Correlated activity supports efficient cortical processing

Chou P. Hung*, Ding Cui, Yueh Peng Chen, Chia Pei Lin, Matthew R. Levine

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

9 Scopus citations

Abstract

Visual recognition is a computational challenge that is thought to occur via efficient coding. An important concept is sparseness, a measure of coding efficiency. The prevailing view is that sparseness supports efficiency by minimizing redundancy and correlations in spiking populations. Yet, we recently reported that "choristers" neurons that behave more similarly (have correlated stimulus preferences and spontaneous coincident spiking), carry more generalizable object information than uncorrelated neurons ("soloists") in macaque inferior temporal (IT) cortex. The rarity of choristers (as low as 6% of IT neurons) indicates that they were likely missed in previous studies. Here, we report that correlation strength is distinct from sparseness (choristers are not simply broadly tuned neurons), that choristers are located in non-granular output layers, and that correlated activity predicts human visual search efficiency. These counterintuitive results suggest that a redundant correlational structure supports efficient processing and behavior.

Original languageEnglish
Article number171
JournalFrontiers in Computational Neuroscience
Volume8
Issue numberJAN
DOIs
StatePublished - 06 01 2015
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2015 Hung, Cui, Chen, Lin and Levine.

Keywords

  • Efficient coding
  • Inferior temporal cortex
  • Macaque
  • Object recognition
  • Visual search

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