Author ORCID Identifier
https://orcid.org/0000-0002-5843-5336
Date of Award
8-10-2021
Degree Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Neuroscience Institute
First Advisor
Eyal Aharoni
Second Advisor
Eddy Nahmias
Third Advisor
Jessica Turner
Fourth Advisor
Isabelle Buard
Abstract
Despite decades of research examining the brain’s contributions to the propensity for antisocial behavior, this process is still poorly understood, owing in part to the highly multivariate relationship between the brain, behavioral phenotypes, and the dynamic environmental contexts in which they operate. An important criterion for evaluating the strength of a given explanation is the degree to which it makes accurate predictions. Prior research has demonstrated that hemodynamic activity related to error-monitoring in the dorsal anterior cingulate cortex (dACC) (Aharoni et al., 2013, 2014) improved predictions of rearrest in a sample of criminal offenders. Yet, it remains unclear how generalizable these results are and whether these effects are task specific.
This dissertation project uses hypothesis-driven approaches to probe the generalizability of the previously demonstrated predictive utility of limbic activity for rearrest, as well as establish and test novel task-based and resting state measures for the same purpose. The first analysis used a large sample (n = 442) of criminal offenders to establish new limbic regions of interest in order to increase the predictive accuracy of a model of reoffense risk developed in a previously published male (n = 95) inmate sample. The second analysis tested the predictive utility of the resting state functional connectivity between these limbic regions and demonstrated robust resting state & multimodal models for the prediction of rearrest in a subset of the same male (n = 91) inmate sample. The final analysis tested the out-of-sample generalizability of the original error-monitoring model tested in Aharoni et al., 2013/2014 in a large sample of male (n = 290) and female (n = 248) offenders. This analysis provides modest support for the predictive utility of error-monitoring activity in the dACC for predictions of rearrest for felonies in women and violent felonies in men, replicating aspects of the previous studies. Overall, these results reinforce and extend research on limbic predictors of recurrent, impulsive antisocial behavior. Implications for clinical and forensic risk assessment are discussed.
DOI
https://doi.org/10.57709/23745980
Recommended Citation
Allen, Corey, "The Neuroprediction of Recidivism: Validation and Extension of the Error-Monitoring Model." Dissertation, Georgia State University, 2021.
doi: https://doi.org/10.57709/23745980
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