The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Recurrent Excitation in Neocortical Circuits
Abstract
The majority of synapses in the mammalian cortex originate from cortical neurons. Indeed, the largest input to cortical cells comes from neighboring excitatory cells. However, most models of cortical development and processing do not reflect the anatomy and physiology of feedback excitation and are restricted to serial feedforward excitation. This report describes how populations of neurons in cat visual cortex can use excitatory feedback, characterized as an effective "network conductance", to amplify their feedforward input signals and demonstrates how neuronal discharge can be kept proportional to stimulus strength despite strong, recurrent connections that threaten to cause runaway excitation. These principles are incorporated into models of cortical direction and orientation selectivity that emphasize the basic design principles of cortical architectures.
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
Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex
Hubel, D. H., & Wiesel, T. N. (1962) · The Journal of Physiology · doi:10.1113/jphysiol.1962.sp006837 · Cited by 13,680
Hopfield, J. J. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.10.3088 · Cited by 6,918
Neuromorphic electronic systems
Mead, C. (1990) · Proceedings of the IEEE · doi:10.1109/5.58356 · Cited by 2,368
Non-Holographic Associative Memory
WILLSHAW, D. J., BUNEMAN, O. P., & LONGUET-HIGGINS, H. C. (1969) · Nature · doi:10.1038/222960a0 · Cited by 979
Neuronal Networks of the Hippocampus
Traub, R. D., & Miles, R. (1991) · doi:10.1017/cbo9780511895401 · Cited by 802
Summation and Division by Neurons in Primate Visual Cortex
Carandini, M., & Heeger, D. J. (1994) · Science · doi:10.1126/science.8191289 · Cited by 649
Patterns of synaptic input to layer 4 of cat striate cortex
McGuire, B., Hornung, J., Gilbert, C., & Wiesel, T. (1984) · The Journal of Neuroscience · doi:10.1523/jneurosci.04-12-03021.1984 · Cited by 275
Orientation selectivity of cortical neurons during intracellular blockade of inhibition
Nelson, S., Toth, L., Sheth, B., & Sur, M. (1994) · Science · doi:10.1126/science.8047882 · Cited by 254
Cited by
(2011) · Cited by 6,993
What we can do and what we cannot do with fMRI
Logothetis, N. K. (2008) · Nature · doi:10.1038/nature06976 · Cited by 3,612
Hierarchical models of object recognition in cortex
Riesenhuber, M., & Poggio, T. (1999) · Nature Neuroscience · doi:10.1038/14819 · Cited by 3,309
Continual lifelong learning with neural networks: A review
Parisi, G. I., Kemker, R., Part, J. L., Kanan, C., & Wermter, S. (2019) · Neural Networks · doi:10.1016/j.neunet.2019.01.012 · Cited by 3,117
Neuronal Avalanches in Neocortical Circuits
Beggs, J. M., & Plenz, D. (2003) · The Journal of Neuroscience · doi:10.1523/jneurosci.23-35-11167.2003 · Cited by 2,325
Metadata
- Authors
- Douglas, R. J., Koch, C., Mahowald, M., Martin, K. A. C., & Suarez, H. H.
- Venue
- Science
- Published
- 1995-08-18
- Volume
- 269
- Issue
- 5226
- Pages
- 981-985
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1991233288
- Cited by
- 980
- References
- 8
- FWCI
- 23.24
- Type
- journal article
- Language
- en
- Open access
- closed
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: Recurrent Excitation in Neocortical Circuits. https://app.cochat.ai/papers/10.1126/science.7638624
- The paper
- Douglas, R. J., Koch, C., Mahowald, M., Martin, K. A. C., & Suarez, H. H. (1995). Recurrent Excitation in Neocortical Circuits. Science. https://doi.org/10.1126/science.7638624
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.
