Common and specific cognitive deficits in schizophrenia: Relationships to function

Julia M. Sheffield, James M. Gold, Milton E. Strauss, Cameron S. Carter, Angus W. MacDonald, J. Daniel Ragland, Steven M. Silverstein, Deanna M. Barch

    Research output: Contribution to journalArticlepeer-review

    32 Scopus citations

    Abstract

    The goals of the present study were to assess the interrelationships among tasks from the MATRICS and CNTRACS batteries, to determine the degree to which tasks from each battery capture unique variance in cognitive dysfunction in schizophrenia, and to determine the ability of tasks from each battery to predict functional outcome. Subjects were 104 schizophrenia patients and 132 healthy control subjects recruited as part of the CNTRACS initiative. All subjects completed four CNTRACS tasks and two tasks from the MATRICS battery: Brief Assessment of Cognition in Schizophrenia Symbol Coding and the Hopkins Verbal Learning Test. Functional outcome was also assessed in the schizophrenia subjects. In both the patient and control groups, we found significant intercorrelations between all higher order cognitive tasks (episodic memory, goal maintenance, processing speed, verbal learning) but minimal relationships with the visual task. For almost all tasks, scores were significantly related to measures of functional outcome, with higher associations between CNTRACS tasks and performance-based measures of function and between one of the MATRICS tasks and self-reported functioning, relative to the other functioning measures. After regressing out variance shared by other tasks, we continued to observe group differences in performance among task residuals, particularly for measures of episodic memory from both batteries, although these residuals did not correlate as robustly with functional outcome as raw test scores. These findings suggest that there exists both shared and specific variance across cognitive tasks related to cognitive and functional impairments in schizophrenia and that measures derived from cognitive neuroscience can predict functional capacity and status in schizophrenia.

    Original languageEnglish (US)
    Pages (from-to)161-174
    Number of pages14
    JournalCognitive, Affective and Behavioral Neuroscience
    Volume14
    Issue number1
    DOIs
    StatePublished - Mar 2014

    Keywords

    • Cognitive control
    • Schizophrenia

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