Examining working memory task acquisition in a disrupted neural network

Frank G. Hillary, John D. Medaglia, Kathleen Gates, Peter C. Molenaar, Julia Slocomb, Alyssa Peechatka, David C. Good

Research output: Contribution to journalArticle

59 Scopus citations

Abstract

There is mounting literature that examines brain activation during tasks of working memory in individuals with neurological disorders such as traumatic brain injury. These studies represent a foundation for understanding the functional brain changes that occur after moderate and severe traumatic brain injury, but the focus on topographical brain-'activation' differences ignores potential alterations in how nodes communicate within a distributed neural network. The present study makes use of the most recently developed connectivity modelling (extended-unified structural equation model) to examine performance during a well-established working-memory task (the n-back) in individuals sustaining moderate and severe traumatic brain injury. The goal is to use the findings observed in topographical activation analysis as the basis for second-level effective connectivity modelling. Findings reveal important between-group differences in within-hemisphere connectivity during task acquisition, with the control sample demonstrating rapid within-left hemisphere connectivity increases and the traumatic brain injury sample demonstrating consistently elevated within-right hemisphere connectivity. These findings also point to important maturational effects from 'early' to 'late' during task performance, including diminished right prefrontal cortex involvement and an anterior to posterior shift in connectivity with increased task exposure. We anticipate that this approach to functional imaging data analysis represents an important future direction for understanding how neural plasticity is expressed in brain disorders.

Original languageEnglish (US)
Pages (from-to)1555-1570
Number of pages16
JournalBrain
Volume134
Issue number5
DOIs
StatePublished - May 2011

All Science Journal Classification (ASJC) codes

  • Clinical Neurology

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