Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 205

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

A model of neocortex

Bienenstock, Elie·1995·Network: Computation in Neural Systems

Abstract

Prompted by considerations about (i) the compositionality of cognitive functions, (ii) the physiology of individual cortical neurons, (iii) the role of accurately timed spike patterns in cortex, and (iv) the regulation of global cortical activity, we suggest that the dynamics of cortex on the 1-ms time scale may be described as the activation of circuits of the synfire-chain type (Abeles 1982, 1991). We suggest that the fundamental computational unit in cortex may be a wave-like spatio-temporal pattern of synfire type, and that the binding mechanism underlying compositionality in cognition may be the accurate synchronization of synfire waves that propagate simultaneously on distinct, weakly coupled, synfire chains. We propose that Hebbian synaptic plasticity may result in a superposition of synfire chains in cortical connectivity, whereby a given neuron participates in many distinct chains. We investigate the behaviour of a much-simplified model of cortical dynamics devised along these principles. Calculations and numerical experiments are performed based on an assumption of randomness of stored chains, in the style of statistical physics. It is demonstrated that: (i) there exists a critical value for the total length of stored chains; (ii) this storage capacity is linear in the network's size; (iii) the behaviour of the network around the critical point is characterized by the self-regulation of the number of synfire waves coactive in the network at any given time.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1088/0954-898x/6/2/004

Cites

5 of 5 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 5 references

Cited by

See all 205

Metadata

Authors
Bienenstock, E.
Venue
Network: Computation in Neural Systems
Published
1995-05-01
Volume
6
Issue
2
Pages
179-224
ISSN
  • 0954-898X (ISSN-L)
  • 1361-6536
OpenAlex
W2152428149
Cited by
205
References
5
FWCI
4.57
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: A model of neocortex. https://app.cochat.ai/papers/10.1088/0954-898x/6/2/004
The paper
Bienenstock, E. (1995). A model of neocortex. Network: Computation in Neural Systems. https://doi.org/10.1088/0954-898x/6/2/004

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.