Opendata, web and dolomites

COGTOM SIGNED

Cognitive tomography of mental representations

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 COGTOM project word cloud

Explore the words cloud of the COGTOM project. It provides you a very rough idea of what is the project "COGTOM" about.

decay    implementations    social    bayesian    piecemeal    algorithms    formalised    cognition    percepts    fundamental    constructs    takes    discovering    models    changing    statistical    off    track    principled    memory    itself    dimensions    systematically    prior    structured    rigorously    accumulates    simply    strength    observations    conclusively    consistent    synthetic    behavioural    learning    analytical    quantitative    experimental    dimension    perceptual    methodological    shelf    interacts    tomography    usable    simultaneously    controls    collected    distributions    ranging    estimate    mind    patterns    model    release    limited    infer    content    interference    quantifiable    reconstruction    doubly    transformations    internal    lack    collaborators    superior    mental    decisions    variety    central    structure    series    criteria    motor    techniques    humans    quantitatively    hypothesis    cognitive    data    machine    stringent    time    heuristic    single    multiple    paradigms    visual    movements    representations   

Project "COGTOM" data sheet

The following table provides information about the project.

Coordinator
KOZEP-EUROPAI EGYETEM 

Organization address
address: NADOR UTCA 9
city: BUDAPEST
postcode: 1051
website: www.ceu.hu

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Hungary [HU]
 Total cost 1˙179˙462 €
 EC max contribution 1˙179˙462 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-COG
 Funding Scheme ERC-COG
 Starting year 2017
 Duration (year-month-day) from 2017-05-01   to  2022-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KOZEP-EUROPAI EGYETEM HU (BUDAPEST) coordinator 1˙179˙462.00

Map

 Project objective

Internal models are fundamental to our understanding of how the mind constructs percepts, makes decisions, controls movements, and interacts with others. Yet, we lack principled quantitative methods to systematically estimate internal models from observable behaviour, and current approaches for discovering their mental representations remain heuristic and piecemeal. I propose to develop a set of novel 'doubly Bayesian' data analytical methods, using state-of-the-art Bayesian statistical and machine learning techniques to infer humans' internal models formalised as prior distributions in Bayesian models of cognition. This approach, cognitive tomography, takes a series of behavioural observations, each of which in itself may have very limited information content, and accumulates a detailed reconstruction of the internal model based on these observations. I also propose a set of stringent, quantifiable criteria which will be systematically applied at each step of the proposed work to rigorously assess the success of our approach. These methodological advances will allow us to track how the structured, task-general internal models that are so fundamental to humans' superior cognitive abilities, change over time as a result of decay, interference, and learning. We will apply cognitive tomography to a variety of experimental data sets, collected by our collaborators, in paradigms ranging from perceptual learning, through visual and motor structure learning, to social and concept learning. These analyses will allow us to conclusively and quantitatively test our central hypothesis that, rather than simply changing along a single 'memory strength' dimension, internal models typically change via complex and consistent patterns of transformations along multiple dimensions simultaneously. To facilitate the widespread use of our methods, we will release and support off-the-shelf usable implementations of our algorithms together with synthetic and real test data sets.

 Publications

year authors and title journal last update
List of publications.
2018 Rodrigo Echeveste, Máté Lengyel
The Redemption of Noise: Inference with Neural Populations
published pages: 767-770, ISSN: 0166-2236, DOI: 10.1016/j.tins.2018.09.003
Trends in Neurosciences 41/11 2019-02-28

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "COGTOM" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "COGTOM" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.1.)

Resonances (2019)

Resonances and Zeta Functions in Smooth Ergodic Theory and Geometry

Read More  

Aware (2019)

Aiding Antibiotic Development with Deep Analysis of Resistance Evolution

Read More  

E-DURA (2018)

Commercialization of novel soft neural interfaces

Read More