Brain network theory can predict whether neuropsychological outcomes will differ from clinical expectations

David E. Warren, Natalie L. Denburg, Jonathan D. Power, Joel Bruss, Eric J. Waldron, Haoxin Sun, Steve E. Petersen, Daniel Tranel

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Objective: Theories of brain-network organization based on neuroimaging data have burgeoned in recent years, but the predictive power of such theories for cognition and behavior has only rarely been examined. Here, predictions from clinical neuropsychologists about the cognitive profiles of patients with focal brain lesions were used to evaluate a brain-network theory (Warren et al., 2014). Method: Neuropsychologists made predictions regarding the neuropsychological profiles of a neurological patient sample (N = 30) based on lesion location. The neuropsychologists then rated the congruence of their predictions with observed neuropsychological outcomes, in regard to the "severity" of neuropsychological deficits and the "focality" of neuropsychological deficits. Based on the network theory, two types of lesion locations were identified: "target" locations (putative hubs in a brain-wide network) and "control" locations (hypothesized to play limited roles in network function). Results: We found that patients with lesions of target locations (N = 19) had deficits of greater than expected severity that were more widespread than expected, whereas patients with lesions of control locations (N = 11) showed milder, circumscribed deficits that were more congruent with expectations. Conclusions: The findings for the target brain locations suggest that prevailing views of brain-behavior relationships may be sharpened and refined by integrating recently proposed network-oriented perspectives.

Original languageEnglish (US)
Pages (from-to)40-52
Number of pages13
JournalArchives of Clinical Neuropsychology
Volume32
Issue number1
DOIs
StatePublished - Feb 1 2017

Keywords

  • Brain
  • Cognition
  • Lesion
  • Network
  • Neuropsychology
  • Profile agreement

PubMed: MeSH publication types

  • Journal Article

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