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In addition to the well-established somatotopy in the pre- and post-central gyrus, there is now strong evidence that somatotopic organization is evident across other regions in the sensorimotor network. This raises several experimental questions: To what extent is activity in the sensorimotor network effector-dependent and effector-independent? How important is the sensorimotor cortex when predicting the motor effector? Is there redundancy in the distributed somatotopically organized network such that removing one region has little impact on classification accuracy? To answer these questions, we developed a novel experimental approach. fMRI data were collected while human subjects performed a precisely controlled force generation task separately with their hand, foot, and mouth. We used a simple linear iterative clustering (SLIC) algorithm to segment whole-brain beta coefficient maps to build an adaptive brain parcellation and then classified effectors using extreme gradient boosting (XGBoost) based on parcellations at various spatial resolutions. This allowed us to understand how data-driven adaptive brain parcellation granularity altered classification accuracy. Results revealed effector-dependent activity in regions of the post-central gyrus, precentral gyrus, and paracentral lobule. SMA, regions of the inferior and superior parietal lobule, and cerebellum each contained effector-dependent and effector-independent representations. Machine learning analyses showed that increasing the spatial resolution of the data-driven model increased classification accuracy, which reached 94% with 1755 supervoxels. Our SLIC-based supervoxel parcellation outperformed classification analyses using established brain templates and random simulations. Occlusion experiments further demonstrated redundancy across the sensorimotor network when classifying effectors. Our observations extend our understanding of effector-dependent and effector-independent organization within the human brain and provide new insight into the functional neuroanatomy required to predict the motor effector used in a motor control task.

Highlights • Volumetric abnormalities detected in the perirhinal, entorhinal memory regions. • Volumetric abnormalities detected in key additional brain regions. • Extensive clinical validation of previous Down Syndrome findings included. • Perirhinal and entorhinal involvement in Alzheimer’s etiology hypothesized., Down syndrome (DS) is a genetic disorder caused by the presence of an extra full or partial copy of chromosome 21 and characterized by intellectual disability. We hypothesize that performing a retrospective analysis of 73 magnetic resonance imaging (MRI) examinations of participants with DS (aged 0 to 22 years) and comparing them to a large cohort of 993 brain MRI examinations of neurotypical participants (aged 0 to 32 years), will assist in better understanding what brain differences may explain phenotypic developmental features in DS, as well as to provide valuable confirmation of prospective literature findings clinically. Measurements for both absolute volumes and volumes corrected as a percentage of estimated total intracranial volume (%ETIV) were extracted from each examination. Our results presented novel findings such as volume increases (%ETIV) in the perirhinal cortex, entorhinal cortex, choroid plexus, and Brodmann’s areas (BA) 3a, 3b, and 44, as well as volume decreases (%ETIV) in the white matter of the cuneus, the paracentral lobule, the postcentral gyrus, and the supramarginal gyrus. We also confirmed volumetric brain abnormalities previously discussed in the literature. Findings suggest the presence of volumetric brain abnormalities in DS that can be detected clinically with MRI.

This study investigated the topological characteristics of brain functional networks in chronic insomnia disorder (CID) patients. The resting-state functional magnetic resonance imaging and graph theory analysis method were applied to investigate the brain functional connectome patterns among 45 CID patients and 32 healthy controls. The brain functional connectome was constructed by thresholding partial correlation matrices of 90 brain regions from an automated anatomical labeling atlas. The topologic properties of brain functional connectomes at both global and nodal levels were tested. The CID patients had decreased number of module (p = .014) and hierarchy (p = .038), and increased assortativity (p = .035). Furthermore, some brain regions located in the default mode network, dorsal attention network, and sensory-motor network in these patients showed altered nodal centralities. Within these areas, the node betweenness of right central paracentral lobule had positive correlation with the Pittsburgh Sleep Quality Index score (R = 0.319, p = .039). The results imply that functional disruptions of CID patients may be related to disruptions in global and regional topological organization of the brain functional connectome, and provide new and important insights to understand the pathophysiological mechanisms of CID., Highlights • Chronic insomnia disorder (CID) patients had disrupted global topological properties. • Many brain regions of CID patients showed altered nodal centralities involving three different resting networks. • Functional disruption of right central paracentral lobule may be a target for therapeutic intervention in pediatric CID. • The disruption of topological organization might be explain the mechanism/reason of functional disruptions of CID.

This study aimed to investigate the effects of lesion side and degree of motor recovery on gray matter volume (GMV) difference relative to healthy controls in right-handed subcortical stroke. Structural MRI data were collected in 97 patients with chronic subcortical ischemic stroke and 79 healthy controls. Voxel-wise GMV analysis was used to investigate the effects of lesion side and degree of motor recovery on GMV difference in right-handed chronic subcortical stroke patients. Compared with healthy controls, right-lesion patients demonstrated GMV increase (P, Highlights • There is a lesion-side effect on gray matter volume in subcortical stroke patients. • Right-sided stroke patients show more extensive GMV changes than left-sided ones. • GMV increase in the SMA may facilitate to motor recovery after stroke.