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Background: Autism and attention-deficit/hyperactivity disorder (ADHD) are comorbid neurodevelopmental disorders that share common and distinct neurobiological mechanisms, with disrupted brain connectivity patterns being a hallmark feature of both conditions. It is challenging to gain a mechanistic understanding of the underlying disorder, because brain connectivity changes in autism and ADHD are heterogeneous. Objectives: The present resting state functional MRI (rs-fMRI) study focuses on investigating the shared and distinct resting state-fMRI connectivity (rsFC) patterns in autistic and ADHD adults using multi-voxel pattern analysis (MVPA). By identifying spatial patterns of fMRI activity across a given time course, MVPA is an innovative and powerful method for generating seed regions of interest (ROIs) without a priori hypotheses. Methods: We performed a data-driven, whole-brain, connectome-wide MVPA on rs-fMRI data collected from 15 autistic, 19 ADHD, and 15 neurotypical (NT) young adults. Results: MVPA identified cerebellar vermis 9, precuneus, and the right cerebellum VI for autistic versus NT, right inferior frontal gyrus and vermis 9 for ADHD versus NT, and right dorsolateral prefrontal cortex for autistic versus ADHD as significant clusters. Post hoc seed-to-voxel analyses using these clusters as seed ROIs were performed for further characterization of group differences. The cerebellum VI, vermis, and precuneus in autistic adults, and the vermis and frontal regions in ADHD showed different connectivity patterns in comparison with NT. Conclusions: The study characterizes the rsFC profile of cerebellum with key cortical areas in autism and ADHD, and it emphasizes the importance of studying the role of the functional connectivity of the cerebellum in neurodevelopmental disorders.

Background: Multivoxel pattern analysis (MVPA) has emerged as a powerful unbiased approach for generating seed regions of interest (ROIs) in resting-state functional connectivity (RSFC) analysis in a data-driven manner. Studies exploring RSFC in multiple sclerosis have produced diverse and often incongruent results. Objectives: The aim of the present study was to investigate RSFC differences between people with relapsing-remitting multiple sclerosis (RRMS) and healthy controls (HC). Methods: We performed a whole-brain connectome-wide MVPA in 50 RRMS patients with expanded disability status scale ≤4 and 50 age and gender-matched HCs. Results: Significant group differences were noted in RSFC in three clusters distributed in the following regions: anterior cingulate gyrus, right middle frontal gyrus, and frontal medial cortex. Whole-brain seed-to-voxel RSFC characterization of these clusters as seed ROIs revealed network-specific abnormalities, specifically in the anterior cingulate cortex and the default mode network. Conclusions: The network-wide RSFC abnormalities we report agree with the previous findings in RRMS, the cognitive and clinical implications of which are discussed herein. Impact statement This study investigated resting-state functional connectivity (RSFC) in relapsing-remitting multiple sclerosis (RRMS) people with mild disability (expanded disability status scale ≤4). Whole-brain connectome-wide multivoxel pattern analysis was used for assessing RSFC. Compared with healthy controls, we were able to identify three regions of interest for significant differences in connectivity patterns, which were then extracted as a mask for whole-brain seed-to-voxel analysis. A reduced connectivity was noted in the RRMS group, particularly in the anterior cingulate cortex and the default mode network regions, providing insights into the RSFC abnormalities in RRMS.

Background: The combination of structural and functional analyses is a biologically valid approach that offers methodological advantages in autism spectrum disorder (ASD) neuroimaging science. The paucity of studies combining these methods constitutes an important knowledge gap. In this study, we investigate structural abnormalities and their associated functional differences in a developmentally homogeneous ASD cohort. Methods: Whole-brain voxel-based morphometry (VBM) analyses were performed on 28 ASD participants and 38 age-matched typically developing healthy controls (HC) to derive gray matter (GM) volume differences. The anatomically relevant clusters identified by VBM served as seed regions of interest (ROI) for resting-state functional-connectivity (RsFc) analysis. Results: Whole-brain VBM analyses revealed significant right lateralized GM volume abnormality in the ASD group, with lower GM volumes in cerebellar lobules VIIb/VIIIa (cluster 1) and significantly higher GM volumes in posterior middle/superior temporal gyri (Brodmann area [BA] 21/22, cluster 2) compared with HC. Whole-brain RsFc analysis in high-functioning ASD (HF-ASD) revealed significant hypoconnectivity of the cerebellar VBM cluster with the right cerebral cortical regions of superior parietal lobule (BA 7) and occipital pole (BA 19) (overlapping with dorsal attention and visual networks, respectively). Cerebral cortical VBM cluster (cluster 2) revealed significant hypoconnectivity in HF-ASD with other task-positive cerebral cortical including the left lateral prefrontal cortex (frontoparietal network) and some aspects of the insula (ventral attention network) and ectopic positive connectivity (lack of anticorrelations) with posterior cingulate cortex and medial prefrontal cortex (default mode network). Conclusions: The cerebro-cerebellar intrinsic functional dysconnectivity based on the whole-brain VBM-derived ROIs may advance our understanding of the compensatory mechanisms associated with ASD and offer cerebellum as a potential target for diagnostic, predictive, prognostic, and therapeutic interventions in ASD. Our findings also provide additional support indicating that functional abnormalities as indexed by RsFc exist in ASD, and highlight that there is likely a relationship between structural and functional abnormalities in this disorder. Impact statement Our findings indicate that functional differences as indexed by resting-state functional connectivity exist in autism spectrum disorder (ASD), and highlight that there is likely a relationship between structural and functional abnormalities in this disorder. Future developments in neuroimaging research should continue investigating structural and associated functional differences in ASD, and in this way complement the behavioral characterization of this disorder, potentially improving diagnosis, prognosis, and prediction.

Cerebellar abnormalities are commonly reported in autism spectrum disorder (ASD). Dentate nuclei (DNs) are key structures in the anatomical circuits linking the cerebellum to the extracerebellum. Previous resting-state functional connectivity (RsFc) analyses reported DN abnormalities in high-functioning ASD (HF-ASD). This study examined the RsFc of the DN in young adults with HF-ASD compared with healthy controls (HCs) with the aim to expand upon previous findings of DNs in a dataset using advanced, imaging acquisition methods that optimize spatiotemporal resolution and statistical power. Additional seed-to-voxel analyses were carried out using motor and nonmotor DN coordinates reported in previous studies as seeds. We report abnormal dentato-cerebral and dentato-cerebellar functional connectivity in ASD. Our results expand and, in part, replicate previous descriptions of DN RsFc abnormalities in this disorder and reveal correlations between DN-cerebral RsFc and ASD symptom severity.

The use of multichannel array head coils in functional and structural magnetic resonance imaging (MRI) provides increased signal-to-noise ratio (SNR), higher sensitivity, and parallel imaging capabilities. However, their benefits remain to be systematically explored in the context of resting-state functional connectivity MRI (fcMRI). In this study, we compare signal detectability within and between commercially available multichannel brain coils, a 32-Channel (32Ch), and a 12-Channel (12Ch) at 3T, in a high-resolution regime to accurately map resting-state networks. We investigate whether the 32Ch coil can extract and map fcMRI more efficiently and robustly than the 12Ch coil using seed-based and graph-theory-based analyses. Our findings demonstrate that although the 12Ch coil can be used to reveal resting-state connectivity maps, the 32Ch coil provides increased detailed functional connectivity maps (using seed-based analysis) as well as increased global and local efficiency, and cost (using graph-theory-based analysis), in a number of widely reported resting-state networks. The exploration of subcortical networks, which are scarcely reported due to limitations in spatial-resolution and coil sensitivity, also proved beneficial with the 32Ch coil. Further, comparisons regarding the data acquisition time required to successfully map these networks indicated that scan time can be significantly reduced by 50% when a coil with increased number of channels (i.e., 32Ch) is used. Switching to multichannel arrays in resting-state fcMRI could, therefore, provide both detailed functional connectivity maps and acquisition time reductions, which could further benefit imaging special subject populations, such as patients or pediatrics who have less tolerance in lengthy imaging sessions.