Opendata, web and dolomites


Cognitive tomography of mental representations

Total Cost €


EC-Contrib. €






 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.

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

Project "COGTOM" data sheet

The following table provides information about the project.


Organization address
address: NADOR UTCA 9
postcode: 1051

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


Take a look of project's partnership.

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


 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.


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 ( 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.)

IMPACCT (2019)

Improved Patient Care by Combinatorial Treatment

Read More  

NeuroMag (2019)

The Neurological Basis of the Magnetic Sense

Read More  

Life-Inspired (2019)

Life-inspired complex molecular systems controlled by enzymatic reaction networks

Read More