with 60 × 5ms light pulses, and averaged over trials.Figure II.27 shows that a response with smaller amplitude but similar shape was evokedin these conditions (n=4 cells from 1 mouse). This result indicates that our system isable to drive photocurrents even with short pulses. However, 12 traces were averaged inorder to obtain a signal to noise ratio large enough to detect a calcium rise, and ∆F/Fp

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Figure II.26: ChR2 and GCaMP5-G: photoactivation protocol. Photoactivation protocol(blue line) was a 9Hz train of light pulses (24 pulses of 60ms duration) with a 5µmdiameter computer generated holography spot. Imaging was performed in the scanlessconfocal configuration, with a power density Pi = 0.5mW/mm2 and an exposure timeof 40ms, yielding a 18-20Hz acquisition rate. Acquisition rate lowers to 9Hz duringphotoactivation because imaging is only performed between the photoactivation pulses.Signal traces shown are single trials. Top. Single cell somatic calcium signal triggeredby photoactivation between t = 0 and t = tp. Red, fit with a piecewise-defined function(linear rising phase and monoexponential decay of decrease time τ = 0.96s). Calciumsignal amplitude (∆F/Fp ) is the fitting function amplitude at tp. Here, ∆F/Fp =107%. P = 25mW/mm2. Bottom. The same experiment is repeated in a control mouseexpressing GCaMP5-G only. P = 75mW/mm2.

were too small to comfortably perform resolution assays. Therefore, we kept on usingthe previous 24 × 60ms light pulses protocol, and found that it reliably evoked calciumsignals (n = 120 cells from 9 mice) in single cells for as long as 5 hours.

II. B.2.3 Photoactivation lateral resolution

We first repeated the photoactivation lateral resolution assay performed in GCaMP3.3animals. We then characterized lateral and axial resolution in single cells. Finally, westudied photoactivation selectivity in groups of neurons.

II. B.2.3.1 Single-cell assays. We quantified the somatic calcium signal ∆F/Fp,d when aphotoactivation spot was placed at a distance d from the soma, and calculated the ratioR =

∆F/Fp,d

∆F/Fp,on−cell(Figure II.28). Photoactivation lateral resolution was first measured

in the coronal plane, orthogonal to the sagittal orientation of MLI dendrites. Similarlyto the results obtained with GCaMP3.3, we found d1/2 < 10µm. However, when thephotoactivation spot was moved just 20µm away from the soma we found that the somatic

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Figure II.27: ChR2 and GCaMP5-G: photoactivation with short pulses. ∆F/F traceshowing a somatic calcium signal triggered by photoactivation with 60 light pulses of 5msduration at 18Hz, along a 5µm spot. The trace is an average of 12 trials on the samecell. A fit with a piecewise-defined function (linear rising phase during photoactivation(blue line) and monoexponential decay) is displayed in red. The amplitude of the calciumsignal (∆F/Fp ) is equal to 7.3% . Similar results were obtained in 3 other cells from thesame mouse. P = 60mW/mm2.

calcium signal vanished (d = 20µm, R = −9× 10−3 (CI95 = [− 7.1× 10−2; 5.3× 10−2]),n=14 cells from 7 mice).

In order to further characterize photoactivation lateral resolution, the spot was thendisplaced within an x-y grid of 15µm period (Figure II.29). Somatic calcium signals wereevoked when either the soma or the dendrites were targeted. Displacing the photoacti-vation spot at a distance d = 30µm from the neuron’s para-sagittal plane (soma and itsprocesses) dramatically decreased the amplitude of the response, with R = 5.3 × 10−2

(CI95 = [2.3× 10−2; 8.3× 10−2]; n = 4 cells from 1 mouse). R was averaged over all thelocations corresponding to d = 30µm in single cells, and then averaged over cells.

To complete the characterization of photoactivation spatial resolution, we measuredsomatic calcium signals when the photoactivation spot was moved along the axial di-rection. To achieve fast axial displacements of the fiberscope, the micro-objective wasmounted on a piezo-electric actuator (MIPOS100SG, Piezosystems Jena). A delay of 60ms was necessary for the device to change position and stabilize. After a soma locationwas determined using SIM, a photoactivation resolution assay was performed as follows.Photoactivation pulses were delivered at a distance z ∈ [0; 80µm] by steps of 10µm usingthe piezo-electric actuator. However, calcium imaging was always performed on-cell. Inconcrete terms, fluorescence was first recorded on-cell. The micro-objective was thenmoved above the cell at a desired position where a single photoactivation pulse of 1 sduration was delivered. As usual, no fluorescence was recorded during photoactivation.Finally, the micro-objective was moved back at its original location where fluorescence

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Figure II.28: ChR2 and GCaMP5-G: photoactivation lateral resolution. Ratio R =∆F/Fp,d

∆F/Fp,on−cellas a function of the distance d between the spot and the soma center in

the coronal plane. For each cell, the first and last measurements were performed with aphotoactivation spot on-cell. The first measurement was taken as ∆F/Fp,on−cell . Greysquares: data from n=14 cells from 7 mice. Black squares: mean of all data. Error barsrepresent 95% confidence intervals of the mean (CI95). P = 8− 50mW/mm2 dependingon the cell. Only cells displaying ∆F/Fp,on−cell ≥ 20% were included.

Figure II.29: ChR2 and GCaMP5-G: 2D photoactivation lateral resolution. Mean ratioR =

∆F/Fp,d

∆F/Fp,on−cellobtained when a photoactivation spot was displaced along a x-y grid of

15µm period (n=4 cells from 1 mouse); right, look-up table; below, a MLI is representedin green with dendrites along a parasagittal plane. P = 40− 60mW/mm2 depending onthe cell. Only cells displaying ∆F/Fp,on−cell ≥ 20% were included.

was recorded again. Hence, traces resembled those presented in Figure II.22. RatiosR =

∆F/Fp,z

∆F/Fp,on−cellwere then plotted against the distance z from the soma (Figure II.30),

showing that somatic calcium signal decreased as the spot was displaced away from the

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cell body (R<0.5 for z < 30µm, n=3 cells from 1 mouse). This axial resolution, largerthan in the lateral plane, is expected considering the extent of MLIs dendrites and axialpropagation of the photoactivation beam (see Figure II.8). Indeed, although we cannotrule out a small contribution of out-of-focus excitation of the soma, this difference canbe mostly explained by excitation of ChR2 in dendrites located in the imaging plane,above the soma. In any case, it still provides spatial selectivity compatible with neuronaltargeting.

Figure II.30: ChR2 and GCaMP5-G: photoactivation axial resolution. Ratio R =∆F/Fp,z

∆F/Fp,on−cellas a function of the distance z between the spot and the soma center in

the axial direction. For each cell, the last measurement was performed with a photoac-tivation spot on the cell. Ratio R =

∆F/Fp,z

∆F/Fp,on−cellwas computed with the highest ∆F/Fp

value as ∆F/Fp,on−cell , due to the relative incertitude in the cell position resulting fromthe probe movement at the brain surface. Grey squares: data from n=3 cells from 1mouse. Black squares: mean of all data. P = 50mW/mm2. Only cells displaying∆F/Fp,on−cell ≥ 20% were included.

II. B.2.3.2 Multiple-cell assays. We then assayed photoactivation selectivity and calciumsignal specificity in sub-populations of neurons (Figure II.31). MLIs were chosen so thattheir soma were in different para-sagittal planes.

We first sequentially photoactivated every single MLI in groups of 5 cells, evokinga response ∆F/Fp,on−cell in the target neuron (Figure II.31, left). We measured thecalcium signal amplitude ∆F/Fp,off−cell in the 4 non-targeted cells. For each neuron,we averaged the 4 ∆F/Fp,off−cell amplitudes obtained when the 4 other neurons were

successively targeted, and computed the ratio Rm =mean(∆F/Fp,off−cell)

∆F/Fp,on−cell. Results showed

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Figure II.31: ChR2 and GCaMP5-G: multiple-cell assays. Simultaneous targeting ofmultiple cells. Top. SIM images. Blue disks indicate positions of photoactivation spots.For readability, their diameter is displayed larger than their actual size in the sample.Grid period: 43µm. Exposure time: 3 × 40ms. Bottom. Corresponding ∆F/F tracesregistered simultaneously in five cells, numbered from 1 to 5 and located in differentparasagittal planes. Left: only cell # 1 was targeted by a photoactivation spot. Center:the 5 cells are simultaneously targeted with a photoactivation spot. Right: The photoac-tivation spot that targeted cell # 1 has been displaced 20µm away in the coronal plane.P = 30mW/mm2.

that one cell could be specifically selected for photoactivation from this homogeneouspopulation (Rm = 6× 10−3; CI95 = [− 1.4× 10−2; 2.6× 10−2]; n= 27 cells from 6 mice).This also suggested that, in these conditions of anesthesia and photoactivation, targetedMLIs were not coupled by any strong excitatory electrical or chemical synapses.

A critical parameter for photoactivation spatial resolution is the photoactivation spotsdensity. Indeed, integrated excitation density (in single photon experiments) is constantin a plane perpendicular to the optical axis. Even though the photoactivation spot isspatially confined in focus, the beam diverges out of focus and can affect excitable struc-tures. The more spots are placed in the sample, the more likely out of focus structures,such as dendrites, may be excited and alter photoactivation spatial selectivity. For this

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reason lateral resolution was tested while several (5) cells were photoactivated simul-taneously. We first targeted the 5 neurons simultaneously, eliciting a calcium signal ofamplitude ∆F/Fp,on−cell in each soma (Figure II.31, center). We then displaced one of thefive photoactivation spots by 20µm, our effective lateral resolution in single-cell assays,in the coronal plane, and measured the remaining response in the corresponding soma∆F/Fp,off−cell (Figure II.31, right). Computing the ratio R showed considerable decreasein the corresponding cell response (R = 0.16; CI95 = [0.096; 0.23]; n= 26 cells from 5mice). This recording of calcium response from targeted neurons showed that resolutionto the cellular level could be achieved when photoactivating a sub-population of ChR2-expressing MLIs. However, R was statistically different from 0 when 5 photoactivationspots were placed in the sample, contrasting with previous results. We hypothesized thatthe increased total amount of light was responsible for a depolarization of the untargetedcell, and that it should be reduced for complete signal extinction. However couplingmechanisms could not be rejected with these experiments.

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II. B.3 Experiments in awake, freely behaving mice

One of the main interest and most promising perspective of our fiberscope would be itsuse in freely behaving animal (see chapter I). Therefore, we designed a head-plate andmicro-objective holder to evaluate the fiberscope performances in awake, unrestrainedmice. In order to characterize the fiberscope imaging capabilities in freely behavingmice, we used P65-P70 double heterozygous PV-Cre; Rainbow [Tabansky et al., 2013]mice. In these PV-Cre; Rainbow animals, eYFP expressed in Purkinje cells. Animalsco-expressing ChR2 and GCaMP5-G in cerebellar MLIs (as in subsection II. B.2) wereused for imaging characterization and to evaluate photoactivation performances.

II. B.3.1 Protocol for experiments in freely behaving mice.

II. B.3.1.1 Head-plate fixation. In order to perform imaging and photoactivation inawake, freely behaving mice, the micro-objective has to be very stable at the brainsurface.

We first designed a single-component holder, made of a headplate and a tube-likepart receiving the micro-objective. We tried to glue it on clean and scrubbed skulls withcyanoacrylate, but found the attachment very loose. Besides, the tube-like part wasrather cumbersome and would have made the craniotomy very uncomfortable for theexperimenter. Therefore, we conceived a two-component system, made of a head-plateand a micro-objective holder. The head-plate was embedded in dental cement, and theholder was screwed in the head-plate, either for animal habituation or after craniotomyto perform the experiment. This approach worked indeed for animal habituation, somuch that we surprisingly found it unnecessary. In fact, a 30 minutes period was alwaysneeded for the animal to habituate to a fake fiberscopic probe, independently of thetraining session. However, rotation of the holder prevented further experimentation inawake unrestrained mice. Hence, we decided to modify the holder so that it could becemented to the head-plate. The detailed protocol, that gave satisfactory results, isdescribed below.

The head-plate (Figure II.32) was fixed at P62-P68 in PV-Cre; Rainbow mice and 29to 86 days post injection in AAV-injected mice. Animals were anesthetized with isofluranesaturated with O2, at an initial amount of 5%, adjusted to the minimal amount prevent-ing pain reflexes (3-5%). Mice were placed in a restraining frame (SG4N, Narishige), ona heating pad, with eyecream and opaque paper on the eyes to prevent dessication andpotential damage caused by high light intensities used during surgery. Buprenorphine(20µg/kg) was injected intraperitoneally for analgesia during surgery. After shaving,the scalp was incised and the periosteum removed. The skull (parietal and interparietalplates) was cleaned up and gently scrubbed with a delicate bone scraper, and H2O2 wasapplied with a cotton bud. Optibond FL primer and adhesive (Kerr) were applied. Thehead-plate (0.25g) was positioned on the skull using an epifluorescence stereo-microscopeto detect the pre-injected fluorescent lobule through the skull, and then cemented lateralto the earlier injection site using photopolymerizable Tetric Evoflow material (Ivoclar Vi-vadent). The skin was then closed with surgical glue (Vetbond) (Figure II.33). An addi-

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tional dose of buprenorphine (20µg/kg) was injected intraperitoneally for post-operativeanalgesia, before placing the animal back in its cage.

Figure II.32: Top and side views of the head-plate (right, 0.25g) and micro-objectiveholder (left, 0.23g) with a centimeter scale. The two custom-made pieces are made inaluminum; the screws (0.13g each) are in stainless steel.

Figure II.33: Picture of an anesthetized mouse, with a head-plate fixed.

The head plate did not affect the mice behaviour, and normal exploration, eating,gnawing, grooming, jumping and sleeping behaviours were observed during the days

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following the surgery (Figure II.34).

Figure II.34: Picture of an awake mouse, with a head-plate fixed.

II. B.3.1.2 Surgery and micro-objective fixation. Experiments were conducted 3 to 4 daysafter head-plate fixation. Animals were anesthetized with isoflurane saturated with O2,with an initial volume of 5% adjusted to the minimal amount preventing pain reflexes(3-5%). Mice were placed in a restraining frame (SG4N, Narishige), on a heating pad,with eyecream and opaque paper on the eyes. Buprenorphine (20µg/kg) was injectedintraperitoneally for analgesia during the surgery. A 2.7mm diameter craniotomy wasperformed using a trephine and a 26G needle to score the final second tablet (FigureII.35). Meninges were kept intact in six mice (and accidentally slightly opened in 2 mice)and kept moistened with HEPES buffered ACSF. The micro-objective was then placedjust touching the brain surface. Agar in ACSF (2%) was used to fill any small spacesbetween the head-plate and objective. Two M2 screws (0.13g each) were used to holdthe micro-objective to its holder (0.23g). The holder was then fixed to the head-platewith Tetric Evoflow photopolymerizable cement, before being filled with agar in ACSF(2%). An additional dose of buprenorphine (20µg/kg) was injected intraperitoneally forpost-operative analgesia before placing the animal back in the experimental cage.

II. B.3.1.3 Experiments in awake mice. A cage of dimensions 40×25×20cm3, containing2 to 3 food pellets was placed on a rotating tray. The animals were put in the experi-mental cage at least one hour before anesthesia in order to habituate them to their newenvironment. During the experiment, starting about 1 hour after the surgery, no con-strains were applied to the mice, and they could behave freely in the cage (Figure II.36).In an effort to limit any excess torque and possible slippage of the micro-objective, weinitially manually rotated the cage. Since then, however, we have found that the mice donot torque the fiber much, and we could let them behave freely and self correct withoutrotating the cage. A red LED and a CCD camera (Orca 05G, Hamamatsu) were used to

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Figure II.35: Picture of an implanted mouse in which a craniotomy has been performed.

film the mouse during the experiment. Normal exploration, eating, gnawing, grooming,jumping and sleeping behaviours were observed during the experimental sessions (up to8 hours).

Figure II.36: Picture of a mouse freely behaving in its cage, with the fiberscopic probefixed to the skull using the head-plate and holder.

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II. B.3.2 Imaging in freely behaving mice

Figure II.37: SIM images of the cerebellar molecular layer recorded in freely behavingmice. Left. Image of eYFP-expressing Purkinje cells dendrites in a PV-Cre; Rainbowmouse. Right. Image of molecular layer interneurons in a AAV-flex-ChR2 and AAV-flex-GCaMP5G double injected PV-Cre mouse. (Inset: enlargement of a single MLI). Scalebars: 10 µm. Grid period: 43 µm. Exposure time: 3× 200µm.

The first difficulty to overcome in freely behaving animal is movement artifacts. Toevaluate field-of-view stability, we considered a stack of epifluorescence images (for highfrequency movements characterization) or SIM images (for low-frequency movements)recorded during the time course of the experiment. One of these images was chosen asthe reference image I, and rotated by a set of angle θi (Iθi). For high-frequency movementcharacterization, only θi (Iθi = 0 was considered. Every image S was translated by x,y and we calculated 2D normalized cross-correlation of S with each Iθi. For each imageS, the rotation θ, the translations x and y are the values maximizing the correlationcoefficient:

Cθi(xi, yi) =

∑

x1,y1

[

S (x1, y1)− S] [

Iθi (x1 − xi, y1 − yi)− I]

∑

x1,y1

[

S (x1, y1)− S]2∑

x1,y1

[

Iθi (x1 − xi, y1 − yi)− I]20.5 (II.14)

where I is the mean of Iθi, and S is the mean of S in the same cropped region as Iθi.Similarly to other fiberscope implementations [Murayama et al., 2007, Flusberg et al.,

2008, Sawinski et al., 2009], we found that the field of view remained stable during highfrequency (20 Hz) wide-field acquistions in PV-Cre; Rainbow mice (Figure II.38). Onaverage, the maximum movements during 100 s were x = 1.6µm and y = 1.2µm (n=30acquisitions from 3 mice) (Fig 3e). Overall, the maximum movement in x or y duringan 100 second period was smaller than 3µm. We concluded that the scanless confocalconfiguration was still a good option for functional fluorescence imaging, and anticipatedthat photoactivation should still be accurate.

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Figure II.38: High frequency movements of the field of view in freely behaving mice. Left;Position of the field of view along x and y monitored at 19Hz during 100s in 3 Rainbowmice. Behaviour of the mouse is indicated as background color; blue: locomotion; yellow:head movement; green: eating; grey: still. For each mouse, this experiment is repeated 10times, and the maximum displacements ∆x and ∆y for each acquisition are reported onthe figure on the right (blue squares and red triangles resp). Note that several acquisitionsgave the same amount of displacement. Averages of maximum movements along x and yover 10 acquisitions are given by black squares and black triangles respectively, for eachmouse. Error bars correspond to CI95.

We also found that the field of view remained stable over long periods of time, witha mean translation and rotation of x = 8.1µm, y = 5.2µm, θ = 1.7° during 200 minutes(n = 6 mice, 2 PV-Cre; Rainbow and 4 AAV-injected PV-Cre) (Figure II.39) and allthe animal activities. Quantification of the field of view movement was conducted in8 freely behaving mice (5 mice expressing ChR2 and GCaMP5-G in MLIs, and 3 miceexpressing eYFP in Purkinje cells). However, in 2 of these mice (one of each type) theexperiment lasted only for approximately 2 hours before the field-of-view went out offocus. Therefore, data from 6 mice only are presented in Figure II.39. In conclusion, ourimplementation should allow experimentation in a stable field of view for at least a fewhours.

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Figure II.39: Low frequency movements of the field of view in freely behaving mice.Quantification of the field of view lateral translation (x, blue squares and y, red triangles)and rotation (θ , green circles) for 200 minutes in 6 mice (2 PV-Cre; Rainbow and 4AAV-injected PV-Cre mice). Top. Field of view translation and rotation in each of the6 mice (one panel per mouse). Bottom. Maximum translation (∆x, blue squares, ∆y,red triangles) and rotation (∆Θ, green circles) for each mouse. Average displacementsover mice are given by black squares (∆x), triangles (∆y), and circles (∆Θ). Error barscorrespond to CI95.

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II. B.3.3 Photoactivation in freely behaving mice

The same imaging/photoactivation protocol used in anesthetized mice was repeated infreely behaving animals to photoactivate single somata. The results showed that calciumsignals could be similarly elicited in the targeted cells (n = 41 cells from 5 mice, FigureII.40). However, baseline level and decay time τ could no more be estimated as theaverage signal before photoactivation, due to baseline instability (see Section II. B.3.5).Therefore, the calcium signal analysis was done as follows. A first estimation of thedecay time (τ0) was obtained using the same protocol as for the anesthetized animals.The decay time τ was then better estimated by fitting the experimental data betweent = 0 and t = tp + 5τ0 with the previous piecewise-defined function (variables: ∆F/Fp

and τ). τ values were extracted from 28 traces obtained in 28 different cells and averaged,giving an estimate of the decrease time in the freely behaving animal (τ=0.81s, CI95 =[0.67s; 0.94s]; n=28 cells from 3 mice). To measure calcium signal amplitudes, we thencalculated F0 as the average of F values in the intervals [−3s; 0] and [tp+5τ ; tp+5τ+3s],and plotted the ∆F/F signal by computing F−F0

F0. ∆F/Fp was determined by fitting the

∆F/F signal in the interval [0; tp + 5τ ] with the previous piecewise-defined function(variable: ∆F/Fp ). Only cells displaying a ∆F/Fp larger than 20% were included in theanalysis. Again, we assumed that these evoked signals corresponded to neuronal firingrate increase.

Figure II.40: Photoactivation in freely behaving mice. Single cell somatic calcium signaltriggered by photoactivation (blue line) (P = 50mW/mm2). Red, fit with a piecewise-defined function (linear rising phase and monoexponential decay). Trace is single trial.

II. B.3.4 Photoactivation lateral resolution in freely behaving mice

We then measured photoactivation lateral resolution in freely behaving animals in single-cell photoactivation assays. We found that the remaining signal when the spot was dis-placed by d = 30µm in the coronal plane was R = 2.67 × 10−2 (CI95 = [ − 6.06 ×10−2; 11.4 × 10−1], n=18 cells from 5 mice) (Figure II.41) and concluded that photoac-tivation was almost as accurate in freely behaving mice as in anesthetized animals, withd1/2,awake ≤ 10µm, d1/2,anesthetized < 10µm and a signal vanishing at d = 30µm in awakemice versus d = 20µm in anaesthetized ones (Figure II.41).

To confirm overall stability of photoactivation and imaging in the awake behaving

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Figure II.41: Photoactivation lateral resolution in freely behaving mice. Ratio R =∆F/Fp,d

∆F/Fp,on−cellas a function of the distance d between the spot and the soma center in the

coronal plane. For each cell, the last measurement was performed with a photoactivationspot on the cell and was taken as ∆F/Fp,on−cell . Grey squares: data from n=18 cellsfrom 5 mice. Black squares: mean of all data. Error bars represent 95% confidenceintervals of the mean. P = 25− 75mW/mm2.

mouse, we repeated our photoactivation protocol every 30s for 15 minutes without repo-sitioning the photoactivation spot. In this case a calcium signal was evoked every time,confirming that displacement of the field of view did not affect our ability to target a cell(n=3 cells from 1 mouse) (Figure II.42).

Figure II.42: Photoactivation repeatability in a freely behaving mouse. The same pho-toactivation protocol (blue lines) is repeated every 30s for 15min (P = 50mW/mm2,Pi = 0.28mW/mm2). Trace has been low-pass filtered with a 5-point moving averagefilter. Note the spontaneous activity frequently occurring between evoked transients.Trace is single trial.

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II. B.3.5 Spontaneous activity in freely behaving mice

Spontaneous calcium transients were recorded in 20 out of 41 photactivated cells of thefreely behaving mice (Figure II.40, bottom and Figure II.43). It is unlikely that our imag-ing protocol was responsible for these events, since the photoactivation threshold seemedunchanged if not higher in awake than in anesthetized animals (range of photoactiva-tion power densities used for all experiments: Pawake = [25mW/mm2; 75mW/mm2],Panesthetized = [8mW/mm2; 60mW/mm2]) and imaging power densities were kept identi-cal if not lower (Pi,awake = [0.28mW/mm2; 0.5mW/mm2], Pi,anesthetized = 0.5mW/mm2).Besides, it is unlikely that these transients were movement artifacts since they were al-ways positive, contrary to random events corresponding to somata moving in and out ofthe confocal spot. One plausible explanation for this spontaneous activity not observedin the anesthetized animals is a reduced suppression of inhibitory cell activity in the ab-sence of anesthetics [Haider et al., 2012]. These neurons would fire preferentially duringcertain behaviours, accessible in awake, behaving animals.

Figure II.43: Spontaneous activity in freely behaving mice. Single cell spontaneoussomatic calcium signals recorded in the scanless confocal modality during 65s. Trace hasbeen low-pass filtered with a 5-point moving average filter.

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II. B.4 Conclusion

In this work, we developed and tested a novel fiberscope designed for simultaneous tar-geted neuronal photoactivation and fonctional fluorescence imaging in freely behavingrodents with near single-cell resolution. We used AAVv-transduced mice co-expressingChR2 and GCaMP in cerebellar MLIs. Although ChR2 and GCaMP activation andexcitation spectra overlap, we found conditions allowing stable fluorescence recordings.

The fiberscope made use of CGH to perform targeted photoactivation. The pho-toactivation protocol used in this study reliably evoked calcium transients in single- ormultiple-cell, recorded with either GCaMP3.3 or GCaMP5-G.

We performed fluorescence imaging with three modalities, by displaying differentmirror-patterns on the DMD. The first modality, widefield epifluorescence, provided im-ages from the entire field of view and was used to place the fiberscope over a brain regionof interest. SIM, the second modality, was used to precisely locate neurons, taking advan-tage of the optical sectionning capability of this technique. Finally, the third modalitycalled scanless multi-point confocal imaging allowed simultaneous functional recordingfrom multiple locations, with single-neuron spatial resolution.

Experiments led in awake unrestrained mice showed a remarkable stability of thefield of view lasting for as long as 8 hours. High-frequency movements were overall lessthan 3 micrometers, and low-frequency movement across 200 minutes sessions were lessthan 10 micrometers in average. Besides, we did not notice any obvious photodamage,based on cells’ fluorescence intensity and responsiveness to photoactivation. Thus, wewere able to photoactivate and record from single neurons for hours. Photoactivationlateral resolution in anesthetized and awake animals was similar, with d1/2 < 10µm, anda signal close to 0 at a distance from the soma d = 20µm in anaesthetized and d = 30µmin freely behaving mice.

In conclusion, the features of this fiberscope are compatible with simultaneous func-tional fluorescence recordings and targeted photoactivation of single-neurons in freelybehaving mice.

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Chapter III

Discussion

Contents

III. A Optogenetics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97

III. A.1 Optogenetics side-effects . . . . . . . . . . . . . . . . . . . . . 97

III. B Optogenetics in freely moving mice with a fiberscope . . . . . . . . . 100

III. B.1 Experimental design . . . . . . . . . . . . . . . . . . . . . . . 100

III. B.2 Setup development . . . . . . . . . . . . . . . . . . . . . . . . 101

III. B.3 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

III. A Optogenetics

III. A.1 Optogenetics side-effects

Optogenetics provides promising tools for functional investigations in Neuroscience. How-ever, the consequences of the procedure leading to proteins expression, protein expressionitself, and activation of photoactivable proteins should be carefully considered.

III. A.1.1 Means of proteins expression

There are several ways to express optogenetic tools in the brain. We will review themand discuss their respective advantages and drawbacks.

III. A.1.1.1 Intracerebral injection of viral vectors. Intracerebral injection of viral vectoris a widely used approach. The vector contains and delivers the transgene to the tar-get cells, resulting in optogenetic tool expression. Virus vectors are relatively easy todevelop and to employ. For these reasons, they allow optogenetic tools screening andprovide great flexibility in the target area by changing injection sites. Besides, condi-tional expression systems, such as the cre-lox system, allow efficient cell-type targeting.However, introduction of the injection canula inside the brain results in blood-brain-barrier (BBB) disruption. Diffusion of plasmatic elements, such as antibodies, inside

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the parenchyma can alter the neurophysiology of the affected area. Also, viral vectorparticles recruit glial cells at the injection site, either by themselves or through neuronalinfection. Finally, several weeks of transgene expression are often needed to reach usablelevels of optogenetic proteins. Hence, studies in prenatal and perinatal animals are notconceivable with this approach. All the same, we consider intracerebral injection of viralvectors a reasonable option, especially when transgenic lines are not available or do notprovide high-enough levels of expression (see below).

III. A.1.1.2 Intravascular injection of viral vectors. An alternative approach to get viralvectors inside the central nervous system is to inject the suspension in the periphery, forexample in the blood compartment [Iwata et al., 2013]. A limitating step here is theBBB, which has to be crossed by the vector, limiting the usable viral vector type andserotype. Besides, targeting of a brain area is less straightforward than with direct insitu injection. Finally, this approach does not allow studies in younger animals than withintracerebral injection. To our knowledge, this method is not easily usable yet.

III. A.1.1.3 Neonatal intracerebroventricular injection of viral vectors. A recent reportshowed that intracerebroventricular injection of viral vector in neonatal mice could lead totargeted expression of optogenetic tools [Chakrabarty et al., 2013]. Because the immunesystem of very young animals does not give any strong response to BBB disruption orinfection, this approach seems to be less invasive than injection in older animals. Eventhough normal development of the nervous system and mothering should be carefullyfollowed, this technique might be quite promising.

III. A.1.1.4 In utero electroporation Non-viral vectors can also be used to obtain opto-genetic tools expression. In utero electroporation of plasmidic constructs has been usedto target protein expression to neuronal cell types in pre and post natal animals [Kolket al., 2011]. Even though a certain spatial restriction in the expression pattern has beenobserved, the number of potential targets seems limited to certain cell types, so that thisapproach does not seem to offer much flexibility in the target brain areas and neurontypes. Besides, late differentiation of neuronal lines might lead to wide expression of thetransgene, hindering expression specificity. This technique is probably restricted to alimited number of applications.

III. A.1.1.5 Transgenic lines: expression level, flexibility Finally, transgenic mice linescarrying optogenetic genes have been and are continuously being developed (for examples,visit the Allen Institute for Brain Science website). These tools are very useful in thesense that expression can be chronic, or induced acutely with exogenous molecules suchas tetracyclins [Sun et al., 2007]. Besides, lines carrying specific expression in target cell-types are becoming available. Expression levels in these conditions seem much lower thanwith viral vectors. Hence, photoactivation of optogenetic tools may require high lightpower densities, while level of protein expression might be less toxic. Expression levels arealso much more homogeneous across the cell population, facilitating comparative studies

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across different neurons. The main limit of this approach is that mice line generation isexpensive, requires relatively long delays (months to years), and does not provide anyflexibility in the transgene. However, once an appropriate line is acquired, its use doesnot require complicated preparation procedures and should be reproducible.

III. A.1.2 Proteins expression consequences

Expression of exogeneous proteins can affect the biological system under studies. De-pending on the nature of molecule, various side-effects can be envisaged.

III. A.1.2.1 Chelators Expression of fluorescent ion chelators, such as GCaMP proteins,might alter cellular proteins steady-state when chronically expressed, or ions steady-statein acute expression conditions. Even if this might not have significant or direct impact onelectrophysiological properties, it may interfere with intracellular signaling. This shouldbe studied and taken into account especially in studies of networks long-term dynamic.

III. A.1.2.2 Membrane proteins Expression of membrane proteins, such as VSFP or pho-toactivable ions channels (i.e. ChR2) and pumps can directly affect membrane properties.Indeed, membrane capacitance and conductance at the steady-state depend on membranemolecular composition. By introducing new components, intrinsic passive properties canbe modified. This should be carefully considered when focusing on network functionalproperties.

III. A.1.3 Consequences of opsins photo-activation on cell biology

Ion channels photoactivation leads to ion fluxes through the membrane. We will focuson ChR2 as one example. We saw in subsection I. B.2 that proton is the prominent ionflowing through ChR2. This might have consequences on intracellular pH buffers. Be-sides, calcium ions are also permeant, and could activate intracellular signaling pathwaysleading to non-physiological long-term alteration of neurons and networks properties.However, we have to say that sodium conductance being much larger than calcium con-ductance, these potential effects might be negligible (at least with the native ChR2).

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III. B Optogenetics in freely moving mice with a fiberscope

In this work, we developed a fiberscope allowing simultaneous neuronal photoactiva-tion and functional fluorescence calcium imaging with near cellular resolution in freelybehaving mice.

Compared with microscopes designed for head-restrained behaving rodents, our de-vice is less constraining, and as such readily enables studies of neuronal activity andnatural behaviors (see section I. A).

Previous implementations of targeted photoactivation in living rodents have beenlimited to anesthetized animals [LeChasseur et al., 2011, Dhawale et al., 2010, Wilsonet al., 2012, Hayashi et al., 2012]. Photoactivation in freely behaving mice and rats haveso far been using wide field illumination (see subsection I. B.3), leading to excitationvolumes of several hundreds of microns on a side. Our fiberscope is to our knowledge theonly optical system permitting photoactivation along easily reconfigurable patterns withnear cellular resolution in freely behaving rodents.

Although single photon functional imaging has been performed in freely behavingrodents with scanless epifluorescence microscopy, this was without any sort of opticalsectioning (see subsectionI. C.1). Our fiberscope, on the other hand, can be used for epi-fluorescence, structured-illumination and multi-point confocal imaging, with the lattertwo modalities providing scanless optical sectioning. Functional imaging in freely behav-ing rodents has been performed with a two-photon microscope, providing better spatialresolution and greater imaging depth (see subsectionI. C.2). Our system, however, hasa larger field of view, permits simultaneous imaging at multiple sites, and the lighterhead-mounted part facilitates experimentation in mice. Our fiberscope can be imple-mented with any visible light source, and is therefore compatible with any optogenetictool of choice. In particular, complete uncoupling between ChR2 photoactivation andcalcium imaging could be achieved using a red calcium indicator. Imaging power density,in that case, would not be limited by ChR2 activation and therefore could be increased,enabling higher imaging speed and/or signal to noise ratio. Moreover, the optical setupcan be tuned for simultaneous multi-color imaging, facilitating functional interrogationof various disparate structures.

The next paragraphs explore some potential improvements in the experimental de-sign, propose technical developments of the whole setup, and suggest a few biologicalinvestigations enabled by the fiberscope as it is now.

III. B.1 Experimental design

The experimental procedure, as described in chapter II, subsections II. A.5.4 and II.B.3.1, comprises two sequential surgeries at the same location, the first for virus vectorinjection, the second to get access to the area of interest with the fiberscope. In practice,this adds a noticeable difficulty from the technical point of view. Indeed, healing from thefirst craniotomy generates fibrosis between the renewed bone and the meninges, makingthe second surgery arduous.

Then, alternatives to this double surgery should be considered. A solution would be

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to use mice lines expressing the optogenetic tools in the cells of interest. Supposing thata given mice line is not available, optogenetic tools expression might also be obtainedby retrograde labelling through virus vector injection in a remote projection location.Then, the first surgery would not affect the second one. If, for any reason, in situvirus vector intracerebral injection cannot be circumvented, a possible option could beto create a chronic window in the skull. A large craniotomy would be performed, so thatthe fiberscope tip would access the brain surface without further surgery. We started totest this, performing a large craniotomy the day of injection and fixing the head-plate onthe same day. The craniotomy and the head-plate hollow were filled with agar, and sealedwith a glass coverslip. Through this window, we could follow bone regrowth, effectiveenough to impair experimentation two weeks after surgery. This procedure worked once,allowing stable imaging of dendrites for a few hours. Even though it is too early toconclude on the actual suitability of this approach, it seems to be worth developing itfurther.

III. B.2 Setup development

III. B.2.1 Single-photon fiberscope

The current fiberscope suffers from three main limitations. The first one is the micro-objective short working distance (60 µm). Second, the fiberscope does not suit for chronicimaging of the same area, although this is of paramount importance for investigatingcell assembly dynamics during learning. Third, the relatively important micro-objectiveouter-diameter (2.6 µm) prevents deep implentation inside small rodents’ brain. Thesethree weaknesses can be easily overcome by the use of another micro-objective. First,a longer micro-objective working distance would allow both access to slightly deeperstructures and use of the fiberscope with sealed chronic windows. Indeed, in our caseat least, imaging was performed at up to 60 µm depth, and would probably have beenpossible at up to 100 µm. Then, if a correct chronic window were implanted, time-lapseimaging over days would be enabled by simply approaching the micro-objective to thewindow surface, providing the working distance is long enough to reach the desired area.Second and alternatively, chronic implantation of the micro-objective would provide aconstant field of view during chronic experimentation. The fiber bundle would then beplugged on the days of experiment and removed on the others. This approach has beensuccessfully implemented by Ziv et al. [Ziv et al., 2013] (without a fiber bundle) and iscertainly appealing [Ziv et al., 2013]. Third, deep structures such as deep nuclei couldbe accessed with a much smaller micro-objective, of, for example, about 1 mm outer-diameter (although what is reasonable to insert inside a rodent’s brain is subjective, forexample Ziv et al and Dombeck et al. inserted canulas of about 2.5 mm diameter toreach the hippocampus [Ziv et al., 2013, Dombeck et al., 2010]).

As a remark, it is pointed out that a second imaging optical pathway can easilybe added to the existing fiberscope, so that simultaneous multi-color imaging could beperformed.

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III. B.2.2 Two-photon fiberscope

Of course, single-photon fluorescence will always be limited to "surface" structures be-cause of light scattering in brain tissue. This is the reason why two-photon fluorescenceimaging is so attractive to neuroscientists. As discussed in Subsection I. C.2, several two-photon fiberscopes have been developed, all of them dedicated to imaging. However, webelieve that testing the cell assembly hypothesis would benefit from optogenetic actua-tors photoactivation. Inspired from our single-photon fiberscope, a two-photon fiberscopemaking use of phase-modulation techniques for targeted photoactivation [Papagiakoumouet al., 2010, Packer et al., 2012] and simultaneous imaging could be developed.

III. B.3 Applications

As it is now, the fiberscope allows simultaneous functional fluorescence imaging andtargeted photoactivation. Its main characteristics are summarized in Table III.1 togetherwith those of the implementations presented in section I. C. Compared to existingsingle-photon microscopes designed for freely behaving rodents, our fiberscope possessesseveral innovative and important features. First and regarding fluorescence imaging,it is the only one providing optical sectionning. Hence, cells can be precisely locatedeven in complex 3D fluorescent structures using SIM, and functional recordings frommultiple sites can be performed with single-cell resolution using scanless multi-pointconfocal microscopy. Moreover, the optical setup can easily be tuned for multi-colorimaging, facilitating functional interrogation of various disparate structures. Second,our fiberscope is the only implementation permitting targeted photoactivation of single-neurons. We can now ask what kind of experiments, among those presented in section I.D, are enabled by this fiberscope.

III. B.3.0.1 The cell assembly Investigations may focus on either the cell assembly for-mation or its role in a behaviour. Cell assembly formation could be studied throughexcitation of single neurons during a behavioural task to enrole them in the assembly,or through inhibition of cell assembly members to detect the emergence of new neuronalcomponents. Causal relationship between an assembly and a behaviour could be testedby excitation of the ensemble to evoke the behaviour, or by inhibition of the assembly (orpart of it) during learning or behaviour. These experiments require to find the cell as-semblies components. Our fiberscope enables functional fluorescence imaging in neuronalpopulations, and should therefore allow detection of cell assemblies members. Then, ca-pability to excite or inhibit cell assembly members is also needed. Our fiberscope canperform targeted photoactivation with near-cellular resolution. Hence, direct testing ofthe cell assembly hypothesis is conceivable. The main limitations in our implementationare the short working distance and the restriction to acute experimentation (see subsec-tion III. B.2.1). Thus, the biological model should be judiciously chosen. We discussthree preparations that could be used to investigate the cell assembly with the fiberscope(using either this micro-objective or one with a slightly longer WD, similar to the oneused by Ziv et al. [Ziv et al., 2013]): the CA1 region of the hippocampus, the neocortex,

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Microscope[Ghoshet al.,2011]

[Ferezouet al.,2006]

[Mu-rayamaet al.,2007] 1

[Mu-rayamaet al.,2007] 2

[Flus-berget al.,2008]

Our im-plemen-tation

Diameter (mm) 2 3 0.5 0.5 1 2.6WD (µm) 150-200 0 100 300 300-400 60FOV (µm) 490-800 3,000 685 155 240-370 240Resolution (µm) 2.5-2.8 8 ? ? 2.8-3.9 2.6OpticalSectioning

No No No No No Yes

Photoactivation No No No No No Yes

Table III.1: Summary table of single-photon fiberscopes. Diameter: probe diameter; WD:working distance; FOV: field of view; Resolution: imaging lateral resolution. [Ghosh et al.,2011]: Integrated microscope. [Ferezou et al., 2006]: Fiberscope, no objective. [Murayamaet al., 2007] 1: Fiberscope, objective. [Murayama et al., 2007] 2: Two-fiber fiberscope,objective. [Flusberg et al., 2008]: Fiberscope, objective.

and the cerebellar cortex.In the hippocampus, CA1 place cells, after cortex excavation, are candidates of choice

to study a cell assembly. Indeed, during a single experimental session, a subset of neuronshas been shown consistently active and detectable using calcium imaging when the animalis at a given location [Ziv et al., 2013]. Thus, cell assembly formation could be investigatedusing targeted photoactivation: 1) the conditions for a single neuron’s integration into theassembly could be tested (firing pattern and timing) [Houweling and Brecht, 2008, Arduinet al., 2013] by direct photoexcitation; 2) once identified, the effects of inhibition ofparticular cell assembly members could be tested by photoinhibition of single neurons andimaging of the remaining cells. Chronic experiments (III. B.2.1) would allow determiningthe consequences of cell assembly members excitation and inhibition on performances inplace recognition tasks.

The neocortex layer 1 (L1) can be reached much more easily through a simple cran-iotomy. Inputs to L1 supposedly carry attention-related informations, which are probablyof great importance in neuronal ensembles generation. Formation of pyramidal cells as-semblies could be studied through visualization and excitation/inhibition of dendriticactivity [Murayama and Larkum, 2009a]. The importance of distinct pyramidal cell pop-ulations, projecting either to sensory or motor areas, in decision making could hence beinvastigated [Chen et al., 2013a]. L1 interneurons could also be the focus of these studies:these cells have recently been well characterized [Jiang et al., 2013], and their putativerole in shaping pyramidal cells activity during higher-order behavioural tasks may betested with the fiberscope.

Similarly to the neocortex, the cerebellar cortex can be chosen to lead these investi-gations. Purkinje cells dendrites indeed receive major inputs from climbing and parallelfibers. Spatio-temporal pattern of dendritic activity in cerebellar microzones could then

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be observed and controlled to infer cell assemblies properties. Comparable approachescould focus on molecular layer interneurons to investigate their role in shaping Purkinjecells firing.

In conclusion, our fiberscope as it is can already enable studies about cell assemblyformation, in different parts of the brain. Learning experimental paradigms are of coursenot excluded, but necessitate chronic experimentation.

III. B.3.0.2 Neurovascular coupling Besides cell assemblies investigation, the fiberscopecould be used to study neurovascular coupling. Visualization of microcirculation beingstraightforward, photoactivation of neurons or astrocytes in freely behaving animals couldprovide insights into the role of these cells in vasodilation/vasoconstriction in vivo .

III. B.3.0.3 Coupling to fMRI Opto-fMRI is an emerging field combining optogenetictools with fMRI. So far, studies have only used widefield photoactivation [Lee et al., 2010]and bulk fluorescence recording [Schulz et al., 2012]. Providing implementation with anon-ferromagnetic objective, the fiberscope could be helpful to precisely characterizefMRI signals cellular origin (principal cells versus interneurons) in specific behaviours.Indeed, correlation between fluorescence and fMRI signals could provide a first hint,and resulting hypotheses could be directly tested by excitation or inhibition of specificpopulations by optogenetic actuators photoactivation. Then, cell assemblies organizationthroughout the whole brain could be investigated. The fiberscope would give access todetailed functional organization of local ensembles, as suggested in III. B.3.0.1, andsimultaneous fMRI measurements would evidence activity in distant structures. Webelieve this approach could be a step forward towards unravelling the neural organizationof behaviour.

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Bibliography

Walther Akemann, Hiroki Mutoh, Amélie Perron, Yun Kyung Park, Yuka Iwamoto, andThomas Knöpfel. Imaging neural circuit dynamics with a voltage-sensitive fluorescentprotein. Journal of neurophysiology, 108(8):2323–2337, October 2012. ISSN 1522-1598.doi: 10.1152/jn.00452.2012. PMID: 22815406.

Jasper Akerboom, Tsai-Wen Chen, Trevor J Wardill, Lin Tian, Jonathan S Marvin,Sevinc Mutlu, Nicole Carreras Calderón, Federico Esposti, Bart G Borghuis, Xiao-nan Richard Sun, Andrew Gordus, Michael B Orger, Ruben Portugues, Florian Engert,John J Macklin, Alessandro Filosa, Aman Aggarwal, Rex A Kerr, Ryousuke Takagi, Se-bastian Kracun, Eiji Shigetomi, Baljit S Khakh, Herwig Baier, Leon Lagnado, SamuelS-H Wang, Cornelia I Bargmann, Bruce E Kimmel, Vivek Jayaraman, Karel Svoboda,Douglas S Kim, Eric R Schreiter, and Loren L Looger. Optimization of a GCaMPcalcium indicator for neural activity imaging. The Journal of neuroscience: the offi-cial journal of the Society for Neuroscience, 32(40):13819–13840, October 2012. ISSN1529-2401. doi: 10.1523/JNEUROSCI.2601-12.2012. PMID: 23035093.

Francesca Anselmi, Cathie Ventalon, Aurélien Bègue, David Ogden, and Valentina Emil-iani. Three-dimensional imaging and photostimulation by remote-focusing and holo-graphic light patterning. Proceedings of the National Academy of Sciences of theUnited States of America, 108(49):19504–19509, December 2011. ISSN 1091-6490.doi: 10.1073/pnas.1109111108. PMID: 22074779.

Richard Apps and Martin Garwicz. Anatomical and physiological foundations of cere-bellar information processing. Nature reviews. Neuroscience, 6(4):297–311, April 2005.ISSN 1471-003X. doi: 10.1038/nrn1646. PMID: 15803161.

Alexander M Aravanis, Li-Ping Wang, Feng Zhang, Leslie A Meltzer, Murtaza Z Mogri,M Bret Schneider, and Karl Deisseroth. An optical neural interface: in vivo controlof rodent motor cortex with integrated fiberoptic and optogenetic technology. Jour-nal of Neural Engineering, 4(3):S143–156, September 2007. ISSN 1741-2560. doi:10.1088/1741-2560/4/3/S02. PMID: 17873414.

Pierre-Jean Arduin, Yves Frégnac, Daniel E Shulz, and Valérie Ego-Stengel. "Mas-ter" neurons induced by operant conditioning in rat motor cortex during a brain-machine interface task. The Journal of neuroscience: the official journal of the

105

Society for Neuroscience, 33(19):8308–8320, May 2013. ISSN 1529-2401. doi:10.1523/JNEUROSCI.2744-12.2013. PMID: 23658171.

Benjamin R Arenkiel, Joao Peca, Ian G Davison, Catia Feliciano, Karl Deisseroth,George J Augustine, Michael D Ehlers, and Guoping Feng. In vivo light-inducedactivation of neural circuitry in transgenic mice expressing channelrhodopsin-2. Neu-ron, 54(2):205–218, April 2007. ISSN 0896-6273. doi: 10.1016/j.neuron.2007.03.005.PMID: 17442243.

Peter Arhem, Göran Klement, and Johanna Nilsson. Mechanisms of anesthesia: towardsintegrating network, cellular, and molecular level modeling. Neuropsychopharmacology:official publication of the American College of Neuropsychopharmacology, 28 Suppl 1:S40–47, July 2003. ISSN 0893-133X. doi: 10.1038/sj.npp.1300142. PMID: 12827143.

Anita E Autry, Megumi Adachi, Elena Nosyreva, Elisa S Na, Maarten F Los, Peng-feiCheng, Ege T Kavalali, and Lisa M Monteggia. NMDA receptor blockade at resttriggers rapid behavioural antidepressant responses. Nature, 475(7354):91–95, July2011. ISSN 1476-4687. doi: 10.1038/nature10130. PMID: 21677641.

Matthew Banghart, Katharine Borges, Ehud Isacoff, Dirk Trauner, and Richard HKramer. Light-activated ion channels for remote control of neuronal firing. NatureNeuroscience, 7(12):1381–1386, December 2004. ISSN 1097-6256. doi: 10.1038/nn1356.PMID: 15558062.

Edward S Boyden, Feng Zhang, Ernst Bamberg, Georg Nagel, and Karl Deisseroth.Millisecond-timescale, genetically targeted optical control of neural activity. Natureneuroscience, 8(9):1263–1268, September 2005. ISSN 1097-6256. doi: 10.1038/nn1525.PMID: 16116447.

Nenad Bozinovic, Cathie Ventalon, Tim Ford, and Jerome Mertz. Fluorescence endomi-croscopy with structured illumination. Optics Express, 16(11):8016–8025, May 2008.ISSN 1094-4087. PMID: 18545511.

Paramita Chakrabarty, Awilda Rosario, Pedro Cruz, Zoe Siemienski, Carolina Ceballos-Diaz, Keith Crosby, Karen Jansen, David R Borchelt, Ji-Yoen Kim, Joanna LJankowsky, Todd E Golde, and Yona Levites. Capsid serotype and timing of injectiondetermines AAV transduction in the neonatal mice brain. PloS one, 8(6):e67680, 2013.ISSN 1932-6203. doi: 10.1371/journal.pone.0067680. PMID: 23825679.

Frédéric Chasles, Benoit Dubertret, and A Claude Boccara. Optimization and character-ization of a structured illumination microscope. Optics express, 15(24):16130–16140,November 2007. ISSN 1094-4087. PMID: 19550902.

Jerry L Chen, Stefano Carta, Joana Soldado-Magraner, Bernard L Schneider, and FritjofHelmchen. Behaviour-dependent recruitment of long-range projection neurons in so-matosensory cortex. Nature, June 2013a. ISSN 1476-4687. doi: 10.1038/nature12236.PMID: 23792559.

106

Tsai-Wen Chen, Trevor J Wardill, Yi Sun, Stefan R Pulver, Sabine L Renninger, AmyBaohan, Eric R Schreiter, Rex A Kerr, Michael B Orger, Vivek Jayaraman, Loren LLooger, Karel Svoboda, and Douglas S Kim. Ultrasensitive fluorescent proteins forimaging neuronal activity. Nature, 499(7458):295–300, July 2013b. ISSN 1476-4687.doi: 10.1038/nature12354. PMID: 23868258.

Brian Y Chow, Xue Han, Allison S Dobry, Xiaofeng Qian, Amy S Chuong, MingjieLi, Michael A Henninger, Gabriel M Belfort, Yingxi Lin, Patrick E Monahan, andEdward S Boyden. High-performance genetically targetable optical neural silencing bylight-driven proton pumps. Nature, 463(7277):98–102, January 2010. ISSN 1476-4687.doi: 10.1038/nature08652. PMID: 20054397.

Stephane Ciocchi, Cyril Herry, Francois Grenier, Steffen B E Wolff, Johannes J Letzkus,Ioannis Vlachos, Ingrid Ehrlich, Rolf Sprengel, Karl Deisseroth, Michael B Stadler,Christian Müller, and Andreas Lüthi. Encoding of conditioned fear in central amygdalainhibitory circuits. Nature, 468(7321):277–282, November 2010. ISSN 1476-4687. doi:10.1038/nature09559. PMID: 21068837.

A B Cubitt, R Heim, S R Adams, A E Boyd, L A Gross, and R Y Tsien. Understanding,improving and using green fluorescent proteins. Trends in biochemical sciences, 20(11):448–455, November 1995. ISSN 0968-0004. PMID: 8578587.

W Denk, J H Strickler, and W W Webb. Two-photon laser scanning fluorescence mi-croscopy. Science (New York, N.Y.), 248(4951):73–76, April 1990. ISSN 0036-8075.PMID: 2321027.

Ashesh K Dhawale, Akari Hagiwara, Upinder S Bhalla, Venkatesh N Murthy, and Dinu FAlbeanu. Non-redundant odor coding by sister mitral cells revealed by light addressableglomeruli in the mouse. Nature Neuroscience, 13(11):1404–1412, November 2010. ISSN1546-1726. doi: 10.1038/nn.2673. PMID: 20953197.

Daniel A Dombeck, Anton N Khabbaz, Forrest Collman, Thomas L Adelman, andDavid W Tank. Imaging large-scale neural activity with cellular resolution inawake, mobile mice. Neuron, 56(1):43–57, October 2007. ISSN 0896-6273. doi:10.1016/j.neuron.2007.08.003. PMID: 17920014.

Daniel A Dombeck, Christopher D Harvey, Lin Tian, Loren L Looger, and David WTank. Functional imaging of hippocampal place cells at cellular resolution duringvirtual navigation. Nature neuroscience, 13(11):1433–1440, November 2010. ISSN1546-1726. doi: 10.1038/nn.2648. PMID: 20890294.

Christoph J Engelbrecht, Richard S Johnston, Eric J Seibel, and Fritjof Helmchen. Ultra-compact fiber-optic two-photon microscope for functional fluorescence imaging in vivo.Optics express, 16(8):5556–5564, April 2008. ISSN 1094-4087. PMID: 18542658.

Isabelle Ferezou, Sonia Bolea, and Carl C H Petersen. Visualizing the cortical represen-tation of whisker touch: voltage-sensitive dye imaging in freely moving mice. Neuron,

107

50(4):617–629, May 2006. ISSN 0896-6273. doi: 10.1016/j.neuron.2006.03.043. PMID:16701211.

Isabelle Ferezou, Florent Haiss, Luc J. Gentet, Rachel Aronoff, Bruno Weber, andCarl C.H. Petersen. Spatiotemporal dynamics of cortical sensorimotor integrationin behaving mice. Neuron, 56(5):907–923, December 2007. ISSN 0896-6273. doi:10.1016/j.neuron.2007.10.007.

Benjamin A Flusberg, Eric D Cocker, Wibool Piyawattanametha, Juergen C Jung, Eu-nice L M Cheung, and Mark J Schnitzer. Fiber-optic fluorescence imaging. NatureMethods, 2(12):941–950, December 2005a. ISSN 1548-7091. doi: 10.1038/nmeth820.PMID: 16299479.

Benjamin A Flusberg, Juergen C Jung, Eric D Cocker, Erik P Anderson, and Mark JSchnitzer. In vivo brain imaging using a portable 3.9 gram two-photon fluorescencemicroendoscope. Optics Letters, 30(17):2272–2274, September 2005b. ISSN 0146-9592.PMID: 16190441.

Benjamin A Flusberg, Axel Nimmerjahn, Eric D Cocker, Eran A Mukamel, Robert P JBarretto, Tony H Ko, Laurie D Burns, Juergen C Jung, and Mark J Schnitzer. High-speed, miniaturized fluorescence microscopy in freely moving mice. Nature methods,5(11):935–938, November 2008. ISSN 1548-7105. doi: 10.1038/nmeth.1256. PMID:18836457.

Romain Franconville, Gaelle Revet, Guadalupe Astorga, Beat Schwaller, and IsabelLlano. Somatic calcium level reports integrated spiking activity of cerebellar interneu-rons in vitro and in vivo. Journal of Neurophysiology, 106(4):1793–1805, October 2011.ISSN 1522-1598. doi: 10.1152/jn.00133.2011. PMID: 21734102.

Kunal K Ghosh, Laurie D Burns, Eric D Cocker, Axel Nimmerjahn, Yaniv Ziv, Abbas ElGamal, and Mark J Schnitzer. Miniaturized integration of a fluorescence microscope.Nature Methods, September 2011. ISSN 1548-7105. doi: 10.1038/nmeth.1694. PMID:21909102.

Werner Göbel, Jason N D Kerr, Axel Nimmerjahn, and Fritjof Helmchen. Miniaturizedtwo-photon microscope based on a flexible coherent fiber bundle and a gradient-indexlens objective. Optics letters, 29(21):2521–2523, November 2004. ISSN 0146-9592.PMID: 15584281.

Yiyang Gong, Jin Zhong Li, and Mark J Schnitzer. Enhanced archaerhodopsin fluores-cent protein voltage indicators. PloS one, 8(6):e66959, 2013. ISSN 1932-6203. doi:10.1371/journal.pone.0066959. PMID: 23840563.

Inbal Goshen, Matthew Brodsky, Rohit Prakash, Jenelle Wallace, Viviana Gradinaru,Charu Ramakrishnan, and Karl Deisseroth. Dynamics of retrieval strategies forremote memories. Cell, 147(3):678–689, October 2011. ISSN 1097-4172. doi:10.1016/j.cell.2011.09.033. PMID: 22019004.

108

Viviana Gradinaru, Kimberly R Thompson, Feng Zhang, Murtaza Mogri, Kenneth Kay,M Bret Schneider, and Karl Deisseroth. Targeting and readout strategies for fastoptical neural control in vitro and in vivo. The Journal of Neuroscience: The OfficialJournal of the Society for Neuroscience, 27(52):14231–14238, December 2007. ISSN1529-2401. doi: 10.1523/JNEUROSCI.3578-07.2007. PMID: 18160630.

Viviana Gradinaru, Murtaza Mogri, Kimberly R Thompson, Jaimie M Henderson, andKarl Deisseroth. Optical deconstruction of parkinsonian neural circuitry. Science(New York, N.Y.), 324(5925):354–359, April 2009. ISSN 1095-9203. doi: 10.1126/sci-ence.1167093. PMID: 19299587.

David S Greenberg, Arthur R Houweling, and Jason N D Kerr. Population imagingof ongoing neuronal activity in the visual cortex of awake rats. Nat Neurosci, 11(7):749–751, July 2008. ISSN 1097-6256. doi: 10.1038/nn.2140.

Bilal Haider, Michael Häusser, and Matteo Carandini. Inhibition dominates sensory re-sponses in the awake cortex. Nature, November 2012. ISSN 1476-4687. doi: 10.1038/na-ture11665. PMID: 23172139.

Yuichiro Hayashi, Yoshiaki Tagawa, Satoshi Yawata, Shigetada Nakanishi, and KazuoFunabiki. Spatio-temporal control of neural activity in vivo using fluorescence mi-croendoscopy. The European journal of neuroscience, 36(6):2722–2732, September2012. ISSN 1460-9568. doi: 10.1111/j.1460-9568.2012.08191.x. PMID: 22780218.

D. O. Hebb. The Organization of Behavior: A Neuropsychological Theory. LawrenceErlbaum Associates Inc, 2002. ISBN 9780805843000.

R Heim, A B Cubitt, and R Y Tsien. Improved green fluorescence. Nature, 373(6516):663–664, February 1995. ISSN 0028-0836. doi: 10.1038/373663b0. PMID: 7854443.

F Helmchen, M S Fee, D W Tank, and W Denk. A miniature head-mounted two-photonmicroscope. high-resolution brain imaging in freely moving animals. Neuron, 31(6):903–912, September 2001. ISSN 0896-6273. PMID: 11580892.

Fritjof Helmchen, Winfried Denk, and Jason N D Kerr. Miniaturization of two-photonmicroscopy for imaging in freely moving animals. Cold Spring Harbor protocols, 2013(10), 2013. ISSN 1559-6095. doi: 10.1101/pdb.top078147. PMID: 24086055.

W T Hermens and J Verhaagen. Viral vectors, tools for gene transfer in the nervoussystem. Progress in neurobiology, 55(4):399–432, July 1998. ISSN 0301-0082. PMID:9654386.

Simon Hippenmeyer, Eline Vrieseling, Markus Sigrist, Thomas Portmann, Celia Laengle,David R Ladle, and Silvia Arber. A developmental switch in the response of DRGneurons to ETS transcription factor signaling. PLoS biology, 3(5):e159, May 2005.ISSN 1545-7885. doi: 10.1371/journal.pbio.0030159. PMID: 15836427.

109

Arthur R Houweling and Michael Brecht. Behavioural report of single neuron stimulationin somatosensory cortex. Nature, 451(7174):65–68, January 2008. ISSN 1476-4687. doi:10.1038/nature06447. PMID: 18094684.

Daniel Huber, Leopoldo Petreanu, Nima Ghitani, Sachin Ranade, Tomás Hromádka,Zach Mainen, and Karel Svoboda. Sparse optical microstimulation in barrel cortexdrives learned behaviour in freely moving mice. Nature, 451(7174):61–64, January2008. ISSN 1476-4687. doi: 10.1038/nature06445. PMID: 18094685.

Masao Ito. Cerebellar circuitry as a neuronal machine. Progress in Neurobiology, 78(3-5):272–303, April 2006. ISSN 0301-0082. doi: 10.1016/j.pneurobio.2006.02.006. PMID:16759785.

Nobuhisa Iwata, Misaki Sekiguchi, Yoshino Hattori, Akane Takahashi, Masashi Asai, BinJi, Makoto Higuchi, Matthias Staufenbiel, Shin-ichi Muramatsu, and Takaomi C Saido.Global brain delivery of neprilysin gene by intravascular administration of AAV vectorin mice. Scientific reports, 3:1472, 2013. ISSN 2045-2322. doi: 10.1038/srep01472.PMID: 23503602.

Xiaolong Jiang, Guangfu Wang, Alice J Lee, Ruth L Stornetta, and J Julius Zhu. Theorganization of two new cortical interneuronal circuits. Nature neuroscience, 16(2):210–218, February 2013. ISSN 1546-1726. doi: 10.1038/nn.3305. PMID: 23313910.

Hideaki E Kato, Feng Zhang, Ofer Yizhar, Charu Ramakrishnan, Tomohiro Nishizawa,Kunio Hirata, Jumpei Ito, Yusuke Aita, Tomoya Tsukazaki, Shigehiko Hayashi, Pe-ter Hegemann, Andrés D Maturana, Ryuichiro Ishitani, Karl Deisseroth, and OsamuNureki. Crystal structure of the channelrhodopsin light-gated cation channel. Nature,482(7385):369–374, February 2012. ISSN 1476-4687. doi: 10.1038/nature10870. PMID:22266941.

Sonja Kleinlogel, Katrin Feldbauer, Robert E Dempski, Heike Fotis, Phillip G Wood,Christian Bamann, and Ernst Bamberg. Ultra light-sensitive and fast neuronal acti-vation with the ca(2+)-permeable channelrhodopsin CatCh. Nature Neuroscience, 14(4):513–518, April 2011. ISSN 1546-1726. doi: 10.1038/nn.2776. PMID: 21399632.

Ho Ko, Sonja B Hofer, Bruno Pichler, Katherine A Buchanan, P Jesper Sjöström, andThomas D Mrsic-Flogel. Functional specificity of local synaptic connections in neocor-tical networks. Nature, 473(7345):87–91, May 2011. ISSN 1476-4687. doi: 10.1038/na-ture09880. PMID: 21478872.

Sharon Margriet Kolk, Annetrude Johanne de Mooij-Malsen, and Gerard Julianus MariaMartens. Spatiotemporal molecular approach of in utero electroporation to function-ally decipher endophenotypes in neurodevelopmental disorders. Frontiers in molecularneuroscience, 4:37, 2011. ISSN 1662-5099. doi: 10.3389/fnmol.2011.00037. PMID:22065947.

110

Silvana Konermann, Mark D Brigham, Alexandro E Trevino, Patrick D Hsu, MatthiasHeidenreich, Le Cong, Randall J Platt, David A Scott, George M Church, and FengZhang. Optical control of mammalian endogenous transcription and epigenetic states.Nature, 500(7463):472–476, August 2013. ISSN 1476-4687. doi: 10.1038/nature12466.PMID: 23877069.

Joel M Kralj, Adam D Douglass, Daniel R Hochbaum, Dougal Maclaurin, and Adam ECohen. Optical recording of action potentials in mammalian neurons using a micro-bial rhodopsin. Nature methods, 9(1):90–95, January 2012. ISSN 1548-7105. doi:10.1038/nmeth.1782. PMID: 22120467.

Alexxai V Kravitz, Benjamin S Freeze, Philip R L Parker, Kenneth Kay, Myo T Thwin,Karl Deisseroth, and Anatol C Kreitzer. Regulation of parkinsonian motor behavioursby optogenetic control of basal ganglia circuitry. Nature, 466(7306):622–626, July 2010.ISSN 1476-4687. doi: 10.1038/nature09159. PMID: 20613723.

Yoan LeChasseur, Suzie Dufour, Guillaume Lavertu, Cyril Bories, Martin Deschenes,Real Vallee, and Yves De Koninck. A microprobe for parallel optical and electricalrecordings from single neurons in vivo. Nature methods, 8(4):319–325, April 2011.ISSN 1548-7105. doi: 10.1038/nmeth.1572. PMID: 21317908.

Jin Hyung Lee, Remy Durand, Viviana Gradinaru, Feng Zhang, Inbal Goshen, Dae-Shik Kim, Lief E Fenno, Charu Ramakrishnan, and Karl Deisseroth. Global and localfMRI signals driven by neurons defined optogenetically by type and wiring. Nature,465(7299):788–792, June 2010. ISSN 1476-4687. doi: 10.1038/nature09108. PMID:20473285.

M Lelek, E Suran, F Louradour, A Barthelemy, B Viellerobe, and F Lacombe. Coherentfemtosecond pulse shaping for the optimization of a non-linear micro-endoscope. Opticsexpress, 15(16):10154–10162, August 2007. ISSN 1094-4087. PMID: 19547364.

John Y Lin, Sharon B Sann, Keming Zhou, Sadegh Nabavi, Christophe D Proulx,Roberto Malinow, Yishi Jin, and Roger Y Tsien. Optogenetic inhibition of synapticrelease with chromophore-assisted light inactivation (CALI). Neuron, 79(2):241–253,July 2013. ISSN 1097-4199. doi: 10.1016/j.neuron.2013.05.022. PMID: 23889931.

Martin J Lohse, Moritz Bünemann, Carsten Hoffmann, Jean-Pierre Vilardaga, and Vi-acheslav O Nikolaev. Monitoring receptor signaling by intramolecular FRET. Cur-rent opinion in pharmacology, 7(5):547–553, October 2007. ISSN 1471-4892. doi:10.1016/j.coph.2007.08.007. PMID: 17919975.

Henry Lütcke, Masanori Murayama, Thomas Hahn, David J Margolis, Simone Astori,Stephan Meyer Zum Alten Borgloh, Werner Göbel, Ying Yang, Wannan Tang, Sebas-tian Kügler, Rolf Sprengel, Takeharu Nagai, Atsushi Miyawaki, Matthew E Larkum,Fritjof Helmchen, and Mazahir T Hasan. Optical recording of neuronal activity with

111

a genetically-encoded calcium indicator in anesthetized and freely moving mice. Fron-tiers in neural circuits, 4:9, 2010. ISSN 1662-5110. doi: 10.3389/fncir.2010.00009.PMID: 20461230.

Christoph Lutz, Thomas S Otis, Vincent DeSars, Serge Charpak, David A DiGregorio,and Valentina Emiliani. Holographic photolysis of caged neurotransmitters. NatureMethods, 5(9):821–827, September 2008. ISSN 1548-7091. doi: 10.1038/nmeth.1241.PMID: 19160517.

James J Mancuso, Jinsook Kim, Soojung Lee, Sachiko Tsuda, Nicholas B H Chow, andGeorge J Augustine. Optogenetic probing of functional brain circuitry. Experimen-tal Physiology, 96(1):26–33, January 2011. ISSN 1469-445X. doi: 10.1113/expphys-iol.2010.055731. PMID: 21056968.

David J Margolis, Henry Lütcke, Kristina Schulz, Florent Haiss, Bruno Weber, SebastianKügler, Mazahir T Hasan, and Fritjof Helmchen. Reorganization of cortical populationactivity imaged throughout long-term sensory deprivation. Nature neuroscience, 15(11):1539–1546, November 2012. ISSN 1546-1726. doi: 10.1038/nn.3240. PMID:23086335.

Damien Maurel, Laëtitia Comps-Agrar, Carsten Brock, Marie-Laure Rives, EmmanuelBourrier, Mohammed Akli Ayoub, Hervé Bazin, Norbert Tinel, Thierry Durroux, Lau-rent Prézeau, Eric Trinquet, and Jean-Philippe Pin. Cell-surface protein-protein in-teraction analysis with time-resolved FRET and snap-tag technologies: application toGPCR oligomerization. Nature methods, 5(6):561–567, June 2008. ISSN 1548-7105.doi: 10.1038/nmeth.1213. PMID: 18488035.

Jerome Mertz. Introduction to Optical Microscopy. Roberts and Company Publishers,2010. ISBN 9780981519487.

Wolfgang Mittmann, Damian J Wallace, Uwe Czubayko, Jan T Herb, Andreas T Schae-fer, Loren L Looger, Winfried Denk, and Jason N D Kerr. Two-photon calcium imagingof evoked activity from l5 somatosensory neurons in vivo. Nature neuroscience, 14(8):1089–1093, August 2011. ISSN 1546-1726. doi: 10.1038/nn.2879. PMID: 21743473.

A Miyawaki, J Llopis, R Heim, J M McCaffery, J A Adams, M Ikura, and R Y Tsien.Fluorescent indicators for ca2+ based on green fluorescent proteins and calmodulin.Nature, 388(6645):882–887, August 1997. ISSN 0028-0836. doi: 10.1038/42264. PMID:9278050.

Maria Müller, Christian Bamann, Ernst Bamberg, and Werner Kühlbrandt. Projectionstructure of channelrhodopsin-2 at 6 å resolution by electron crystallography. Journalof Molecular Biology, October 2011. ISSN 1089-8638. doi: 10.1016/j.jmb.2011.09.049.PMID: 22001017.

Kartikeya Murari, Ralph Etienne-Cummings, Gert Cauwenberghs, and Nitish Thakor.An integrated imaging microscope for untethered cortical imaging in freely-moving

112

animals. Conference proceedings: ... Annual International Conference of theIEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicineand Biology Society. Conference, 2010:5795–5798, 2010. ISSN 1557-170X. doi:10.1109/IEMBS.2010.5627825. PMID: 21097102.

Masanori Murayama and Matthew E Larkum. Enhanced dendritic activity in awake rats.Proceedings of the National Academy of Sciences of the United States of America, 106(48):20482–20486, December 2009a. ISSN 1091-6490. doi: 10.1073/pnas.0910379106.PMID: 19918085.

Masanori Murayama and Matthew E Larkum. In vivo dendritic calcium imaging witha fiberoptic periscope system. Nature protocols, 4(10):1551–1559, 2009b. ISSN 1750-2799. doi: 10.1038/nprot.2009.142. PMID: 19798087.

Masanori Murayama, Enrique Pérez-Garci, Hans-Rudolf Lüscher, and Matthew ELarkum. Fiberoptic system for recording dendritic calcium signals in layer 5 neocorti-cal pyramidal cells in freely moving rats. Journal of neurophysiology, 98(3):1791–1805,September 2007. ISSN 0022-3077. doi: 10.1152/jn.00082.2007. PMID: 17634346.

Georg Nagel, Tanjef Szellas, Wolfram Huhn, Suneel Kateriya, Nona Adeishvili, PeterBerthold, Doris Ollig, Peter Hegemann, and Ernst Bamberg. Channelrhodopsin-2, adirectly light-gated cation-selective membrane channel. Proceedings of the NationalAcademy of Sciences of the United States of America, 100(24):13940–13945, November2003. ISSN 0027-8424. doi: 10.1073/pnas.1936192100. PMID: 14615590.

J Nakai, M Ohkura, and K Imoto. A high signal-to-noise ca(2+) probe composed of asingle green fluorescent protein. Nature biotechnology, 19(2):137–141, February 2001.ISSN 1087-0156. doi: 10.1038/84397. PMID: 11175727.

M A Neil, R Juskaitis, and T Wilson. Method of obtaining optical sectioning by us-ing structured light in a conventional microscope. Optics letters, 22(24):1905–1907,December 1997. ISSN 0146-9592. PMID: 18188403.

H S Orbach and L B Cohen. Optical monitoring of activity from many areas of the invitro and in vivo salamander olfactory bulb: a new method for studying functionalorganization in the vertebrate central nervous system. The Journal of Neuroscience:The Official Journal of the Society for Neuroscience, 3(11):2251–2262, November 1983.ISSN 0270-6474. PMID: 6631479.

H S Orbach, L B Cohen, and A Grinvald. Optical mapping of electrical activity in ratsomatosensory and visual cortex. The Journal of Neuroscience: The Official Journalof the Society for Neuroscience, 5(7):1886–1895, July 1985. ISSN 0270-6474. PMID:4020423.

M Ormö, A B Cubitt, K Kallio, L A Gross, R Y Tsien, and S J Remington. Crystalstructure of the aequorea victoria green fluorescent protein. Science (New York, N.Y.),273(5280):1392–1395, September 1996. ISSN 0036-8075. PMID: 8703075.

113

Mingxing Ouyang, He Huang, Nathan C Shaner, Albert G Remacle, Sergey A Shiryaev,Alex Y Strongin, Roger Y Tsien, and Yingxiao Wang. Simultaneous visualizationof protumorigenic src and MT1-MMP activities with fluorescence resonance energytransfer. Cancer research, 70(6):2204–2212, March 2010. ISSN 1538-7445. doi:10.1158/0008-5472.CAN-09-3698. PMID: 20197470.

Adam M Packer, Darcy S Peterka, Jan J Hirtz, Rohit Prakash, Karl Deisseroth, andRafael Yuste. Two-photon optogenetics of dendritic spines and neural circuits. Naturemethods, November 2012. ISSN 1548-7105. doi: 10.1038/nmeth.2249. PMID: 23142873.

Eirini Papagiakoumou, Francesca Anselmi, Aurélien Bègue, Vincent de Sars, JesperGlückstad, Ehud Y Isacoff, and Valentina Emiliani. Scanless two-photon excitationof channelrhodopsin-2. Nature Methods, 7(10):848–854, October 2010. ISSN 1548-7105. doi: 10.1038/nmeth.1505. PMID: 20852649.

Alessandro Papale, Milica Cerovic, and Riccardo Brambilla. Viral vector approachesto modify gene expression in the brain. Journal of neuroscience methods, 185(1):1–14, December 2009. ISSN 1872-678X. doi: 10.1016/j.jneumeth.2009.08.013. PMID:19699233.

Wibool Piyawattanametha, Eric D Cocker, Laurie D Burns, Robert P Barretto, Juer-gen C Jung, Hyejun Ra, Olav Solgaard, and Mark J Schnitzer. In vivo brain imagingusing a portable 2.9 g two-photon microscope based on a microelectromechanical sys-tems scanning mirror. Optics letters, 34(15):2309–2311, August 2009. ISSN 0146-9592.PMID: 19649080.

Marco Polin, Kosta Ladavac, Sang-Hyuk Lee, Yael Roichman, and David Grier. Opti-mized holographic optical traps. Optics express, 13(15):5831–5845, July 2005. ISSN1094-4087. PMID: 19498588.

David W. Russell and Mark A. Kay. Adeno-associated virus vectors and hematology.Blood, 94(3):864–874, August 1999.

B Sauer and N Henderson. Site-specific DNA recombination in mammalian cells by thecre recombinase of bacteriophage p1. Proceedings of the National Academy of Sciencesof the United States of America, 85(14):5166–5170, July 1988. ISSN 0027-8424. PMID:2839833.

Juergen Sawinski, Damian J. Wallace, David S. Greenberg, Silvie Grossmann, WinfriedDenk, and Jason N. D. Kerr. Visually evoked activity in cortical cells imaged in freelymoving animals. Proceedings of the National Academy of Sciences, 106(46):19557 –19562, November 2009. doi: 10.1073/pnas.0903680106.

Frank Schnütgen, Nathalie Doerflinger, Cécile Calléja, Olivia Wendling, Pierre Cham-bon, and Norbert B Ghyselinck. A directional strategy for monitoring cre-mediatedrecombination at the cellular level in the mouse. Nature Biotechnology, 21(5):562–565,May 2003. ISSN 1087-0156. doi: 10.1038/nbt811. PMID: 12665802.

114

Kristina Schulz, Esther Sydekum, Roland Krueppel, Christoph J Engelbrecht, FelixSchlegel, Aileen Schröter, Markus Rudin, and Fritjof Helmchen. Simultaneous BOLDfMRI and fiber-optic calcium recording in rat neocortex. Nature methods, 9(6):597–602,June 2012. ISSN 1548-7105. doi: 10.1038/nmeth.2013. PMID: 22561989.

Nathan C Shaner, Robert E Campbell, Paul A Steinbach, Ben N G Giepmans, Amy EPalmer, and Roger Y Tsien. Improved monomeric red, orange and yellow fluorescentproteins derived from discosoma sp. red fluorescent protein. Nat Biotech, 22(12):1567–1572, December 2004. ISSN 1087-0156. doi: 10.1038/nbt1037.

Nathan C Shaner, Paul A Steinbach, and Roger Y Tsien. A guide to choosing fluo-rescent proteins. Nat Meth, 2(12):905–909, December 2005. ISSN 1548-7091. doi:10.1038/nmeth819.

Shy Shoham, Daniel H O’Connor, Dmitry V Sarkisov, and Samuel S-H Wang. Rapidneurotransmitter uncaging in spatially defined patterns. Nature Methods, 2(11):837–843, November 2005. ISSN 1548-7091. doi: 10.1038/nmeth793. PMID: 16278654.

Christoph Stosiek, Olga Garaschuk, Knut Holthoff, and Arthur Konnerth. In vivo two-photon calcium imaging of neuronal networks. Proceedings of the National Academyof Sciences of the United States of America, 100(12):7319–7324, June 2003. ISSN0027-8424. doi: 10.1073/pnas.1232232100. PMID: 12777621.

Yan Sun, Xigu Chen, and Dong Xiao. Tetracycline-inducible expression systems: newstrategies and practices in the transgenic mouse modeling. Acta biochimica et biophys-ica Sinica, 39(4):235–246, April 2007. ISSN 1672-9145. PMID: 17417678.

Stephanie Szobota, Pau Gorostiza, Filippo Del Bene, Claire Wyart, Doris L Fortin,Kathleen D Kolstad, Orapim Tulyathan, Matthew Volgraf, Rika Numano, Holly LAaron, Ethan K Scott, Richard H Kramer, John Flannery, Herwig Baier, DirkTrauner, and Ehud Y Isacoff. Remote control of neuronal activity with a light-gated glutamate receptor. Neuron, 54(4):535–545, May 2007. ISSN 0896-6273. doi:10.1016/j.neuron.2007.05.010. PMID: 17521567.

Inna Tabansky, Alan Lenarcic, Ryan W Draft, Karine Loulier, Derin B Keskin, Jacque-line Rosains, José Rivera-Feliciano, Jeff W Lichtman, Jean Livet, Joel N H Stern,Joshua R Sanes, and Kevin Eggan. Developmental bias in cleavage-stage mouse blas-tomeres. Current biology: CB, 23(1):21–31, January 2013. ISSN 1879-0445. doi:10.1016/j.cub.2012.10.054. PMID: 23177476.

Mathew Tantama, Yin Pun Hung, and Gary Yellen. Optogenetic reporters: Fluorescentprotein-based genetically encoded indicators of signaling and metabolism in the brain.Progress in brain research, 196:235–263, 2012. ISSN 1875-7855. doi: 10.1016/B978-0-444-59426-6.00012-4. PMID: 22341329.

115

Lin Tian, S Andrew Hires, Tianyi Mao, Daniel Huber, M Eugenia Chiappe, Sreekanth HChalasani, Leopoldo Petreanu, Jasper Akerboom, Sean A McKinney, Eric R Schre-iter, Cornelia I Bargmann, Vivek Jayaraman, Karel Svoboda, and Loren L Looger.Imaging neural activity in worms, flies and mice with improved GCaMP calciumindicators. Nature Methods, 6(12):875–881, December 2009. ISSN 1548-7105. doi:10.1038/nmeth.1398. PMID: 19898485.

Hsing-Chen Tsai, Feng Zhang, Antoine Adamantidis, Garret D Stuber, Antonello Bonci,Luis de Lecea, and Karl Deisseroth. Phasic firing in dopaminergic neurons is sufficientfor behavioral conditioning. Science (New York, N.Y.), 324(5930):1080–1084, May2009. ISSN 1095-9203. doi: 10.1126/science.1168878. PMID: 19389999.

Roger Y Tsien. Indicators based on fluorescence resonance energy transfer (FRET).Cold Spring Harbor protocols, 2009(7):pdb.top57, July 2009. ISSN 1559-6095. doi:10.1101/pdb.top57. PMID: 20147227.

Matthew Volgraf, Pau Gorostiza, Rika Numano, Richard H Kramer, Ehud Y Isacoff, andDirk Trauner. Allosteric control of an ionotropic glutamate receptor with an opticalswitch. Nature Chemical Biology, 2(1):47–52, January 2006. ISSN 1552-4450. doi:10.1038/nchembio756. PMID: 16408092.

Sabrina Wend, Hanna J Wagner, Konrad Müller, Matias D Zurbriggen, Wilfried Weber,and Gerald Radziwill. Optogenetic control of protein kinase activity in mammaliancells. ACS synthetic biology, October 2013. ISSN 2161-5063. doi: 10.1021/sb400090s.PMID: 24090449.

Nathan R Wilson, Caroline A Runyan, Forea L Wang, and Mriganka Sur. Division andsubtraction by distinct cortical inhibitory networks in vivo. Nature, 488(7411):343–348,August 2012. ISSN 1476-4687. doi: 10.1038/nature11347. PMID: 22878717.

Ilana B Witten, Shih-Chun Lin, Matthew Brodsky, Rohit Prakash, Ilka Diester, PolinaAnikeeva, Viviana Gradinaru, Charu Ramakrishnan, and Karl Deisseroth. Choliner-gic interneurons control local circuit activity and cocaine conditioning. Science (NewYork, N.Y.), 330(6011):1677–1681, December 2010. ISSN 1095-9203. doi: 10.1126/sci-ence.1193771. PMID: 21164015.

Claire Wyart, Filippo Del Bene, Erica Warp, Ethan K Scott, Dirk Trauner, HerwigBaier, and Ehud Y Isacoff. Optogenetic dissection of a behavioural module in thevertebrate spinal cord. Nature, 461(7262):407–410, September 2009. ISSN 1476-4687.doi: 10.1038/nature08323. PMID: 19759620.

Sunggu Yang, Eirini Papagiakoumou, Marc Guillon, Vincent de Sars, Cha-Min Tang, andValentina Emiliani. Three-dimensional holographic photostimulation of the dendriticarbor. Journal of neural engineering, 8(4):046002, August 2011. ISSN 1741-2552. doi:10.1088/1741-2560/8/4/046002. PMID: 21623008.

116

Ofer Yizhar, Lief E Fenno, Matthias Prigge, Franziska Schneider, Thomas J Davidson,Daniel J O’Shea, Vikaas S Sohal, Inbal Goshen, Joel Finkelstein, Jeanne T Paz, KatjaStehfest, Roman Fudim, Charu Ramakrishnan, John R Huguenard, Peter Hegemann,and Karl Deisseroth. Neocortical excitation/inhibition balance in information pro-cessing and social dysfunction. Nature, 477(7363):171–178, September 2011. ISSN1476-4687. doi: 10.1038/nature10360. PMID: 21796121.

Morad Zahid, Mateo Vélez-Fort, Eirini Papagiakoumou, Cathie Ventalon, María CeciliaAngulo, and Valentina Emiliani. Holographic photolysis for multiple cell stimulationin mouse hippocampal slices. PloS One, 5(2):e9431, 2010. ISSN 1932-6203. doi:10.1371/journal.pone.0009431. PMID: 20195547.

Boris V Zemelman, Georgia A Lee, Minna Ng, and Gero Miesenböck. Selective pho-tostimulation of genetically chARGed neurons. Neuron, 33(1):15–22, January 2002.ISSN 0896-6273. PMID: 11779476.

Boris V Zemelman, Nasri Nesnas, Georgia A Lee, and Gero Miesenbock. Photochem-ical gating of heterologous ion channels: remote control over genetically designatedpopulations of neurons. Proceedings of the National Academy of Sciences of theUnited States of America, 100(3):1352–1357, February 2003. ISSN 0027-8424. doi:10.1073/pnas.242738899. PMID: 12540832.

Feng Zhang, Alexander M Aravanis, Antoine Adamantidis, Luis de Lecea, and Karl Deis-seroth. Circuit-breakers: optical technologies for probing neural signals and systems.Nature Reviews. Neuroscience, 8(8):577–581, August 2007a. ISSN 1471-003X. doi:10.1038/nrn2192. PMID: 17643087.

Feng Zhang, Li-Ping Wang, Martin Brauner, Jana F Liewald, Kenneth Kay, NatalieWatzke, Phillip G Wood, Ernst Bamberg, Georg Nagel, Alexander Gottschalk, andKarl Deisseroth. Multimodal fast optical interrogation of neural circuitry. Nature,446(7136):633–639, April 2007b. ISSN 1476-4687. doi: 10.1038/nature05744. PMID:17410168.

Yaniv Ziv, Laurie D Burns, Eric D Cocker, Elizabeth O Hamel, Kunal K Ghosh, Lacey JKitch, Abbas El Gamal, and Mark J Schnitzer. Long-term dynamics of CA1 hip-pocampal place codes. Nature neuroscience, February 2013. ISSN 1546-1726. doi:10.1038/nn.3329. PMID: 23396101.

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vivien szabo optogénétique chez la souris éveillée et ... · acknowledgements i could not have...

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