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Neuronal arithmetic
Open accessAbstract
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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“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]
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“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]
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“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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Metadata
- Authors
- Silver, R. A.
- Affiliations
- University College London (GB)
- Corresponding author
- Silver, R. Angus
- ORCID
- 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
- PMC
- PMC4750293
- 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
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- 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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