keyevents$intheformationofthebraininitiative september2011 ... · chemists/biochemists developing...

Key Events in the Formation of the BRAIN Initiative September 2011 – April 2013

Date Event Outcome Documents Dec 2011 Small group of

participants presents White paper to NIH, DARPA, and OSTP

Agenda PPT Presentation Group Photos

of 1

Friday, December 16, 2011

10:00-‐11:30 NIH

Story Landis National Institute of Neurological Disorders and Stroke NINDS

12:30-‐1:30

DARPA Dr. Jay Schnitzer, DSO Director COL Christian Macedonia, DSO Program Manager Dr. Robert Colwell, MTO Deputy Director Dr. Timothy Broderick, MTO Program Manager

3:00-‐4:00

OSTP Tom Kalil Office of Science & Technology Policy OSTP

Participants Miyoung Chun George Church Jay Schnitzer Michael Roukes Rafa Yuste Story Landis Thomas Lee Tom Kalil

Pau l A l i v i s a to s Be r ke l e y / LBL

George Church Har va rd

Ra lph Green span UCSD/Kav l i

Michae l Roukes Ca l t e c h /Kav l i

Ra f ae l Yus te Co l umb i a /Kav l i Miyoung Chun Kav l i Founda t i on

FUNCTIONAL CONNECTOMICS: ��TOWARD AN ACTIVITY MAP OF THE BRAIN

Separate events leading up to today’s meeting:

¡  Sep 2010: Kavl i Pr ize Celebrat ion in Oslo, the idea to explore poss ib i l i t ies at the inter face between neurosc ience and nanosc ience is generated

¡  Sep 2011: Workshop on “Oppor tun i t ies at the Inter face of Neurosc ience and Nanosc ience” , i s he ld at Chicheley Hal l , UK – sponsored by Kav l i , Al len , and Gatsby Foundat ions

Outcome of the wor kshop: “The Bra in Act iv i ty Map Project” & emergence of five leading sc ient is ts in neurosc ience , nanosc ience , and systems bio logy

¡  Oct 2011: White paper & pre l iminar y technica l document are generated and submitted to OSTP; fur ther c i rcu lated to federa l funding agencies as wel l as other pr ivate foundat ions

¡  Dec 2011: In i t ia l meet ings to sol ic i t ear ly input f rom funding agencies

CONTEXT

Alivisatos, Church, Greenspan, Roukes, Yuste, Chun - (c) 2011 2 16 Dec 2011

WE NEED NEW METHODS


overarching goal: understanding how the brain works problem: emerging properties of brain function

“ What apparatus, in general terms, enables the brain to implement its remarkable performance?

The number of components (neurons) in the brain is probably about 1011 . The number of synapses, or contacts , between them is perhaps 1015 . On the average ever y neuron receives some thousands of dist inct inputs and itsel f connects to many other neurons.

The physical layout of most of the components is not par t icular ly neat .

How might one make some headway through this impossible jungle? ”

Franc is H Cr ick (1979) Think ing about the bra in .

Scient ific Amer ican 241: 219–232

Goal 1: Measure every action potential for every neuron in complete brain circuits

Goal 2: Manipulate the activity of every neuron in these circuits Goal 3: Computationally analyze/model these circuits Goal 4: (concurrent) Develop technological platforms to permit

scale-up to ever-larger hierarchical brain structures.

GOALS


worm fly fish mouse

Goal 1: Measure every action potential for every neuron in complete brain circuits

GOALS (DETAILS)


¡  Optical approach: Image act ion potent ia ls v ia Ca and voltage indicator ¡  Electrophysiologica l approach: 10k channels and upward ¡  Next-gen photonics-based s i l icon probes with nanopar t ic le indicator s

¡  Futur ist ic genomics approaches for reconstr uct ing act ion potent ia ls

Goal 1: Measure every action potential for every neuron in complete brain “circuits”

Goal 2: Manipulate the activity of every neuron in

complete brain circuits

GOALS (DETAILS)


¡  Optogenet ics & caged compounds ¡  Nanopar t ic les coupled to nanoprobes ¡  Local chemical modulat ion through probe-based microfluidics

¡  Genetic str ategy



complete brain “circuits” Goal 3: Computationally analyze/model complete brain

circuits

GOALS (DETAILS)


¡  Data reduct ion, management, and analys is ¡  Computat ional models to address brain c ircuit complexity



complete brain “circuits” Goal 3: Computationally analyze/model complete brain

“circuits” Goal 4: (concurrent) Develop technological platforms

to permit scale-up to ever-larger hierarchical brain structures.

GOALS (DETAILS)

¡  Fast , 3D imaging in scatter ing media ¡  Highly-mult ip lexed e lectrophys io log ica l recording (megaprobe project) ¡  Next-Gen photonic-based S i -probe plat form for deep st imulat ion & recording ¡  Mult iphys ica l measurements : imaging p lus voltage , chemica l & force “fields” ¡  Transform prototypes into robust instr umentat ion for neurosc ience community ¡  Novel Computat ional Approaches , mass ive data handl ing and storage


¡  Scientific goals §  Measure ever y spike to obtain a complete functional descr iption of the circuit (analogous

to the genome) §  Decipher neural code: tackle the emergent proper ties of brain circuits §  Solve connectivity diagrams: Reverse engineer neural circuits

¡  Medical goals §  Develop novel assays for brain diseases §  Emergent hypotheses for pathophysiology of brain disease

¡  Development of Powerful New Technology §  Significant technological investment is cr itical; the project itself is l ikely to be the only

pr incipal near-term dr iver tech development

¡  Training of a new generation of interdisciplinary scientists

¡  Historical Precedents §  In condensed matter physics: “More is Different” (P. Anderson; emergent proper ties) §  Statistical mechanics, Magnetism, Dynamical Systems, Non-equilibr ium thermodynamics §  Proven success of “big science” in molecular biology: The Human Genome Project

WHY?


PARALLEL: HUMAN GENOME PROJECT

technology evolution


Single investigator

Academic Center

Large-Scale Industrialization

Genome Center

PRECEDENT : GENOME PROJECT


Genome Project : 20 to 200 researcher s per center. Modest Tech Development in Academic labs + tech transfer. One company inside (GTC) and one outside (Celera). Battel le repor t: 140-fold return on investment. SNP, HapMap, 1000 Genomes Project: Mainly deploying technologies. Several companies: Affymetr ix, I l lumina, LifeTech, CompleteGenomics. NHGRI $1000 genome: Aggressive Tech Dev: Broad tech por tfol io: dozens of academic star tups, large companies. Mil l ion-fold cost reduction in 7 year s.

ORGANIZATIONAL PRECEDENTS


¡  Experimental neuroscientists explor ing worm, fish, mouse , rat , tur t le ,

…primates

¡  Computer scientists at the forefront of massive data mining technologies

¡  Computational neuroscientists bui lding models/analyses with next-gen complexity

¡  Chemists/biochemists developing nanopar t ic le and molecular repor ter s (for st imulat ion and recording)

¡  Nanoscientists ; and engage their key exper t faci l i t ies and staf f

¡  State-of-the-ar t microchip research foundries to translate “one-ofs” into prototypes capable of scale-up and production en masse

¡  Industrial partners to subsequently enable mass production and system integrat ion: enabl ing real izat ion and deployment of robust , integrated measurement instr uments

WHO MUST WE ENGAGE ��TO MAKE THIS HAPPEN?


A DRAFT ROADMAP


15 years: Entire brains behaving

10 years: 1 million neurons

5 years: 50,000 neurons

A DRAFT ROADMAP





§  Example target circuits:

§  C. elegans §  Mouse olfactor y bulb mitral cells §  Mouse retinal ganglion cells §  Mouse cor tical brain slice §  …

A DRAFT ROADMAP





§ Technology §  Optical: achieve >100 Hz spike sampling §  Electrophysiological: full 10kHz bandwidth §  Typical time records: ~1h §  Develop next-gen FAST optical voltage

repor ters (>1 kHz) §  Computational optics §  3D Optogenetics

A DRAFT ROADMAP





§  Example target circuits: §  Drosophila §  Mouse Retina §  Zebrafish §  Mouse hippocampus §  Mouse cor tical area §  Mouse models of disease §  Etruscan Shrew cor tex

A DRAFT ROADMAP





§  Example brain structures:

§  Entire cor tex in behaving mouse

§  Entire hippocampus in behaving rat

§  Cor tical area in awake pr imates

§  Human patients: brain-machine interface

A DRAFT ROADMAP





§ Technology §  Highly-multiplexed, Silicon neural

probes (shanks): large-scale integration §  Photonic-based sensing: access

multiphysical “fields”

On#Chip(Fiber(Coupler(

Op0cal(Resonators((enable(Wavelength((Division(Mul0plexing)(

Integrated((Op0cal(Waveguide(

Separately#Addressable(Op0cal(EmiEer(“Pixels”(

External(Op0cal(Waveguide((from(Emission(Mul0plexer)(

Probe(Body(

Probe(Shanks(

Large Databases: Comparison ¡  Anatomic connectome

1500 neurons : 1×1013 raw pixels

So, 7×106 mouse cor t ical cel ls would be 50 ×1015 Bytes (= 50 PB)

¡  Genome image data per year wor ldwide: 30 PB .

¡  Astrophysics growing at 0.5 PB per year.

THE COMING DATA DELUGE


1h time record

4 GB

200 TB

20 PB

Brain Activity Map – Raw Data Rates assume (5x5x5)=125 imaging voxels per cel l body

300 neurons at 12 bits/voxel at 50 Hz : ~ 180MB/s

50k neurons at 12 bits/voxel at 10 kHz : ~ 750 GB/s

7M cor t ical cel ls at 12 bits/voxel at 10kHz : ~105TB/s

1 bit

¡ Devices and techniques for diagnosing brain disorder s ear l ier and more accurately

¡  Strategies for fine control brain stimulation to rebalance diseased circuits

¡  Sensit ive , miniature , and intel l igent nanosystems for engineer ing and environmental applications

¡  Convergence of biotechnology and nanotechnology

¡ Development of new capabil it ies for storage and manipulation of massive datasets

¡ Development of novel, biological ly-inspired, computational devices.

LARGER BENEFITS


¡  Functional , rather than structural , dynamic connectome

¡ Not a disembodied “Blue Brain” Model, but real data

¡  Completely open access to data

¡  Collaborative , rather than competit ive

¡ Develop, deploy next-gen instrumentation to community

CONTRAST W/ OTHER INITIATIVES


¡ We can coordinate funding suppor t among var ious resources ranging from Federal Funding Agencies, Pr ivate Foundations, and Industr y

COLLABORATION AMONG ��FUNDING AGENCIES

NIH

DARPA Initiation of the Brain

Activity Map

Private Foundations

Industry

NSF

Others

Project Completion

¡  Santa Monica Kavl i Workshop: Milestones and Specific Aims

§  Januar y 28-30, 2012

§  Participants

§ Organizers:

§  Paul Alivisatos, George Church, Ralph Greenspan, Michael Roukes, & Rafa Yuste

§ Neuroscience:

§  Karl Diesseroth, Eve Marder, Thanos Siapas, Christof Koch, A.S. Chiang, & Sebastian Seung

§ Nanoscience:

§ Hongkun Park, Andreas Tolias, & Oskar Painter,

§  Imaging:

§ Xiaowei Zhuang, & Scott Fraser

NEXT STEPS?


¡ WE NEED YOUR ADVICE: § Large Scale: too large for Grants or Foundations. Big Science

§  Interdisciplinar y Effor t

§ Repercussions for Science and Society

§ Ensure Public Buy-in

§ Ensure open access to all data § Human Genome Like Project

WHERE DO WE GO FROM HERE?


NEW TOOLS

“ New directions in science are launched by new tools much more often than by new concepts.

The effect of a concept-dr iven revolution is to explain old things in new ways.

The effect of a tool-driven revolution is to discover new things that have to be explained. ”

Freeman Dyson (1997) Imagined Wor lds

Har vard Univer s i ty Press , Cambr idge , MA


THANK YOU