Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 239

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Biophysical model of a Hebbian synapse.

Open access
Zador, A, Koch, C, Brown, T H·1990·Proceedings of the National Academy of Sciences

Abstract

We present a biophysical model of electrical and Ca(2+) dynamics following activation of N-methyl-D-aspartate (NMDA) receptors located on a dendritic spine. The model accounts for much of the phenomenology of the induction of long-term potentiation at a Hebbian synapse in hippocampal region CA1. Computer simulations suggested four important functions of spines in this Ca(2+)-dependent synaptic modification: (i) compartmentalizing transient changes in [Ca(2+)] to just those synapses that satisfy the conjunctive requirement for synaptic modification; (ii) isolating the spine head from changes in the [Ca(2+)] at the dendritic shaft; (iii) amplifying the concentration changes at those synapses; and (iv) increasing the voltage dependence of the processes underlying long term potentiation induction. This proposed role of spines in the regulation of Ca(2+) dynamics contrasts with traditional approaches to spine function that have stressed electronic properties. This model can be used to explore the computational implications of Hebbian synapses.

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 · 10.1073/pnas.87.17.6718

Cites

4 of 4 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 4 references

Cited by

See all 239

Metadata

Authors
Zador, A., Koch, C., & Brown, T. H.
Venue
Proceedings of the National Academy of Sciences
Published
1990-09
Volume
87
Issue
17
Pages
6718-6722
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2021285984
Cited by
239
References
4
FWCI
4.38
Type
journal article
Language
en
Open access
green

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: Biophysical model of a Hebbian synapse. https://app.cochat.ai/papers/10.1073/pnas.87.17.6718
The paper
Zador, A., Koch, C., & Brown, T. H. (1990). Biophysical model of a Hebbian synapse. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.87.17.6718

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.