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Cited by 441

The DOI matches its Crossref record; 98 of the 98 references it cites were found in a registry or an index.

Revisiting the role of persistent neural activity during working memory

Open access
Sreenivasan, Kartik K., Curtis, Clayton E., D’Esposito, Mark·2014·Trends in Cognitive Sciences

Abstract

What are the neural mechanisms underlying working memory (WM)? One influential theory posits that neurons in lateral prefrontal cortex (lPFC) store WM information via persistent activity. In this review, we critically evaluate recent findings that together indicate that this model of WM needs revision. We argue that sensory cortex, not lPFC, maintains high-fidelity representations of WM content. In contrast, lPFC simultaneously maintains representations of multiple goal-related variables that serve to bias stimulus-specific activity in sensory regions. This work highlights multiple neural mechanisms supporting WM, including temporally dynamic population coding in addition to persistent activity. These new insights focus the question on understanding how the mechanisms that underlie WM are related, interact, and are coordinated in lPFC and sensory cortices.

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Crossref · 10.1016/j.tics.2013.12.001

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Metadata

Authors
Sreenivasan, K. K., Curtis, C. E., & D’Esposito, M.
Venue
Trends in Cognitive Sciences
Publisher
Elsevier BV
Published
2014-02
Volume
18
Issue
2
Pages
82-89
ISSN
1364-6613 (ISSN-L)
OpenAlex
W1996507113
Cited by
441
References
98
FWCI
4.21
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Revisiting the role of persistent neural activity during working memory. https://app.cochat.ai/papers/10.1016/j.tics.2013.12.001
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Sreenivasan, K. K., Curtis, C. E., & D’Esposito, M. (2014). Revisiting the role of persistent neural activity during working memory. Trends in Cognitive Sciences. https://doi.org/10.1016/j.tics.2013.12.001

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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.