Neural correlates of reliability-based cue weighting during multisensory integration

Christopher R. Fetsch, Alexandre Pouget, Gregory C. Deangelis, Dora E. Angelaki

Research output: Contribution to journalArticlepeer-review

219 Scopus citations

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 randomly. The monkeys appropriately placed greater weight on the more reliable cue, and population decoding of neural responses in the dorsal medial superior temporal area closely predicted behavioral cue weighting, including modest deviations from optimality. We found 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.

Original languageEnglish (US)
Pages (from-to)146-154
Number of pages9
JournalNature neuroscience
Volume15
Issue number1
DOIs
StatePublished - Jan 2012
Externally publishedYes

ASJC Scopus subject areas

  • General Neuroscience

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