Structural and Functional Connectivity of Frontostriatal and Frontoparietal Networks as Endophenotypes of ADHD

The sample (n=240, 8 groups, ages 10-20, IQ \> 80) consists of (1) 30 ADHD probands with DAT1 variants, (2) 30 same-sex unaffected siblings, (3) 30 ADHD probands without DAT1 gene variants, who were age-, sex-, and IQ-matched to Group 1, (4) 30 same-sex unaffected siblings of Group 3, (5) 30 age-, sex- and IQ-matched TD controls for each of 4 groups (Groups 1, 2, 3 \& 4). The assessments include psychiatric interviews, self-administered questionnaires (CBCL and SNAP-IV for ADHD and behavioral problems; the SAICA for school and social function), neurocognitive assessments (WISC-III-R or WAIS-III for intelligence, Conner's CPT for sustained attention, inhibition, and vigilance, CANTAB for executive functions and visuo-spatial memory), and MRI assessments (Structural MRI, DSI and rsfMRI). Brain Imaging: (1) Structural MRI (T1- and T2-weighted images), DSI and rsfMRI data will be acquired on a 3T MRI system with a 32-channel head coil. DSI employs a pulsed-gradient spin-echo echo planar imaging (EPI) sequence by applying 102 diffusion gradient vectors and the maximum diffusion sensitivity = 4000 s/mm2, and rsfMRI is a 6-minute scan using a gradient-echo EPI sequence with 180 volumes. (2) Structural connectivity analysis: DSI tractography will be performed using in-house software (DSI studio, http://dsi-studio.labsolver.org/Home). Tracts-of-interest in the frontostriatal circuit and the frontoparietal circuit will be identified, and tract-specific analysis will be used to analyze the microstructural integrity along individual tract bundles. (3) Functional connectivity analysis: SPM8 program and in-house MATLAB codes will be used for analyses of rsfMRI data. Region-of-interests (ROIs) will be placed in the nodes of the corresponding circuits according to an anatomical template (WFU\_PickAtlas 3.03). These ROIs will serve for tract determination in the tractography procedure and for seed regions in which BOLD signals are extracted for regression analysis among nodes.