Emerging evidence has associated autism spectrum disorder (ASD) with static functional connectivity abnormalities between multiple brain regions. However, the temporal dynamics of intra-and interhemispheric functional connectivity patterns remain unknown in ASD. Resting-state functional magnetic resonance imaging data were analyzed for 105 ASD and 102 demographically matched typically developing control (TC) children (age range: 7-12 years) available from the Autism Brain Imaging Data Exchange database. Whole-brain functional connectivity was decomposed into ipsilateral and contralateral functional connectivity, and sliding-window analysis was utilized to capture the intra-and interhemispheric dynamic functional connectivity density (dFCD) patterns. The temporal variability of the functional connectivity dynamics was further quantified using the standard deviation (SD) of intra-and interhemispheric dFCD across time. Finally, a support vector regression model was constructed to assess the relationship between abnormal dFCD variance and autism symptom severity. Both intra-and interhemispheric comparisons showed increased dFCD variability in the anterior cingulate cortex/medial prefrontal cortex and decreased variability in the fusiform gyrus/inferior temporal gyrus in autistic children compared with TC children. Autistic children additionally showed lower intrahemispheric dFCD variability in sensorimotor regions including the precentral/postcentral gyrus. Moreover, aberrant temporal variability of the contralateral dFCD predicted the severity of social communication impairments in autistic children.These findings demonstrate altered temporal dynamics of the intra-and interhemispheric functional connectivity in brain regions incorporating social brain network of ASD, and highlight the potential role of abnormal interhemispheric communication dynamics in neural substrates underlying impaired social processing in ASD.
K E Y W O R D Sautism spectrum disorder, dynamic functional connectivity, interhemisphere, intrahemisphere, resting-state functional magnetic resonance imaging
Objective
The insula consists of functionally diverse subdivisions, and each division plays different roles in schizophrenia neuropathology. The current study aimed to investigate the abnormal patterns of dynamic functional connectivity (dFC) of insular subdivisions in schizophrenia and the effect of antipsychotics on these connections.
Methods
Longitudinal study of the dFC of insular subdivisions was conducted in 42 treatment-naive first-episode patients with schizophrenia at baseline and after 8 weeks of risperidone treatment based on resting-state functional magnetic resonance image (fMRI).
Results
At baseline, patients showed decreased dFC variance (less variable) between the insular subdivisions and the precuneus, supplementary motor area and temporal cortex, as well as increased dFC variance (more variable) between the insular subdivisions and parietal cortex, compared with healthy controls. After treatment, the dFC variance of the abnormal connections were normalized, which was accompanied by a significant improvement in positive symptoms.
Conclusions
Our findings highlighted the abnormal patterns of fluctuating connectivity of insular subdivision circuits in schizophrenia and suggested that these abnormalities may be modified after antipsychotic treatment.
Accumulating neuroimaging evidence shows that age estimation obtained from brain connectomics reflects the level of brain maturation along with neural development. It is well known that autism spectrum disorder (ASD) alters neurodevelopmental trajectories of brain connectomics, but the precise relationship between chronological age (ChA) and brain connectome age (BCA) during development in ASD has not been addressed. This study uses neuroimaging data collected from 50 individuals with ASD and 47 age- and gender-matched typically developing controls (TDCs; age range: 5–18 years). Both functional and structural connectomics were assessed using resting-state functional magnetic resonance imaging and diffusion tensor imaging data from the Autism Brain Imaging Data Exchange repository. For each participant, BCA was estimated from structure–function connectomics through linear support vector regression. We found that BCA matched well with ChA in TDC children and adolescents, but not in ASD. In particular, our findings revealed that individuals with ASD exhibited accelerated brain maturation in youth, followed by a delay of brain development starting at preadolescence. Our results highlight the critical role of BCA in understanding aberrant developmental trajectories in ASD and provide the new insights into the pathophysiological mechanisms of this disorder.
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