The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches
Open accessAbstract
The repertoire of neural activity patterns that a cortical network can produce constrains the ability of the network to transfer and process information. Here, we measured activity patterns obtained from multisite local field potential recordings in cortex cultures, urethane-anesthetized rats, and awake macaque monkeys. First, we quantified the information capacity of the pattern repertoire of ongoing and stimulus-evoked activity using Shannon entropy. Next, we quantified the efficacy of information transmission between stimulus and response using mutual information. By systematically changing the ratio of excitation/inhibition (E/I) in vitro and in a network model, we discovered that both information capacity and information transmission are maximized at a particular intermediate E/I, at which ongoing activity emerges as neuronal avalanches. Next, we used our in vitro and model results to correctly predict in vivo information capacity and interactions between neuronal groups during ongoing activity. Close agreement between our experiments and model suggest that neuronal avalanches and peak information capacity arise because of criticality and are general properties of cortical networks with balanced E/I.
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.
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
A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
Information theory and statistical mechanics
Jaynes, E. T. (1957) · Physical Review · doi:10.1103/physrev.106.620 · Cited by 12,931
Coordinated memory replay in the visual cortex and hippocampus during sleep
Ji, D., & Wilson, M. A. (2007) · Nature Neuroscience · doi:10.1038/nn1825 · Cited by 1,669
Stimulus onset quenches neural variability: A widespread cortical phenomenon
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., et al. (2010) · Nature Neuroscience · doi:10.1038/nn.2501 · Cited by 1,084
Turning on and off recurrent balanced cortical activity
Shu, Y., Hasenstaub, A., & McCormick, D. A. (2003) · Nature · doi:10.1038/nature01616 · Cited by 1,054
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
Optimal dynamical range of excitable networks at criticality
Kinouchi, O., & Copelli, M. (2006) · Nature Physics · doi:10.1038/nphys289 · Cited by 831
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
Spontaneous Events Outline the Realm of Possible Sensory Responses in Neocortical Populations
Luczak, A., Barthó, P., & Harris, K. D. (2009) · Neuron · doi:10.1016/j.neuron.2009.03.014 · Cited by 593
Small modulation of ongoing cortical dynamics by sensory input during natural vision.
Fiser, J., Chiu, C., & Weliky, M. (2004) · Nature · doi:10.1038/nature02907 · Cited by 423
Cited by
Sohal, V. S., & Rubenstein, J. L. R. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0426-0 · Cited by 988
The Functional Benefits of Criticality in the Cortex
Shew, W. L., & Plenz, D. (2013) · The Neuroscientist · doi:10.1177/1073858412445487 · Cited by 607
Self-citationSelf-organized criticality as a fundamental property of neural systems
Hesse, J., & Gross, T. (2014) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2014.00166 · Cited by 440
The Modulation of BOLD Variability between Cognitive States Varies by Age and Processing Speed
Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs055 · Cited by 276
A free energy principle for a particular physics
Friston, K. (2019) · arXiv · doi:10.48550/arxiv.1906.10184 · Cited by 222
Metadata
- Authors
- Shew, W. L., Yang, H., Yu, S., Roy, R., & Plenz, D.
- Venue
- The Journal of Neuroscience
- Publisher
- Society for Neuroscience
- Published
- 2011-01-05
- Volume
- 31
- Issue
- 1
- Pages
- 55-63
- ISSN
- 0270-6474 (ISSN-L)
- 1529-2401
- OpenAlex
- W1993887342
- Cited by
- 588
- References
- 11
- FWCI
- 16.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches. https://app.cochat.ai/papers/10.1523/jneurosci.4637-10.2011
- The paper
- Shew, W. L., Yang, H., Yu, S., Roy, R., & Plenz, D. (2011). Information Capacity and Transmission Are Maximized in Balanced Cortical Networks with Neuronal Avalanches. The Journal of Neuroscience. https://doi.org/10.1523/jneurosci.4637-10.2011
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
