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CausalBrain SIGNED

Dynamic directed functional connectivity of causal learning

Total Cost €

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EC-Contrib. €

0

Partnership

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 CausalBrain project word cloud

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

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Project "CausalBrain" data sheet

The following table provides information about the project.

Coordinator
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS 

Organization address
address: RUE MICHEL ANGE 3
city: PARIS
postcode: 75794
website: www.cnrs.fr

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 France [FR]
 Total cost 196˙707 €
 EC max contribution 196˙707 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2019
 Duration (year-month-day) from 2019-06-01   to  2021-05-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR (PARIS) coordinator 196˙707.00

Map

 Project objective

Humans have an extraordinary capacity to infer cause-effect relations and form beliefs about the causal effect of actions. This ability provides the basis for rational decision-making and allows people to engage in meaningful life and social interactions. In fact, alterations of cognitive processes involved in causal learning have been found in patients affected by psychiatric disorders such as obsessive-compulsive disorder, schizophrenia and addiction. The formation of causal beliefs relies on learning rules determined by the contingency between actions and outcomes. Although fronto-striatal areas are known to be involved in the cogntive architecture of causal beliefs, it is still unknown how these brain regions interact to learn causal structures. This project aims to unravel the link between functional brain networks and causal reasoning. We hypothesize that causal representation are implemented in a dynamic distributed network of directed functional interactions between brain regions and that this network is shaped by learning. We will characterize the modulations of brain circuits involved in learning phases as well as the brain networks responsible of internal representations of contingency values and associated uncertainty. We are going to pursue these two aims by analyzing magneto-encephalografic and intracranial electro-encephalographic data collected during a causal reasoning task. We will use state-of-the-art methods for dynamic directed connectivity estimation. In addition, we will develop machine learning pipelines to found those subnetworks that implement the cognitive architecture of causal learning. Overall, we will be able to understand whether causal learning and the psychological internal variables predicted by rational theories are reflected in dynamically changing directional influences in whole-brain circuits.

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

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