Abnormal connectivity is likely a key component of the neural basis of ASD. Resting state fcMRI is an emerging technique for studying brain circuitry, which can be used with individuals who cannot actively perform cognitive tasks in the scanner. Studies utilizing fcMRI techniques in high functioning ASD have identified abnormal connectivity between brain regions during task-free “resting states”. However, as fcMRI studies have not been reported in low functioning individuals with ASD, it is unknown whether functional connectivity abnormalities are generalizable across the autism spectrum.
1) identify fcMRI abnormalities in lower functioning (LFA) and higher functioning (HFA) adolescents with ASD and idiopathic developmental delay (DD) 2) evaluate the relationship between functional connectivity and clinical severity.
Three task-free fcMRI scans with physiological monitoring were collected on all participants. A subset of cognitively impaired participants with ASD (i.e., the LFA group) and all participants with DD were scanned under propofol sedation (Amundsen et al . 2005). Study participants are part of a larger longitudinal cohort first diagnosed at age 3-4 years. Data collection is ongoing. Valid data has been obtained on 41 participants (HFA = 7; LFA = 14; Control = 16; DD = 4). Participants scanned while awake (i.e., without propofol) were instructed to close their eyes, relax and let their mind wander. Participant scanned under sedation were not provided specific instructions. Scans were analyzed using standard preprocessing steps. In addition, physiological correction was applied using Retroicor and a low-pass filter removed frequencies above .1 Hz. Resting state networks were identified using MELODIC’s model-free independent component analysis with multi-session temporal concatenation. Tests for between-group differences (HFA v Control; LFA v DD; HFA v LFA) and the correlational analyses were conducted using FSL’s dual regression. Statistical significance was determined using threshold-free cluster enhancement corrected for multiple comparisons (p < .05).
Over 30 components were identified in each group; only a-priori defined resting-state networks will be presented: default mode network (DMN), dorsal attention network (DAN), right ventral attention network (R-VAN), left ventral attention network (L-VAN), and salience network (SN; HFA & control only). Contrasts not specifically reported are null findings. For LFA v DD (both sedated), the LFA had significantly greater connectivity in the R-VAN and reduced connectivity in the DAN. For HFA v control, the HFA showed significantly increased connectivity in the SN and decreased connectivity in the DMN and the L-VAN. In general, HFA and LFA had similar patterns for all networks, albeit with decreased connectivity in the LFA group. Lastly, in the HFA group, stronger connectivity in the SN was correlated to increased ADOS severity. Specific anatomical loci will be further described.
Large-scale brain system abnormalities are observable in both higher and lower functioning individuals with ASD. All resting state networks except the SN were observable under propofol-induced anesthesia. The observation of lower connectivity with LFA within the context of sedation effects and in relation to the DD group will be discussed. Abnormal connectivity will be discussed within the context of symptomotology.
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