Synergistic Coding of Visual Information in Columnar Networks

Sunny Nigam, Sorin Pojoga, Valentin Dragoi

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


Incoming stimuli are encoded collectively by populations of cortical neurons, which transmit information by using a neural code thought to be predominantly redundant. Redundant coding is widely believed to reflect a design choice whereby neurons with overlapping receptive fields sample environmental stimuli to convey similar information. Here, we performed multi-electrode laminar recordings in awake monkey V1 to report significant synergistic interactions between nearby neurons within a cortical column. These interactions are clustered non-randomly across cortical layers to form synergy and redundancy hubs. Homogeneous sub-populations comprising synergy hubs decode stimulus information significantly better compared to redundancy hubs or heterogeneous sub-populations. Mechanistically, synergistic interactions emerge from the stimulus dependence of correlated activity between neurons. Our findings suggest a refinement of the prevailing ideas regarding coding schemes in sensory cortex: columnar populations can efficiently encode information due to synergistic interactions even when receptive fields overlap and shared noise between cells is high.

Original languageEnglish (US)
Pages (from-to)402-411.e4
Issue number2
StatePublished - Oct 23 2019


  • cortical columns
  • information theory
  • laminar recordings
  • redundancy
  • synergy

ASJC Scopus subject areas

  • Neuroscience(all)


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