NEURO-POPCODE

Learning to read the code of large neural populations

 Coordinatore WEIZMANN INSTITUTE OF SCIENCE 

Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.

 Nazionalità Coordinatore Israel [IL]
 Totale costo 1˙438˙996 €
 EC contributo 1˙438˙996 €
 Programma FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call ERC-2012-StG_20111109
 Funding Scheme ERC-SG
 Anno di inizio 2013
 Periodo (anno-mese-giorno) 2013-01-01   -   2017-12-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    WEIZMANN INSTITUTE OF SCIENCE

 Organization address address: HERZL STREET 234
city: REHOVOT
postcode: 7610001

contact info
Titolo: Dr.
Nome: Elad
Cognome: Schneidman
Email: send email
Telefono: +972 8 934 2239
Fax: +972 8 934 4131

IL (REHOVOT) hostInstitution 1˙438˙996.00
2    WEIZMANN INSTITUTE OF SCIENCE

 Organization address address: HERZL STREET 234
city: REHOVOT
postcode: 7610001

contact info
Titolo: Ms.
Nome: Gabi
Cognome: Bernstein
Email: send email
Telefono: +972 8 934 6728
Fax: +972 8 934 4165

IL (REHOVOT) hostInstitution 1˙438˙996.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

neural    read    mathematical    encoding    fundamental    codes    framework    construct    brain    code    neurons    effect    natural    learning    hundreds    machine    plausible    biologically    population    thesaurus    patterns    networks    stimuli    populations   

 Obiettivo del progetto (Objective)

'Information is represented and transmitted in the brain by the joint activity of large groups of neurons. Understanding how information is “written” in these population patterns, and how it is read and processed, is a fundamental question in neuroscience. Yet, because of the huge number of potential activity patterns and complexity of natural stimuli, most of our understanding of the code relies on single neuron studies. We will extend and apply mathematical tools from information theory, machine learning, and physics, to overcome this ‘curse of dimensionality’ and build neural dictionaries relating activity and stimuli at an unparalleled resolution of hundreds of neurons. To identify the fundamental design principles of neural population codes we will study the spatial and spatio-temporal activity of hundreds of neurons from the retina, tectum, and cortical networks responding to naturalistic and artificial stimuli. Our primary goals are: (a) to characterize the encoding ‘codebooks’ of large populations of neurons, and the effect of network noise on encoding, and thus construct a thesaurus for neural populations, (b) use this thesaurus to develop new family of decoders of population activity which would be biologically plausible and accurate for natural stimuli, (c) characterize adaptation at the level of the code of networks of neurons, and the effect of learning on population neural codes, (d) explore “learnability” as a key feature of the neural code, and construct biologically plausible models of how the brain can learn to read population codes and compute, and (e) merge these ideas into a new mathematical framework that will connect the architecture of neural interaction networks and the properties of their neural codes. Our work will establish a new mathematical framework for studying the neural code, which will entail important implications for neural prostheses and brain machine interfaces, as well as brain-inspired learning algorithms.'

Altri progetti dello stesso programma (FP7-IDEAS-ERC)

ICE&LASERS (2012)

Innovative Concepts for Extracting climate and atmospheric composition records from polar ice cores using new LASER Sensors

Read More  

GENOMEFUN (2013)

Genomics of adaptive divergence in Fungi

Read More  

PAST (2014)

Pre-Columbian Amazon-Scale Transformations

Read More