Identification of network-level coding units for real-time representation of episodic experiences in the hippocampus

Longnian Lin, Remus Osan, Shy Shoham, Wenjun Jin, Wenqi Zuo, Joe Z. Tsien

Research output: Contribution to journalArticle

102 Scopus citations

Abstract

To examine the network-level organizing principles by which the brain achieves its real-time encoding of episodic information, we have developed a 96-channel array to simultaneously record the activity patterns of as many as 260 individual neurons in the mouse hippocampus during various startling episodes. We find that the mnemonic startling episodes triggered firing changes in a set of CA1 neurons in both startle-type and environment-dependent manners. Pattern classification methods reveal that these firing changes form distinct ensemble representations in a low-dimensional encoding subspace. Application of a sliding window technique further enabled us to reliably capture not only the temporal dynamics of real-time network encoding but also postevent processing of newly formed ensemble traces. Our analyses revealed that the network-encoding power is derived from a set of functional coding units, termed neural cliques, in the CA1 network. The individual neurons within neural cliques exhibit "collective cospiking" dynamics that allow the neural clique to overcome the response variability of its members and to achieve real-time encoding robustness. Conversion of activation patterns of these coding unit assemblies into a set of real-time digital codes permits concise and universal representation and categorization of discrete behavioral episodes across different individual brains.

Original languageEnglish (US)
Pages (from-to)6125-6130
Number of pages6
JournalProceedings of the National Academy of Sciences of the United States of America
Volume102
Issue number17
DOIs
StatePublished - Apr 26 2005

Keywords

  • Cell assembly
  • Episodic memory
  • Neural clique
  • Neural code
  • Startle

ASJC Scopus subject areas

  • General

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