Cited by 1,289Neural dynamics and brain functionMemory and Neural MechanismsNeuroscience and Neuropharmacology Research

Neural syntax: cell assemblies, synapsembles, and readers

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Buzsáki, György·2010·Neuron

Abstract

A widely discussed hypothesis in neuroscience is that transiently active ensembles of neurons, known as "cell assemblies," underlie numerous operations of the brain, from encoding memories to reasoning. However, the mechanisms responsible for the formation and disbanding of cell assemblies and temporal evolution of cell assembly sequences are not well understood. I introduce and review three interconnected topics, which could facilitate progress in defining cell assemblies, identifying their neuronal organization, and revealing causal relationships between assembly organization and behavior. First, I hypothesize that cell assemblies are best understood in light of their output product, as detected by "reader-actuator" mechanisms. Second, I suggest that the hierarchical organization of cell assemblies may be regarded as a neural syntax. Third, constituents of the neural syntax are linked together by dynamically changing constellations of synaptic weights ("synapsembles"). The existing support for this tripartite framework is reviewed and strategies for experimental testing of its predictions are discussed.

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Crossref · 10.1016/j.neuron.2010.09.023

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  • These systems are highly structured temporally, e.g., containing nested gamma and theta oscillation structures that are phase locked to sequences of place-cell responses, interfering oscillators frequency-shifted by the animal's motion velocity, tuned cellular resonances, and other neural phenomena that lie far outside a conventional artificial neural network description.

    “These systems are highly structured temporally, e.g., containing nested gamma and theta oscillation structures that are phased locked to sequences of place-cell responses, interfering oscillators frequency-shifted by the animal's motion velocity (Zilli and Hasselmo, 2010), tuned cellular resonances (Giocomo et al., 2007; Buzsáki, 2010), and other neural phenomena that lie far outside a convention”

    From Toward an integration of deep learning and neuroscience (2016) · cites this paper as Buzsáki, 2010

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Research works printed but not linked: 2

  1. Pikovsky M Rosenblum Kurths J Synchronization: a unified approach to nonlinear science 2001 Cambridge Cambridge University Press
  2. Rumelhart DE McLelland JL the PDP Research Group Parallel Distributed Processing: Explorations in the Microstructure of cognition - Vol. 1 Foundations 1986 Cambridge, MA MIT Press

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Authors
Buzsáki, G.
Affiliations
Rutgers, The State University of New Jersey (US)
Corresponding author
Buzsáki, György
Venue
Neuron
Publisher
Elsevier BV
Published
2010-11
Volume
68
Issue
3
Pages
362-385
ISSN
0896-6273 (ISSN-L)
OpenAlex
W1996874802
Cited by
1,289
References
351
Citations by year
2026: 78 · 2025: 88 · 2024: 93 · 2023: 73 · 2022: 90 · 2021: 108 · 2020: 83 · 2019: 92 · 2018: 93 · 2017: 82 · 2016: 93 · 2015: 90 · 2014: 77 · 2013: 71 · 2012: 46
FWCI
3.37
Type
journal article
Language
en
Open access
Locations
  • Neuron (publishedVersion)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (acceptedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Science Foundation (SBE 0542013)
  • National Institutes of Health (MH54671, NS034994)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
Keywords
cell assemblies, synaptic weights, memory encoding, neural basis of behavior
MeSH terms
Animals, Brain, Electrophysiology, Humans, Models, Neurological, Neural Pathways, Neurons, Synapses

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