Network measures predict neuropsychological outcome after brain injury
- Category
- General Reference
- author-supplied keywords
- keywords
- authors
- David E. Warren
- Jonathan D. Power
- Joel Bruss
- Natalie L. Denburg
- Eric J. Waldron
- Haoxin Sun
- Steven E. Petersen
- Daniel Tranel
- title
- Network measures predict neuropsychological outcome after brain injury
- type
- journal
- year
- 2014
- source
- Proceedings of the National Academy of Sciences of the United States of America
- pages
- 14247-14252
- volume
- 111
- issue
- 39
- publisher
- National Academy of Sciences
Abstract
Hubs are network components that hold positions of high importance for network function. Previous research has identified hubs in human brain networks derived from neuroimaging data; however, there is little consensus on the localization of such hubs. Moreover, direct evidence regarding the role of various proposed hubs in network function (e.g., cognition) is scarce. Regions of the default mode network (DMN) have been frequently identified as "cortical hubs" of brain networks. On theoretical grounds, we have argued against some of the methods used to identify these hubs and have advocated alternative approaches that identify different regions of cortex as hubs. Our framework predicts that our proposed hub locations may play influential roles in multiple aspects of cognition, and, in contrast, that hubs identified via other methods (including salient regions in the DMN) might not exert such broad influence. Here we used a neuropsychological approach to directly test these predictions by studying long-term cognitive and behavioral outcomes in 30 patients, 19 with focal lesions to six "target" hubs identified by our approaches (high system density and participation coefficient) and 11 with focal lesions to two "control" hubs (high degree centrality). In support of our predictions, we found that damage to target locations produced severe and widespread cognitive deficits, whereas damage to control locations produced more circumscribed deficits. These findings support our interpretation of how neuroimaging-derived network measures relate to cognition and augment classic neuroanatomically based predictions about cognitive and behavioral outcomes after focal brain injury.
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Identifiers
- doi: 10.1073/pnas.1322173111 (Google search)
- issn: 10916490
- sgr: 84907587741
- scopus: 2-s2.0-84907587741
- pui: 600072232