The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Cortical State Determines Global Variability and Correlations in Visual Cortex
Open accessAbstract
The response of neurons in sensory cortex to repeated stimulus presentations is highly variable. To investigate the nature of this variability, we compared the spike activity of neurons in the primary visual cortex (V1) of cats with that of their afferents from lateral geniculate nucleus (LGN), in response to similar stimuli. We found variability to be much higher in V1 than in LGN. To investigate the sources of the additional variability, we measured the spiking activity of large V1 populations and found that much of the variability was shared across neurons: the variable portion of the responses of one neuron could be well predicted from the summed activity of the rest of the neurons. Variability thus mostly reflected global fluctuations affecting all neurons. The size and prevalence of these fluctuations, both in responses to stimuli and in ongoing activity, depended on cortical state, being larger in synchronized states than in more desynchronized states. Contrary to previous reports, these fluctuations invested the overall population, regardless of preferred orientation. The global fluctuations substantially increased variability in single neurons and correlations among pairs of neurons. Once this effect was removed, pairwise correlations were reduced and were similar regardless of cortical state. These results highlight the importance of cortical state in controlling cortical operation and can help reconcile previous studies, which differed widely in their estimate of neuronal variability and pairwise correlations.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“These variations in state exert an effect on sensory evoked neural activity that can be as significant as variations in the sensory stimulus itself”
From Waking state: rapid variations modulate neural and behavioral responses (2015) · cites this paper as Scholvinck et al., 2015
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Shadlen, M. N., & Newsome, W. T. (1998) · The Journal of Neuroscience · doi:10.1523/jneurosci.18-10-03870.1998 · Cited by 2,178
Reliability of spike timing in neocortical neurons
Mainen, Z. F., & Sejnowski, T. J. (1995) · Science · doi:10.1126/science.7770778 · Cited by 1,950
Dynamics 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
Spatio-temporal correlations and visual signalling in a complete neuronal population
Pillow, J. W., Shlens, J., Paninski, L., Sher, A., Litke, A. M., Chichilnisky, E. J., & Simoncelli, E. P. (2008) · Nature · doi:10.1038/nature07140 · Cited by 1,332
Grouping of brain rhythms in corticothalamic systems
Steriade, M. (2006) · Neuroscience · doi:10.1016/j.neuroscience.2005.10.029 · Cited by 1,296
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
The Asynchronous State in Cortical Circuits
Renart, A., de la Rocha, J., Bartho, P., Hollender, L., Parga, N., Reyes, A., & Harris, K. D. (2010) · Science · doi:10.1126/science.1179850 · Cited by 1,106
Measuring and interpreting neuronal correlations
Cohen, M. R., & Kohn, A. (2011) · Nature Neuroscience · doi:10.1038/nn.2842 · Cited by 1,059
The statistical reliability of signals in single neurons in cat and monkey visual cortex
Tolhurst, D. J., Movshon, J. A., & Dean, A. F. (1983) · Vision Research · doi:10.1016/0042-6989(83)90200-6 · Cited by 1,002
Spontaneously emerging cortical representations of visual attributes
Kenet, T., Bibitchkov, D., Tsodyks, M., Grinvald, A., & Arieli, A. (2003) · Nature · doi:10.1038/nature02078 · Cited by 924
Harris, K. D., & Thiele, A. (2011) · Nature reviews. Neuroscience · doi:10.1038/nrn3084 · Cited by 915
Organization of cell assemblies in the hippocampus
Harris, K. D., Csicsvari, J., Hirase, H., Dragoi, G., & Buzsáki, G. (2003) · Nature · doi:10.1038/nature01834 · Cited by 901
Ts'o, D., Gilbert, C., & Wiesel, T. (1986) · Journal of Neuroscience · doi:10.1523/jneurosci.06-04-01160.1986 · Cited by 843
Functional specificity of local synaptic connections in neocortical networks
Ko, H., Hofer, S. B., Pichler, B., Buchanan, K. A., Sjöström, P. J., & Mrsic‐Flogel, T. D. (2011) · Nature · doi:10.1038/nature09880 · Cited by 834
Internal brain state regulates membrane potential synchrony in barrel cortex of behaving mice
Poulet, J. F. A., & Petersen, C. C. H. (2008) · Nature · doi:10.1038/nature07150 · Cited by 796
Linking Spontaneous Activity of Single Cortical Neurons and the Underlying Functional Architecture
Tsodyks, M. V., Kenet, T., Grinvald, A., & Arieli, A. (1999) · Science · doi:10.1126/science.286.5446.1943 · Cited by 715
Decorrelated neuronal firing in cortical microcircuits
Ecker, A. S., Berens, P., Keliris, G. A., Bethge, M., Logothetis, N. K., & Tolias, A. S. (2010) · Science · doi:10.1126/science.1179867 · Cited by 640
Spatial and Temporal Scales of Neuronal Correlation in Primary Visual Cortex
Smith, M. A., & Kohn, A. (2008) · Journal of Neuroscience · doi:10.1523/jneurosci.2929-08.2008 · Cited by 600
Basal forebrain activation enhances cortical coding of natural scenes
Goard, M. J., & Dan, Y. (2009) · Nature Neuroscience · doi:10.1038/nn.2402 · Cited by 558
Statistical Signs of Synaptic Interaction in Neurons
Moore, G., Segundo, J. P., Perkel, D. H., & Levitan, H. (1970) · Biophysical Journal · doi:10.1016/s0006-3495(70)86341-x · Cited by 544
Dynamics of orientation tuning in macaque primary visual cortex
Ringach, D. L., Hawken, M. J., & Shapley, R. M. (1997) · Nature · doi:10.1038/387281a0 · Cited by 538
Stimulus Dependence of Neuronal Correlation in Primary Visual Cortex of the Macaque
Kohn, A., & Smith, M. A. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.5106-04.2005 · Cited by 532
Partitioning neuronal variability
Goris, R. L. T., Movshon, J. A., & Simoncelli, E. P. (2014) · Nature Neuroscience · doi:10.1038/nn.3711 · Cited by 528
Correlated Firing in Macaque Visual Area MT: Time Scales and Relationship to Behavior
Bair, W., Zohary, E., & Newsome, W. T. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-05-01676.2001 · Cited by 510
Membrane Potential and Firing Rate in Cat Primary Visual Cortex
Carandini, M., & Ferster, D. (2000) · Journal of Neuroscience · doi:10.1523/jneurosci.20-01-00470.2000 · Cited by 413
Population imaging of ongoing neuronal activity in the visual cortex of awake rats
Greenberg, D. S., Houweling, A. R., & Kerr, J. N. D. (2008) · Nature Neuroscience · doi:10.1038/nn.2140 · Cited by 412
Low Response Variability in Simultaneously Recorded Retinal, Thalamic, and Cortical Neurons
Kara, P., Reinagel, P., & Reid, R. C. (2000) · Neuron · doi:10.1016/s0896-6273(00)00072-6 · Cited by 404
Rules of Connectivity between Geniculate Cells and Simple Cells in Cat Primary Visual Cortex
Alonso, J., Usrey, W. M., & Reid, R. C. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-11-04002.2001 · Cited by 385
Efficient Discrimination of Temporal Patterns by Motion-Sensitive Neurons in Primate Visual Cortex
Buračas, G. T., Zador, A. M., DeWeese, M. R., & Albright, T. D. (1998) · Neuron · doi:10.1016/s0896-6273(00)80477-8 · Cited by 380
State Dependence of Noise Correlations in Macaque Primary Visual Cortex
Ecker, A. S., Berens, P., Cotton, R. J., Subramaniyan, M., Denfield, G. H., Cadwell, C. R., Smirnakis, S. M., Bethge, M., & Tolias, A. S. (2014) · Neuron · doi:10.1016/j.neuron.2014.02.006 · Cited by 338
Cyclic and Sleep-Like Spontaneous Alternations of Brain State Under Urethane Anaesthesia
Clement, E., Richard, A., Thwaites, M., Ailon, J., Peters, S. R., & Dickson, C. T. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002004 · Cited by 337
Unreliable evoked responses in autism
Dinstein, I., Heeger, D. J., Lorenzi, L., Minshew, N. J., Malach, R., & Behrmann, M. (2012) · Neuron · doi:10.1016/j.neuron.2012.07.026 · Cited by 318
Visual cortex neurons in monkeys and cats: Detection, discrimination, and identification
Geisler, W. S., & Albrecht, D. G. (1997) · Visual Neuroscience · doi:10.1017/s0952523800011627 · Cited by 285
Collective dynamics in human and monkey sensorimotor cortex: predicting single neuron spikes
Truccolo, W., Hochberg, L. R., & Donoghue, J. P. (2009) · Nature Neuroscience · doi:10.1038/nn.2455 · Cited by 248
Okun, M., Naim, A., & Lampl, I. (2010) · Journal of Neuroscience · doi:10.1523/jneurosci.5062-09.2010 · Cited by 241
The Suppressive Field of Neurons in Lateral Geniculate Nucleus
Bonin, V., Mante, V., & Carandini, M. (2005) · Journal of Neuroscience · doi:10.1523/jneurosci.3562-05.2005 · Cited by 239
Spontaneous and driven cortical activity: implications for computation.
Ringach, D. L. (2009) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2009.07.005 · Cited by 234
The response variability of striate cortical neurons in the behaving monkey
Vogels, R., Spileers, W., & Orban, G. A. (1989) · Experimental Brain Research · doi:10.1007/bf00275002 · Cited by 234
The variability of discharge of simple cells in the cat striate cortex
Dean, A. F. (1981) · Experimental Brain Research · doi:10.1007/bf00238837 · Cited by 231
Amplification of Trial-to-Trial Response Variability by Neurons in Visual Cortex
Carandini, M. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020264 · Cited by 210
Mechanisms of Neuronal Computation in Mammalian Visual Cortex
Priebe, N. J., & Ferster, D. (2012) · Neuron · doi:10.1016/j.neuron.2012.06.011 · Cited by 209
Sensory stimulation shifts visual cortex from synchronous to asynchronous states
Tan, A. Y. Y., Chen, Y., Scholl, B., Seidemann, E., & Priebe, N. J. (2014) · Nature · doi:10.1038/nature13159 · Cited by 206
Response Variability and Timing Precision of Neuronal Spike Trains In Vivo
Reich, D. S., Victor, J. D., Knight, B. W., Ozaki, T., & Kaplan, E. (1997) · Journal of Neurophysiology · doi:10.1152/jn.1997.77.5.2836 · Cited by 205
Visual orientation and spatial frequency discrimination: a comparison of single neurons and behavior
Bradley, A., SKOTTUN, B. C., Ohzawa, I., Sclar, G., & Freeman, R. D. (1987) · Journal of Neurophysiology · doi:10.1152/jn.1987.57.3.755 · Cited by 201
Trial-to-Trial Variability and State-Dependent Modulation of Auditory-Evoked Responses in Cortex
Kisley, M. A., & Gerstein, G. L. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-23-10451.1999 · Cited by 193
Curto, C., Sakata, S., Marguet, S. L., Itskov, V., & Harris, K. D. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.2053-09.2009 · Cited by 157
Response variability and orientation discrimination of single cells in striate cortex of cat
Heggelund, P., & Albus, K. (1978) · Experimental Brain Research · doi:10.1007/bf00239727 · Cited by 135
Neuronal Selectivity and Local Map Structure in Visual Cortex
Nauhaus, I., Benucci, A., Carandini, M., & Ringach, D. L. (2008) · Neuron · doi:10.1016/j.neuron.2008.01.020 · Cited by 129
Functional Mechanisms Shaping Lateral Geniculate Responses to Artificial and Natural Stimuli
Mante, V., Bonin, V., & Carandini, M. (2008) · Neuron · doi:10.1016/j.neuron.2008.03.011 · Cited by 119
Brody, C. D. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.80.6.3345 · Cited by 117
State-Dependent Representation of Amplitude-Modulated Noise Stimuli in Rat Auditory Cortex
Marguet, S. L., & Harris, K. D. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5773-10.2011 · Cited by 98
Correlations and brain states: from electrophysiology to functional imaging
Kohn, A., Zandvakili, A., & Smith, M. A. (2009) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2009.06.007 · Cited by 90
Shared and Private Variability in the Auditory Cortex
DeWeese, M. R., & Zador, A. M. (2004) · Journal of Neurophysiology · doi:10.1152/jn.00197.2004 · Cited by 86
Coding of stimulus sequences by population responses in visual cortex
Benucci, A., Ringach, D. L., & Carandini, M. (2009) · Nature Neuroscience · doi:10.1038/nn.2398 · Cited by 76
Population Rate Dynamics and Multineuron Firing Patterns in Sensory Cortex
Okun, M., Yger, P., Marguet, S. L., Gérard-Mercier, F., Benucci, A., Katzner, S., Busse, L., Carandini, M., & Harris, K. D. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.1831-12.2012 · Cited by 75
Saleem, A. B., Chadderton, P. T., Apergis‐Schoute, J., Harris, K. D., & Schultz, S. R. (2010) · Journal of Computational Neuroscience · doi:10.1007/s10827-010-0228-5 · Cited by 66
Sadagopan, S., & Ferster, D. (2012) · Neuron · doi:10.1016/j.neuron.2012.05.007 · Cited by 62
Temporal properties of surround suppression in cat primary visual cortex
Durand, S., Freeman, T., & Carandini, M. (2007) · Visual Neuroscience · doi:10.1017/s0952523807070563 · Cited by 41
Ch'ng, Y. H. (2010) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2010.00020 · Cited by 40
The variability of the maintained discharge of cat dorsal lateral geniculate cells.
Levine, M. W., & Troy, J. B. (1986) · The Journal of Physiology · doi:10.1113/jphysiol.1986.sp016120 · Cited by 33
Contrast gain control, noise and spike threshold in the early visual system
Bonin, V. (2005) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-a-005115413 · Cited by 1
Cited by
Sorted by citations
Waking state: rapid variations modulate neural and behavioral responses
McGinley, M. J., Vinck, M., Reimer, J., Batista-Brito, R., Zagha, E., Cadwell, C. R., Tolias, A. S., Cardin, J. A., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.012 · Cited by 801
“…et al., 2007; Gentet et al., 2010; Haider et al., 2013; Lee et al., 2013; McGinley et al., 2015; Nelson et al., 2013; Niell and Stryker, 2010; Polack et al., 2013; Poulet and Petersen, 2008; Reimer et al., 2014; Scholvinck et al., 2015; Vinck et al., 2015; Zagha et al., 2013; Zhou et al., 2014).”
InfluentialCortical membrane potential signature of optimal states for sensory signal detection
McGinley, M. J., David, S. V., & McCormick, D. A. (2015) · Neuron · doi:10.1016/j.neuron.2015.05.038 · Cited by 728
Cortical Areas Interact through a Communication Subspace
Semedo, J. D., Zandvakili, A., Machens, C. K., Yu, B. M., & Kohn, A. (2019) · Neuron · doi:10.1016/j.neuron.2019.01.026 · Cited by 395
Correlations and Neuronal Population Information
Kohn, A., Coen-Cagli, R., Kanitscheider, I., & Pouget, A. (2016) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-070815-013851 · Cited by 372
Neuronal Firing Rate Homeostasis Is Inhibited by Sleep and Promoted by Wake
Hengen, K. B., Pacheco, A. T., McGregor, J. N., Hooser, S. D. V., & Turrigiano, G. G. (2016) · Cell · doi:10.1016/j.cell.2016.01.046 · Cited by 302
Metadata
- Authors
- Schölvinck, M. L., Saleem, A. B., Benucci, A., Harris, K. D., & Carandini, M.
- Affiliations
- University College London (GB)
- UCL Queen Square Institute of Neurology (GB)
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2015-01-07
- Volume
- 35
- Issue
- 1
- Pages
- 170-178
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- PMC
- PMC4287140
- OpenAlex
- W1969233644
- Cited by
- 198
- References
- 61
- Citations by year
- 2026: 2 · 2025: 6 · 2024: 13 · 2023: 10 · 2022: 12 · 2021: 16 · 2020: 21 · 2019: 21 · 2018: 26 · 2017: 27 · 2016: 28 · 2015: 16
- FWCI
- 19.46
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion, cc-by)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- GlaxoSmithKline
- Wellcome Trust (095668, 095669)
- Engineering and Physical Sciences Research Council (EP/I005102/1, EP/I005102/2, EP/K015141/1)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- neural variability, cortical state, primary visual cortex, lateral geniculate nucleus, spike train correlations, global fluctuations, cortical synchronization, population coding, crystallographic texture
- MeSH terms
- Animals, Cats, Female, Nerve Net, Photic Stimulation, Random Allocation, Visual Cortex, Visual Pathways
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 ›
Are you an author, or do you see a problem with this page? Request a review
