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

ABSTRACT: Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof of concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n=71), incarcerated youth with low psychopathic traits (n=72), and non-incarcera

SUBMITTER: Steele VR 

PROVIDER: S-EPMC4903946 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature