Perceptual learning reduces interneuronal correlations in macaque visual cortex

Yong Gu, Sheng Liu, Christopher R. Fetsch, Yun Yang, Sam Fok, Adhira Sunkara, Gregory C. DeAngelis, Dora E. Angelaki

Research output: Contribution to journalArticlepeer-review

128 Scopus citations

Abstract

Responses of neurons in early visual cortex change little with training and appear insufficient to account for perceptual learning. Behavioral performance, however, relies on population activity, and the accuracy of a population code is constrained by correlated noise among neurons. We tested whether training changes interneuronal correlations in the dorsal medial superior temporal area, which is involved in multisensory heading perception. Pairs of single units were recorded simultaneously in two groups of subjects: animals trained extensively in a heading discrimination task, and "naive" animals that performed a passive fixation task. Correlated noise was significantly weaker in trained versus naive animals, which might be expected to improve coding efficiency. However, we show that the observed uniform reduction in noise correlations leads to little change in population coding efficiency when all neurons are decoded. Thus, global changes in correlated noise among sensory neurons may be insufficient to account for perceptual learning.

Original languageEnglish (US)
Pages (from-to)750-761
Number of pages12
JournalNeuron
Volume71
Issue number4
DOIs
StatePublished - Aug 25 2011
Externally publishedYes

ASJC Scopus subject areas

  • General Neuroscience

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