Project description
Is a human sense of probability Bayesian in nature?
Bayesian inference optimally estimates probabilities from limited and noisy data taking into account levels of uncertainty. The EU-funded NEURAL-PROB project proposes that the human sense of probability is Bayesian, based on the notion that human probability estimates are accompanied by rational confidence levels defining their precision. This Bayesian nature of the human sense of probability constrains the estimation, neural representation and use of probabilities. The researchers will build their theory by combining psychology, computational models and neuroimaging. Characterisation of the sense of probability will improve our understanding of how human brains represent our world with probabilistic internal models, the way they learn and make decisions.
Fields of science
- natural sciencesmathematicsapplied mathematicsstatistics and probabilitybayesian statistics
- social sciencespsychology
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programme(s)
Topic(s)
Funding Scheme
ERC-STG - Starting Grant
Host institution
75015 Paris 15
France
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Beneficiaries (1)
75015 Paris 15
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