Pharmacological Dissociation of Control Circuits in ADHD and Alcohol Dependence

University Of Michigan At Ann Arbor, Ann Arbor MI

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Abstract

DESCRIPTION (provided by applicant): Attention-deficit hyperactivity disorder (ADHD) is a serious and prevalent disorder, and roughly 50% of adults with ADHD have comorbid substance use disorders (SUDS). Influential models of ADHD posit distinct 'cold' executive deficits including inattention and distractibility and 'hot' executive deficits including excess reward- seeking and inability to delay gratification, with the latter especially prominent in ADHD patients who go on to develop comorbid SUDS. Though deficits in prefrontal regulation are clearly implicated in ADHD and SUDS, prefrontal regulation is not a unitary phenomenon. Distinct prefrontal circuits implement attention control, regulation of attention and suppression of distractions, and appetitive control, regulation of motivation and reward seeking. Additionally, stimulants that enhance dopamine and norepinephrine neurotransmission are known to enhance attention control, while naltrexone, an antagonist of opioid receptors, has been shown to modulate motivation and reward seeking. Thus potentially dissociable forms of prefrontal regulatory failure may be associated with distinct clusters of symptoms in ADHD and SUDS, and these circuits may exhibit different patterns of pharmacological modulation. To investigate these hypotheses, we will use fMRI to investigate healthy controls and adults with ADHD, alcohol dependence, and ADHD comorbid with alcohol dependence in response to methylphenidate, naltrexone, and placebo challenge. We will employ well- validated tasks that probe attention control and appetitive control circuits. We will dissociate attention and appetitive control circuits using ROI-based activation analyses, functional connectivity analyses, and multivariate pattern classification methods. This project advances the goals of delineating the neural basis of dysfunction in ADHD and SUDS, developing biologically-based classification in these disorders, and spurring the development of improved, more tailored treatments.