University of Michigan
Ann Arbor, Michigan, 48109, United States
NCT Number: NCT03393390
The purpose of this study is to learn more about the functioning of particular types of regions of the brain, specifically, those related to externalizing disorders such as Attention Deficit Hyperactivity Disorder (ADHD), Oppositional Defiance Disorder (ODD), and Conduct Disorder (CD). Brain function of children and adolescents with externalizing disorders such as ADHD, ODD, and CD will be compared to the brain function of those without. Functional Magnetic Resonance Imaging (fMRI) will be used to monitor brain activity at work and at resting states.
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Notify Me6 year–18 year
All sexes
Observational
Ann Arbor, Michigan, 48109, United States
The goal of this research proposes to take a developmental neuroimaging approach to elucidating brain mechanisms that lead to distinct forms of impulsivity in youth with externalizing disorders, including attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and conduct disorder (CD). Roughly 12-15% of youth suffer from at least one of these disorders (many of them have more than one) and they go on to experience serious adverse outcomes over the course of their lifetimes including increased rates of substance abuse, violence and criminality, maladjustment, and suicide. The absence of a biological, and in particular a neurodevelopmental, understanding of the pathophysiology of distinct kinds of impulsivity has been a major barrier to improving clinical care for impulsive youth; it has hindered efforts at building better nosology, earlier and more reliable diagnosis, and more effective treatments.
The NIMH Research Domain Criteria (RDoC) Initiative encourages clinical scientists to no longer think in terms of single categorical diagnoses (whose boundaries may in fact be drawn incorrectly), but rather to identify disorder-spanning constructs. Inspired by the RDoC Initiative, our research aims to delineate the neural mechanisms of distinct forms of impulsivity in youth from a transdiagnostic perspective that spans the three main externalizing disorders, ADHD, CD, and ODD, as well as across subtypes of these disorders (e.g., ADHD inattentive, hyperactive/impulsive, and combined types). More specifically, the study aims to develop a new class of imaging-based biomarkers for specific forms of impulsivity-markers that are rooted in aberrant brain maturation patterns.
Developing neuroimaging markers of impulsivity could have a number of important clinical impacts. For example, these markers could provide a basis for more objective diagnosis, facilitate earlier diagnosis, catalyze the development of new treatments, and help to guide the selection of treatments.
For this study, 270 youth subjects will be recruited, 135 with at least one externalizing disorder and 135 matched controls, between the ages of 6-18 . All participants will receive the following: 1) a comprehensive clinical/neurological assessment to quantify impulsivity symptoms; and 2) an fMRI session (structural, diffusion tensor imaging, resting, and task). Three cohorts are recruited: childhood (6-9 years; n=90), early adolescence (10-13 years; n=90), and middle adolescence (14-18; n=90).
The main aim of the study is to use imaging results to generate normative maturational curves for each component in the brain's regulatory control architecture using a multi-level linear mixed effects model. Multivariate models that predict types of impulsivity based on component expression will then be constructed.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Subjects will meet with a clinician who will determine if they meet diagnostic criteria for an externalizing disorder.
Subjects will undergo an fMRI scan where images will be taken for observational purposes only, not as a means of diagnosis.
Time frame: Single fMRI session lasting no more than 2 hours
Resting state fMRI functional connectivity maps will be used to generate normative growth curves for each component in the brain's regulatory control architecture using a multi-level linear mixed effects model. Each individual's deviation from their expected growth (based on the normative growth chart) is calculated and is utilized to predict clinical outcome variables.
University of Michigan
Other
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