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Neural correlates of reliability-based cue weighting during multisensory integration

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Neural correlates of reliability-based cue weighting during multisensory integration

Auteurs : Christopher R. Fetsch [États-Unis] ; Alexandre Pouget [États-Unis, Suisse] ; Gregory C. Deangelis [États-Unis] ; Dora E. Angelaki [États-Unis]

Source :

Nature Neuroscience [ 1097-6256 ] ; 2011.

RBID : PMC:3398428

Abstract

Integration of multiple sensory cues is essential for precise and accurate perception and behavioral performance, yet the reliability of sensory signals can vary across modalities and viewing conditions. Human observers typically employ the optimal strategy of weighting each cue in proportion to its reliability, but the neural basis of this computation remains poorly understood. We trained monkeys to perform a heading discrimination task from visual and vestibular cues, varying cue reliability at random. Monkeys appropriately placed greater weight on the more reliable cue, and population decoding of neural responses in area MSTd nicely predicted behavioral cue weighting, including modest deviations from optimality. We further show that the mathematical combination of visual and vestibular inputs by single neurons is generally consistent with recent theories of optimal probabilistic computation in neural circuits. These results provide direct evidence for a neural mechanism mediating a simple and widespread form of statistical inference.

Url:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398428

DOI: 10.1038/nn.2983
PubMed: 22101645
PubMed Central: 3398428

Affiliations:

Le document en format XML

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Neural correlates of reliability-based cue weighting during multisensory integration

Neural correlates of reliability-based cue weighting during multisensory integration

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Abstract

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