Objective
Recent research suggests that to control bodily movements the brain relies on Bayes-optimal predictive models that are updated by sensory prediction error. This assumption may be generalised within a new formal account of motor control as active (Bayesian) inference. Active inference explains motor control in terms of hierarchical Bayesian filtering or predictive coding, i.e. as belief updating and suppression of prediction error to optimise a hierarchical generative model in the brain; thereby the weighting of prediction errors by their predicted precision determines their relative impact on hierarchical inference. This novel proposal still lacks concrete empirical investigation. The proposed project will close this research gap by testing whether cortical information flow during manual actions, requiring visuomotor adaptation and cognitive control of attention, follows the principles of active inference. In two fMRI experiments and one MEG experiment, participants will move a photorealistic virtual hand model via an MR-compatible data glove to perform simple manual tracking tasks in a virtual reality environment. The precision of prediction errors at multiple levels of a previously established cortical motor control hierarchy will be experimentally manipulated via visuoproprioceptive conflicts (introduced by delayed visual movement feedback) and via attentional allocation – either stimulus-driven (via increased sensory noise) or endogenous (instructed) – to visual or proprioceptive movement feedback. Active inference’s specific predictions about information flow between and within cortical areas will be tested with recently established dynamic causal modelling of the modelled hemodynamic (fMRI) or spectral (MEG) responses. Active inference appeals to a general free-energy principle of brain function; this contribution will thus promote interdisciplinary exchange of knowledge about self- and world-representation in the brain and will be of general public interest.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence generative artificial intelligence
- natural sciences computer and information sciences software software applications virtual reality
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF-EF-ST - Standard EF
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2016
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
WC1E 6BT LONDON
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.