A thesaurus for a neural population code

Elad Ganmor, Ronen Segev, Elad Schneidman

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

Information is carried in the brain by the joint spiking patterns of large groups of noisy, unreliable neurons. This noise limits the capacity of the neural code and determines how information can be transmitted and read-out. To accurately decode, the brain must overcome this noise and identify which patterns are semantically similar. We use models of network encoding noise to learn a thesaurus for populations of neurons in the vertebrate retina responding to artificial and natural videos, measuring the similarity between population responses to visual stimuli based on the information they carry. This thesaurus reveals that the code is organized in clusters of synonymous activity patterns that are similar in meaning but may differ considerably in their structure. This organization is highly reminiscent of the design of engineered codes. We suggest that the brain may use this structure and show how it allows accurate decoding of novel stimuli from novel spiking patterns.

Original languageEnglish
Article numbere06134
JournaleLife
Volume4
Issue numberSeptember2015
DOIs
StatePublished - 8 Sep 2015

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Immunology and Microbiology
  • General Neuroscience

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