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Cited by 351

The DOI matches its Crossref record; 52 of the 52 references it cites were found in a registry or an index.

Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons.

Matell, Matthew S., Meck, Warren H., Nicolelis, Miguel A. L.·2003·Behavioral Neuroscience

Abstract

This study investigated the firing patterns of striatal and cortical neurons in rats in a temporal generalization task. Striatal and cortical ensembles were recorded in rats trained to lever press at 2 possible criterion durations (10 s or 40 s from tone onset). Twenty-two percent of striatal and 15% of cortical cells had temporally specific modulations in their firing rate, firing at a significantly different rate around 10 s compared with 40 s. On 80% of trials, a post hoc analysis of the trial-by-trial consistency of the firing rates of an ensemble of neurons predicted whether a spike train came from a time window around 10 s versus around 40 s. Results suggest that striatal and cortical neurons encode specific durations in their firing rate and thereby serve as components of a neural circuit used to represent duration.

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Metadata

Authors
Matell, M. S., Meck, W. H., & Nicolelis, M. A. L.
Venue
Behavioral Neuroscience
Published
2003
Volume
117
Issue
4
Pages
760-773
ISSN
  • 0735-7044 (ISSN-L)
  • 1939-0084
OpenAlex
W2164789388
Cited by
351
References
52
FWCI
7.44
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons. https://app.cochat.ai/papers/10.1037/0735-7044.117.4.760
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Matell, M. S., Meck, W. H., & Nicolelis, M. A. L. (2003). Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons. Behavioral Neuroscience. https://doi.org/10.1037/0735-7044.117.4.760

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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.