CausalBrain · Dynamic directed functional connectivity of causal learning
Horizon 2020 — Marie Skłodowska-Curie Actions
- Duration
- 2019-06-01 → 2021-08-31
- EU contribution
- €196,708
- Participants
- 1
- Scheme
- MSCA-IF
Lines connect the coordinator with its partners.
Results in brief
Dynamic directed functional connectivity of causal learning
Comprehending how we learn causal relations has been an issue dating as far back as antiquity. Even with today’s advances in technology and neuroscience, among other fields, the exact pathway the brain uses to build such beliefs remains elusive. The working hypothesis of the CausalBrain project was that several brain regions are involved through directed interactions in forming networks to help the brain learn. By using magnetoencephalographic data collected during a causal learning task, the project aimed to clarify this pathway further, and to test current causal learning theories against behavioral and brain data. Unfortunaly, the fellow of the Marie-Curie fellowship (Andrea Insabato) resigned after one month and a half from the start of the projet on the 13th October 2019.
Data: CORDIS, © European Union
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.
Original text from CORDIS.
Participants
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS · ParisCoordinatorFrance
Links
Data: CORDIS, © European Union