Neural syntax: cell assemblies, synapsembles, and readers
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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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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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Visual stimuli recruit intrinsically generated cortical ensembles
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Tasks for inhibitory interneurons in intact brain circuits
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Self-citationSelective entrainment of gamma subbands by different slow network oscillations
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Ephaptic coupling to endogenous electric field activity: Why bother?
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Portraits of communication in neuronal networks
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Cognit activation: a mechanism enabling temporal integration in working memory
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Neural versus alternative integrative systems: molecular insights into origins of neurotransmitters
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Early Cognitive Experience Prevents Adult Deficits in a Neurodevelopmental Schizophrenia Model
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Toward an integration of deep learning and neuroscience
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Cognitive and Physiologic Impacts of the Infraslow Oscillation
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- Authors
- Buzsáki, G.
- Affiliations
- Rutgers, The State University of New Jersey (US)
- Corresponding author
- Buzsáki, György
- ORCID
- Buzsáki, György
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2010-11
- Volume
- 68
- Issue
- 3
- Pages
- 362-385
- ISSN
- 0896-6273 (ISSN-L)
- PMC
- PMC3005627
- 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
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 989 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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