Pairwise Synchrony and Correlations Depend on the Structure of the Population Code in Visual Cortex

Veronika Koren, Ariana R. Andrei, Ming Hu, Valentin Dragoi, Klaus Obermayer

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

In visual areas of primates, neurons activate in parallel while the animal is engaged in a behavioral task. In this study, we examine the structure of the population code while the animal performs delayed match-to-sample tasks on complex natural images. The macaque monkeys visualized two consecutive stimuli that were either the same or different, while being recorded with laminar arrays across the cortical depth in cortical areas V1 and V4. We decode correct choice behavior from neural populations of simultaneously recorded units. Utilizing decoding weights, we divide neurons into most informative and less informative and show that most informative neurons in V4, but not in V1, are more strongly synchronized, coupled, and correlated than less informative neurons. Because neurons are divided into two coding pools according to their coding preference, in V4, but not in V1, spiking synchrony, coupling, and correlations within the coding pool are stronger than across coding pools. Koren et al. show that in a match-to-sample visual task with naturalistic stimuli, the matching and non-matching of stimuli is signaled by a change in the structure of population responses. Neurons with similar response form binary coding pools. Coding pools also influence the strength of pairwise correlations and synchrony.

Original languageEnglish (US)
Article number108367
JournalCell Reports
Volume33
Issue number6
DOIs
StatePublished - Nov 10 2020

Keywords

  • behavior
  • choice
  • classification
  • discrimination
  • information
  • monkey
  • neural coding
  • noise correlations
  • population code
  • visual cortex

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)

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