Project Summary Increasing numbers of children are diagnosed or treated for Attention Deficit Hyperactivity Disorder (ADHD), yet its diagnosis and treatment remain controversial, specific etiologies remain uncertain, and clinical prediction is poor. The research and training activities proposed in this K23 application advance the PI's long- term career goal of establishing an independent, translational program of research characterizing individual differences in the psychological, cognitive, and neurobiological processes contributing to ADHD. The proposed training emphasizes skill development in: 1) advanced analysis approaches for electrophysiological data; 2) integrating these analytical approaches in the context of cognitive neuroscience models of attention and working memory for translational work; 3) learning conceptual and practical tools related to identification of developmentally-sensitive, multivariate refined phenotypes; and 4) additional training in research ethics and professional development. Skills are developed through didactic instruction, hands-on experience in data collection and analysis, and intensive mentorship related to the closely-linked research and training aims. Consensus is emerging that effective measurement of pathophysiological mechanisms is essential for improvement of both pharmacological and non-pharmacological treatments of ADHD. Neurocognitive measures, broadly defined, are seen as particularly promising for understanding mechanisms of ADHD and creating alternative phenotypes. They have also been central to efforts at novel treatment development, for example via computerized cognitive training of working memory and electroencephalogram (EEG)-based neurofeedback. However, data on efficacy of these new treatments remain unconvincing. This is likely, at least in part, because the mechanisms of cognitive control being targeted are not adequately specified or contextualized. In order to move the field forward, at least three issues need to be resolved: 1) the appropriate fractionation of cognitive control deficits needs to be clarified and trial-by-trial neurophysiological predictors of performance need to be identified; 2) differences in how control processes are implemented across emotional contexts need to be characterized; and 3) cognitive, emotional, and neurophysiological predictors need to be related to clinical outcomes. EEG measures, including resting and evoked oscillatory activity and evoked response potentials (ERPs) are ideal for these purposes because they provide millisecond-level quantification of the neurophysiological response associated with these psychological processes and thus can help clarify the neurophysiological bases of impairments. The proposed study applies EEG/ERP methodology to resolve questions related to cognitive and emotional control deficits in a sample of 150 children with and without ADHD, ages 12-16 years, recruited from a larger longitudinal study. Aim 1 tests hypotheses stemming from the adaptive gain theory that ADHD-related deficits in working memory and performance variability result from a common problem in attention optimization and identifies trial-by-trial neurophysiological predictors of performance. Aim 2 integrates the attention dysregulation described in Aim 1 with two novel ADHD emotion-based types previously identified by the PI. Finally, in Aim 3, cognitive and EEG/ERP markers are incorporated in a recursive decision-making algorithm to identify multivariate refined phenotype profiles for each emotion-based ADHD type. The potential impact of this work over time would be to help sharpen psychiatric nosology and provide improved clinical diagnosis, characterization, and prediction. Ultimately, there is the potential to move psychology and psychiatry toward personalized approaches to treatment and spur novel treatment development.
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NIH ExPorter