Cited by 481Neural dynamics and brain functionNeuroscience and Neuropharmacology ResearchAdvanced Memory and Neural Computing

Neuronal arithmetic

Open access
Silver, R. Angus·2010·Nature Reviews Neuroscience

Abstract

The vast computational power of the brain has traditionally been viewed as arising from the complex connectivity of neural networks, in which an individual neuron acts as a simple linear summation and thresholding device. However, recent studies show that individual neurons utilize a wealth of nonlinear mechanisms to transform synaptic input into output firing. These mechanisms can arise from synaptic plasticity, synaptic noise, and somatic and dendritic conductances. This tool kit of nonlinear mechanisms confers considerable computational power on both morphologically simple and more complex neurons, enabling them to perform a range of arithmetic operations on signals encoded ina variety of different ways.

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Crossref · 10.1038/nrn2864

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176 of 176 references verified0 citation errors · 0 not checkable

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  • Neuromodulation can regulate single-synapse computations at the hippocampal mossy fiber synapse.

    “Our findings indicate that neuromodulation can regulate single-synapse computations at the hippocampal mossy fiber synapse [1,103].”

    From Presynaptic cAMP-PKA-mediated potentiation induces reconfiguration of synaptic vesicle pools and channel-vesicle coupling at hippocampal mossy fiber boutons (2024) · cites this paper as [103]

    The section “Synaptic depression and gain modulation” describes how a modulatory inhibitory input and synaptic depression alter neuronal gain, including at cerebellar mossy fibre–granule cell synapses (page unavailable). It does not establish that neuromodulation regulates computations at a single hippocampal mossy fiber synapse; the cited example is in the cerebellum and concerns neuronal gain. (LLM, conf=0.84)

    Experimental — accuracy not yet measured
  • The Hill function fits stimulus-response data in a wide set of biological systems.

    “This agrees with general evidence that the Hill function fits stimulus-response data in a wide set of biological systems [123–128].”

    From Fibromyalgia pathogenesis explained by a neuroendocrine multistable model (2024) · cites this paper as [124]

    The section on multiplicative operations says neuronal input–output relationships can be fitted with empirical functions, but it does not identify the Hill function. Searches for “Hill” and for stimulus–response fitting across biological systems found no passage addressing the claim. (LLM, conf=0.74)

    Experimental — accuracy not yet measured
  • Cortical GABAergic inhibition has a crucial role in regulating the gain of sensory responses.

    “Although recent work has identified some potential mechanisms for excitatory regulation of cortical gain97,98, several lines of evidence suggest that cortical GABAergic inhibition has a crucial role in regulating the gain of sensory responses5,99,100 (FIG. 1).”

    From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [100]

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1 of the 177 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

  1. [6]Rall W Reiss RF Neuronal Theory and Modeling 1964 73 97 Stanford Univ. Press
  2. [122]Mel B Stuart GJ Spruston N Hausser M Dendrites 2008 271 284 Oxford Univ. Press
  3. [126]Stuart G Spruston N Häusser M Dendrites 2008 Oxford Univ. Press Oxford

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Authors
Silver, R. A.
Affiliations
University College London (GB)
Corresponding author
Silver, R. Angus
Venue
Nature Reviews Neuroscience
Published
2010-06-09
Volume
11
Issue
7
Pages
474-489
ISSN
  • 1471-003X (ISSN-L)
  • 1471-0048
OpenAlex
W4233766477
Cited by
481
References
177
Citations by year
2026: 23 · 2025: 32 · 2024: 26 · 2023: 22 · 2022: 39 · 2021: 35 · 2020: 35 · 2019: 34 · 2018: 34 · 2017: 23 · 2016: 38 · 2015: 48 · 2014: 30 · 2013: 23 · 2012: 25
FWCI
1.44
Type
journal article
Language
en
Open access
Locations
  • Nature reviews. Neuroscience (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • UCL Discovery (University College London) (submittedVersion)
Funders
  • Wellcome Trust (064413)
  • Biotechnology and Biological Sciences Research Council (BB/F005490/1)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Memory and Neural Computing
Keywords
neural computation, synaptic plasticity, synaptic noise, neuronal morphology, neural coding, dendritic integration
MeSH terms
Animals, Dendrites, Humans, Mathematics, Nerve Net, Synaptic Transmission, Neurons, Synapses

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