Prefrontal gray matter volume predicts metacognitive accuracy following traumatic brain injury

Emily C. Grossner, Rachel A. Bernier, Einat K. Brenner, Kathy S. Chiou, Frank G. Hillary

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Objective: To examine metacognitive ability (MC) following moderate to severe traumatic brain injury (TBI) using an empirical assessment approach and to determine the relationship between alterations in gray matter volume (GMV) and MC. Method: A sample of 62 individuals (TBI n = 34; healthy control [HC] n = 28) were included in the study. Neuroimaging and neuropsychological data were collected for all participants during the same visit. MC was quantified using an approach borrowed from signal detection theory (Type II area under the receiver operating characteristic curve calculation) to evaluate judgments during a modified version of the 3rd edition of the Wechsler Adult Intelligence Scale's Matrix Reasoning subtest where half of the items were presented randomly and half were presented in the order of increasing difficulty. Retrospective confidence judgments were collected on an item-by-item basis. Brain volumetric analyses were conducted using FreeSurfer software. Results: Analyses of the modified Matrix Reasoning task data demonstrated that HCs significantly outperformed TBIs (ordered: d = .63; random: d = .58). There was a significant difference between groups for MC for the randomly presented stimuli (d = .54) but not the ordered stimuli. There was an association between GMV and MC in the TBI group between the right orbital region and MC (R 2 = .11). In the HC group, there were associations between the left posterior (R 2 = .17), left orbital (R 2 = .29), and left dorsolateral (R 2 = .21) regions and MC. Conclusions: These results are consistent with those of previous research on MC in the cognitive neurosciences, but this study demonstrates that injury may moderate the regional contributions to MC.

Original languageEnglish (US)
Pages (from-to)484-494
Number of pages11
JournalNeuropsychology
Volume32
Issue number4
DOIs
StatePublished - May 2018

All Science Journal Classification (ASJC) codes

  • Neuropsychology and Physiological Psychology

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