Abnormal brain structure in youth who commit homicide

Abstract

BackgroundViolence that leads to homicide results in an extreme financial and emotional burden on society. Juveniles who commit homicide are often tried in adult court and typically spend the majority of their lives in prison. Despite the enormous costs associated with homicidal behavior, there have been no serious neuroscientific studies examining youth who commit homicide.MethodsHere we use neuroimaging and voxel-based morphometry to examine brain gray matter in incarcerated male adolescents who committed homicide (n = 20) compared with incarcerated offenders who did not commit homicide (n = 135). Two additional control groups were used to understand further the nature of gray matter differences: incarcerated offenders who did not commit homicide matched on important demographic and psychometric variables (n = 20) and healthy participants from the community (n = 21).ResultsCompared with incarcerated adolescents who did not commit homicide (n = 135), incarcerated homicide offenders had reduced gray matter volumes in the medial and lateral temporal lobes, including the hippocampus and posterior insula. Feature selection and support vector machine learning classified offenders into the homicide and non-homicide groups with 81% overall accuracy.ConclusionsOur results indicate that brain structural differences may help identify those at the highest risk for committing serious violent offenses.

The Development of Severe and Chronic Violence Among Youth: The Role of Psychopathic Traits and Reward Processing

“…And indeed, youth with these traits appear to be at risk to commit some of the most severe acts of violence. Cope and colleagues [60] found that incarcerated adolescents who had committed murder scored significantly higher in psychopathic traits than incarcerated adolescents who had not murdered. In this sample, the CU features of psychopathy appeared to most strongly distinguish youth who had committed homicide, evincing a moderately large effect size ( d = 0.87) [60].…”

“…Cope and colleagues [60] found that incarcerated adolescents who had committed murder scored significantly higher in psychopathic traits than incarcerated adolescents who had not murdered. In this sample, the CU features of psychopathy appeared to most strongly distinguish youth who had committed homicide, evincing a moderately large effect size ( d = 0.87) [60]. 4 Agar [57] found that among youth homicide offenders, psychopathy was associated with a higher degree of instrumentality, sexual violence, and gratuitous violence (i.e., “excessive violence beyond the level necessary to accomplish the homicide and/or caused the victim unnecessary pain and suffering”).…”

“…Moreover, this imbalance in reinforcement may predispose these youth to a virulent cycle wherein violence becomes intrinsically rewarding and propagates increasingly severe and frequent acts of such violence [7, 50, 57, 60]. Yet, this deleterious conditioning cycle may actually proffer the strategies to prevent their violence.…”

“… 4 Cope et al [60] reported Pearson effect sizes ( r = .40). We converted to Cohen’s d using the formula: $d=\surd \frac{4r^2}{1-r^2}$.…”

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders

“…A growing body of literature supports this paralimbic hypothesis suggesting individuals with elevated psychopathic traits exhibit aberrant structure (specifically reduced grey matter volume and density) and function in many regions: anterior cingulate cortex (ACC), bilateral amygdala, bilateral hippocampus, medial orbitofrontal cortex (mOFC), bilateral orbitofrontal cortex (OFC), bilateral parahippocampus, posterior cingulate cortex (PCC), & bilateral temporal pole (Figure 1). Adults and youth with elevated psychopathic traits exhibit similar paralimbic neural dysfunction (Blair, 2006; Budhani and Blair, 2005; Cope et al, 2014; Ermer et al, 2012; Ermer et al, 2013; Harenski et al, 2014; Kiehl, 2006; Lockwood et al, 2013; Marsh et al, 2008; Motzkin et al, 2011; Raine et al, 2003). Deficits appear to be specific to the orbitofrontal cortex (Budhani and Blair, 2005; Cope et al, 2014; Ermer et al, 2013), insula (Lockwood et al, 2013), amygdala (Harenski et al, 2014; Marsh et al, 2008), PCC (Ermer et al, 2013), parahippocampal gyrus (Ermer et al, 2013), and ACC (Cope et al, 2014; Ermer et al, 2013; Marsh et al, 2008).…”