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Stimulus onset quenches neural variability: a widespread cortical phenomenon
Open accessAbstract
Neural responses are typically characterized by computing the mean firing rate, but response variability can exist across trials. Many studies have examined the effect of a stimulus on the mean response, but few have examined the effect on response variability. We measured neural variability in 13 extracellularly recorded datasets and one intracellularly recorded dataset from seven areas spanning the four cortical lobes in monkeys and cats. In every case, stimulus onset caused a decline in neural variability. This occurred even when the stimulus produced little change in mean firing rate. The variability decline was observed in membrane potential recordings, in the spiking of individual neurons and in correlated spiking variability measured with implanted 96-electrode arrays. The variability decline was observed for all stimuli tested, regardless of whether the animal was awake, behaving or anaesthetized. This widespread variability decline suggests a rather general property of cortex, that its state is stabilized by an input.
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“Decline of spiking variability at sensory onset is a known universal cortical phenomenon assigned to stabilization of a network state (45).”
From Neural correlates of perceptual decision-making in the primary somatosensory cortex (2026) · cites this paper as [45]
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Shadlen, M. N., & Newsome, W. T. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-10-03870.1998 · Cited by 2,178
Self-citationReliability of spike timing in neocortical neurons
Mainen, Z. F., & Sejnowski, T. J. (1995) · Science · doi:10.1126/science.7770778 · Cited by 1,950
Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity
van Vreeswijk, C., & Sompolinsky, H. (1996) · Science · doi:10.1126/science.274.5293.1724 · Cited by 1,831
Neural Basis of a Perceptual Decision in the Parietal Cortex (Area LIP) of the Rhesus Monkey
Shadlen, M. N., & Newsome, W. T. (2001) · Journal of Neurophysiology · doi:10.1152/jn.2001.86.4.1916 · Cited by 1,755
Self-citationDynamics of ongoing activity: explanation of the large variability in evoked cortical responses
Arieli, A., Sterkin, A., Grinvald, A., & Aertsen, A. (1996) · Science · doi:10.1126/science.273.5283.1868 · Cited by 1,660
Attention improves performance primarily by reducing interneuronal correlations
Cohen, M. R., & Maunsell, J. H. R. (2009) · Nature Neuroscience · doi:10.1038/nn.2439 · Cited by 1,163
Self-citationNeural Control of Voluntary Movement Initiation
Hanes, D. P., & Schall, J. D. (1996) · Science · doi:10.1126/science.274.5286.427 · Cited by 1,145
Generating Coherent Patterns of Activity from Chaotic Neural Networks
Sussillo, D., & Abbott, L. F. (2009) · Neuron · doi:10.1016/j.neuron.2009.07.018 · Cited by 1,092
A relationship between behavioral choice and the visual responses of neurons in macaque MT
Britten, K. H., Newsome, W. T., Shadlen, M. N., Celebrini, S., & Movshon, J. A. (1996) · Visual Neuroscience · doi:10.1017/s095252380000715x · Cited by 1,049
Self-citationMatching Behavior and the Representation of Value in the Parietal Cortex
Sugrue, L. P., Corrado, G. S., & Newsome, W. T. (2004) · Science · doi:10.1126/science.1094765 · Cited by 1,030
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Research works printed but not linked: 2
- Abbott, L.F., Rajan, K. & Sompolinsky, H. Interactions between intrinsic and stimulus-dependent activity in recurrent neural networks. in Neuronal Variability and its Functional Significance (eds Ding, M. & Glanzman, D.) (in the press).
- Lee, D. & Seo, H. Neural and behavioral variability related to stochastic choices during a mixed-strategy game. in Neuronal Variability and its Functional Significance (eds Ding, M. & Glanzman, D.) (in the press).
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Dimensionality reduction for large-scale neural recordings
Cunningham, J. P., & Yu, B. M. (2014) · Nature Neuroscience · doi:10.1038/nn.3776 · Cited by 1,219
Self-citationA hierarchy of intrinsic timescales across primate cortex
Murray, J. D., Bernacchia, A., Freedman, D. J., Romo, R., Wallis, J. D., Cai, X., Padoa-Schioppa, C., Pasternak, T., Seo, H., Lee, D., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3862 · Cited by 990
Attention improves performance primarily by reducing interneuronal correlations
Cohen, M. R., & Maunsell, J. H. R. (2009) · Nature Neuroscience · doi:10.1038/nn.2439 · Cited by 1,163
Self-citationHarris, K. D., & Thiele, A. (2011) · Nature reviews. Neuroscience · doi:10.1038/nrn3084 · Cited by 915
Cortical Control of Arm Movements: A Dynamical Systems Perspective
Shenoy, K. V., Sahani, M., & Churchland, M. M. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062111-150509 · Cited by 865
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Metadata
- Authors
- Churchland, M. M., Yu, B. M., Cunningham, J. P., Sugrue, L. P., Cohen, M. R., Corrado, G. S., Newsome, W. T., Clark, A. M., Hosseini, P., Scott, B. B., Bradley, D. C., Smith, M. A., Kohn, A., Movshon, J. A., Armstrong, K. M., Moore, T., Chang, S. W., Snyder, L. H., Lisberger, S. G., Priebe, N. J., Finn, I. M., Ferster, D., Ryu, S. I., Santhanam, G., Sahani, M., & Shenoy, K. V.
- Affiliations
- Stanford Medicine (US)
- Stanford University (US)
- Howard Hughes Medical Institute (US)
- University of Chicago (US)
- University of Pittsburgh (US)
- Albert Einstein College of Medicine (US)
- New York University (US)
- Washington University in St. Louis (US)
- The University of Texas at Austin (US)
- Northwestern University (US)
- Gatsby Computational Neuroscience Unit (GB)
- Corresponding author
- Churchland, Mark M
- ORCID
- Churchland, Mark M
- Yu, Byron M
- Cunningham, John P
- Sugrue, Leo P
- Cohen, Marlene R
- Corrado, Greg S
- Newsome, William T
- Clark, Andrew M
- Scott, Benjamin B
- Smith, Matthew A
- Kohn, Adam
- Movshon, J Anthony
- Moore, Tirin
- Chang, Steve W
- Snyder, Lawrence H
- Lisberger, Stephen G
- Priebe, Nicholas J
- Ryu, Stephen I
- Sahani, Maneesh
- Shenoy, Krishna V
- Venue
- Nature Neuroscience
- Published
- 2010-02-21
- Volume
- 13
- Issue
- 3
- Pages
- 369-378
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC2828350
- OpenAlex
- W2105380935
- Cited by
- 1,084
- References
- 62
- Citations by year
- 2026: 53 · 2025: 74 · 2024: 74 · 2023: 64 · 2022: 55 · 2021: 86 · 2020: 62 · 2019: 94 · 2018: 54 · 2017: 80 · 2016: 83 · 2015: 69 · 2014: 61 · 2013: 65 · 2012: 52
- FWCI
- 33.17
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- National Institutes of Health (DP1OD006409)
- National Eye Institute (EY 05603, R37EY004440, 1 EY13138-01, R00EY018894, R01EY016774, R01EY003878, EY014924, EY018894, K99EY018894, R01EY002017, EY015958, EY04440, R01EY014924, R01EY013138, R01EY019288, EY-016774, R37EY005603, R01EY004440, F32EY015958, R01EY005603, R56EY014924, EY019288, EY 02017, R01EY004726, R01EY012135)
- National Institute of Neurological Disorders and Stroke (R01NS054283)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- neural response variability, stimulus onset, neuronal firing rate, extracellular recording, intracellular recording, membrane potential, monkeys, cats, anesthetized animals
- MeSH terms
- Action Potentials, Anesthesia, Animals, Cats, Cerebral Cortex, Electrodes, Implanted, Factor Analysis, Statistical, Macaca fascicularis, Macaca mulatta, Macaca nemestrina, Membrane Potentials, Microelectrodes, Motor Activity, Neurons, Neuropsychological Tests, Time Factors, Video Recording, Visual Perception, Wakefulness, Databases, Factual
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