The DOI matches its Crossref record; 176 of the 177 references it cites were found in a registry or an index.
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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Cites
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Cited by
Sorted by citations
GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits
Tremblay, R., Lee, S., & Rudy, B. (2016) · Neuron · doi:10.1016/j.neuron.2016.06.033 · Cited by 2,033
Normalization as a canonical neural computation
Carandini, M., & Heeger, D. J. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3136 · Cited by 1,906
Interneuron cell types are fit to function
Kepecs, A., & Fishell, G. (2014) · Nature · doi:10.1038/nature12983 · Cited by 1,110
The log-dynamic brain: how skewed distributions affect network operations
Buzsáki, G., & Mizuseki, K. (2014) · Nature reviews. Neuroscience · doi:10.1038/nrn3687 · Cited by 1,006
Uncertainty and stress: Why it causes diseases and how it is mastered by the brain
Peters, A., McEwen, B. S., & Friston, K. (2017) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2017.05.004 · Cited by 652
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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