Neural coding of cell assemblies via spike-timing self-information

Meng Li, Kun Xie, Hui Kuang, Jun Liu, Deheng Wang, Grace E. Fox, Zhifeng Shi, Liang Chen, Fang Zhao, Ying Mao, Joseph Zhuo Tsien

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Cracking brain's neural code is of general interest. In contrast to the traditional view that enormous spike variability in resting states and stimulus-triggered responses reflects noise, here, we examine the “Neural Self-Information Theory” that the interspike-interval (ISI), or the silence-duration between 2 adjoining spikes, carries self-information that is inversely proportional to its variability-probability. Specifically, higher-probability ISIs convey minimal information because they reflect the ground state, whereas lower-probability ISIs carry more information, in the form of “positive” or “negative surprisals,” signifying the excitatory or inhibitory shifts from the ground state, respectively. These surprisals serve as the quanta of information to construct temporally coordinated cell-assembly ternary codes representing real-time cognitions. Accordingly, we devised a general decoding method and unbiasedly uncovered 15 cell assemblies underlying different sleep cycles, fear-memory experiences, spatial navigation, and 5-choice serial-reaction time (5CSRT) visual-discrimination behaviors. We further revealed that robust cell-assembly codes were generated by ISI surprisals constituted of ~20% of the skewed ISI gamma-distribution tails, conforming to the “Pareto Principle” that specifies, for many events-including communication-roughly 80% of the output or consequences come from 20% of the input or causes. These results demonstrate that real-time neural coding arises from the temporal assembly of neural-clique members via silence variability-based self-information codes.

Original languageEnglish (US)
Pages (from-to)2563-2576
Number of pages14
JournalCerebral Cortex
Volume28
Issue number7
DOIs
StatePublished - Jan 1 2018

Fingerprint

Information Theory
Cognition
Reaction Time
Fear
Noise
Sleep
Communication
Brain
Discrimination (Psychology)
Spatial Navigation

Keywords

  • Cell assembly
  • Interspike-interval
  • Neural codes
  • Neural self-information
  • Spike timing

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

Cite this

Neural coding of cell assemblies via spike-timing self-information. / Li, Meng; Xie, Kun; Kuang, Hui; Liu, Jun; Wang, Deheng; Fox, Grace E.; Shi, Zhifeng; Chen, Liang; Zhao, Fang; Mao, Ying; Tsien, Joseph Zhuo.

In: Cerebral Cortex, Vol. 28, No. 7, 01.01.2018, p. 2563-2576.

Research output: Contribution to journalArticle

Li, M, Xie, K, Kuang, H, Liu, J, Wang, D, Fox, GE, Shi, Z, Chen, L, Zhao, F, Mao, Y & Tsien, JZ 2018, 'Neural coding of cell assemblies via spike-timing self-information', Cerebral Cortex, vol. 28, no. 7, pp. 2563-2576. https://doi.org/10.1093/cercor/bhy081
Li M, Xie K, Kuang H, Liu J, Wang D, Fox GE et al. Neural coding of cell assemblies via spike-timing self-information. Cerebral Cortex. 2018 Jan 1;28(7):2563-2576. https://doi.org/10.1093/cercor/bhy081
Li, Meng ; Xie, Kun ; Kuang, Hui ; Liu, Jun ; Wang, Deheng ; Fox, Grace E. ; Shi, Zhifeng ; Chen, Liang ; Zhao, Fang ; Mao, Ying ; Tsien, Joseph Zhuo. / Neural coding of cell assemblies via spike-timing self-information. In: Cerebral Cortex. 2018 ; Vol. 28, No. 7. pp. 2563-2576.
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