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
Schizophrenia has been conceptualized as a disorder arising from structurally pathological alterations to white‐matter fibers in the brain. However, few studies have focused on white‐matter functional changes in schizophrenia. Considering that converging evidence suggests that white‐matter resting state functional MRI (rsfMRI) signals can effectively depict neuronal activity and psychopathological status, this study examined white‐matter network‐level interactions in antipsychotic‐naive first‐episode schizophrenia (FES) to facilitate the interpretation of the psychiatric pathological mechanisms in schizophrenia. We recruited 42 FES patients (FESs) and 38 healthy controls (HCs), all of whom underwent rsfMRI. We identified 11 white‐matter functional networks, which could be further classified into deep, middle, and superficial layers of networks. We then examined network‐level interactions among these 11 white‐matter functional networks using coefficient Granger causality analysis. We employed group comparisons on the influences among 11 networks using network‐based statistic. Excitatory influences from the middle superior corona radiate network to the superficial orbitofrontal and deep networks were disrupted in FESs compared with HCs. Additionally, an extra failure of suppression within superficial networks (including the frontoparietal network, temporofrontal network, and the orbitofrontal network) was observed in FESs. We additionally recruited an independent cohort (13 FESs and 13 HCs) from another center to examine the replicability of our findings across centers. Similar replication results further verified the white‐matter functional network interaction model of schizophrenia. The novel findings of impaired interactions among white‐matter functional networks in schizophrenia indicate that the pathophysiology of schizophrenia may also lie in white‐matter functional abnormalities.
Aberrant topological organization of brain connectomes underlies pathological mechanisms in major depressive disorder (MDD). However, accumulating evidence has only focused on functional organization in brain gray-matter, ignoring functional information in white-matter (WM) that has been confirmed to have reliable and stable topological organizations. The present study aimed to characterize the functional pattern disruptions of MDD from a new perspective—WM functional connectome topological organization. A case-control, cross-sectional resting-state functional magnetic resonance imaging study was conducted on both discovery [91 unmedicated MDD patients, and 225 healthy controls (HCs)], and replication samples (34 unmedicated MDD patients, and 25 HCs). The WM functional networks were constructed in 128 anatomical regions, and their global topological properties (e.g., small-worldness) were analyzed using graph theory-based approaches. At the system-level, ubiquitous small-worldness architecture and local information-processing capacity were detectable in unmedicated MDD patients but were less salient than in HCs, implying a shift toward randomization in MDD WM functional connectomes. Consistent results were replicated in an independent sample. For clinical applications, small-world topology of WM functional connectome showed a predictive effect on disease severity (Hamilton Depression Rating Scale) in discovery sample (r = 0.34, p = 0.001). Furthermore, the topologically-based classification model could be generalized to discriminate MDD patients from HCs in replication sample (accuracy, 76%; sensitivity, 74%; specificity, 80%). Our results highlight a reproducible topologically shifted WM functional connectome structure and provide possible clinical applications involving an optimal small-world topology as a potential neuromarker for the classification and prediction of MDD patients.
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.
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