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Probabilistic brains: knowns and unknowns

Identifieur interne : 001943 ( Main/Merge ); précédent : 001942; suivant : 001944

Probabilistic brains: knowns and unknowns

Auteurs : Alexandre Pouget [États-Unis, Suisse, Royaume-Uni] ; Jeffrey M. Beck [États-Unis] ; Wei Ji Ma [États-Unis] ; Peter E. Latham [Royaume-Uni]

Source :

Nature neuroscience [ 1097-6256 ] ; 2013.

RBID : PMC:4487650

Abstract

There is strong behavioral and physiological evidence that the brain both represents probability distributions and performs probabilistic inference. Computational neuroscientists have started to shed light on how these probabilistic representations and computations might be implemented in neural circuits. One particularly appealing aspect of these theories is their generality: they can be used to model a wide range of tasks, from sensory processing to high-level cognition. To date, however, these theories have only been applied to very simple tasks. Here we discuss the challenges that will emerge as researchers start focusing their efforts on real-life computations, with a focus on probabilistic learning, structural learning and approximate inference.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4487650

DOI: 10.1038/nn.3495
PubMed: 23955561
PubMed Central: 4487650

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PMC:4487650

Le document en format XML

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Probabilistic brains: knowns and unknowns

Probabilistic brains: knowns and unknowns

Source :

Abstract

Links toward previous steps (curation, corpus...)

Links to Exploration step

Le document en format XML

Pour manipuler ce document sous Unix (Dilib)

Pour mettre un lien sur cette page dans le réseau Wicri

Pour générer des pages wiki