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Cited by 246

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Network measures predict neuropsychological outcome after brain injury

Open access
Warren, David E., Power, Jonathan D., Bruss, Joel, Denburg, Natalie L., Waldron, Eric J., Sun, Haoxin, Petersen, Steven E., Tranel, Daniel·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: Thought depends on the brain, and cognitive neuroscience has shown that different sets of brain regions (systems) support different cognitive abilities. We hypothesized that complex cognition might be especially supported by hub brain locations that participate in many such systems. We studied neurological patients with focal brain lesions, and found that damage to hub locations produced much greater cognitive impairment than damage to other locations. This work may improve the understanding of outcomes of brain injuries (from, e.g., stroke, resection, or trauma) and help inform prognosis and rehabilitation efforts.

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Crossref · 10.1073/pnas.1322173111

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Metadata

Authors
Warren, D. E., Power, J. D., Bruss, J., Denburg, N. L., Waldron, E. J., Sun, H., Petersen, S. E., & Tranel, D.
Venue
Proceedings of the National Academy of Sciences
Published
2014-09-15
Volume
111
Issue
39
Pages
14247-14252
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2020641665
Cited by
246
References
7
FWCI
12.77
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Network measures predict neuropsychological outcome after brain injury. https://app.cochat.ai/papers/10.1073/pnas.1322173111
The paper
Warren, D. E., Power, J. D., Bruss, J., Denburg, N. L., Waldron, E. J., Sun, H., Petersen, S. E., & Tranel, D. (2014). Network measures predict neuropsychological outcome after brain injury. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1322173111

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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.