Reward deficit models of addiction posit weaknesses in reward sensitivity to be promotive of substance dependence, while the externalizing spectrum model views substance problems as arising in large part from a general disinhibitory liability. The current study sought to integrate these perspectives by testing for separate and interactive associations of disinhibition and reward dysfunction with interview-assessed substance use disorders (SUDs). Community and college adults (N = 199) completed a scale measure of trait disinhibition and performed a gambling-feedback task yielding a neural index of reward sensitivity, the 'Reward Positivity' (RewP). Disinhibition and blunted RewP independently predicted SUDs, and also operated synergistically, such that participants - in particular, men - with high levels of disinhibition together with blunted RewP exhibited especially severe substance problems. Though limited by its cross-sectional design, this work provides new information about the interplay of disinhibition, reward processing, and gender in SUDs and suggests important directions for future research.

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical structural model of psychological symptoms formulated to improve the reliability and validity of clinical assessment. Neurobiology can inform assessments of early risk and intervention strategies, and the HiTOP model has greater potential to interface with neurobiological measures than traditional categorical diagnoses given its enhanced reliability. However, one complication is that observed biological correlates of clinical symptoms can reflect various factors, ranging from dispositional risk to consequences of psychopathology. In this paper, we argue that the HiTOP model provides an optimized framework for conducting research on the biological correlates of psychopathology from an ontogenetic perspective that distinguishes among indicators of liability, current symptoms, and consequences of illness. Through this approach, neurobiological research can contribute more effectively to identifying individuals at high dispositional risk, indexing treatment-related gains, and monitoring the consequences of mental illness, consistent with the aims of the HiTOP framework.
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