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Multimodal imaging measures predict rearrest
Open Access Articles
  • Vaughn R. Steele, Mind Research Network and Lovelace Biomedical and Environmental Research Institute
  • Eric D. Claus, RAND Corporation
  • Eyal Aharoni, RAND Corporation
  • Gina M. Vincent, University of Massachusetts Medical School
  • Vince D. Calhoun, University of New Mexico
  • Kent A. Kiehl, University of New Mexico
UMMS Affiliation
Department of Psychiatry, Systems and Psychosocial Advances Research Center
Publication Date
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Rearrest has been predicted by hemodynamic activity in the anterior cingulate cortex (ACC) during error-processing (Aharoni et al., 2013). Here, we evaluate the predictive power after adding an additional imaging modality in a subsample of 45 incarcerated males from Aharoni et al. (2013). Event-related potentials (ERPs) and hemodynamic activity were collected during a Go/NoGo response inhibition task. Neural measures of error-processing were obtained from the ACC and two ERP components, the error-related negativity (ERN/Ne) and the error positivity (Pe). Measures from the Pe and ACC differentiated individuals who were and were not subsequently rearrested. Cox regression, logistic regression, and support vector machine (SVM) neuroprediction models were calculated. Each of these models proved successful in predicting rearrest and SVM provided the strongest results. Multimodal neuroprediction SVM models with out of sample cross-validating accurately predicted rearrest (83.33%). Offenders with increased Pe amplitude and decreased ACC activation, suggesting abnormal error-processing, were at greatest risk of rearrest.

  • error-processing,
  • event-related potentials,
  • functional magnetic resonance imaging,
  • neuroprediction,
  • recidivism
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Copyright © 2015 Steele, Claus, Aharoni, Vincent, Calhoun and Kiehl. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

DOI of Published Version
Front Hum Neurosci. 2015 Aug 3;9:425. doi: 10.3389/fnhum.2015.00425. eCollection 2015. Link to article on publisher's site
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Link to Article in PubMed
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Creative Commons License
Creative Commons Attribution 4.0
Citation Information
Vaughn R. Steele, Eric D. Claus, Eyal Aharoni, Gina M. Vincent, et al.. "Multimodal imaging measures predict rearrest" Vol. 9 (2015) ISSN: 1662-5161 (Linking)
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