Project Summary

Francisco Xavier Castellanos, M.D. (Distinguished Investigator 2005) of New York University, seeks to determine whether slow neuronal physiological fluctuations are related to the symptoms of inattention intrinsic to Attention Deficit/Hyperactivity Disorder (ADHD). Recent research has demonstrated the pivotal discovery that slow neuronal oscillations in a rat model are specifically sensitive to dopaminergic drugs, including low dose psychostimulants, such as Ritalin (methylphenidate), which are widely used to treat ADHD. Dr. Castellanos seeks to find empirical evidence that fluctuations in cerebral hemodynamic measures, heart-rate variability, and indirect but quantifiable measures of attentional efficiency are tightly linked, and that they are comparably modulated by psychostimulants. He has begun to find behavioral evidence that attentional efficiency fluctuates more in children with ADHD than in controls at the predicted slow frequencies. These oscillations can be observed by closely tracking behavior (e.g., by measuring fluctuations in reaction time (RT)), by recording regional cerebral blood flow with optical imaging or fMRI, or by analyzing beat-to-beat cardiac variability. In secondary data analyses, he observed that these irregular slow oscillations in RT were decreased by Ritalin in children with ADHD. Dr. Castellanos believes that a dopaminergic deficiency in the ability to appropriately modulate these very low frequency fluctuations in neuronal activity represents one of the fundamental causes of behavioral symptoms such as difficulty sustaining attention, forgetfulness, disorganization, and careless errors which characterize the inattention dimension of ADHD. The next steps in validating such a potential "endophenotype" are (1) to simultaneously collect behavioral (response time and accuracy), cardiovascular (heart rate variability), and cerebrovascular (fluctuations in oxygenated hemoglobin concentration) data from individuals with well-characterized ADHD and age- and sex-matched control subjects with rigorous attention to temporal parameters; and (2) to collaborate with another researcher to conduct linear and non-linear time-series analyses using his innovative data-reduction algorithms. Confirming this hypothesis would allow neurobiological stratification for genetic studies, provide the basis for early identification of at-risk children, motivate the development of novel treatments and prevention strategies, and provide an objective physiologically-based benchmark to determine their efficacy.

Program Area: ATTENTION-DEFICIT & DISRUPTIVE BEHAVIOR DISORDER\Attention Deficit Hyperactivity Disorder (ADHD)

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