fens-ibro 2011 bookletthe fens-ibro students introduce will themselves and, from that moment on,...

Lausanne & Geneva FENS-‐IBRO Training Center

Imaging Brain Function in Animals and Humans August 28th -‐ September 16th 2011

Sponsored by

Organized by

L a u s anne & G ene v a F ENS -‐ I BRO T r a i n i n g C en t e r


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Organizers Olaf Blanke

Ecole Polytechnique Fédérale de Lausanne (EPFL)

Bogdan Draganski

Lausanne University Hospital (CHUV)

Rolf Gruetter

Ecole Polytechnique Fédérale de Lausanne (EPFL)

Christoph Michel

Brain & Behavior Laboratory (BBL), University of Geneva

Micah Murray

Lausanne University Hospital (CHUV)

Patrik Vuilleumier

Brain & Behavior Laboratory (BBL), University of Geneva



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Coordination Sonia Bolea

Lemanic Neuroscience Doctoral School, University of Lausanne

1. Overview The Lausanne & Geneva FENS-IBRO Training Center will be dedicated to state-of-the-art mapping of brain functions and dysfunctions. The principal objectives will be to train participants in the latest available methods/technologies, the latest available analysis techniques, and the current applications in basic and clinical neuroscience research. Emphasis will be placed on three domains: 1) cutting-edge imaging technologies and their mutual integration, 2) advanced signal analysis, and 3) combined applications of different methods for inter-species and basic-clinical translational research. Specific methods that will be covered in the program include electrophsysiological recordings (high-resolution scalp EEG and intracranial recordings in humans and animal models), fMRI, spectroscopy, PET, optical imaging, structural imaging and tractography, TMS, and peripheral psychophysiology.

Invited Speakers: Laura Astolfi, Katarzyna Blinowska, Stefan Debener, Leon Deouell, Elia

Formisano, Hauke Heekeren, Stefan Kiebel, Lee Miller, Kia Nobre, Guy Orban, Mathias Pessiglione, Gilles Pourtois, Patricia Reuter-Lorenz, Jorge Ripoll, Charles Schroeder, Gregor Thut, Robert Turner, Mark Wallace, Bruno Weber and Nikolaus Weiskopf.

Local Faculty: Daphne Bavelier, Olaf Blanke, Domenica Buetti, Stephanie Clarke, Marzia

De Luzia, Bogdan Draganski, Stephan Eliez, Richard Frackowiak, Didier Grandjean, Rolf Gruetter, Nouchine Hadjikhani, Patric Hagmann, Petra Hüppi, Ferath Kherif, Pierre Magistretti, Christoph Michel, Micah Murray, Melissa Saenz, Sophie Schwartz, Margitta Seeck, Jean-Philippe Thiran, Dimitri Van de Ville, Wietske van der Zwaag, Serge Vulliemoz and Patrik Vuilleumier.



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2. Program The Lausanne & Geneva FENS-IBRO Training Center will be held in three Lemanic institutions:

Week 1 at the CHUV August 29 – September 2

Human systems neuroscience imaging applications

Week 2 at the EPFL September 5-9

Imaging advances and translational aspects



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Week 3 at the Brain & Behaviour Laboratory, Unige September 12-16

Large-scale neuronal networks

The program starts on Sunday August 28th at 5:30pm with a welcome dinner in the Café de Grancy, in Lausanne. The FENS-IBRO students introduce will themselves and, from that moment on, they are encouraged to share their meals and coffee breaks with local and invited speakers. On the very first day of the FENS-IBRO Training Center, a general introductory meeting will be held. The students will be appointed to three lab courses (3 different lab courses in total). We will make sure that students choose complementary approaches among different weeks, and that each student will be admitted to his/her research lab course of preference at least once during the three weeks. Literature and readings will be provided during this introduction. The mornings will be devoted to lectures and general discussions. For the discussions, material in form of methods papers or review papers will be provided ahead of time. Invited speakers, but also faculty, postdocs and PhD students from the host institution, will participate in these discussions. Thus, the morning sessions will provide opportunities for the students to informally discuss with faculty and lab members, the presented techniques, experimental results of their projects, as well as ideas for new experiments. Students are encouraged to discuss the lectures and their research interests with the speakers during the scheduled discussion sessions in the mornings, and during lunch. The discussions will have an informal format, facilitating interaction between faculty and students. Following the morning lectures, the students will start experimental work in their host labs in small groups (2-3 students). Each experimental project will last for a week. The PI of the host lab will introduce the students to the lab as a whole, and will make a schedule for the experimental work together with the students. The supervisor will provide readings on the specific imaging technique. The experiments will be conducted under the guidance of an experienced post-doc or PhD student



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from the lab, and by the PI of the lab and faculty members. Questions about the experiments and analysis approaches will be discussed on a daily basis. This intense mentoring will guarantee an optimal access of the FENS-IBRO students to the imaging techniques in the host lab. The evenings will be reserved for two sessions of slide presentations by the students, one lecture on ethics, two round tables on “Careers in Science” and “Science Communication”, and presentations by the students about the experimental projects. On the first two evenings each student will shortly present his/her work and research interests. Students will also display a poster in each of the three institutions. This will allow everyone to get acquainted with each other at both a personal and scientific level. Two round table discussions are planned, on the following topics:

- Careers in Science: different career paths will be presented, in academic research, industry, medical consulting and administration of research and training activities.

- Science Communication: public awareness activities organized in the Lemanic area will be presented. An expert on Science Communication will give you tips to better communicate your research to the media.

Guy Organ, from the FENS-CARE Committee, will give a lecture about Ethics in Animal Research. Every week on Friday the FENS-IBRO students will present what they have done during the week in the FENS-IBRO labs. This is a good opportunity to exchange ideas about the techniques learned.



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3. Facilities Accommodation for the first two weeks in Lausanne will be in the Maison de Rhodanie, a UNIL students’ housing facility located by the lake, and 15 min by bus from the CHUV and 10 min from the EPFL. Each student will have a single room with a desk to work. Faculty will be hosted in the Hotel Nash Carlton.

For the last week in Geneva, the students will move to the Hotel Carmen, 10 min by foot from the UNIGE host labs. Faculty will be hosted at the Hotel Adriatica.

A lecture room, exclusively reserved for the students of the FENS-IBRO Training Center, is available at all three teaching locations. Coffee will be served in these rooms in between the lectures. The lecture rooms are located in the same building as the host labs. Thus, students can easily reach the host labs after the morning sessions. The lecture rooms will also be used for the evening sessions.

Lunch and dinner services are available on site or nearby, on campus. Students will have lunch with the invited speakers, and with members of the host lab, faculty and other students.

Free passes for public transport, that are needed to commute between the housing facilities and teaching venues, will be provided for faculty and students.

4. Laboratory facilities The participating institutions include the University and University Hospital of Geneva (HUG and UNIGE), the University Hospital Center and University of Lausanne (CHUV and UNIL), and the Swiss Federal Institute of Technology in Lausanne (EPFL). Multi-institutional imaging centres already exist in Lausanne and Geneva that will provide high-level technological platforms for the practical experimental teaching of the students. These include the Center of Biomedical Imaging that has imaging platforms at five different institutions (CIBM), and the Brain and Behaviour Laboratory (BBL) at the University of Geneva that combines the faculties of medicine and psychology. Consequently, the high level of existing interactions between the participating institutions will allow for a highly cohesive training center for the external participants. Existing infrastructure:

CHUV-UNIL: 3 T human MRI, 190-channel EEG, 92-channel fMRI-EEG, TMS EPFL: 7 T human MRI, 14.1 T rodent scanner, animal PET camera, 200-ch EEG, TMS, virtual reality lab with 190-ch EEG, rotation chair combined with EEG HUG: 3 T human MRI, 256-ch EEG, 128-ch intracranial EEG, 256-ch fMRI-EEG UNIGE: 3 T human MRI, 256-ch EEG, 256-ch fMRI-EEG, TMS, Psychophysiology



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At the CHUV, the practical work of the students will be largely completed within the auspices of the Centre for Biomedical Imaging (CIBM). This is a multidisciplinary facility situated within the Radiology Department with participating faculty/laboratories from the Department of Clinical Neurosciences (among others). These include an MRI lab with a 3Tesla MR scanner, 2 EEG labs (with up to 160-channel acquisition and the possibility of simultaneous EEG-TMS and EEG-MRI), a psychophysiology lab, an acoustics lab, and well as neuropsychological testing facilities. Practical work will take place in an open-space floor within the CIBM that houses post-docs and students. This setting will foster an active and dynamic exchange between FENS-IBRO students and local students, post-docs, and faculty. At the UNIGE, the practical work of the students will mainly be performed at the Brain and Behavior Laboratory (BBL). This is a multidisciplinary research centre recently created by the University of Geneva and dedicated to integrative studies on the cerebral bases of human mental functions, emotions, and behaviour (see htpp://bbl.unige.ch for Information). The BBL occupies a large space within the main research building at the University Medical Centre (CMU). It includes different laboratories with state-of-the art infrastructure. This includes a MRI lab with a 3Tesla MR scanner, an EEG lab with 256-channel MRI-compatible EEG and TMS, a psychophysiology lab, an acoustic lab, a sleep laboratory, a behavioral lab, and a virtual reality room. The MRI lab is equipped with multimodal peripheral devices for stimulus presentation (visual, auditory, thermal, olfactory) and subject monitoring behaviour with eye-tracker, bodily physiological measures, as well as concomitant EEG, which provides an ideal setup for a fruitful demonstrations of current methodological sophistication in human neuroimaging. Besides these research facilities, a practical course at the University Hospital will demonstrate the structural and functional imaging in epilepsy patients including intracranial EEG recordings and electrocortical stimulation.



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FENS-IBRO Training Center lab 1.1 Multimodal structural image analysis in neuroscience Faculty: Meritxell Bach-Cuadra and Bogdan Draganski Postdocs/PhD Students: Jürgen Dukart and Anne Ruef (LREN) Description: The project is divided in two modules where participants will learn methods for automated multispectral tissue classification developed at MIAL as well as image processing and analysis algorithms within the SPM framework. We will use quantitative structural magnetic resonance imaging data capturing in vivo tissue properties of the brain allowing for accurate data handling and straightforward interpretation. Additionally, there will be a brief excursus in exploring anatomical connectivity features of the brain based on diffusion-weighted imaging. Techniques: Tissue classification, diffephic registration and statistical analysis in the framework Statistical Parametric Mapping Multispectral tissue classification - own methods Location: - LREN (Laboratoire de recherche en neuroimagerie): CHUV, CIBM building - MIAL (Medical Image Analysis Laboratory): CHUV, CIBM building, and EPFL, LTS5 lab

FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 1.2 Electrical neuroimaging correlates of duration encoding Faculty: Lucas Spierer Postdocs/PhD Students: Fosco Bernasconi Description: The general aim of this project is to investigate the neural underpinnings of the encoding of supra-second visual temporal intervals. Analyses will be mainly performed in the brain-space using distributed linear electrical source estimations from scalp-recorded EEG. Techniques: Psychophysics and EEG source imaging Location: Room Micropolis, Rue du Bugnon 23 Phone number: 021 314 80 85




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FENS-IBRO Training Center lab 1.3

Visual and auditory temporal processing Faculty: Domenica Bueti Postdocs/PhD Students: Paolo Salvioni Description: The general goal of the project is to characterize the functional organization of temporal mechanisms in visual and auditory cortices. Using magnetic stimulation (TMS) techniques in healthy volunteers I will: a) disclose the differential contribution of primary and secondary visual areas (i.e. V5/MT) to the temporal coding of visual durations; b) clarify the relationship between visual and auditory cortices in the neural representation of visual durations. The students will be involved in every stage of the experimental processing from experimental design to data collection and analysis. Overall, this project will offer the students the opportunity to become familiar with the most used psychophysical procedures of data analysis (e.g. thresholds estimation, fitting to psychometric functions). Most importantly they will learn the basis of experimental design optimization, acquisition and analysis of TMS data. Techniques: Psychophysics and TMS Location: Room Micropolis, Rue du Bugnon 23 Phone number: 021 314 7512 (CIBM) FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 1.4 Single-trial Event-related Potential Analysis Faculty: Marzia De Lucia Description: The student will learn advanced techniques for analyzing Event Related Potential at single-trial level and will attempt at generalizing the method to compare single subjects and group-level analysis. Techniques: EEG; single-trial topographic analysis Location: CIBM/CHUV, Lausanne Phone number: 021 314 6828 FENS-IBRO Students: 1



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Multivariate analyses in neuroimaging Faculty: Ferath Kherif & Jürgen Dukart Description: Introduction to multivariate analyses, comparison between univariate and multivariate results. Classification approaches: supervised and unsupervised. Theoretical and applications to different datasets : Language, memory and clinical data (fMRI and structural). Techniques: Multivariate Linear Model (PCA, PLS, CVA), MVB (Multivariate Brain Decoding), Unsupervised Classification and Supervised Classification. Location: Room Micropolis, Rue du Bugnon 23 Phone number: 021 314 9593 FENS-IBRO Students: 1



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Introduction to ERP analyses in Cartool Faculty: Micah Murray Postdocs/PhD Students: Antonia Thelen Description: This project will allow participants to get an overview of the ERP pre-processing and analysis tools available in Cartool. Participants will have exemplar datasets available, but are also welcome to come with their own data that they wish to examine. We detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. For each step of these analyses, we provide both a conceptual and mathematical description as well as hands-on experience of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. Our aim is to show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets. Location: Room Micropolis, Rue du Bugnon 23 Phone number: Antonia Thelen 078 737 1292 FENS-IBRO Students: 2-3



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fMRI, Retinotopic and Tonotopic Mapping of Sensory Cortex Faculty: Melissa Saenz Postdocs/PhD Students: Sandra DaCosta Description: Retinotopic and tonotopic mapping with fMRI allow the identification of individual fields within visual cortex (V1, V2, V3 …) and auditory cortex (A1, R), which is a useful step in visual and auditory experiments. Students will learn how to apply the commonly-used “traveling wave” method for topographic mapping using different software platforms (Brain Voyager and SPM). As an examplar, we’ll use high-resolutio data collected with 7 Tesla fMRI for tonotopic mapping of auditory cortex. Location: CIBM/CHUV, Lausanne Phone number: 079 623 20 35 FENS-IBRO Students: 2



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Tracking the brain dynamics of gut hormone influences on visual food discrimination in women after gastric bypass surgery Ulrike Toepel and Jean-Francois Knebel (Departments for Clinical Neurosciences and Radiology) Description: Endocrine factors convey information about energy needs to brain regions involved in homeostatic control of feeding. However, food intake as well as pre-ingestion visual food perception has been shown to involve brain regions related to reward valuation and cognitive control (Gibson et al. 2010). The extent to which low-level physiological-endocrine factors interact with these higher-level cognitive processes and brain areas implicated therein remains to be determined. Spatio-temporal brain response modulations for the explicit categorization of food vs. non-food objects as well as the implicit discrimination of high- vs. low-energetic foods have previously been shown (Toepel et al. 2009), with the latter especially attributed to varying reward properties of the food subclasses and decision-making processes induced by viewing them. Gastric bypass surgery is one of the most effective treatments with long-term weight loss effects. The surgery does not only result in food restriction and nutritional malabsorption, but substantially modifies endocrine gut functions (Rodieux et al. 2008). Our long-term project is thus concerned with the interplay of food motivation and endocrine factors on visual food perception in women. The trainee will be implicated in EEG analyses at the group-level (operated women vs. weight-matched controls), and learn how to address correlations between spatio-temporal brain dynamics, gut hormone measures and questionnaire data. However, in case of interest these analyses can be link with approaches to single participant, single trial analyses (cf. project of Dr. Marzia de Lucia). Techniques: EEG, event-related potentials, multifactorial statistics Location: Room Micropolis, Rue du Bugnon 23 Phone number: 021 314 1317 FENS-IBRO Students: 1



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From functional connectivity to effective connectivity: New methods for analysis of integration mechanisms in human brain Faculty: Maria Knyazeva Postdocs: Cristian Carmeli & Romana Rytsar Description: The project is devoted to methods of imaging large-scale functional/effective connectivity and their application to real human EEG data.

Day 1 Introduction: The state of art in the imaging of distributed neural processes. Application of the functional and effective connectivity imaging to some basic neuroscience and to clinical neuroscience problems. Review of recent research of the Connectivity Neuroimaging Group. Hands-on: High-density EEG techniques of recording and pre-processing (ANT 128-channel EEG/ERP machine). Days 2-3 Hands-on: Analysis of head functional connectivity/synchronization in real EEG data. Imaging of whole-head EEG synchronization with Matlab software. EEG data based on a cognitive paradigm (“diamond” illusion) and EEGs from our clinical database will be used. Different strategies for computing synchronization will be explored. Days 4-5 Hands-on: Implementation of DCM for the analysis of effective connectivity in cortical networks based on fMRI data with SPM8 software. The dynamics of effective connectivity in visual integration paradigm will be considered in Alzheimer’s patients and healthy aged subjects. Different models of interacting regions will be compared using Bayesian model selection procedure. An example of statistical analysis of the effective connectivity will be demonstrated.

Techniques: EEG Synchronization; Multivariate mapping of EEG synchronization topography; Statistical analysis of synchronization maps. Dynamic causal modelling. Bayesian model comparison.



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Literature: 1: Carmeli C, Knyazeva MG, Innocenti GM, De Feo O. Assessment of EEG synchronization based on state-space analysis. Neuroimage. 2005 Apr 1;25(2):339-54. PubMed PMID: 15784413.

2: Knyazeva MG, Carmeli C, Fornari E, Meuli R, Small M, Frackowiak RS, Maeder P. Binding under Conflict Conditions: State-Space Analysis of Multivariate EEG Synchronization. J Cogn Neurosci. 2011 Sep;23(9):2363-75. Epub 2010 Oct 14. PubMed PMID: 20946055. 3: Knyazeva MG, Jalili M, Brioschi A, Bourquin I, Fornari E, Hasler M, Meuli R, Maeder P, Ghika J. Topography of EEG multivariate phase synchronization in early Alzheimer's disease. Neurobiol Aging. 2010 Jul;31(7):1132-44. Epub 2008 Sep 5.PubMed PMID: 18774201. 4: Knyazeva MG, Jalili M, Frackowiak RS, Rossetti AO. Psychogenic seizures and frontal disconnection: EEG synchronisation study. J Neurol Neurosurg Psychiatry. 2011 May;82(5):505-11. Epub 2011 Mar 14. PubMed PMID: 21402746. 5: Rytsar R, Fornari E, Frackowiak RS, Ghika JA, Knyazeva MG. Inhibition in early Alzheimer's disease: An fMRI-based study of effective connectivity. Neuroimage. 2011 Aug 1;57(3):1131-9. Epub 2011 May 15. PubMed PMID: 21616155. Location: Room Micropolis, Rue du Bugnon 23 Phone number: 021 314 3231 / 021 314 9644 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 2.1 From animal cage to NMR magnet: what goes into measuring brain metabolism and function in vivo Faculty: CIBM Description: This project aims to address the general question why we perform animal brain imaging in vivo and how on a practical basis this is achieved. Students will be expected to be keen observers of the primary surgical procedures involved for performing in vivo experiments, how animals are handled and how they are loaded into an NMR holder. Students will learn how to evaluate the quality of an animal’s physiology during the course of an NMR experiment; how to evaluate the choice of anesthetics; and what measures should be taken when physiology becomes pathological. Students will have the opportunity to prepare brain slices, and make observations under the microscope for the identification of brain region, white vs grey matter, ventricules and the blood brain barrier. Students will also have the opportunity to observe NMR imaging in progress and to evaluate the animal’s physiology. Techniques: Microsurgery, blood gas analyzers, animal physiology monitoring, light microscopy Location: CIBM building Phone number: Madame Laure Bardouillet 021 693 79 67




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FENS-IBRO Training Center lab 2.2 Metabolic studies by in vivo 13C MR spectroscopy Faculty: João M.N. Duarte, Bernard Lanz & Jessica Bastiaansen Description: NMR spectroscopy (MRS) in combination with administration of specific 13C-enriched substrates has been strategically used to probe metabolism and its regulation in animals or humans. State-of-the-art in vivo 13C MRS techniques at high magnetic field (e.g. 9.4 T or 14.1 T at the LIFMET-CIBM) allow the simultaneous determination of a number of metabolic fluxes that are related to physiological functions in a non-invasive way. In addition, advances in the field of hyperpolarized MR provide the opportunity to study metabolism with unprecedented sensitivity and increased time resolution, highlighting fast biochemical processes. The purpose of the present study is to elucidate the advantages and disadvantages of both thermal equilibrium and hyperpolarized 13C MRS for in vivo studies. For that, both MRS techniques will be employed to detect 13C labeling curves upon infusion of either [1,6-13C]glucose or hyperpolarized [1-13C]acetate in rodents. In addition, to understand the role of the detected metabolic fluxes, experiments will be performed in a rat model of acute encephalopathy induced by hyperamonemia. These experiments will involve both data acquisition and processing. Techniques: 13C MRS, hyperpolarized MRS Location: LIFMET, building CH F1 Phone number: 021 693 7681 FENS-IBRO Students: 3



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Exploring the neuron-glial dynamics with Multimodality microscopy Faculty: Pierre Marquet & Pierre Magistretti Postdocs/PhD Students: Pascal Jourdain, Nicolas Pavillon, Jonas kühn, Stéphane Chamot Description: The goal of this project is to investigate the dynamics of the neuron-glial network with an integrated imaging technique involving digital holographic microscopy (DHM), a new non-invasive 3D optical imaging technique with a nanoscale resolution, video fluorescence microscopy and electrophysiology. A special attention will be given to study how neuronal activity modifies neuron-glial morphology in cellular micro-domains in relation with specific intracellular ions concentration changes (Na+, K+, Ca2+ etc.). Practically, minute cellular morphological changes will be assessed by DHM measurements and ion intracellular concentration by the utilization of fluorescence probes. Students will have the opportunity to observe living cells with the DHM and to get an overview of how data of different nature can be processed in order to provide relevant information on specific cell processes. Techniques: - Digital holographic microscopy (DHM), - Video fluorescence microscopy - Electrophysiology Location: Laboratory of Neuroenergetics and Cellular Dynamics, SV-BMI, Lab AI3217, EPFL, Lausanne Phone number: 021 693 17 24 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 2.4 Towards deep grey matter segmentation Faculty: Jose Marques Description: During this project we will acquire structural images of the brain, and will evaluate the potential of the different acquisition parameters to perform either grey white matter automatic segmentation or sub-thalamic and basal ganglia nuclei manual segmentation. Techniques: MRI Location: CIBM @ Ecole Polythechnique Féderale de Lausanne Phone number: 021 693 7968 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 2.5 Analysis of brain responses to vestibular stimulation using 7 T fMRI Faculty: Roberto Martuzzi & Mario Prsa Description: Previous studies suggest that vestibular stimuli are processed by a network of brain regions and among these regions, the parieto-insular vestibular cortex (PIVC) plays a pivotal role. One of the methods for stimulation the vestibular cortex without the need of a real movement is the galvanic vestibular stimulation (GVS), which consists in stimulating the vestibular nerve by placing an electrode pair on the skin close to the ears. Using MR compatible electrodes is therefore possible to stimulate the vestibular cortex in the MR environment. The aim of the project is to investigate the functional organization of the PIVC using 7T fMRI and GVS. Students will be involved in both the acquisition and the analysis of fMRI data. Techniques: fMRI Location: Room AI2201, EPFL (this room is part of the LNCO) Phone number: 021 693 1775 FENS-IBRO Students: 3



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MR spectroscopy of animal brain Faculty: Vladimir Mlynarik Postdocs/PhD Students: Cristina Cudalbu and Mélanie Craveiro Description: Localized spectroscopy and spectroscopic imaging of rat or mouse brain enable to monitor concentrations of about 20 metabolites in various brain regions. Various animal models will be measured during this course and characteristic changes in metabolite concentrations will be observed. Techniques: In vivo proton localized MR spectroscopy or spectroscopic imaging Location: LIFMET, building CH F1 Phone number: 021 6937685 FENS-IBRO Students: 3



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FENS-IBRO Training Center lab 2.7 Optical imaging and fMRI of tactile sensory processing in mice Faculty: Carl Petersen & Rolf Gruetter Postdocs/PhD Students: Dr. Nathalie Just Description: The mouse provides a useful model system for studying mechanistic aspects of brain function. Mice receive important sensory information from mystacial vibrissae. These whiskers surrounding the snout allow mice to discriminate textures and to build up spatial representations useful for object recognition and navigation. Techniques: Here, we aim to measure sensory responses evoked by whisker stimulation in anesthetized mice through intrinsic optical imaging and fMRI. Location: Day 1: Intrinsic optical imaging – Laboratory of Sensory Processing - AI3117 Days 2-5: fMRI - Laboratory of functional and metabolic imaging - CH F1 626 Phone number: Carl Petersen – 021 693 1721 Nathalie Just – 021 693 7983 FENS-IBRO Students: 3



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FENS-IBRO Training Center lab 2.8 fMRI at 7 Tesla Faculty: Van der Zwaag & Hadjikhani Description: The goal of this project is to measure brain function in response to both subliminal stimuli, which are not consciously perceived and supraliminal, consciously perceived stimuli. A fast subconscious neural network is thought to exist in parallel to a slower, more explicit processing of danger stimuli. Here, we want to visualize the processing of subliminal fear stimuli using fMRI, focusing on the amygdalae, which are an important node for fear processing. The used functional paradigm is based on series of consecutively displayed images. All experiments will be done on the 7T MRI system at the CIBM laboratory on the EPFL campus. The student(s) will be involved in data acquisition and will undertake the data processing of the fMRI data. Monitoring of physiological measures (heartbeat and respiration) will be included to allow reduction of physiological noise as part of the post-processing. Techniques: fMRI – data acquisition and processing (FSL) Location: LIFMET laboratory, EPFL Phone number: 021 693 7687 – 021 683 1807 FENS-IBRO Students: 3



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FENS-IBRO Training Center lab 3.1 Bistable perception of speech sounds Faculty: Narly Golestani Postdocs/PhD Students: Alexis Hervais-Adelman Description: Lexical context has a significant impact on the perception of phonemes. For example, an ambiguous phoneme /?/ between /t/ and /d/ can be perceived as either of these sounds. However, if presented at the end of a word, e.g. woo/?/, then it will be likely to be perceived as /d/, producing the percept of the word "wood", rather than the nonword "woot". This lexical bias in the perception of ambiguous speech sounds is called the Ganong effect. But what happens when both alternative percepts are words? For example, an ambiguous phoneme between /s/ and /f/ placed in the context /?/unny, can be perceived as either /s/- "sunny" or /f/- "funny". In this case, when the ambiguous word is presented repeatedly, listeners report hearing the percept switch between the two alternatives. We can use EEG to investigate the neural basis of the switch. In this project we would record and analyse the EEG correlates of a listener who is presented with a series of words containing such ambiguous sounds. By examining the state of the brain immediately before the presentation of such ambiguous words, we can determine whether there are states that determine the perception of the ambiguous phoneme. Techniques: High-resolution EEG Location: CMU/BBL Phone number: 022 2 37 95 866 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.2 A mouse model for large-scale brain networks Faculty: Christoph Michel Postdocs/PhD Students: Charles Quairiaux Description: In this project the recording and topographic analysis of up to 32-channel epicranial evoked potentials in rodents will be demonstrated. The method allows to study large-scale functional networks in these animals, giving the possibility to study effects of development, lesion, and recovery. Combination with intracranial recordings of local field potentials in different layers and current density analysis will also be demonstrated and the relation to multi-unit recordings will be studied. Techniques: Epicranial and intracranial EEG in rodents Location: CMU, 8th floor Phone number: 022 379 53 79 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.3 Dynamic connectivity between EEG sources Faculty: Christoph Michel Postdocs/PhD Students: Gijs Plomp Description: In this project we will study the connectivity changes between underlying sources of the EEG. Available connectivity measures include correlation, coherence, and Granger-causal modeling (PDC/DTF). Experience in Matlab is desirable. We can work with data from our lab, but alternatively you can bring your own data. Techniques: Functional Connectivity Analysis with EEG Location: CMU/BBL Phone number: 022 379 53 79 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.4 EEG-TMS combination Faculty: Christoph Michel Postdocs/PhD Students: Tonia Rihs, Vincent Rochas Description: In this project, we will combine TMS with EEG. We will apply repetitive TMS over motor cortex and measure its effects in the offline EEG by comparing the pre- and post-TMS EEG recording for a simple Go, No-Go motor task. We are interested in the effect of repetitive TMS on anticipatory brain activity before execution of a task. We will analyse the topography of the event related anticipatory EEG as well as the TMS induced changes for the amplitude of the mu-frequency-band. The aim of this project is to familiarize you with TMS recordings and the analysis of TMS induced changes in the time and frequency domain of the EEG using Brain Vision Analyser and Cartool for the EEG analysis. Techniques: TMS, EEG/EP analysis Location: CMU/BBL Phone number: 022 379 54 63 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.5 ERP correlates of subliminally presented stimuli Faculty: Christoph Michel Postdocs/PhD Students: Holger Sperdin Description: This project will involve the recording (2 or 3 participants depending on time) and the subsequent spatio-temporal analysis of high-resolution ERPs (256 channels) in response to subliminally presented stimuli. No prior specific knowledge is required. Participants could also bring some personal ERP data that could be analyzed using our spatio-temporal analysis and source localization methods. Techniques: High-resolution EEG Location: CMU/BBL Phone number: 022 379 53 97 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.6 EEG – microstates and the relation to conscious mentation Faculty: Christoph Michel Postdocs/PhD Students: Miralena Tomescu Description: The constant rise of interest in the brain’s resting state reflects the fundamental need of understanding the elementary building blocks of conscious mentation. Here we propose to reason out human mental activity using different induced states of consciousness. For this we will explore the spatial properties of the global EEG scalp potential field and the evolution of these potential fields over time which follows very idiosyncratic rules similar across subjects, known as EEG microstates, the “atoms of thought”. Techniques: High-resolution EEG Location: CMU/BBL Phone number: 022 379 54 57 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.7 Functional MRI combined with peripheral physiological measures Faculty: Sebastian Rieger Postdocs/PhD Students: Wiebke Trost / Christoph Hofstetter Description: The project will demonstrate the acquisition of fMRI data combined with physiological measures such as skin conductance, electromyography, heart-rate, respiration, and eye tracking. Changes in these bodily measures provide useful information to assess the affective or motivational impact of experimental manipulations during cognitive paradigms, or to remove confounds in BOLD signal changes measured during resting state conditions. Techniques: fMRI, SCR, EMG, EKG, eye-tracking. Location: CMU/BBL Phone number: 022 - 37 95 369 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.8 Pattern recognition methods for neuroimaging Faculty: Dimitri Van De Ville Postdocs/PhD Students: Jonas Richiardi Description: The neuroimaging community heavily relies on statistical inference to explain measured brain activity given the experimental paradigm. Undeniably, this method has led to many results, but it is limited by the richness of the generative models that are deployed, typically in a mass-univariate way. Such an approach is suboptimal given the high-dimensional and complex spatiotemporal correlation structure of neuroimaging data. Over the recent years, techniques from pattern recognition have brought new insights in where and how information is stored in the brain by prediction of the stimulus or state from the data. Pattern recognition is intrinsically multivariate and the underlying models are data driven. Moreover, the predictive setting is more powerful for many applications, including clinical diagnosis and brain-computer interfacing. This project will show the key features and challenges of pattern recognition methods when applied to fMRI data. In particular we will demonstrate how different measures can be extracted from fMRI, such as activity levels or connectivity strengths, and how these can me modelled in a predictive setting. Techniques: FMRI, Signal Processing, Machine Learning Location: Bâtiment d’appui, Radiologie, Etage P, HUG, Geneva Phone number: 022/3725215 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.9 Simultaneous high resolution EEG and fMRI Faculty: Serge Vuillemoz Postdocs/PhD Students: Laurent Spinelli Description: In this project the recording of high-density EEG (256 channels) in the MRI will be demonstrated and the correction and spatio-temporal analysis of the EEG and the convolution of EEG signals with the BOLD response will be learned. Techniques: EEG and fMRI Location: Bâtiment d’appui, Neurologie, 2eme Etage, HUG, Geneva Phone number: 022 379 54 63 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.10 Functional MRI of pain processing Faculty: Patrik Vuilleumier Postdocs/PhD Students: Yann Cojan / Corrado Corradi dell’Acqua Description: The project will illustrate the combination of fMRI with thermal and painful stimulation. Assessing the brain responses to pain provides important clues in several domains related to affective and social processes (e.g. empathy), and for the assessment of analgesic treatments using drugs or non-pharmacological means (e.g. hypnosis). The project will present the use of an MRI-compatible thermode device and some experimental applications. Techniques: fMRI, thermode Location: CMU/BBL Phone number: 022 - 37 95 369 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.11 fMRI of odor processing Faculty: Patrik Vuilleumier Postdocs/PhD Students: Sylvain Deplanque, Aline Pichon Description: The project will illustrate the combination of fMRI with olfactory stimulation. Studying brain responses to odors provides unique insights into emotional processes, but requires a complex setup to deliver odorants without other tactile stimulation due to air flow changes. The project will demonstrate the principles and application of an new MRI compatible olfactometer device allowing the administration of more than 20 different odorants to each nostril separately. Techniques: fMRI, olfactometer Location: CMU/BBL Phone number: 022 - 37 95 369 FENS-IBRO Students: 2

- Fabien / Frank: real-time fMRI - Aline / Sylvain: olfactory stimulation during fMRI - Yann / Corrado: pain stimulation during fMRI - Gwladys / Camille: ASL and mood disorders - Swann / Christoph / Hamdi: Emotion induction and fMRI



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FENS-IBRO Training Center lab 3.12 Functional MRI to assess changes in affective states through network connectivity analysis Faculty: Patrik Vuilleumier Postdocs/PhD Students: Swann Pichon / Hamdi Eryilmaz Description: The project will illustrate fMRI methodology to induce transient emotions by exposure to movies and measure subsequent impact on both resting activity and stimulus evoked responses. A method for whole-brain connectivity analysis based on wavelet band correlations will be introduced. Techniques: fMRI, connectivity analysis. Location: CMU/BBL Phone number: 022 - 37 95 369 FENS-IBRO Students: 2



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FENS-IBRO Training Center lab 3.13 Real-time fMRI and neurofeedback Faculty: Patrik Vuilleumier Postdocs/PhD Students: Frank Scharnowsky / Fabien Robineau Description: An application of fMRI for real-time imaging and neurofeedback will be illustrated using visual and motor protocols. This methodology may allow participants to regulate the activity of selective regions in their own brain and thus be used to promote plasticity, learning, or therapeutic effects in various domains. The different steps necessary to identify regions of interest and provide real-time feedback will be explained. Techniques: fMRI, Turbo-Voyager Location: CMU/BBL Phone number: 022 - 37 95 369 FENS-IBRO Students: 2



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5. Faculty abstracts Laura Astolfi University of Rome “Sapienza” and Fondazione Santa Lucia Hospital, Rome, Italy Imaging the Social Brain: estimation of the cortical activity and connectivity from simultaneous multi-subject EEG recordings Understanding the neural mechanisms responsible for human social behavior is a challenging issue. The possibility of recording simultaneously the cerebral neuroelectric activity in different subjects (EEG hyperscanning) during the execution of different tasks can return useful information about the “internal” cerebral state of the subjects, in order to understand the cerebral processes generating and generated by social cooperation or competition. We introduce the concept of hyper-brain network, a connectivity pattern representing at once the information flow among the cortical regions of a single brain as well as the relations among the areas of two distinct brains. Results obtained in a study of different groups recorded during a popular card game revealed a larger activity in prefrontal and anterior cingulated cortex in different frequency bands for the player that leads the game when compared to other players. Results collected in a population of 52 subjects during the performance of the Iterated Prisoner’s Dilemma suggested that the most consistently activated structure is the orbitofrontal region (roughly described by the Brodmann area 10) during the condition of competition. It could be speculated whether the pattern of cortical connectivity between different cortical areas in different subjects could be employed as a tool for assessing the outcome of the subject’s choice in advance. Graph analysis of hyper-brain networks constructed from the 26 couples of individuals playing the Prisoner’s Dilemma reveals the possibility to predict non-cooperative interactions during the decision-making phase. The hyper-brain networks of two defectors show a significantly low number inter-brain links and overall higher modularity—i.e., the tendency to form two separate subgraphs—than couples playing cooperative or tit-for-tat strategies. The decision to defect can be ‘‘read’’ in advance by evaluating the changes of connectivity pattern in the hyper-brain network. Katarzyna Blinowska Department of Biomedical Physics, University of Warsaw, Poland Determination of Directed Connectivity - How to Avoid Pitfalls Several measures of connectivity are being currently used: classical measures such as correlation and coherence, measures based on Granger causality principle and nonlinear measures. Bivariate coherence, Partial Directed Coherence, Granger Causality Index, Directed Transfer Function (DTF), direct Directed Transfer Function (dDTF), Short-time Directed Transfer Function (SDTF) and nonlinear estimators of connectivity will be considered. Performance of different measures describing propagation of EEG activity will be compared, by means of simulations and application to experimental signals. In particular the differences between pair-wise and multichannel estimates will be highlighted. The influence of noise and volume conduction will be considered. The pitfalls in application of particular methods will be pointed out. The estimator of activity propagation in time and frequency will be introduced and its performance will be illustrated by means of its applications



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to motor and cognitive experiments. Dynamical information transfer will be evaluated and compared with the available anatomical and physiological evidence. Stephanie Clarke Service of Neuropsychology and Neurorehabilitation, CHUV, Lausanne Parallel and hierarchical processing in human auditory cortex Evidence from human and non-human primate studies supports a dual-pathway model of audition, with partially segregated cortical networks for sound recognition and sound localisation, referred to as the What and Where streams. The separation between the streams occurs, at least partially, on the supratemporal plane, as suggested by architectonic, hodological and activation studies. Beyond the supratemporal plane, the What and the Where streams involve, respectively, the temporal and parietal convexities. Recent electrophysiological, fMRI and TMS studies demonstrated a rapid and specific processing within each stream, with distinct behaviourally relevant stages of processing. In normal subjects learning-induced plasticity was shown to implicate specific parts of auditory networks. Following focal brain lesions the What and Where networks are progressively reorganised and offer thus a useful model for postlesional plasticity. Stefan Debener Department of Psychology, Universiyt of Oldenburg, Germany Benefits and pitfalls of EEG-informed fMRI analysis Electromagnetic fields as measured with electroencephalogram (EEG) are a direct consequence of neuronal activity and feature the same timescale as the underlying cognitive processes, while hemodynamic signals as measured with functional magnetic resonance imaging (fMRI) are related to the energy consumption of neuronal populations. It is obvious that a combination of both techniques is a very attractive aim in neuroscience, in order to achieve both high temporal and spatial resolution for the non-invasive study of brain functions subserving cognition. During the last decade a number of research groups have taken up this challenge and developed different methods of EEG-fMRI integration. I will give an overview and present one approach named EEG-informed fMRI analysis in more detail. This requires the concurrent recording of both modalities and the subsequent linear decomposition of the EEG data with independent component analysis (ICA) before trial-by-trial fluctuations of the EEG can be used to predict the fMRI-BOLD response. Applications of this approach will be presented and more recent developments in the field will be discussed. Leon Deouell Department of Psychology and Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel



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The problem with the eyes: why eye movements should be taken (more) seriously in EEG and MEG research Eye movements are a critical part of our visual systems, part of what is now known as ‘active sensing’. At the same time, eye movements affect the measurement of neurophysiological data in complex ways. While in the field of fMRI there is some awareness of the fact that eye movements should be controlled while participants perform various tasks using eye tracking, in the EEG and MEG field this potential confound has been only rudimentarily accounted for. The reason may be the assumption that eye movements can be sufficiently monitored using simple amplitude thresholds on electroencephalogram channels, and over reliance on averaging techniques. However, recent studies show that this may be an overly optimistic view, as eye movements may be a task related, non-random effect. Those, some classical effects may indeed be an artifact of poor control of eye movements. I will discuss various mechanisms by which eye movements can affect electric and magnetic measurements, both in the time domain and in the spectral domain. These include cases in which ocular or extraocular muscles signal is mistaken to be of neural origin, as well as cases in which eye movements or eye position affect truly neural signals in a non-random way. Potential remedies with or without dedicated eye tracking will be also discussed. Elia Formisano Maastricht Brain Imaging Center (MBIC), Faculty of Psychology and Neuroscience, Maastricht University, The Netherlands Decoding the listening brain with machine learning and functional neuroimaging Machine learning and pattern recognition techniques are being increasingly employed in functional magnetic resonance imaging (fMRI) data analysis. By taking into account the spatial pattern of brain activity measured simultaneously at many locations, these methods allow detecting subtle, non-strictly localized effects that may remain invisible to the conventional analysis with univariate statistical methods. In this lecture, after a general methodological introduction, I will illustrate several recent studies in which machine learning and functional neuroimaging are combined to understand the functional architecture of the human auditory cortex and to unravel the neural representations involved in the brain processing of natural sounds (e.g. human voices, speech, music). Stefan Kiebel Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany Dynamic Causal Modelling for EEG and MEG In my talk I will motivate and describe Dynamic Causal Modelling (DCM) for EEG and MEG data, which is a Bayesian analysis technique to infer about effective brain connectivity. The method can be applied to several data types like evoked responses, induced and evoked power data or phase responses. Here, I will illustrate the use of DCM using evoked response potentials acquired under the mismatch negativity paradigm and show how the technique can easily be applied to other auditory experimental paradigms. In particular, DCM uses Bayesian model comparison which



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allows one to identify, in a statistically principled way, the model (i.e., hypothesis) which best explains the data, both for single- and multi-subject data. DCM is part of the Statistical Parametric Mapping software and can be obtained from http://www.fil.ion.ucl.ac.uk/spm/. Patric Hagmann Department of Radiology, University Hospital Center & University of Lausanne (CHUV-UNIL), Lausanne, Switzerland MR connectomics MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches. Christoph Michel Functional Brain Mapping Laboratory, Dept. of Fundamental Neurosciences, University Medical School, Geneva, Switzerland Electrical Neuroimaging: Methods and Applications Electrical Neuroimaging refers to the analysis of multichannel EEG with tools that look at the temporal dynamics of the scalp potential field and the neuronal generators of these fields. This course will give an overview of this neuroimaging method and will explain the basic methodological principles. It will illustrate the enormous potential for the dynamic mapping of brain functions with electrical neuroimaging with a particular focus on the mapping of spontaneous resting-state EEG in healthy subjects and in clinical populations. Lee Miller Dept. of Neurobiology, Physiology, & Behavior and Center for Mind & Brain, University of California, Davis, CA, USA Auditory cognitive neuroscience: experimental approaches using fMRI and EEG Brain imaging with acoustic stimuli presents many unique challenges, from experimental design to data analysis. I will describe several approaches that can improve the specificity and power of auditory cognitive neuroimaging paradigms. These include techniques for presenting stimuli in MRI



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scanner noise, creating ecologically valid cognitive tasks using virtual space, characterizing near-threshold or bistable perceptual phenomena, minimizing earphone artifacts, and analyzing EEG waveforms for temporally overlapping sounds. For instance, we used high-density EEG to address how listeners select a single speech stream among many competing talkers – the so-called “cocktail party effect”. Unfortunately EEG signals to continuous, overlapping sounds comprise a complex mixture whose components are not easily attributed to the stimuli. We therefore developed a time-frequency template-matching analysis method that quantifies how much of a given sound is represented in the ongoing EEG. Using this technique, we found that sustained selective attention to speech acts as a gain control on the early auditory cortical responses, greatest at a frequency of 4-8 Hz. I will address the strengths, limitations, and alternatives for this and other approaches that help us characterize the neural bases of auditory perception and cognition. Mathias Pessiglione Institut du Cerveau et de la Moelle épinière, Hôpital Pitié-Salpêtrière, Paris, France Dopamine as a teaching signal: some evidence from neuroimaging, models and patients Computational models of reinforcement learning have shown that reward prediction errors can explain how performance is improved in a variety of situations. Dopamine neurons seem to signal such prediction errors (actual minus expected reward) in the primate brain. Accordingly, dopamine release has been assumed to represent a teaching signal that is used to update the values of environmental cues and/or undertaken actions. This hypothesis has been corroborated by a number of pharmacological studies manipulating dopamine transmission. However, a substantial literature has implicated dopamine in other processes that also participate in goal-directed behavior, such as motor skills, incentive motivation and decision-making. In my talk, I will address this controversy by presenting a comprehensive series of studies combining pharmacological challenge, computational modeling and functional neuroimaging. Results support the theory that dopamine primarily serves as a teaching signal. They might provide insight into several pathological conditions such as Parkinson’s disease, Tourette’s syndrome and pathological gambling. Gilles Pourtois Psychopathology & Affective Neuroscience Lab, Ghent University, Belgium Disentangle cognitive control processes during error monitoring using topographic evoked potential mapping Error monitoring is a fundamental cognitive process enabling learning and the implementation of remedial actions. The detection of response errors is achieved through the swift activation of a reinforcement learning signal within a specific brain network, involving cortical (Rostral Cingulate Zone) as well as subcortical (mesencephalic) dopaminergic-dependent regions. Converging neuroscience evidence shows that error detection is associated with specific electrophysiological responses following error commission, including the error-related negativity (ERN) as well as the error-positivity (Pe). In this paper, I present recent topographic evoked potential results shedding light on effects of proactive top-down attention control as well as retroactive conscious monitoring



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on this generic error-detection brain system. More specifically, these neurophysiological findings suggest (i) that errors are rapidly differentiated from correct responses thanks to an ultra fast emotional tagging of perceived action failures, and the rapid recruitment of additional emotional control regions (e.g. insula and orbitofrontal cortex). Intriguingly, the detailed study of neurophysiological processes occurring before the commission of response errors also shows (ii) that anticipatory attention control system (e.g. precuneus) can reliably predict and influence these early error detection brain processes (i.e. ERN). Moreover, (iii) these emotional control regions form a salience detection network, whose rapid involvement is necessary to lead to the conscious appraisal of action failures (i.e. Pe). Altogether, these new EEG results inform about the temporal dynamic of several brain systems involved in error monitoring, and they suggest that the conscious detection of response errors may actually be a more complex cognitive process than previously thought. Patricia A. Reuter-Lorenz Professor of Psychology, Cognition and Cognitive Neuroscience Program, University of Michigan, USA Aging Mind and Brain: Decline and Compensation Brain imaging reveals regions of greater activity in older than younger adults, even when performance is age-equivalent. This talk will consider the importance of these patterns and discuss this general outcome in the context of a theory I have advanced referred to as CRUNCH, compensation-related utilization of neural circuits hypothesis. CRUNCH proposes that older adults recruit more neural circuits at lower levels of task demand than younger adults, and that this over-recruitment occurs in response to declining neural efficiency. In my talk, I will explain how the CRUNCH framework can be useful for identifying patterns of activation related to increased vulnerability and potentially for defining targets for neurocognitive interventions. Jorge Ripoll Visiting Professor at ETH, Institute for Biomedical Engineering, D-ITETtra, Zurich, Switzerland / Inst. of Electronic Structure & Laser, Foundation for Research and Technology-Hellas (FORTH), Crete, Greece Concurrent Optical and MR Imaging: New Approaches and Hurdles to Overcome In this talk I will begin by presenting the main approaches and assumptions involved in optical tomography, in particular how 3D images of probe concentration can be obtained through optical measurements in-vivo. The integration of an optical imaging setup in an MRI bore will be discussed, and new approaches and the first in-vivo applications presented, together with the significant advantages that the use of a priori anatomical information has on the optical imaging problem. The current state of the art of hybrid optical-MRI setups will be presented, along with a discussion of the next hurdles to overcome in order to increase sensitivity and specificity and obtain complementary information from both techniques.



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Jean-Philippe Thiran Swiss Federal Institute of Technology Lausanne (EPFL) Institute of Electrical Engineering (IEL) Signal Processing Laboratory (LTS5) Lausanne, Switzerland Diffusion MR image analysis: towards global brain connectivity analysis In this talk I will discuss diffusion MR imaging as a tool for macroscopic studying brain connectivity in-vivo. I will first explain how MR imaging can be used to measure diffusion in the human brain and how the diffusion phenomenon is related to white matter architecture. Several diffusion MR protocols will be presented, including Diffusion Tensor Imaging (DTI) and Diffusion Spectrum Imaging (DSI). Then I will show advanced image analysis techniques developed to infer information on brain connectivity from diffusion MR images, and how this can be applied to study global brain connectivity both in normal and pathological cases. Gregor Thut Centre for Cognitive Neuroimaging, University of Glasgow, UK Probing the role of oscillatory brain activity in visual cortex excitability and visual perception using TMS and EEG There is converging evidence from psychophysics, animal electrophysiology, human electro-/magnetoencephalography (EEG/MEG) and transcranial magnetic stimulation (TMS) that brain oscillations in lower frequency bands (theta to alpha) play an important role in attention and perception. This talk will cover recent contributions from combined TMS-EEG research to this topic. It will focus on rhythms over parieto-occiptal areas and how their spectral features (power and phase) relate to TMS-inferred visual cortex excitability, and to visual perception. I will survey recent studies on the relationship between spontaneous variability in ongoing brain oscillations, visual cortex excitability, and visual detection/discrimination. I will also present new data on how these oscillations over visual areas can be modulated through non-visual input (such as sounds, or direct stimulation by TMS). These data reveal that sounds or TMS bias ongoing oscillations, such that they become phase-aligned to the non-visual event (occipital phase locking), or become further entrained when repeated events are frequency-tuned to the ongoing oscillations (parieto-occipital power enhancement). Notably, the evoked brain waves in lower frequency bands (here alpha) causally impact visual perception and are co-varying (cycling) with TMS-inferred visual cortex excitability. This is supportive of oscillatory power over parieto-occipital cortex regulating visual input and phase-alignment playing a crucial role in shaping neuronal sensitivity. Robert Turner Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany MRI at 7 Tesla



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The high spin magnetization at 7T and greatly improved RF coil technology provide much better SNR than at lower field strengths. The goal of in-vivo Brodmann mapping of anatomically distinct regions of grey matter, on the basis of MRI-visible myeloarchitecture, now appears to be at least partly feasible, which enables precise association of function with neuronal substrate. With appropriate MRI methods, cortical layering due to the myelinated bands of Baillarger has been observed in several regions, such as primary visual cortex V1, and the visual motion area V5. A study of normally sighted and congenitally blind volunteer subjects reveals that the myelinated layer structure of V1, the Stria of Gennari, remains unaltered in blindness, showing that this structure is independent of visual input for development in childhood or maintenance in adulthood. At 7T, 350 micron resolution in-vivo images of human hippocampus allow unwrapping of its folded structure. The basal ganglia are visualized with unprecedented clarity, and their magnetic susceptibility can be mapped, indicating iron content. MRI of the corpus callosum also shows unexpected fine-scale structure. We perform comparisons of cortical structure visualized with microscopy of stained cadaver brain sections, ex-vivo MRI and in-vivo MRI. Examples will be shown of the S1/M1 border, and a complete automated parcellation of primary visual cortex. The first successful implementations of BOLD fMRI and diffusion-weighted MRI, using the very fast imaging technique of echo-planar imaging (EPI) required to avoid the artefactual effects of head movement, were made by Turner in the years 1989-1991. BOLD-EPI was performed in cat brain at 2T, later at 4T with human subjects (1992), and DW-EPI was performed with human volunteers at 1.5 T in 1990. However, there are significant challenges at 7T in regard to EPI, associated with susceptibility artifact and the short transverse relaxation time T2*. We have found solutions to these problems, and excellent EPI images can now be obtained. These novel methods enable an isotropic single-shot fMRI resolution of 0.65 mm, with enough SNR to measure localized BOLD signal changes. A study of cortical layer-specific activity of motor and somatosensory cortex will be described, showing differential time-courses for a range of motor tasks. Good diffusion-weighted images with isotropic 0.8 mm resolution can also be obtained, showing fibre crossings in detail, and well-defined grey matter anisotropy in adult living brain. These dramatic improvements in spatial resolution will open new windows into the understanding of human brain function, rendering obsolete analysis methods that require extensive normalization and smoothing of brain images. Wietske van der Zwaag Laboratory of functional and metabolic imaging, University of Lausanne Introduction to fMRI at ultra-high field In this talk, I will give an outline of both the advantages and challenges of ultra-high field (7 Tesla or higher) for fMRI and of the problems and the different ways in which these can be overcome. The physiological origin of the BOLD response will be discussed to allow an understanding of the effects of a choice of magnetic field strength. The use of ultra-high field MRI scanners can offer important benefits for functional MRI studies, such as a higher signal-to-noise ratio. However, the stronger magnetic field also has some drawbacks. Specifically, the trade-off between increased SNR,



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BOLD sensitivity and BOLD specificity due to the increased susceptibility effects and the increased image artifacts and physiological noise will be discussed. Some of the highly-accelerated sequences developed and high spatial resolution studies performed to make optimal use of the ultra-high field systems will be presented. Dimitri Van de Ville Department of Radiology and Medical Informatics, University of Geneva / Institute of Bioengineering, EPFL, Lausanne Brain dynamics and fractal behavior: a story about (fast) EEG microstates and (slow) fMRI resting-state networks Spontaneous brain activity during "resting state" has become an intriguing research topic over the past few years. It allows to probe into the intrinsic organisation of the brain in large-scale functional networks. In the first part of this talk, I will illustrate a surprising link between EEG microstates and fMRI resting-state networks. Specifically, the rapid occurrence signals (100ms dynamics) of the EEG microstates---only four microstates are predominant to describe spontaneous EEG---are convolved with the hemodynamic response function (reducing the dynamics to the 10s timescale) and fed into a general linear model to analyze the simultaneous fMRI recordings, revealing four large-scale resting-state networks; i.e., the visual, auditory, self-referential, and dorsal attention networks. In the second part, I will uncover the mechanism that explains how timescales so different can be linked. Specifically, we underpin the hypothesis that scale-free behavior of EEG microstate dynamics is responsible for this surprising connection. Using wavelet-based fractal analysis, we found a clear signature of monofractality over 6 dyadic scales covering the 256ms-10s range. Moreover, the degree of long-range dependency was maintained when shuffling the local microstate labels but became indistinguishable from white noise when equalizing microstate durations, which indicates that temporal dynamics are their key characteristic. In sum, the four rapidly varying EEG microstates seem to represent the neurophysiological correlates of four known RSNs and their scale-free dynamics allow them to be measured at the slow fMRI timescale. [1] D. Van De Ville, J. Britz, C.M. Michel. EEG Microstate Sequences in Healthy Humans at Rest Reveal Scale-Free Dynamics. (2010). Proceedings of the National Academy of Sciences of the USA. vol 107. pp 18179-18184. [2] J. Britz, D. Van De Ville, C.M. Michel. BOLD Correlates of EEG Topography Reveal Rapid Resting-State Network Dynamics. (2010). NeuroImage. vol 52. pp 1162-1170. Mark Wallace Multisensory Research Laboratory, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA Single-unit approaches to studying multisensory integration



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I will present single unit methods as they apply to studies of multisensory integration. I'll cover some background, as well as some of my development work and the new spatiotemporal analyses.

6. Students’ abstracts Retrieving out-of-body experiences: Third person perspective encoding perturbs hippocampus activity during retrieval Loretxu Bergouignan(1); Lars Nyberg(2); H. Henrik Ehrsson(1) (1) Karolinska Institute (2) Umeå University If most life experiences are presumably encoded from a first person perspective (E1PP), encoding from a third person perspective (E3PP) can happen during dissociative experiences of stressful events (Brewin et al. 2010). Life experiences are by definition uncontrollable, here, we modeled a life-like social stress interaction with a professional actor (playing a nasty professor) and created a controllable autobiographical like encoding condition. In addition, with a perceptual illusion we simulated the experience of being out-side one’s body in healthy subjects (Ehrsson 2007) to study the effect of the two types of encodings: E3PP vs. E1PP. We then assessed episodic memory retrieval a week after the occurrence of the encodings behaviorally (study 1) and analyzing brain activity during retrieval (study 2). The E3PP caused significantly less access to episodic retrieval (less Remember response). Moreover we observed the classical autobiographical memory network activation for both E1PP and E3PP retrievals with a crucial activity difference in the left posterior hippocampus. If the activity of the hippocampus decreased with repetition for E1PP, it had an opposite pattern for E3PP, with no activation in the first retrievals, and showing an over-activation after high repetition of retrievals. A dissociative view of an event has thus an immediate impact on the subsequent memorability of the event and its neural pattern. This causal relationship is a fundamental step in our understanding of neurocognitive processes that obstruct the integration of personal experiences into autobiographical memories. Gender affects the effect of the serotonin transporter gene and childhood adversity on hippocampal volume Daphne Everaerd1,2, Lotte Gerritsen1,2, Mark Rijpkema1, Thomas Frodl3, Barbara Franke2,4, Iris van Oostrom2, Guillén Fernández1,5, Indira Tendolkar1,2 1 Radboud University Nijmegen, Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands 2 Department of Psychiatry, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Centre for Neuroscience, Nijmegen, The Netherlands 3 Department of Psychiatry, Institute of Neuroscience, University Dublin, Trinity College, Dublin, Ireland 4 Department of Human Genetics, Radboud University Nijmegen Medical Centre, Institute for Genetic and Metabolic Disease, Nijmegen, The Netherlands



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5 Department of Cognitive Neuroscience, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands Short (S) allele carriers of the serotonin transporter linked polymorphic region (5-HTTLPR) show more depressive symptoms, in particular after stressful life events and childhood adversity. Volume reductions in the hippocampus have also been associated with a greater risk for major depressive disorder and an association between this genotype and hippocampal volume was found in healthy subjects in some studies, but not all. We hypothesize that sex has a modulatory effect on this gene x environment interaction on hippocampus volume, thereby explaining previous false-negative findings. A total of 357 young, healthy subjects (136 males, 221 females) with magnetic resonance imaging data at 3 Tesla were included in this study. The 5-HTTLPR genotype was determined as a triallelic locus by also genotyping the single nucleotide polymorphism (rs25531) in this region. For automatic segmentation of the hippocampus we used the FIRST module of FSL. Childhood adversity (CA) was assessed with the List of Threatening Life Events questionnaire (Brugha). There was a significant genotype x sex x severe CA interaction (p=0.010), as well as a significant two-way interaction genotype x severe CA (p=0.007) in the male subgroup. Post-hoc tests revealed that this interaction was driven by an association between severe CA and smaller hippocampal volume in male S-allele carriers. Interestingly, there was no main effect of genotype in the male subgroup. Females with the L/L genotype however had larger hippocampal volumes than female S-allele carriers (p=0.023). In summary, our results show that sex significantly modulates the interaction between 5-HTTLPR genotype and childhood events. This finding could explain the inconsistent results of previous studies on 5-HTTLPR and CA effects on hippocampal volume. Neural plasticity of voice processing: Evidence from event-related potentials in congenitally blind and sighted controls Julia Föcker*#, Anna Best*, Cordula Hölig* and Brigitte Röder* #Brain & Cognitive Sciences, University of Rochester, New York *Biological Psychology and Neuropsychology, University of Hamburg, Germany Blind individuals have to rely much more on vocal information compared to sighted individuals in order to identify other people. Previous studies have suggested faster processing of auditory input in the blind compared to sighted controls and an enhanced activation of temporal and occipital cortical regions during voice processing. The present experiment used event-related potentials (ERPs) to single out the sub-processes of auditory person identification that reorganize and allow for superior voice processing after congenital blindness. A priming paradigm was employed in which two successive voices (S1 and S2) of either the same (50% of the trials) or different actors were presented. Congenitally blind and matched sighted participants made an old-young decision on the S2. While reaction times were shorter in person-congruent trials than in person-incongruent trials for both groups, congenitally blind showed faster learning rates than sighted controls. ERPs to S2 stimuli in person-incongruent as compared to person-congruent trials were enhanced at early processing stages (100-160 ms) in congenitally blind participants only. A similar later negative ERP effect (> 200 ms) was found in both, sighted individuals and congenitally blind. These effects had a



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centro-parietal topography in the sighted but a posterior topography in the congenitally blind. These results provide evidence for an improvement of early voice processing stages and a reorganization of the person identification system as a neural correlate of compensatory performance following congenital blindness. Computationally Efficient Non-Parametric inference from fMRI Searchlight Classification Tal Golan (1), Uri Hertz (1) (2), Amir Amedi (2) (1) (3) (1) The Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel. (2) Department of Medical Neurobiology, The Institute for Medical Research Israel-Canada (IMRIC), Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel. (3) The Cognitive Science Program, The Hebrew University of Jerusalem, Jerusalem, Israel. Since the early 2000s, Multi-Voxel Pattern Analysis (MVPA) has gained momentum as a powerful alternative to Region of Interest (ROI) activation analysis of fMRI. Kriegeskorte, Goebel and Bandettini (2006) suggested applying MVPA to ROIs sampled systematically by a searchlight procedure. This method enables exploratory localization of multivariate information, unconstrained by predefined ROIs. We hold that while being an attractive alternative to the prevalent mass-univariate approach to brain mapping, its adaptation by the neuroscientific community raises issues of statistical inference. Kriegeskorte et al’s (2006) original method employed a multivariate distance measure as its statistic. This statistic was computed for each searchlight location, tested against a null distribution computed by label permutation and corrected for multiple-testing by standard FDR procedure. However, most of the authors who adapted the searchlight procedure employed a classification scheme, in which the statistic used was cross-validation classification accuracy. The usage of this statistic offers intuitive interpretation and natural extension to cross-stimulus and multiclass designs. The downside is the high computational cost of training standard classifiers such as Support Vector Machines for each searchlight location. Due to this cost, label-permutation testing becomes unfeasible and many authors resort to using a parametric T-test, contrasting the across-subject mean of the cross-validation accuracy map with chance level. Often, it is then corrected to multiple testing by a cluster threshold based on Random Field Theory (RFT). We argue that this method poses unnecessary limitations: Its power is compromised by the need of inter-subject voxel-to-voxel agreement, its validity is dependent on the fulfillment of RFT assumptions and obviously it disallows any single-subject inference. We demonstrate that regularized least-squares classification (Rifkin, Yeo & Poggio, 2003) enables producing both true accuracy maps and label permuted null accuracy maps at a low computational cost. These null accuracy maps can be used to produce voxel-wise or cluster-wise statistical thresholds, which are powerful and essentially distribution free. Increased Functional Connectivity Indicates The Severity Of Cognitive Impairment In Multiple Sclerosis David J. Hawellek a1, Joerg F. Hipp ab, Christopher M. Lewis cde, Maurizio Corbetta def, Andreas K. Engel a



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a: Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany b: Centre for Integrative Neuroscience, University of Tübingen, 72076 Tübingen, Germany c: Ernst Stüngmann Institute in Cooperation with Max Planck Society, 60528 Frankfurt, Germany d: Department of Clinical Sciences and Bioimaging G. D’Annunzio University, 66100 Chieti, Italy e: Institute for Advanced Biomedical Technologies, G. D’Annunzio University, 66100 Chieti, Italy f: Departments of Neurology, Radiology, Anatomy and Neurobiology, Washington University School of Medicine, 63110, St. Louis, MO, USA Correlations in spontaneous brain activity provide powerful access to large-scale organizational principles of the central nervous system. An important prerequisite for deriving inferences about cognitive processes from these couplings is a detailed understanding of how the structural integrity of the underlying circuits is reflected in this covariance. We studied the impact of multiple sclerosis, which leads to severe disintegration of the central white matter, on functional connectivity patterns in spontaneous cortical activity. Using a data driven approach based on a prominent pattern of behavioral pathology, we identified distinct networks that exhibit increases in functional connectivity despite the presence of drastic and diffuse reductions of the central white matter integrity. The default mode network emerged as a core target of these connectivity modulations, showing enhanced functional coupling between bilateral inferior parietal cortex, posterior cingulate and medial prefrontal cortex. These findings imply a complex and diverging relation of anatomical and functional connectivity in early multiple sclerosis and, thus, add an important observation for understanding how CNS integrity may be reflected in the spontaneous covariance of functional signals. Formation and consolidation of semantic memory Nora Hennies, Dr. Penny Lewis, Prof. Matt Lambon-Ralph University of Manchester (Neuroscience amd Aphasia Research Unit), UK Several neurodegenerative diseases, especially semantic dementia, drastically demonstrate the importance of semantic memory (conceptual knowledge) for fundamental cognitive processes, which allow us to form coherent concepts and generalise this knowledge to new situations. How is conceptual knowledge formed and consolidated? A neurocomputational model for semantic memory (Rogers et al., 2004) suggests that conceptual knowledge is formed by the gradual extraction of a statistical pattern over various experiences. The idea that semantic representations are formed by semanticization of episodic memories was already formulated in an influential approach to declarative memory, the complementary learning systems (CLS) framework by McClelland et al. in 1995. This model further proposes that episodic memories strongly depend on the hippocampus, while semantic memories, which are characterised by general, abstract knowledge, are represented in the neocortex and mainly hippocampus-independent. This qualitative difference in the memory storage between the hippocapus and the neocortex implies a shift from hippocampus to neocortex with semanticization. The process of semanticization has also been reported in sleep research. Nowadays there is a growing body of evidence that sleep promotes a qualitative memory change to more abstract and



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generalized representations. It is hypothesized that during REM-sleep three processes: unitization, assimilation and abstraction, cause this sleep-dependent qualitative memory change (Walker & Stickgold, 2010). Hence sleep might provide a mechanism for the extraction of a statistical pattern over various experiences. In the PhD undertaken we investigate the formation of conceptual knowledge and the role of sleep in this process. Therefore we address the hypothesis that this qualitative memory change from detailed, context-bound representations to more abstract, generalized pattern is accompanied by a sleep-dependent shift from hippocampus to the neocortex. We have developed a paradigm, which allows to track the formation of abstract conceptual knowledge over several learning sessions. Several neuroimaging techniques (fMRI, EEG and TMS) will be applied at different time points to investigate the functional anatomy and role of sleep. Rogers, T. T., Ralph, M. A. L., Garrard, P., Bozeat, S., McClelland, J. L., Hodges, J. R., and Patterson, K. (2004). Structure and deterioration of semantic memory: a neuropsychological and computational investigation. Psychological Review, 111(1):205-35. Walker, M. P. and Stickgold, R. (2010). Overnight alchemy: sleep-dependent memory evolution. Nat Rev Neurosci, 11(3):218; author reply 218. Simultaneous EEG/fMRI Analysis of Steady-State Visual Evoked Responses Esin Karahan1, Muge Ozker1, Ali Bayram1, Zubeyir Bayraktaroglu2, Basri Erdogan1, Itir Kasikci3, Cengizhan Ozturk1, Ahmet Ademoglu1, Tamer Demiralp2 1. Bogazici University, Institute of Biomedical Engineering, Istanbul, Turkey, 2. Istanbul University, Istanbul Faculty of Medicine, Department of Physiology, Istanbul, Turkey, 3. Istanbul University, Institute of Experimental Medicine, Istanbul, Turkey The correlation between the synchronization patterns of EEG and BOLD is an important aspect of EEG-fMRI integration. Steady-state visual evoked potentials (SSVEPs) generate stationary synchronized EEG patterns sustaining through the BOLD response in the form of oscillations at stimulation frequency and its harmonics. The aim of this study was to investigate the behavior of BOLD and EEG responses to the synchronization of neuronal activations. We used EEG/fMRI simultaneous recordings from subjects during presentation of flickering stimuli at a wide range of frequencies from 6 Hz to 46 Hz. We analyzed EEG/fMRI data through a hierarchical modeling where BOLD parameter and spectral amplitudes of SSVEPs are correlated. We found frequency range specific correlations between BOLD and SSVEP amplitudes despite the fact that statistical parametric maps of BOLD activation over stimulation frequencies showed activation at all frequency ranges. We found BOLD/SSVEP correlations in the primary viusal cortex only for only for the stimulation frequencies between 14 and 26 Hz (beta range). Absence of a correlation in alpha frequency range between BOLD and SSVEP, may imply the resonance of the thalamo-cortical alpha oscillator without an increase in total synaptic acitivity. This study was supported by TUBITAK project #108S101.



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Structural changes induced by one week of motor training are associated with the rate of learning and predict improvements in performance one year later Sofía Landi, Federico Baguear and Valeria Della-Maggiore Department of Physiology, School of Medicine, University of Buenos Aires, Argentina. The neural bases of motor adaptation have been extensively explored in human and nonhuman primates. A network including the cerebellum, primary motor and the posterior parietal cortex appears to be crucial for this type of learning. Yet, to date, it is unclear whether these regions contribute directly or indirectly to the formation of motor memories. Here we trained subjects on a complex visuomotor rotation associated with long-lasting retention to identify potential sites of structural plasticity induced by adaptation. T1 and diffusion weighted images were acquired from 12 right-handed young participants before and after seven days of 40-min daily training on a task that required adaptation to a complex optical rotation using the right hand. On average, adaptation was achieved after 6 days of training. One week of training induced i) an increment in local gray-matter concentration over the hand area of the contralateral primary motor cortex and ii) an increase in fractional anisotropy of corticospinal fibers connecting the hand area, that correlated with the speed of learning. During a second exposure to the perturbation one year later (test), subjects adapted within a time window of minutes, strongly indicating the formation of a long-lasting motor memory. Moreover, the change in grey matter concentration measured immediately after training predicted long-term memory one year later. Our study suggests that motor adaptation induces structural plasticity in primary motor circuits. In addition, it provides the first piece of evidence indicating that early structural changes induced by motor learning may impact on behavior up to one year after training. Experience and action observation networks in the brain: Integrating findings across physical differences and physical disability Sook-Lei Liew1,2, Tong Sheng1,3, Shihui Han4, & Lisa Aziz-Zadeh1,2,3 1. Brain and Creativity Institute, University of Southern California, Los Angeles, CA, USA 2. Department of Occupational Therapy, University of Southern California, Los Angeles, CA, USA 3. Neuroscience Graduate Program, University of Southern California, Los Angeles, CA, USA 4. Department of Psychology, Peking University, Beijing, China How do our experiences shape the neural networks involved in understanding others? Cognitive neuroscience has focused roles of action observation networks (such as the putative human mirror neuron system (MNS)) and higher-level cognitive networks (such as the mentalizing system), to be able to fully extract another’s intentions from observing his or her actions. Much of this research suggests that we use our own sensorimotor representations (such as in the MNS) to understand more familiar actions, while we use neural regions associated with higher-level reasoning (e.g., mentalizing system) to understand unfamiliar actions. However, here I will present three fMRI studies that suggest that under some circumstances, we in fact use our own sensorimotor regions to understand physically different others. In addition, if our own motor capabilities are affected, such as after a stroke, we recruit different variations of these same networks.



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(1) First, an fMRI case study of a woman born without arms or legs suggests that she engages both MNS and mentalizing regions when she observes actions that are physically impossible for her, such as using scissors or going onto her tiptoes. (2) Second, an fMRI study with16 typically developed individuals observing videos of this visually-novel participant without arms performing stump actions and videos of visually-familiar participants performing hand actions suggests that understanding a novel body part (e.g., upper stump) evokes much greater activity in one’s own sensorimotor regions than understanding a familiar body part (e.g., hand). In addition, this sensorimotor activation is attenuated by experience with the visually novel limb. (3) In the third study, I present findings from 12 participants with chronic stroke resulting in moderate to severe hemiplegia and 12 age-matched non-disabled participants as they observe actions performed by both limbs. The results here suggest that for stroke participants, observing the limb that corresponds to their paretic limb in fact generates greater ipsilesional MNS activation, as though trying to more effortfully engage these sensorimotor areas for actions they can no longer perform. Together, these studies suggest that when observing novel or difficult-to-perform actions or individuals that are physically different from ourselves, we may in fact effortfully engage our own sensorimotor regions to make sense of those around us, a finding which has implications for both basic and clinical neuroscience. Analysis of predictors based on stimulus properties influencing P3a amplitudes in an auditory attention orienting task C.A. Mugruza Vassallo 1, D.D. Potter 1, C. Pernet 2, G.A. Rousselet 3 1 School of Psychology, University of Dundee, UK. 2 SFC Brain Imaging Research Centre, Division of Clinical Neurosciences, Western General Hospital, Edinburgh, UK. 3 Centre for Cognitive Neuroimaging (CCNi), Department of Psychology, University of Glasgow, UK. Introduction: Several studies suggest that P3a amplitude is highly correlated with time or number of trials between two un-expected or non-standard stimuli (e.g. Gonsalvez & Polich, 2002). Potter et al. (2008) found in event-related potential (ERP) evidence of differences in the distribution of the P3a component which suggests a dissociation of activity in stimulusdriven (SDN) and goal-driven networks (GDN) of the attention reorienting system (Corbetta et al., 2008). To explore the feasibility of the dissociation of SDN and GDN in P3a components with a posterior parametric experiment, we have used single trial across-subject averaging of 15 EEG (control participant) to study the effects of auditory stimulus probability, frequency, amplitude and duration on P3a ERP amplitude and distribution. Results: Novel P3a amplitude showed significant variation over time but does not decrease in the long-term, was not simply predicted by inter-trial intervals as predicted by Gonsalvez & Polich (2002) with a non-significant correlation near to 0.3, and showed a significant variation with Inter-Stimulus Interval was significant in Cz.



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There were tested correlations of current preceding novel (PN) with other conditions. There were correlations between properties of the same sound and many weak or non-significant with most of the other sounds. P3a amplitude showed contrast correlations between left and right presentation and greater than 0.5 in sound Duration, Mean Amplitude and Frequency. The P3a amplitude evoked by novel stimuli was lateralized to the right hemisphere, even when sound was presented in the left ear. This may be consistent with activation of the stimulus-driven system Corbetta et al. (2002, 2008) acting in conjunction with the goal driven system during attention orienting. Ongoing work: In a single subject were used two stimulus properties Duration and Frequency of (Novel-Number(t-1)) as predictors added as categorical variables in a design matrix (X) and obtaining the estimators assuming a general linear function over all the electrodes. Next steps: Extend the analysis of predictors as a regressors of P3a waves (this was about amplitudes) and find estimators at each condition in single and multiple subjects. Also, extend the analysis to 10 schizophrenics participant and do a preliminar analysis of a pilot simultaneous EEG/fMRI experiment. Sensory competition in the face processing areas of the human brain Krisztina Nagy 1, Mark W. Greenlee 2, Gyula Kovács 1,2 1Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary 2Institute of Psychology, University of Regensburg, Regensburg, Germany The concurrent presentation of multiple stimuli in the visual field may trigger mutually suppressive interactions throughout the ventral visual stream. While several studies have been performed on sensory competition effects among non-face stimuli relatively little is known about the interactions in the human brain for multiple face stimuli. In the present study we assigned the neuronal background of the sensory competition in an event-related functional magnetic resonance imaging (fMRI) study using multiple face stimuli. We varied the ratio of faces and phase-noise images within a composite display with a constant number of peripheral stimuli, thereby manipulating the competitive interactions between faces. For contralaterally presented stimuli we observed strong competition effects in the fusiform face area (FFA) bilaterally and in the right lateral occipital area (LOC), but not in the occipital face area (OFA), suggesting different roles in competition. When we increased the spatial distance among pairs of faces the magnitude of suppressive interactions was reduced in the FFA. Surprisingly, the magnitude of competition depended on the visual hemifield of the stimuli: ipsilateral stimulation reduced the competition effects in the right FFA and LOC while it increased that in the FFA and LOC of the left hemisphere. This suggests a left hemifield dominance of sensory competition. Our results support the sensory competition theory of multiple stimulus processing of faces and suggests that this effect is the result of several cortical areas in both hemispheres.



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Voice-sensitive neurons in the primate brain Catherine Perrodin, Christoph Kayser, Nikos K. Logothetis and Christopher I. Petkov CP, CK, NKL, CIP: Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany. NKL: Imaging Science and Biomedical Engineering, University of Manchester, Manchester, UK. CIP: Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK The brain is thought to generate selective and efficient representations of important sensory events such as communicative signals, yet the various sensory systems might instantiate such selective representations in different ways. Since the 1980s the processing of facial information by ‘face’ cells has been repeatedly studied. Although auditory ‘voice’ regions showing a strong fMRI activity preference for the voice of conspecific individuals have now been identified in humans and monkeys, the fMRI signal cannot specify the encoding properties of the underlying neurons or whether fMRI voice-preferring clusters contain ‘voice cells’. We investigated the responses of neurons in an fMRI-identified voice cluster in awake macaque monkeys and provide the first systematic evidence for voice cells, defined, in analogy to face cells, as neurons responding at least two-fold stronger to conspecific voices than to heterospecific animal voices or natural/environmental sounds. Surprisingly, whereas face clusters contain high proportions of face-preferring cells that respond broadly to many faces, we found a considerable yet, by comparison, moderate proportion of voice-preferring cells that exhibited a sparse-coding strategy for voices. The observed selective representation for individual voices might stem from the different evolutionary pressures that would have affected how the auditory system has specialized relative to the visual. In all cases, our results highlight the interesting processing strategies used by the primate brain to encode auditory and visual components of communication signals. Mechanistic model of anterior cingulate cortex network during emotional and cognitive processes Ramírez-Mahaluf JP, Compte A. Institut d' investicions biomèdiques August Pi i Sunyer. (Inst) The anterior cingulate cortex (ACC) is important for cognitive and affective regulation, where the cognitive and emotional information is processed separately. Its two major subdivisions subserve distinct functions, with a dorsal cognitive division and a rostro–ventral affective division. However, we still lack a mechanistic understanding of the role of ACC in psychiatric pathology and how it participates in the impairment of the cognitive and emotional regulation. We hypothesize that the ACC manages situations of conflicting emotional and cognitive demand through the reciprocal inhibitory relationships between the dorsal “cognitive” region, and the rostral-anterior “affective” region. We build our computational model using the Brian simulator. We define the model at the neural network level with excitatory and inhibitory spiking neurons as constituent elements (integrate-and-fire model) and conductance-based AMPA, NMDA and GABAA synapses in their connectivity. The model include two microcircuits in the ventral and dorsal ACC. Both microcircuits receive inputs



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and send output in close interaction with the whole-brain and are reciprocally connected in order to simulate the mutual suppression between these two areas. The model show that both microcircuits are bistable and predict the normal reciprocal suppression between ventral and dorsal ACC during cognitive and emotional tasks. To test this we design two behavioral tasks to fMRI: 1) Sadness Provocation 2) Spatial working memory with filtering component before and after of sadness state (WM1 and WM2). We analyze functional activations and connectivity during the task between ventral and dorsal ACC and in working memory networks. During the WM2 the ventral ACC revealed higher activity that WM1 and dorsal ACC revealed activity in the opposite direction. The pattern of functional activations of the working memory networks show several changes; in the cortical areas; BA 6, 47 and 9 (right) revealed higher activity during WM1, but in the other hand BA; 9 (left) and 10 (left) lower activity during the same task. In addition, the functional connectivity of the working memory networks also show several changes. This pattern of functional activations and connectivity suggests that ACC manages situations of conflicting emotional and cognitive as predicted by our model. Behavioral and neural correlates of the interaction between tactile and proprioceptive signals Liliana Rincon-Gonzalez 1 and Stephen Helms Tillery 1,2 1 - School of Biological & Health Systems Engineering, Graduate Program in Biomedical Engineering, and 2 - Dept. of Psychology, Arizona State University, Tempe, Arizona, USA Somatosensation is divided into multiple discrete modalities that we think of separably: e.g. tactile, proprioceptive, and temperature sensation. However, all these modalities interact during stereognosis, and understanding this interaction would fill a gap in somatosensory neuroscience. My lab is presently examining the relationship between tactile and proprioceptive modalities in this context. We propose that tactile sensation is encoded in a two-dimensional map, which undergoes continual dynamic modification by an underlying proprioceptive map. In recent work, we have looked at both the structure of this proprioceptive map and also the neural correlates of the interaction between posture and tactile perception. My recent work has examined the proprioceptive map: specifically I have reconstructed and analyzed the spatial structure of the estimation errors that resulted when subjects reported the location of their unseen hand across a 2D horizontal workspace. I found that the spatial structure of the estimation errors was stable across time and mirrored across hands, but subject-specific. The magnitude of the errors was smaller closer to the body and when tactile feedback was provided. Finally, the structure of the pattern of errors was independent of tactile feedback. These results confirm prior results and extend them by showing that this map is idiosyncratic across subjects but highly conserved within subjects. Other members of the group have shown that tactile feedback from the fingers is not independent of hand posture. We are now using fMRI to study how the finger representations in somatosensory cortex depend on proprioceptive input by evaluating the effect of different finger postures on those cortical representations. First, we are using electrotactile stimulation of the fingertips to map the discrete representations of finger sensation in somatosensory cortex. At the same time, we are evaluating the sensitivity of these representations to hand posture by measuring how these representations are altered by changed hand postures. We hypothesize that cortical representations of the fingers will be affected by changing the hand’s posture.



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Understanding how these disparate signals are processed to produce sensation is crucial for providing somatosensory feedback to neuroprosthetics, a major goal of my current research group. Functional connectivity and epilepsy: a non-linear resting state fMRI investigation of temporal lobe, frontal lobe and idhiopathid generalized epilepsy Santarnecchi E.1, Polizzotto N.R.2, Vatti G.1, Marino D.1, Pucci B.1, Rossi A.1, Rocchi R.1 1-University of Siena, Siena, Italy, 2-University of Pittsburgh, Pittsburgh, United States Purpose: connectivity in epilepsy can be affected by alterations of sources/targets of projections or by plasticity mediated changes related to seizures over the course of the illness. Here we put forward the use of fMRI “resting-state” (fMRI-RS) methodology to characterize functional connectivity patterns in epilepsy patients and adress its specificity in different conditions. Furthmore we assessed the possibility to use a wide fMRI-RS normative database for single patient management. Method: epilepsy patients accessing the Department of Neurology of the University of Siena - TLE (n= 23 left, 18 right, 7 bilateral), FLE (n=19), EGI (n=6) - and 150 controls underwent no-task, seizure-free fMRI (1.5 T Phillips Intera, 178 scans,TR=2.5). After preprocessing and spurious variance removal, time series were extracted from anatomically defined ROI. Normalized pairwise connectivity matrices entered specific statistics aimed to address: 1. Group related differences including the focus and at distance; 2. Lateralization; 3. Sensibility of different connectivity measures; 4. the possibility of connectivity-based diagnosis/localization by pulling single cases and comparing connectivities against normative data. Results: we observed 1.differences inside networks both including the putative focus and at distance; 2. on the bigger patient sample, TLE, hippocampus-to-all-brain connectivity differentiates right vs left TLE; 3. Non-linear associations - mutual information (< 0.1Hz) - appears to be more sensitive than linear approaches to group differences, and (4.) in mapping deviations of single subjects. Conclusion: we provide evidence supporting the use of connectivity oriented analysis to uncover local and diaschis/compensatory changes useful for epilepsy research and management. Facial Expressions mediate Amygdalar-Frontal Modulation during a Mentalizing Task M M Schmitgen¹, S Bluschke², H Walter³, K Schnell¹ ¹Department of General Psychiatry, Heidelberg University Hospital, University of Heidelberg, Heidelberg, Germany; ²Division of Medical Psychology, University of Bonn, Bonn, Germany; ³Department of Psychiatry and Psychotherapy, Division of Mind and Brain Research A prerequisite for successful social interaction is an approtiate inference on another person's affective state. Purpose of our study was to clarify the role of information contained in emotional facial expressions in mentalizing tasks. In order to examine this question 20 false-belief comic strips consisting of three sequent pictures were presented to 22 healthy participants in a 3 Tesla MRI scanner. Half of these comic strips were free of direct cues for affective states and half of them



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included emotional facial expressions. Participants were instructed to judge whether the protagonist feels better, equal or worse than in the preceding picture. Judgements about affective state of the protagonist showed significantly higher activation of specific parts of the mentalizing network (right temporal pole and posterior superior temporal sulcus) and limbic system (right amygdala and hippocampus) whilst presentation of pictures containing facial expressions of the protagonist. Also functional (by calculating psychophysiological interactions) and effective connectivity (by structural equation modelling) analyses indicate amygdalar-frontal modulation while performing the task. Especially psychophysiological interactions reveal modulation of bilateral frontal areas via right amygdala during presentation of pictures with facial expressions. Furthermore shortened reaction times in pictures including cues for affective states indicate usage of this additional information to ease performing the task. We conclude that whilst mentalizing, emotional facial expressions are a source of information which is processed in the phylogenetic older limbic system and permit modulation on phylogenetic younger frontal cortical areas to consequently support building an appropriate inference on another person's affective state. Implementation of migraine aura model for fMRI studies Artem Shatillo, Rashid Giniatullin, Olli Gröhn Department of Neurobiology, A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland The main underlying event in aura phase of migraine is cortical spreading depression (CSD) which is a slow wave of neuronal and glial depolarization that spreads across the cortex with a speed of 2-7 mm/min. The aim of this work was to implement a robust protocol for induction of CSD in the 9.4T magnet for continuous BOLD fMRI data acquisition with simultaneous local field potentials (LFP) recording in rats. Animal preparations, consisting of femoral artery and vein canulation, cranial window opening and insertion of LFP electrode to ipsilateral frontal cortex was conducted under isoflurane anesthesia. Urethane anesthesia 1.25 g/kg and muscle relaxation with ventilation (pancuronium bromide, 0.5 mg/kg/h i.v.) was used for data collection. We induced CSD after 100 baseline BOLD images by applying 1M KCl solution (10?l) to intact meninges for 13 Wistar rats. The following imaging time was 1h (900 images). During that period, 1-5 CSD waves were observed on LFP and BOLD recordings. Based on BOLD data we calculated CSD properties: mean propagation speed of 5.3 ± 1.4 mm/min and duration of 129 ± 25 s. Developed protocol allowed us to elicit CSD with very characteristic properties in all KCl treated animals, which makes this model usable for further migraine fMRI studies. Evaluation of Consistency in Group Independent Component Analysis of Brain Resting State fMRI Exploiting Automatic Spectral Classification Criteri N. Soldati, S. Robinson, G. Basso, L. Bruzzone, J. Jovicich CIMEC, Center for Mind/Brain science, University of Trento, Trento, Italy / Faculty of Engineering, Department of Telecommunication Engineering, University of Trento, Trento, Italy



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INTRODUCTION: Resting State Networks (RSN) in brain activity are often explored with data-driven methods as Independent Component Analysis (ICA).This is due to the lack of a priori regressors for model-driven analysis. Moreover, Group ICA (GICA) can extract RSN common to a group of subjects. One challenge with Independent Components (IC) is their interpretation as function of the number of IC to be extracted by algorithms, since this number is a user-defined variable. More IC may facilitate the distinction of sources consistently different across subjects, but it may also artificially separate sources that are not consistently different across subjects. Here we exploit the frequency characterization of the extracted IC and classification methods to assess consistency of an IC across different subjects. METHOD: GICA was applied to a set of resting fMRI data of 30 healthy subjects, extracting 30, 57 and 70 ICs. After extraction each IC was transformed into a frequency spectra. The dataset consists of: number of IC, spectra, subjects. The dataset was split into a training set (15 subjects) and a test set (other 15 subjects) to train and test various classifiers. The best classifier was adopted in the subsequent analysis. The classification of each IC is done automatically, allowing the estimation of a missclassification rate, i.e. how much an IC distribution is different from all others. The lower the missclassification rate the more consistent the IC is across subjects. RESULTS: Reporting the number of consistent RSN changing the number of extracted IC permits a reduction only to consistent ones. Extraction of 70 IC instead of 30 allows the identification of three additional consistent RSN. CONCLUSIONS: This metric can support automatic RSN identification. A RSN is correctly identified only if it is consistent across subjects. Similarly physiological noise, whose spectra is quite consistent between subjects, can be identified and removed. An effective help is given in rejection of mixed sources hardly identifiable only exploiting the spatial maps, as it is often done. This method may be useful when investigating RSN as biomarkers in clinical groups since it will characterize consistent ICs within a group. BIBLIOGRAPHY: Calhoun et al. 2008; Soldati et al. 2009 On optimal group-assignment of inter-individual common brain dynamics: Identification of visual working memory-related cortical activity from group-study EEG G. TURI (1,2,3), C. HAENSCHEL (4), W. SINGER (2), M. WIBRAL (3) (1) Dept. Cognitive Neuroscience, Institute of Psychology, Goethe University Frankfurt (2) Dept. Neurophysiology, Max Planck Institute for Brain Research, Frankfurt (3) Brain Imaging Ctr. Frankfurt, MEG Unit, Goethe University Frankfurt (4) Department of Psychology, City University, London



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Impairments in cortical activity recorded by electro-/magnetoencephalography (EEG/MEG) may indicate cognitive deficits caused by nervous system disorders. A typical approach to investigate the relationship between cortical activity and cognitive deficits is to decompose group-study data into mutually independent components (ICs) and to compare task-related IC activities within and between the groups. However, it is yet unclear how to assign inter-individual ICs in order to optimally emphasize group-ICs (gICs), when comparing numerous high-dimensional datasets. Recently, we proposed a combinatorial approach using the Hungarian algorithm for clustering working memory-related scalp event-related potentials. Here we present a robust extension of our method for optimally assigning activities from various datasets. The presented method uses an iterative approach of multiple generalized assignments in order to minimize the average cluster variance of group-assigned activities. We applied our method to EEG recordings from schizophrenia patients and control subjects performing a visual working memory (WM) task (Haenschel et al., 2009) and investigated the clustered activities with respect to WM load and WM phases in both groups. The performance of the method was validated on simulations with high-dimensional IC datasets. Instable and poorly estimated gICs were simulated by varying the number and similarity of gICs over the datasets, while additional inter-/intra-individual IC variability was taken into account by varying the degree of time-delays within and between the datasets. Our simulations show that, if gICs are consistently included in all datasets, then all stable clusters consist of mutually correctly assigned gICs, irrespective of the actual number of gICs or the dataset size. In addition, if gICs are only partially included in the datasets, then stable clusters still comprise mutually correctly assigned gICs, provided that gICs have a sufficient self-similarity. Results from EEG datasets indicate stable clusters of WM-related phase-locked activity in both groups. Importantly, WM-related activity of the control group tends to be more stable and better discriminable from instable activity clusters, indicating a higher within-group variability of schizophrenia patients. Furthermore, using a combined non-linear and time-delayed similarity measure suggests a successful clustering of instable intra-/inter-individual activity, such as phase-unlocked activity. Processing of motion in depth and optic flow share a common brain area S. van Stijn1, A. Kohler2, W. Singer1, H. S. Lee1; 1Max Planck Institute for Brain Research, Frankfurt am Main, Germany; 2Department of Psychiatric Neurophysiology, University Hospital of Psychiatry, Lausanne, Switzerland Motion in depth has recently been proposed to be processed within or in the vicinity of human MT complex (hMT+). These studies often used: 1) random-dot stereograms (RDSs) that contain disparity-defined surfaces to isolate stereoscopic components from monocular components; 2) motion localizers that recruit multiple functionally and retinotopically distinct subregions of the motion-selective cortex. In this study we aim: 1) to differentiate the contributions of the surface component and the motion-in-depth component; 2) to locate the responsible subregions of hMT+ specialized for the isolated component with fMRI. We used RDSs where all stimuli contained a



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number of layers composed of black random-dots on frontoparallel planes. These planes were stacked in the in-depth direction against a gray background predefining the motion path. In each frame, dots in one of the layers switched from black to white and then returned to black in the successive frame during which the contrast switching took place in another layer. When switching occurred in neighboring layers toward one direction, observers perceived a plane smoothly traversing in depth. When switching occurred in arbitrary layers in succession, observers perceived no coherent motion. Both conditions require a prior process of representing a plane (white random-dot layer) in depth, which is possible only after binocular combination. In the third condition the contrast-switching dots were selected across arbitrary layers, which appeared as twinkling dots in depth. By contrasting these conditions in block designs, we found that both V3A and a region anterior to hMT+ are involved in the process. When the surface component was the contrasting feature the focus of the activation was found within V3A. Whereas, when the motion in depth was the contrasting component, the focus of activation shifted to the anterior subregion of hMT+. We further localized a non-retinotopic hMT+ subregion (pMSTd) by locating the ipsilateral activation to the optic flow in the peripheral hemifield beyond 12 degrees. This subregion of hMT+ well coincided with the activation area of the isolated motion-in-depth stimulus. We suggest that this anterior subregion of hMT+ (pMSTd) is specialized for the processing of the motion in 3-D.



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7. External Faculty

Laura Astolfi University of Rome “Sapienza” and Fondazione Santa Lucia Hospital Rome, Italy

Katarzyna Blinowska Department of Biomedical Physics, University of Warsaw, Poland

Stefan Debener Department of Psychology, Universiyt of Oldenburg, Germany

Leon Deouell Department of Psychology and Edmond and Lily Safra Center for Brain Sciences (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel

Elia Formisano Associate Professor (UHD), Faculty of Psychology & Neuroscience, Department of Experimental Psychology, University of Maastricht, The Netherlands



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Hauke Heekeren Max Planck Institute for Human Development and Department of Education and Psychology, Freie Universität Berlin, Germany

Stefan Kiebel Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

Lee Miller Dept. of Neurobiology, Physiology, & Behavior and Center for Mind & Brain, University of California, Davis, CA, USA

Kia Nobre Brain & Cognition Laboratory, Department of Experimental Psychology, University of Oxford, UK

Guy Orban FENS CARE Committee Member Division of Neurophysiology, Katholieke Universiteit Leuven Leuven, Belgium



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Mathias Pessiglione Institut du Cerveau et de la Moelle épinière, Hôpital Pitié-Salpêtrière, Paris, France

Gilles Pourtois Psychopathology & Affective Neuroscience Lab, Ghent University, Belgium

Patricia A. Reuter-Lorenz The Cognitive and Affective Neuropsychology Laboratory, University of Michigan, Ann Arbor, MI, USA

Jorge Ripoll Visiting Professor at ETH, Institute for Biomedical Engineering, D-ITETtra, Zurich, Switzerland / Inst. of Electronic Structure & Laser, Foundation for Research and Technology-Hellas (FORTH), Crete, Greece

Charles Schroeder Laboratory for Cognitive Neuroscience and Neuroimaging, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA

Gregor Thut Centre for Cognitive Neuroimaging, University of Glasgow, UK



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Robert Turner Director, Neurophysics Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

Mark Wallace Multisensory Research Laboratory, Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA

Bruno Weber University Hospital Zurich, Nuclear Medicine, Zurich, Switzerland

Nikolaus Weiskopf Wellcome Trust Centre for Neuroimaging, UCL Neuroscience London, UK



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8. Local Faculty

Daphne Bavelier Faculty of Psychology and Sciences of Education (FPSE), University of Geneva, Switzerland

Olaf Blanke Laboratory of Cognitive Neuroscience, Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Domenica Buetti Functional Electrical Neuroimaging Laboratory (FENL), EEG core of the Center for Biomedical Imaging, Radiology Department, CHUV, Lausanne, Switzerland

Stephanie Clarke Service of Neuropsychology and Neurorehabilitation, CHUV, Lausanne, Switzerland

Marzia De Luzia Functional Electrical Neuroimaging Laboratory (FENL), EEG core of the Center for Biomedical Imaging, Radiology Department, CHUV, Lausanne, Switzerland



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Bogdan Draganski Laboratoire de recherche en neuroimagerie (LREN), Service of Neurology, CHUV, Lausanne, Switzerland

Stephan Eliez Service Médico-‐Pédagogique (SMP) and Faculty of Medicine, University of Geneva, Switzerland

Richard Frackowiak Laboratoire de recherche en neuroimagerie (LREN), Service of Neurology, CHUV, Lausanne, Switzerland

Didier Grandjean Neuroscience of Emotion and Affective Dynamics Lab, Faculté de Psychologie et des Sciences de l'Education and Swiss Centre for Affective Sciences, Geneva, Switzerland

Rolf Gruetter Centre for Biomedical Imaging (CIBM), Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland



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Nouchine Hadjikhani Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Harvard Medical School and Harvard-‐MIT-‐HST, Boston, MA, USA

Patric Hagmann Department of Radiology, University Hospital Center & University of Lausanne (CHUV-‐UNIL) Signal Processing Laboratory 5 LTS5, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland

Petra Hüppi Division of Child Development, Childrens Hospital, Geneva, Switzerland

Ferath Kherif Laboratoire de recherche en neuroimagerie (LREN), Service of Neurology, CHUV, Lausanne, Switzerland

Pierre Magistretti Laboratory of Neuroenergetics and Cellular Dynamics (LNDC), Brain Mind Institute, Ecole Polytechnique Fédérale de Lausanne (EPFL) / Center for Psychiatric Neuroscience (CNP), University of Lausanne, Switzerland



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Christoph Michel Functional Brain Mapping Laboratory, Dept. of Fundamental Neurosciences, University Medical School, Geneva, Switzerland

Micah Murray Functional Electrical Neuroimaging Laboratory (FENL)

Melissa Saenz Laboratoire de recherche en neuroimagerie (LREN), Service of Neurology, CHUV, Lausanne, Switzerland

Sophie Schwartz Laboratory of Neurology & Imaging of Cognition (LabNIC), Brain and Behavior Laboratory (BBL), University Medical Centre (CMU), University of Geneva, Switzerland

Margitta Seeck Clinique de Neurologie, Unité d'évaluation préchirurgicale d'épilepsie, Unité d'épileptologie et d'EEG, Geneva University Hospital (HUG), Geneva, Switzerland



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Jean-‐Philippe Thiran Swiss Federal Institute of Technology Lausanne (EPFL), Institute of Electrical Engineering (IEL), Signal Processing Laboratory (LTS5), Lausanne, Switzerland

Dimitri Van de Ville Medical Image Processing Lab (MIPLab), Department of Radiology and Medical Informatics, University of Geneva / Institute of Bioengineering, EPFL, Lausanne, Switzerland

Wietske van der Zwaag Laboratory of functional and metabolic imaging, University of Lausanne, Switzerland

Serge Vulliemoz Presurgical epilepsy evaluation unit, Neurology Service, HUG, Geneva, Switzerland

Patrik Vuilleumier Laboratory of Neurology & Imaging of Cognition (LabNIC), Brain and Behavior Laboratory (BBL), University Medical Center (CMU), University of Geneva, Switzerland



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9. Students

Loretxu Bergouignan Dept. of Neuroscience, Karolinska Institute Paris, Stockholm, Sweden

Daphne Sophie Everaerd Centre for Neuroscience, Radboud University Nijmegen Medical Centre, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands

Julia Föcker Dept. of Brain and Cognitive Sciences, University of Rochester, NY, USA

Tal Golan ICNC/ELSC, Hebrew University of Jerusalem, Israel

David Hawellek Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany



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Nora Hennies Neuroscience and Aphasia Research Unit, School of Psychological Sciences, University of Manchester, UK Esin Karahan Senvardar Institute of Biomedical Engineering, Bogazici University, Istanbul, Turkey

Sofia Landi Department of Physiology, University of Buenos Aires, Argentina

Sook-Lei Liew Brain and Creativity Institute / Department of Occupational Therapy, University of Southern California, Los Angeles, CA, USA

Carlos Mugruza Vassallo Dept. of Neuroscience and Development / School of Psychology, University of Dundee, UK

Krisztina Nagy Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary



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Catherine Perrodin Dept. of Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Tübingen, Germany Juan Pablo Ramirez Mahaluf Dept. of Systems Neuroscience, IDIBAPS, Barcelona, Spain

Liliana Rincón Gonzalez Dept. of Biomedical Engineering, Arizona State University, Tempe, Arizona, USA

Emiliano Santarnecchi Dept. of Neurological and Sensorial Sciences, University of Siena, Siena, Italy

Mike Schmitgen Center for Psychosocial Medicine, Heidelberg University Hospital, Heidelberg, Germany

Artem Shatillo Dept. of Neurobiology, University of Eastern Finland, Kuopio, Finland



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Nicola Soldati CIMeC-Center for Mind/Brain Science, University of Trento, Rovereto, TN, Italy Georg Turi Department of Cognitive Neuroscience, Institute of Psychology, Goethe University / Department of Neurophysiology, Max Planck Institute for Brain Research / Brain Imaging Center Frankfurt, MEG Unit, Goethe University Frankfurt, Germany Sylvia van Stijn Department of Neurophysiology, Max Planck Institute for Brain Research, Frankfurt am Main, Germany



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The Lemanic Neuroscience Academic Environment

University of Geneva (UNIGE)

University of Lausanne (UNIL)

Ecole Polytechnique Fédéral de Lausanne (EPFL)

CHUV – Centre Hospitalier Universitaire Vaudois

HUG – Hôpitaux Universitaires de Genève



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NOTES

fens-ibro 2011 bookletthe fens-ibro students introduce will themselves and, from that moment on,...

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