Objective
The neural bases of adaptive behavior in social environments are far from being understood. We propose to use both computational and neuroscientific methodologies to provide new and more accurate models of learning in interactive settings. The long-term objective is to develop a neural theory of learning: a mathematical framework that describes the computations mediating social learning in terms of neural signals, structures and plasticity. We plan to develop a model of adaptive learning based on three basic principles: (1) the observation of the outcome of un-chosen options improves the decisions taken in the learning process, (2) learning can be transferred from one domain to another, and (3) learning can be transferred from one agent to another (i.e. social learning). In all three cases, humans appear able to construct and transfer knowledge from sources other than their own direct experience, an underappreciated though we believe critical aspect of learning. Our approach will combine neural and behavioral data with computational models of learning. The hypotheses will be formalized into machine learning algorithms and neural networks of “regret” learning, to quantify the evolution of the learning computations on a trial-by-trial basis from the sequence of stimuli, choices and outcomes. The existence and accuracy of the predicted computations will be then tested on neural signals recorded with functional magnetic resonance imaging (fMRI). The potential findings of this project could lead us to suggest general principles of social learning, and we will be able to measure and model neural activation to show those general principles in action. In addition, our results could have important implications into policy-making - by revealing what type of information agents are naturally inclined to better learn from - and clinical practice - by outlining potential diagnostic procedures and behavioral therapies for disorders affecting social behavior.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences computer and information sciences artificial intelligence machine learning transfer learning
- engineering and technology medical engineering diagnostic imaging magnetic resonance imaging
- natural sciences computer and information sciences artificial intelligence computational intelligence
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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.
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.
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.
ERC-2013-CoG
See other projects for this call
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.
Host institution
38122 TRENTO
Italy
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.