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.
Patients with ADHD and substance use disorders present with varying combinations of attention dysfunction and appetitive dysfunction. There is a critical need to better classify these patients in terms of single or joint presence of attention and appetitive dysfunction and to better tailor pharmacotherapy to addressing one or both deficits. The proposed study will use neuroimaging to neurally and pharmacologically dissociate brain circuits underlying attention and appetitive control. This will facilitate more refined biologically-based diagnosis and treatment selection. It will also advance research aimed at specifically targeting problems with appetitive control.
| Chang, Soo-Eun; Angstadt, Michael; Chow, Ho Ming et al. (2018) Anomalous network architecture of the resting brain in children who stutter. J Fluency Disord 55:46-67 |
| Kessler, Daniel; Angstadt, Mike; Sripada, Chandra S (2017) Reevaluating ""cluster failure"" in fMRI using nonparametric control of the false discovery rate. Proc Natl Acad Sci U S A 114:E3372-E3373 |
| Kessler, Daniel; Angstadt, Michael; Sripada, Chandra (2016) Growth Charting of Brain Connectivity Networks and the Identification of Attention Impairment in Youth. JAMA Psychiatry 73:481-9 |
| Sripada, Chandra S; Kessler, Daniel; Angstadt, Mike (2014) Lag in maturation of the brain's intrinsic functional architecture in attention-deficit/hyperactivity disorder. Proc Natl Acad Sci U S A 111:14259-64 |
| Sripada, Chandra; Kessler, Daniel; Fang, Yu et al. (2014) Disrupted network architecture of the resting brain in attention-deficit/hyperactivity disorder. Hum Brain Mapp 35:4693-705 |
| Sripada, Chandra; Kessler, Daniel; Jonides, John (2014) Methylphenidate blocks effort-induced depletion of regulatory control in healthy volunteers. Psychol Sci 25:1227-34 |
| Watanabe, Takanori; Scott, Clayton D; Kessler, Daniel et al. (2014) SCALABLE FUSED LASSO SVM FOR CONNECTOME-BASED DISEASE PREDICTION. Proc IEEE Int Conf Acoust Speech Signal Process 2014:5989-5993 |
| Sripada, Chandra; Angstadt, Michael; Kessler, Daniel et al. (2014) Volitional regulation of emotions produces distributed alterations in connectivity between visual, attention control, and default networks. Neuroimage 89:110-21 |
| Swain, James E; Sripada, Chandra; Swain, John D (2014) Using big data to map the network organization of the brain. Behav Brain Sci 37:101-2 |
| Sripada, Chandra; Swain, John D; Ho, S Shaun et al. (2014) Automatic goals and conscious regulation in social cognitive affective neuroscience. Behav Brain Sci 37:156-7 |
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