synapses coursera lecture#1

7/17/2019 Synapses Coursera Lecture#1

http://slidepdf.com/reader/full/synapses-coursera-lecture1 1/42

Synapses, neurons and brains

I dan Segev

Lesson #1

Brain excitements for the 21st century



Kick start

• Great thinkers think about the brain

• How it (us) all started?

• Brain Blossom worldwide

• Structure of modern brain-research centers

• The problem with “understanding the brain”



"You, your joys and sorrows, your

memories and your ambitions, your sense

of personal identity and your free will are in

fact no more than the behavior of a vastassembly of nerve cells and their

associated molecules"

(Francis Crick, Nobel Laureate 1962 – “the

father of DNA”).

"Machine think? You bet! We’re machines and we

think, don’t we?" (Claude Shannon – “the father of information age”)



“ he most

incomprehensible thing

about the world is that it

is at all comprehensible

So what is the route to comprehend the brain?



The start

Or

3.5 Billion years of life on earth

The Homo sapiens sapiens

&

The ~ 100 years old “Human Brain Project”



3.5 Billion years

Life begins - Bacteria

500 Million years

Fish

300 Million years

Reptiles

200 Million years

Mammals

70 Million years

Primates

200,000 years

Humans



The development of mammalian “big brains”

200 Million years - TODAY



800

900

1000

1100

1200

1300

1400

1500

00.20.40.60.811.21.41.6.8

Millions

Millions of years ago

B r a i n w e i g h t ( g r )

C u l t u r a l e v o l u t i o n

Modern Humans ~ 200,000 years & Cultural Evolution

Culture explosion of Homo sapiens sapiens

Language/Math

5,000 years

Science

3,000 years

Modern Computers

70 years

Art

(60,000 - 30,000 ago)

Cell Phones, ICT

Today

Understanding/rep

airing our brain

Today

Million years

B r a i n

w e i g h t - g r



1. Brain Blossom Worldwide

The Jerusalem Brain

(Norman Foster)



A view from the inside (of the brain)



Quantitative Analysisof Neuronal circuits

Plasticity & DevelopmentalNeuroscience

Computational

&theoreticalNeuroscience

Human & PrimateBehavior and Cognition

Neuroscience ofNeurological & cognitiveDisorders

Structure of modern brain centers & central role of theory

(+ new curriculum for “Leonardo da Vinci” brain-researchers)



Theory/Modeling

Neurobiology &Medicine

Computer Science

Psychology

Applied Physics & Engineering

The “da Vinci” generation of brain researchers



Perspective: Some new dramatic ($ billions) projects for the brain

1. Allen Institute – Seatle, USA (Mouse/Human brain atlas – recently new

focus on mouse vision)

2. Janelia farm – DC, USA (Industrial scale Inst. for connecting network

level anatomy and physiology to s specific behavior)

3. EU Human Brain Project - EPFL, Lausanne Switzerland (ICT-based brain

research platform, integrating data and knowledge from different disciplines,

and catalyzing world-wide effort to achieve understanding of the brain,

propose new treatments for brain diseases and new brain-like computing

technologies) - Lesson #7.

4. President Obama’s “Brain Activity Map” initiative (Creating revolutionary

tools to measure/stimulate millions or even billions or neurons

simultaneously)



The BI G - dif f icult question:

What does it mean “To Understand the brain?”

Clearl y - A THEORY is required to

explains how the brain ingredients

(i ts anatomical units; its electro-chemical signals)

generate “high level” phenomena

(perception, action, emotions) F r

o m m

o l e c u l e

s t o b e h a v i o r

Meters

Centimeters

Millimeter

s

Micrometers

Nanometers



Recent Brain-Excitements

1. Connectomics – Complete 3D road-map for the brain

2. Brainbow – Colorful, genetically-designed, brains

3. Brain-machine/computer interface (BMI)

4. Optogenetics – Light-activated brain circuits

5. Computer simulation of the brain - Blue Brain Project”



Modern neuroanatomy

Mapping/visualizing the wiring diagram of the brain

Connecting fine structure to mental activities in healthand in neuro-psychiatric disorders



Beginning of Modern Neuroscience – Cellular Anatomy

The two giants: Camillo Golgi (Italy) & S. Ramon Y Cajal (Spain) – Nobel Prize 1906

Using Golgi staining method

Very small % of cells stained

Connections (synapses) - not seen

C a m i l l o G o l g i

S

. R a m o n Y C a j a l

The neuron doctrine (Cajal)

Our brain is built from individual cells



Frontiers 1: Connectomics - modern brain anatomy

Electron microscope (EM) reconstruction of a whole piece of brain (nanometers

resolution). All neurons (and other cell types) and all connections (synapses)

Courtesy of Mitya Chklovskii (Janelia Farm)

Based on hippocampus data from Kristen Harris (U. Texas, Austin)



Connectomics – complete 3D reconstruction a small volume of

mammalian cortex

Courtesy of Sebastian Seung (MIT)



Some prospects for the Connectomics

1. We will have, for the first time ever, the “ blue print” (the

anatomical foundation) of a whole (healthy and sick) brain

2. We may start to bridge the “structure-to-function” problem (lecture

#6) and enable realistic computer simulations (“simulation- based”

research) of the respected (healthy or sick) network (lecture #7)

F ti 2 “B i b ” t h l


http://slidepdf.com/reader/full/synapses-coursera-lecture1 23/42Brainbow-1 : stochastic recombination usin incom atible lox variants.

Frontiers 2. “Brainbow” technology

Genetic staining of neurons in vivo (light microscope – micrometer resolution)

Courtesy of Jeff Lichtman, Jean Livet and Joshua R. Sanes

Brainbow transgenes drive the combinatorial expression of several fluorescent proteins (XFPs) in

neurons, resulting in the colour-tagging of individual cells.

“ ”



“Brainbow” images – The colorful brain



Some prospects for the Brainbow

1. The structural basis for learning in the brain

2. Tagging and genetic-characterization of the different cell-types (the building blocks) in a given system (e.g., retina)

3. Tracing short-and-long range connections in brain circuits



Frontiers 3. Brain Machine/Computer Interface (BMI)

On-line BMI requires “reading” the electrical activity

( its“electrical language” – its code – lessons #3 & #4 )

in well-defined (functional) regions.



From Brain to Machine

Spikes in a cell



Brain-activated robot arm

Courtesy of Miguel Nicolelis (Duke University)



Courtesy of Andrew Schwartz, Univ. Pittsburgh

Monkey’s brain activity used for self feeding with a robotic arm

From machine (pulses generated by a battery) to brain



The

Basal

Ganglia

From machine (pulses generated by a battery) to brain

(the amazing success of BMI for ameliorating Parkinosn’s)

Normal

ParkinsonCourtesy of Hagai Berman, Hebrew Univ.

Parkinson



Implanting stimulating electrodes in patient’s brain (fully alert)

Stimulatingelectrodes

Pulsegenerator



Deep Brain Stimulation

Patient: Male, 58 years old (PD Eight years, with extreme on-off)

Courtesy of Hagai Bergman, Zvi Israel, Hadassah University Hospital, Jerusalem

(For ameliorating Parkison’s symptoms)

Post-operation Pre-operation



Courtesy of Miguel Nicolelis (Duke University)

Future challenges for BMI

1. Develop chronic brain nano- probes

2. Develop telemetric communication with the brain

3. Develop real-time multi

(millions?) signal processing

methods

4. Improving robotic arm and

“Closing the loop” Stimulation +

recording



H a u s s er an d S m

i t h ,N a t ur e2 0 0 7

Frontiers 3: OPTOGENETICSFrontier 4. Optogenetics

Optical stimulation (and recording) from single neurons in the living brain

Channel Rhodopsin opens with blue light

Causes spikes

Natronomonas pharaonis activated with yellow light

Prevents spikes



Light-activated (~100 neurons) controlling mouse behavior

Courtesy of Karel Svoboda, Janelia Farm



Frontier 5. Computer simulation of neuronal circuits

Integrating anatomical and physiological data to provide “understanding”

I am never content unti l I have constructed a mathematical model of what I am studying.

I f I succeed in making one, I understand; otherwise I do not ’ William Thomson (Lord Kelvin)



The Blue Brain Project

Using the powerful “Blue-Gene” IBM Computer for realistic

simulation of the cortical circuits

Courtesy of Henry Markram and the Blue Brain team (EPFL, Switzerland)

Step 1 – Mathematical models of neurons’ spiking activity



real

model

Step 1 Mathematical models of neurons spiking activity



Connecting model components (modeled neurons) as in real cortical circuit



Computer voyage into cortical circuit (the cortical column)

Computer simulation of 10 000 neurons and 100 M



Computer simulation of 10,000 neurons and 100 M

synapses in 2 cubic mm of cortical circuit

(electrical activity is color coded)



End of lesson 1

synapses coursera lecture#1

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