This study aims to conduct the first investigation of the neurobiological underpinnings of social communicative impairments, i.e., autistic traits (AT), in children with ADHD and ASD. AT, a key feature of autism spectrum disorder (ASD), occurs in 20-30% of children with ADHD. These children incur relatively elevated school failure and poor global functioning, highlighting the clinical significance of AT in children with ADHD (ADHD+AT).
We aim to advance our understanding of AT across ADHD and ASD, applying state of the art brain imaging methodology as a first step in efforts to foster advances in treatment. Hypotheses emanate from the literature and our preliminary data.
We aim to test that intrinsic functional connectivity (iFC) between the fusiform face area (FFA) and rostral anterior cingulate cortex (ACC) underpins AT across ASD and ADHD diagnoses. Specifically, we hypothesize: H1a: FFA-ACC iFC is reduced in children with ASD and in those with ADHD+AT, relative to children with ADHD but no AT (ADHD-AT); H1b: Across groups, weaker FFA-ACC iFC is associated with more severe AT. H2a: FFA-ACC iFC is positively associated with accuracy in emotion face recognition, and H2b: FFA-ACC iFC is significantly more related to accuracy on an emotion task than on a control non-emotion task. In addition, we will explore 1) similarities between R-fMRI and task-fMRI connectivity; 2) brain-behavior relationships beyond the FFA-ACC circuit, deriving whole-brain voxelwise R- fMRI metrics and iFC between regions-of-interest representing the `social brain'; 3) behavioral relations with structural connectivity indexed by fractional anisotroy, focusing on the inferior frontal occipital fasciculus, and other relevant tracts; and 4) data-drive approaches combining available clinical and imaging data to identify homogenous neurophenotypes regardless of diagnosis. Methods. We anticipate obtaining complete datasets from at least 70 children per group - ADHD+AT, ADHD-AT, and ASD (total N=210), group-matched for age, sex, full IQ, handedness and socioeconomic status. Assessments. A partial list includes: Autism Diagnostic Observation Schedule-2 (administered blind to all other clinical data), K-SADS and ADI-R interviews, Parent and Teacher rating scales. The emotion face recognition task, and the holistic configural face processing task will assess emotion face processing; a Go-No Go task, and motion tracking will measure attention and motion. Brain-behavior analyses will rely on resting state fMRI (R-fMRI), structural, diffusion tensor imaging and task- fMRI (matching face task). Significance. The study informs the neurobiology of a shared phenotype, and will bring the field closer to a neural stratification of individuals with AT a critical step for developing neuroscientifically-informed treatments. Additionally, we will share unidentified data with National Database for Autism Research yearly to accelerate scientific progress.
A substantial proportion of children with attention-deficit/hyperactivity disorder have autistic traits for which clinicians have no effective treatmens. We propose to use advanced brain imaging methods to identify circuit(s) responsible for difficulties in recognizing facial expressions and relating socially to others. If we are correct, ur results would support the development and improvement of new treatments.
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|Aoki, Yuta; Yoncheva, Yuliya N; Chen, Bosi et al. (2017) Association of White Matter Structure With Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder. JAMA Psychiatry 74:1120-1128|
|Solomon, Marjorie; Di Martino, Adriana (2017) Increasing Traction for Discovery: The Research Domain Criteria Framework and Neurodevelopmental Disorders. Biol Psychiatry Cogn Neurosci Neuroimaging 2:458-460|