2022
DOI: 10.1016/j.nicl.2022.103238
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Hemodynamic activity in the limbic system predicts reoffending in women

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Cited by 4 publications
(6 citation statements)
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“…First, our results highlight the importance of considering multiple approaches to estimating resting-state alterations on a local (i.e., ALFFs and intra-network connectivity) and global (inter-network connectivity) scale, as these complimentary neurobiological measures are likely to account for alternative types of variance in explaining behavioral traits (see Thijssen and Kiehl, 2017 ). Second, our results suggest that altered resting-state functional connectivities associated with psychopathic traits present similarly in incarcerated adolescent girls and incarcerated adult women and adolescent boys (Allen et al, 2022b ), potentially identifying stable markers for work seeking to predict subsequent antisocial actions utilizing brain-based metrics (Aharoni et al, 2013 , 2022 ; Allen et al, 2022a ). More specifically, psychopathy related paralimbic and default mode network alterations in the form of increased low-frequency ALFFs, decreased mid-frequency ALFFs, and increased high-frequency ALFFs were identified across adolescent and adult samples, suggesting that these neurobiological/trait correlates may be stable across development (Thijssen and Kiehl, 2017 ; Allen et al, 2022b ).…”
Section: Discussionmentioning
confidence: 78%
See 1 more Smart Citation
“…First, our results highlight the importance of considering multiple approaches to estimating resting-state alterations on a local (i.e., ALFFs and intra-network connectivity) and global (inter-network connectivity) scale, as these complimentary neurobiological measures are likely to account for alternative types of variance in explaining behavioral traits (see Thijssen and Kiehl, 2017 ). Second, our results suggest that altered resting-state functional connectivities associated with psychopathic traits present similarly in incarcerated adolescent girls and incarcerated adult women and adolescent boys (Allen et al, 2022b ), potentially identifying stable markers for work seeking to predict subsequent antisocial actions utilizing brain-based metrics (Aharoni et al, 2013 , 2022 ; Allen et al, 2022a ). More specifically, psychopathy related paralimbic and default mode network alterations in the form of increased low-frequency ALFFs, decreased mid-frequency ALFFs, and increased high-frequency ALFFs were identified across adolescent and adult samples, suggesting that these neurobiological/trait correlates may be stable across development (Thijssen and Kiehl, 2017 ; Allen et al, 2022b ).…”
Section: Discussionmentioning
confidence: 78%
“…The construct of psychopathy is characterized as an array of traits, including callousness, impulsivity, poor decision-making, and a lack of empathy. These traits, alone, and in combination, have been found to be associated with poor interpersonal relationship success and treatment outcomes, and increased rates of substance use and rearrest (Taylor and Lang, 2006 ; Reidy et al, 2013 ; Mooney et al, 2019 ; Sohn et al, 2020 ; Allen et al, 2022a ; Edwards et al, 2023 ). The societal cost of psychopathy to taxpayers is estimated to be nearly $460 billion per year, with $56.7 billion being accounted for by juveniles (Anderson, 1999 ; Caldwell et al, 2006 ; Kiehl and Hoffman, 2011 ; Cope et al, 2014 ; Reidy and Holland, 2018 ).…”
Section: Introductionmentioning
confidence: 99%
“…This recidivism data was examined continuously (i.e., time [in months] to first felony re-offense following release outcomes) via multivariate Cox proportional-hazard regressions. Consistent with other studies from our research group [68,69], time at risk was defined as the time period between an individual's release date and their felony re-offense date or the end of the follow up window (August 31, 2019) for those who did not commit a felony offense. In participants with all available data (i.e., n = 221 offenders), ~ 74% of our participants (i.e., n = 164) committed a felony offense following their release from the juvenile correctional facility.…”
Section: Data Analysesmentioning
confidence: 96%
“…In an often-cited study, Kent Kiehl's group showed that it was possible to predict rearrest of offenders using fMRI (Aharoni et al, 2013;Allen et al, 2022). The offenders performed a go/no-go impulse control task while their brain was being scanned with fMRI.…”
Section: Predictionmentioning
confidence: 99%