Choice-related activity and correlated noise in subcortical vestibular neurons

Sheng Liu, Yong Gu, Gregory C. Deangelis, Dora Angelaki

Research output: Contribution to journalArticle

Abstract

Functional links between neuronal activity and perception are studied by examining trial-by-trial correlations (choice probabilities) between neural responses and perceptual decisions. We addressed fundamental issues regarding the nature and origin of choice probabilities by recording from subcortical (brainstem and cerebellar) neurons in rhesus monkeys during a vestibular heading discrimination task. Subcortical neurons showed robust choice probabilities that exceeded those seen in cortex (area MSTd) under identical conditions. The greater choice probabilities of subcortical neurons could be predicted by a stronger dependence of correlated noise on tuning similarity, as revealed by population decoding. Significant choice probabilities were observed almost exclusively for neurons that responded selectively to translation, whereas neurons that represented net gravito-inertial acceleration did not show choice probabilities. These findings suggest that the emergence of choice probabilities in the vestibular system depends on a critical signal transformation that occurs in subcortical pathways to distinguish translation from orientation relative to gravity.

Original languageEnglish (US)
Pages (from-to)89-97
Number of pages9
JournalNature Neuroscience
Volume16
Issue number1
DOIs
StatePublished - Jan 1 2013

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Noise
Neurons
Gravitation
Macaca mulatta
Brain Stem
Population

ASJC Scopus subject areas

  • Neuroscience(all)

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Choice-related activity and correlated noise in subcortical vestibular neurons. / Liu, Sheng; Gu, Yong; Deangelis, Gregory C.; Angelaki, Dora.

In: Nature Neuroscience, Vol. 16, No. 1, 01.01.2013, p. 89-97.

Research output: Contribution to journalArticle

Liu, Sheng ; Gu, Yong ; Deangelis, Gregory C. ; Angelaki, Dora. / Choice-related activity and correlated noise in subcortical vestibular neurons. In: Nature Neuroscience. 2013 ; Vol. 16, No. 1. pp. 89-97.
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