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(2007) A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. NeuroImage, 37: 90-101. Resting State Functional Connectivity in Autism Spectrum Disorders: An fMRI Study Gagan Joshi MD, John Gabrieli PhD, Joseph Biederman MD, Rachel Goldin BA, Gretchen Reynolds BA, & Susan Whitfield-Gabrieli, PhD Pediatric Psychopharmacology Clinical and Research Program at Massachusetts General Hospital & Massachusetts Institute of Technology, Boston MA Background Methods Rs-Fc profile in autism exhibits bilateral increase in functional connectivity of amygdala to the regions of the brain that are implicated in autism. This altered Rs-Fc profile in autism may serve as a neuromarker for autism. Future studies with larger sample size are warranted. Phenotyping ASD participants were recruited from the referrals to a specialized ambulatory program for autism spectrum disorders and to a child & adolescent psychiatry ambulatory care clinic at a university-affiliated hospital. ASD participants fulfilled DSM-IV-TR PDD diagnoses of ASD as established by clinical diagnostic interview. In the age, sex, and IQ matched healthy controls (N=16) significant ASD traits and diagnosis was ruled out by the Social communication questionnaire and clinical psychiatric interview respectively. Full- scale IQ of the participants was assessed with the Vocabulary and Matrix Reasoning subtests of the Wechsler Abbreviated Scale of Intelligence 9 . Imaging Data Acquisition: A 6-minute resting state scan was acquired while subjects fixated on a cross (T2 weighted gradient echo TR/TE/Flip = 6000ms/30ms/90°, 67 contiguous interleaved oblique slices, voxel size: 2.0 X 2.0 X 2.0). The sequence had prospective acquisition correction (PACE) for head motion 10 . Data Analysis: Resting-state data were analyzed using a seed driven approach with in-house, custom software (Whitfield-Gabrieli; http://www.nitrc.org/projects/conn/). Data were realigned, coregistered, normalized, and spatially smoothed with 6-mm kernel. Physiological and other spurious sources of noise were estimated using the aCompcor method 11 , and removed together with movement-related covariates. The residual BOLD time-series were band-pass filtered over a low-frequency window of interest (0.009Hz<f<0.08Hz). Correlation maps were produced by extracting the residual BOLD time course from bilateral anatomically defined Amygdala (WFU_Pickatlas) seed regions, and computing Pearson’s correlation coefficients between that time course and the time course of all other voxels. Correlation coefficients were then converted to normally distributed scores using Fischer’s transform to allow for second-level General Linear Model analyses. Between group differences with the amygdala seed regions were calculated. Autism Spectrum Disorders (ASDs) refers to a group of neurodevelopmental disorders characterized by varying degrees of impairment in social interaction, communication, and ridged/ repetitive patterns of behavior 1 . There is strong evidence that autism is associated with abnormal brain development, but the nature of the aberrant neurodevelopment is not well characterized 2 . Converging lines of evidence indicate that autism is a disorder of brain connectivity 3 . Task related abnormalities in functional connectivity (Fc) are observed within regions of the brain in autism 4 . The resting state (Rs) networks are intrinsic, spontaneous, robust and reliable, low- frequency fluctuations in the fMRI BOLD exhibit specific networks of the human brain in the absence of overt task. The brain regions that are active during the Rs constitute the brain’s default mode network (DMN) 5 . Weaker coherence of Fc from posterior to anterior subsystems in Rs DMNs are reported in autism, although the findings are not consistent probably due to differences in study populations and designs 6,7 . Amygdala plays a crucial role in social cognition. Functional hyperactivation of amygdala on fMRI is noted on face processing tasks in individuals with ASD 8 . We hypothesize that individuals with ASDs will exhibit atypical profile of Rs-Fc of amygdala. In individuals with ASD relative to Controls: • bilaterally increased Fc of amygdala to other regions of the brain. • bilateral amygdalar increased Fc to insula, orbital frontal, and medial orbital frontal regions of the brain. This study examines the integrity of the resting state functional connectivity of amygdala in individuals with ASD. Bilateral Amygdalar Resting State Functional Hyperconnectivity Associated with ASD Anatomical Location of Bilateral Amygdala Seed Regions Characteristics of the ASD Participants Functional Connectivity with Amygdala Functional connectivity with amygdala significantly: positive negative (anticorrelation) Objective Controls ASD ASD > Controls Results ASD Subjects (N) 17 Gender (Male) 17 (100%) Race (Caucasian) 16 (94%) Handedness (Right) 16 (94%) Age (Years) 20.4 ±3.5 (Range: 16-28) IQ (Full scale) 109.5 ±11.8 (Range: 82-130) Medication Naïve 05 (29%) ASD Subtypes Autistic Disorder 10 (59%) Asperger's Disorder 04 (23%) PDD-NOS 03 (18%) Insula Orbital Frontal Medial Orbital Frontal Conclusions References Supported by: The Pediatric Psychopharmacology Council Fund; The Norma Fine Pediatric Psychopharmacology Fellowship Fund McGovern Institute at MIT; PHS grant DA023427; Poitras Center for Affective Disorders Research; Ellison Medial Foundation Disclosures: None relevant to this presentation View publication stats View publication stats