To date, most studies on autism spectrum disorder (ASD) have focused on specific age ranges, while the mechanisms underlying the entire developmental process of autism patients remain unclear. The aim of this study was to investigate the alterations in brain function in autistic individuals at different developmental stages by resting-state functional MRI (rs-fMRI). We obtained rs-fMRI data from 173 ASD and 178 typical development (TD) individuals in Autism Brain Imaging Data Exchange, spanning child, adolescent, and adult groups. We characterized local brain activity using the amplitude of low-frequency fluctuations (ALFFs), regional homogeneity (ReHo), dynamic ALFF (dALFF), and dynamic ReHo (dReHo) metrics. Pearson correlation analyses were conducted on relationships between Autism Diagnostic Observation Schedule scores and activity measures in abnormal brain regions. We found abnormal ALFF values in the medial and lateral orbitofrontal gyrus and right insula cortex with ASD compared with the TD group. In addition, compared with adolescents with ASD, we found that adults with ASD exhibited an increase in dReHo values in the posterior lateral frontal lobe. We also found that changes in ALFF were associated with the severity of autism. We found abnormal activity in multiple brain regions in individuals with autism and correlated it with clinical characteristics. Our results may provide some help for further exploring the age-related neurobiological mechanisms of ASD patients.

Background/Objectives: Schizophrenia is a severe psychiatric disorder characterized by deficits in perception and advanced cognitive functions. Prior studies have reported abnormal lateralization in cortical morphology and functional connectivity in schizophrenia. However, it remains unclear whether schizophrenia affects hemispheric asymmetry in the hierarchical organization of functional connectome. Methods: Here, we apply a gradient mapping framework to the hemispheric functional connectome to estimate the first three gradients, which characterize unimodal-to-transmodal, visual-to-somatomotor, and somatomotor/default mode-to-multiple demand hierarchy axes. We then assess between-group differences in intra- and inter-hemispheric asymmetries of these three functional gradients. Results: We find that, compared to healthy controls, patients with schizophrenia exhibit significantly altered hemispheric asymmetry in functional gradient across multiple networks, including the dorsal attention, ventral attention, visual, and control networks. Region-level analyses further reveal that patients with schizophrenia show significantly abnormal hemispheric gradient asymmetries in several cortical regions in the dorsal prefrontal gyrus, medial superior frontal gyrus, and somatomotor areas. Lastly, we find that hemispheric asymmetries in functional gradients can differentiate between patients and healthy controls and predict the severity of positive symptoms in schizophrenia. Conclusions: Collectively, these findings suggest that schizophrenia is associated with altered hemispheric asymmetry in functional hierarchy, providing novel perspectives for understanding the atypical brain lateralization in schizophrenia.

Background/Objectives: Cocaine use disorder (CUD) poses a worldwide health challenge, with severe consequences for brain function. However, the phase dynamics underlying CUD and the transitions between CUD and health remain poorly understood. Methods: Here, we used resting-state functional magnetic resonance imaging (fMRI) data from 43 CUD patients and 45 healthy controls (HCT). We performed empirical analysis to identify phase-coherence states and compared their probabilities of occurrence between conditions. To further explore the underlying mechanism, we employed computational modeling to replicate the observed state probabilities for each condition. These generated whole-brain models enabled us to simulate external perturbations and identify optimal brain regions mediating transitions between HCT and CUD. Results: We found that CUD was associated with a reduced occurrence probability of the state dominated by the default mode network (DMN). Perturbing the nucleus accumbens, thalamus, and specific regions within the default mode, limbic and frontoparietal networks drives transitions from HCT to CUD, while perturbing the hippocampus and specific regions within the visual, dorsal attention, and DMN facilitates a return from CUD to HCT. Conclusions: This study revealed altered DMN-related dynamics in CUD from the phase perspective and provides potential regions critical for state transitions. The results contribute to understanding the pathogenesis of CUD and the development of therapeutic stimulation strategies.