Cerebellar gray matter and lobular volumes correlate with core autism symptoms

AbstractNeuroanatomical differences in the cerebellum are among the most consistent findings in autism spectrum disorder (ASD), but little is known about the relationship between cerebellar dysfunction and core ASD symptoms. The newly-emerging existence of cerebellar sensorimotor and cognitive subregions provides a new framework for interpreting the functional significance of cerebellar findings in ASD. Here we use two complementary analyses — whole-brain voxel-based morphometry (VBM) and the SUIT cerebellar atlas — to investigate cerebellar regional gray matter (GM) and volumetric lobular measurements in 35 children with ASD and 35 typically-developing (TD) children (mean age 10.4 ± 1.6 years; range 8–13 years). To examine the relationships between cerebellar structure and core ASD symptoms, correlations were calculated between scores on the Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview (ADI) and the VBM and volumetric data. Both VBM and the SUIT analyses revealed reduced GM in ASD children in cerebellar lobule VII (Crus I/II). The degree of regional and lobular gray matter reductions in different cerebellar subregions correlated with the severity of symptoms in social interaction, communication, and repetitive behaviors. Structural differences and behavioral correlations converged on right cerebellar Crus I/II, a region which shows structural and functional connectivity with fronto-parietal and default mode networks. These results emphasize the importance of the location within the cerebellum to the potential functional impact of structural differences in ASD, and suggest that GM differences in cerebellar right Crus I/II are associated with the core ASD profile

Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images

[EN] The human cerebellum plays an essential role in motor control, is involved in cognitive function (i.e., attention, working memory, and language), and helps to regulate emotional responses. Quantitative in-vivo assessment of the cerebellum is important in the study of several neurological diseases including cerebellar ataxia, autism, and schizophrenia. Different structural subdivisions of the cerebellum have been shown to correlate with differing pathologies. To further understand these pathologies, it is helpful to automatically parcellate the cerebellum at the highest fidelity possible. In this paper, we coordinated with colleagues around the world to evaluate automated cerebellum parcellation algorithms on two clinical cohorts showing that the cerebellum can be parcellated to a high accuracy by newer methods. We characterize these various methods at four hierarchical levels: coarse (i.e., whole cerebellum and gross structures), lobe, subdivisions of the vermis, and the lobules. Due to the number of labels, the hierarchy of labels, the number of algorithms, and the two cohorts, we have restricted our analyses to the Dice measure of overlap. Under these conditions, machine learning based methods provide a collection of strategies that are efficient and deliver parcellations of a high standard across both cohorts, surpassing previous work in the area. In conjunction with the rank-sum computation, we identified an overall winning method.The data collection and labeling of the cerebellum was supported in part by the NIH/NINDS grant R01 NS056307 (PI: J.L. Prince) and NIH/NIMH grants R01 MH078160 & R01 MH085328 (PI: S.H. Mostofsky). PMT is supported in part by the NIH/NIBIB grant U54 EB020403. CERES2 development was supported by grant UPV2016-0099 from the Universitat Politecnica de Valencia (PI: J.V. Manjon); the French National Research Agency through the Investments for the future Program IdEx Bordeaux (ANR-10-IDEX-03-02, HL-MRI Project; PI: P. Coupe) and Cluster of excellence CPU and TRAIL (HR-DTI ANR-10-LABX-57; PI: P. Coupe). Support for the development of LiviaNET was provided by the National Science and Engineering Research Council of Canada (NSERC), discovery grant program, and by the ETS Research Chair on Artificial Intelligence in Medical Imaging. The authors wish to acknowledge the invaluable contributions offered by Dr. George Fein (Dept. of Medicine and Psychology, University of Hawaii) in preparing this manuscript.Carass, A.; Cuzzocreo, JL.; Han, S.; Hernandez-Castillo, CR.; Rasser, PE.; Ganz, M.; Beliveau, V.... (2018). Comparing fully automated state-of-the-art cerebellum parcellation from magnetic resonance images. NeuroImage. 183:150-172. https://doi.org/10.1016/j.neuroimage.2018.08.003S15017218

Reduced Basal Ganglia Tissue Iron Concentration in School-Age Children with Attention Deficit/Hyperactivity Disorder is Localized to Limbic Circuitry

Supporting Dat

Reduced dominant motor cortex inhibition is associated with increased tic severity in children with Tourette syndrome

Aim: Compare transcranial magnetic stimulation (TMS)-derived measures of motor cortex (M1) physiology between children with and without Tourette syndrome (TS) and dimensionally analyze TMS measures with TS-related tic and urge symptom severity. Method: 60 8-12-year-old children (30 TS, 3 girls, 10 years, 10 months [1 year, 3 months]; 30 typically developing children - TDC, 7 girls, 10 years, 7 months [1 year, 3 months]) participated. Within TS, 15 children (1 girl, 10 years, 11 months [1 year, 3 months]) had comorbid Attention-Deficit/Hyperactivity Disorder (ADHD), rated with the Conners 3rd Edition and the parent-reported ADHD rating scale. Tic severity was rated with the Yale Global Tic Severity Scale (YGTSS), and premonitory urge severity with the Individualized Premonitory Urge for Tics Scale (I-PUTS) for children with TS. M1 short interval cortical inhibition (SICI) and intracortical facilitation (ICF) were compared between diagnostic groups and, within TS, correlated with symptom severity using repeated measures regressions. Results: Accounting for ADHD, we found no difference in SICI or ICF in TS vs. TDC (p>.1). Within TS, reduced M1 SICI predicted greater total (p=.012) and global (p=.002) tic severity. There were no associations with urge severity (p>.5). Interpretation: Reduced M1 SICI is robustly associated with increased tic, but not urge, severity

Distinct frontal lobe morphology in girls and boys with ADHD

Objective: This study investigated whether frontal lobe cortical morphology differs for boys and girls with ADHD (ages 8–12 years) in comparison to typically developing (TD) peers. Method: Participants included 226 children between the ages of 8–12 including 93 children with ADHD (29 girls) and 133 TD children (42 girls) for which 3T MPRAGE MRI scans were obtained. A fully automated frontal lobe atlas was used to generate functionally distinct frontal subdivisions, with surface area (SA) and cortical thickness (CT) assessed in each region. Analyses focused on overall diagnostic differences as well as examinations of the effect of diagnosis within boys and girls. Results: Girls, but not boys, with ADHD showed overall reductions in total prefrontal cortex (PFC) SA. Localization revealed that girls showed widely distributed reductions in the bilateral dorsolateral PFC, left inferior lateral PFC, right medial PFC, right orbitofrontal cortex, and left anterior cingulate; and boys showed reduced SA only in the right anterior cingulate and left medial PFC. In contrast, boys, but not girls, with ADHD showed overall reductions in total premotor cortex (PMC) SA. Further localization revealed that in boys, premotor reductions were observed in bilateral lateral PMC regions; and in girls reductions were observed in bilateral supplementary motor complex. In line with diagnostic group differences, PMC and PFC SAs were inversely correlated with symptom severity in both girls and boys with ADHD. Conclusions: These results elucidate sex-based differences in cortical morphology of functional subdivisions of the frontal lobe and provide additional evidence of associations among SA and symptom severity in children with ADHD

Behavioural and neural basis of anomalous motor learning in children with autism

Autism spectrum disorder is a developmental disorder characterized by deficits in social and communication skills and repetitive and stereotyped interests and behaviours. Although not part of the diagnostic criteria, individuals with autism experience a host of motor impairments, potentially due to abnormalities in how they learn motor control throughout development. Here, we used behavioural techniques to quantify motor learning in autism spectrum disorder, and structural brain imaging to investigate the neural basis of that learning in the cerebellum. Twenty children with autism spectrum disorder and 20 typically developing control subjects, aged 8-12, made reaching movements while holding the handle of a robotic manipulandum. In random trials the reach was perturbed, resulting in errors that were sensed through vision and proprioception. The brain learned from these errors and altered the motor commands on the subsequent reach. We measured learning from error as a function of the sensory modality of that error, and found that children with autism spectrum disorder outperformed typically developing children when learning from errors that were sensed through proprioception, but underperformed typically developing children when learning from errors that were sensed through vision. Previous work had shown that this learning depends on the integrity of a region in the anterior cerebellum. Here we found that the anterior cerebellum, extending into lobule VI, and parts of lobule VIII were smaller than normal in children with autism spectrum disorder, with a volume that was predicted by the pattern of learning from visual and proprioceptive errors. We suggest that the abnormal patterns of motor learning in children with autism spectrum disorder, showing an increased sensitivity to proprioceptive error and a decreased sensitivity to visual error, may be associated with abnormalities in the cerebellum