Shunting Inhibition Modulates Neuronal Gain during Synaptic Excitation
Open accessAbstract
Neuronal gain control is important for processing information in the brain. Shunting inhibition is not thought to control gain since it shifts input-output relationships during tonic excitation rather than changing their slope. Here we show that tonic inhibition reduces the gain and shifts the offset of cerebellar granule cell input-output relationships during frequency-dependent excitation with synaptic conductance waveforms. Shunting inhibition scales subthreshold voltage, increasing the excitation frequency required to attain a particular firing rate. This reduces gain because frequency-dependent increases in input variability, which couple mean subthreshold voltage to firing rate, boost voltage fluctuations during inhibition. Moreover, synaptic time course and the number of inputs also influence gain changes by setting excitation variability. Our results suggest that shunting inhibition can multiplicatively scale rate-coded information in neurons with high-variability synaptic inputs.
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Shunting inhibition combined with excitatory drive can modulate gain.
“Moreover, shunting inhibition combined with excitatory drive can modulate gain77, and excitatory or inhibitory synaptic input can modulate the gain of a larger, non-linear driving input to a cell78.”
From Mechanisms underlying gain modulation in the cortex (2020) · cites this paper as [77]
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- Authors
- Mitchell, S. J., & Silver, R. A.
- Affiliations
- University College London (GB)
- Corresponding author
- Silver, R.Angus
- Venue
- Neuron
- Publisher
- Elsevier BV
- Published
- 2003-05
- Volume
- 38
- Issue
- 3
- Pages
- 433-445
- ISSN
- 0896-6273 (ISSN-L)
- OpenAlex
- W2109251081
- Cited by
- 602
- References
- 70
- Citations by year
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- FWCI
- 10.16
- 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, 3730 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)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Wellcome Trust
- European Commission
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Ion channel regulation and function
- Keywords
- shunting inhibition, cerebellar granule cells, input-output relationship, synaptic conductance, input variability, rate coding, tonic inhibition
- MeSH terms
- Action Potentials, Animals, Cell Membrane, Cerebellar Cortex, Electric Stimulation, Models, Neurological, Neural Inhibition, Neural Pathways, Synaptic Transmission, Neurons, Synapses, Sodium Channels, Rats, Sprague-Dawley, Excitatory Postsynaptic Potentials, Rats
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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