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Cited by 188

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Lag threads organize the brain’s intrinsic activity

Open access
Mitra, Anish, Snyder, Abraham Z., Blazey, Tyler, Raichle, Marcus E.·2015·Proceedings of the National Academy of Sciences

Abstract

Significance: It is well known that slow intrinsic activity, as measured by resting-state fMRI in a variety of animals including humans, is organized into temporally synchronous networks. The question of whether intrinsic activity contains reproducible temporal sequences has received far less attention. We have previously shown that human resting-state fMRI contains a highly reproducible lag structure. Here, we demonstrate that this lag structure is of high dimensionality and consists of multiple highly reproducible temporal sequences, which we term “lag threads.” Moreover, we demonstrate that the well-known zero-lag temporal correlation structure of intrinsic activity emerges as a consequence of lag structure. Thus, lag threads may represent a fundamental and previously unsuspected level of organization in resting-state activity.

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Metadata

Authors
Mitra, A., Snyder, A. Z., Blazey, T., & Raichle, M. E.
Venue
Proceedings of the National Academy of Sciences
Published
2015-03-30
Volume
112
Issue
17
Pages
E2235-44
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W1973545621
Cited by
188
References
28
FWCI
10.33
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Lag threads organize the brain’s intrinsic activity. https://app.cochat.ai/papers/10.1073/pnas.1503960112
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Mitra, A., Snyder, A. Z., Blazey, T., & Raichle, M. E. (2015). Lag threads organize the brain’s intrinsic activity. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1503960112

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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.