Atypical Resting-State Functional Connectivity of Intra/Inter-Sensory Networks Is Related to Symptom Severity in Young Boys With Autism Spectrum Disorder.

Autism spectrum disorder (ASD) has been reported to have altered brain connectivity patterns in sensory networks, assessed using resting-state functional magnetic imaging (rs-fMRI). However, the results have been inconsistent. Herein, we aimed to systematically explore the interaction between brain sensory networks in 3-7-year-old boys with ASD (N = 29) using independent component analysis (ICA). Participants were matched for age, head motion, and handedness in the MRI scanner. We estimated the between-group differences in spatial patterns of the sensory resting-state networks (RSNs). Subsequently, the time series of each RSN were extracted from each participant's preprocessed data and associated estimates of interaction strength between intra- and internetwork functional connectivity (FC) and symptom severity in children with ASD. The auditory network (AN), higher visual network (HVN), primary visual network (PVN), and sensorimotor network (SMN) were identified. Relative to TDs, individuals with ASD showed increased FC in the AN and SMN, respectively. Higher positive connectivity between the PVN and HVN in the ASD group was shown. The strength of such connections was associated with symptom severity. The current study might suggest that the abnormal connectivity patterns of the sensory network regions may underlie impaired higher-order multisensory integration in ASD children, and be associated with social impairments.

Reduced Hippocampal Volume and Its Relationship With Verbal Memory and Negative Symptoms in Treatment-Naive First-Episode Adolescent-Onset Schizophrenia.

Accumulating neuroimaging evidence has shown remarkable volume reductions in the hippocampi of patients with schizophrenia. However, the relationship among hippocampal morphometry, clinical symptoms, and cognitive impairments in schizophrenia is still unclear. In this study, high-resolution structural magnetic resonance imaging data were acquired in 36 patients with adolescent-onset schizophrenia (AOS, age range: 13-18 years) and 30 age-, gender-, and education-matched typically developing controls (TDCs). Hippocampal volume was assessed automatically through volumetric segmentation and measurement. After adjusting for total intracranial volume, we found reduced hippocampal volume in individuals with AOS compared with TDCs, and the hippocampal volume was positively correlated with verbal memory and negatively correlated with negative symptoms in AOS. In addition, mediation analysis revealed the indirect effect of hippocampal volume on negative symptoms via verbal memory impairment. When the negative symptoms were represented by 2 dimensions of deficits in emotional expression (EXP) and deficits in motivation and pleasure (MAP), the indirect effect was significant for EXP but not for MAP. Our findings provide further evidence of hippocampal volume reduction in AOS and highlight verbal memory impairment as a mediator to influence the relationship between hippocampal morphometry and negative symptoms, especially the EXP dimension of negative symptoms, in individuals with AOS.

Mapping Progressive Gray Matter Alterations in Early Childhood Autistic Brain.

Autism spectrum disorder is an early-onset neurodevelopmental condition. This study aimed to investigate the progressive structural alterations in the autistic brain during early childhood. Structural magnetic resonance imaging scans were examined in a cross-sectional sample of 67 autistic children and 63 demographically matched typically developing (TD) children, aged 2-7 years. Voxel-based morphometry and a general linear model were used to ascertain the effects of diagnosis, age, and a diagnosis-by-age interaction on the gray matter volume. Causal structural covariance network analysis was performed to map the interregional influences of brain structural alterations with increasing age. The autism group showed spatially distributed increases in gray matter volume when controlling for age-related effects, compared with TD children. A significant diagnosis-by-age interaction effect was observed in the fusiform face area (FFA, Fpeak = 13.57) and cerebellum/vermis (Fpeak = 12.73). Compared with TD children, the gray matter development of the FFA in autism displayed altered influences on that of the social brain network regions (false discovery rate corrected, P < 0.05). Our findings indicate the atypical neurodevelopment of the FFA in the autistic brain during early childhood and highlight altered developmental effects of this region on the social brain network.

Subcortical structural covariance in young children with autism spectrum disorder.

Abnormalities in the structure of subcortical regions are central to numerous behaviors affected by autism spectrum disorder (ASD), and these regions may undergo atypical coordinated neurodevelopment. However, relatively little is known about morphological correlations among subcortical structures in young children with ASD. In this study, using volumetric-based methodology and structural covariance approach, we investigated structural covariance of subcortical brain volume in 40 young children with ASD (<7.5 years old) and 38 age-, gender-, and handedness-matched typically developing (TD) children. Results showed that compared with TD children, children with ASD exhibited decreased structural covariation between the left and right cerebral hemispheres, specifically between the left and right thalami, right globus pallidus and left nucleus accumbens, and left globus pallidus and right nucleus accumbens. Compared with TD children, children with ASD exhibited increased structural covariation between adjacent regions, such as between the right globus pallidus and right putamen. Additionally, abnormalities in subcortical structural covariance can predict social communication and repetitive and stereotypic behavior in young children with ASD. Overall, these results suggest decreased long-range structural covariation and enhanced local covariation in subcortical structures in children with ASD, highlighting aberrant developmental coordination or synchronized maturation between subcortical regions that play crucial roles in social cognition and behavior in ASD.

Alterations of White Matter Microstructure in Subcortical Vascular Mild Cognitive Impairment with and without Depressive Symptoms.

BACKGROUND: Depressive symptoms were thought to increase the risk of vascular dementia. Previous studies reported widespread white matter damages in the subcortical vascular mild cognitive impairment (svMCI), but little is known about the mechanism of depressive symptoms in svMCI. OBJECTIVE: In the current study, we aim to explore the white matter microstructural alterations in svMCI with depressive symptoms, and their associations with clinical measurements. METHODS: Fifty-eight subjects including 18 svMCI with depression (svMCI+D), 17 svMCI without depression (svMCI-D), and 23 normal controls (NC) were included in the study. Voxel-based analyses were performed on fractional anisotropy (FA) and mean diffusivity (MD). RESULTS: Compared to NC, both svMCI groups showed decreased FA in the bilateral insula and the left precentral gyrus, and increased MD in the cerebellum. Compared to svMCI-D, svMCI+D showed increased FA in left precentral gyrus. Moreover, svMCI+D showed significant correlation between the increased MD in the cerebellum and the Hamilton Depression Rating Scale (HAMD) scores. CONCLUSION: Our findings of white matter alterations might be associated with executive function and memory performance in the svMCI patients. Moreover, the structural alterations in the cerebellum might underlie the mechanism of depressive symptoms in svMCI patients.

Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with considerable neuroanatomical heterogeneity. Thus, how and to what extent the brains of individuals with ASD differ from each other is still unclear. In this study, brain structural MRI data from 356 right-handed, male subjects with ASD and 403 right-handed male healthy controls were selected from the Autism Brain Image Data Exchange database (age range 5-35 years old). Voxel-based morphometry preprocessing steps were conducted to compute the gray matter volume maps for each subject. Individual neuroanatomical difference patterns for each ASD individual were calculated. A data-driven clustering method was next utilized to stratify individuals with ASD into several subtypes. Whole-brain functional connectivity and clinical severity were compared among individuals within the ASD subtypes identified. A searchlight analysis was applied to determine whether subtyping ASD could improve the classification accuracy between ASD and healthy controls. Three ASD subtypes with distinct neuroanatomical difference patterns were revealed. Different degrees of clinical severity and atypical brain functional connectivity patterns were observed among these three subtypes. By dividing ASD into three subtypes, the classification accuracy between subjects of two out of the three subtypes and healthy controls was improved. The current study confirms that ASD is not a disorder with a uniform neuroanatomical signature. Understanding neuroanatomical heterogeneity in ASD could help to explain divergent patterns of clinical severity and outcomes.