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The Genomic Action Potential
Abstract
Neurons compute in part by integrating, on a time scale of milliseconds, many synaptic inputs and generating a digital output-the "action potential" of classic electrophysiology. Recent discoveries indicate that neurons also perform a second, much slower, integration operating on a time scale of minutes or even hours. The output of this slower integration involves a pulse of gene expression which may be likened to the electrophysiological action potential. Its function, however, is not directed toward immediate transmission of a synaptic signal but rather toward the experience-dependent modification of the underlying synaptic circuitry. Commonly termed the "immediate early gene" (IEG) response, this phenomenon is often assumed to be a necessary component of a linear, deterministic cascade of memory consolidation. Critical review of the large literature describing the phenomenon, however, leads to an alternative model of IEG function in the brain. In this alternative, IEG activation is not directed at the consolidation of memories of a specific inducing event; instead, it sets the overall gain or efficiency of memory formation and directs it to circuits engaged by behaviorally significant contexts. The net result is a sharpening of the selectivity of memory formation, a recruitment of temporally correlated associations, and an ultimate enhancement of long-term memory retrieval.
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“bGRNs thus have the ability to directly influence the architecture and activity of NNs by modulating neuronal excitability and connectivity (57).”
From Behavior-related gene regulatory networks: A new level of organization in the brain (2020) · cites this paper as [57]
In the citing paper
“The NN operates on the millisecond-to-second scales (for neuronal firing) and may induce the rapid activation of immediate early genes (IEGs) associated with behavior (57).”
From Behavior-related gene regulatory networks: A new level of organization in the brain (2020) · cites this paper as [57]
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Metadata
- Authors
- Clayton, D. F.
- Venue
- Neurobiology of Learning and Memory
- Publisher
- Elsevier BV
- Published
- 2000-11
- Volume
- 74
- Issue
- 3
- Pages
- 185-216
- ISSN
- 1074-7427
- Cited by
- 322
- References
- 231
- Language
- en
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
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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.
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.