Sex Differences and Behavioral Associations with Typically Developing Pediatric Regional Cerebellar Gray Matter Volume.

The cerebellum contributes to motor and higher-order control throughout neurodevelopment, with marked growth during childhood. Few studies have investigated differential associations of cerebellar morphometry with function in males and females. The present study examines sex differences in regional cerebellar gray matter volume (GMV) and the moderating effect of sex on the relationship between GMV and motor, cognitive, and emotional functions in a large cohort of typically developing (TD) children. Participants included 371 TD children (123 females, age 8-12 years). A convolutional neural network-based approach was employed for cerebellar parcellation. Volumes were harmonized using ComBat to adjust for hardware-induced variations. Regression analyses examined the effect of sex on GMV and whether sex moderated the relationship between GMV and motor, cognitive, and emotional functions. Males showed larger GMV in right lobules I-V, bilateral lobules VI, crus II/VIIb, and VIII, left lobule X, and vermis regions I-V and VIII-X. Greater motor function correlated with less vermis VI-VII GMV in females. Greater cognitive function correlated with greater left lobule VI GMV in females and less left lobule VI GMV in males. Finally, greater internalizing symptoms correlated with greater bilateral lobule IX GMV in females but less in males. These findings reveal sexually dimorphic patterns of cerebellar structure and associations with motor, cognitive, and emotional functions. Males generally show larger GMV than females. Larger GMV was associated with better cognitive functioning for females and better motor/emotional functioning for males.

Developmental deviation in delay discounting as a transdiagnostic indicator of risk for child psychopathology.

BACKGROUND: The tendency to prefer smaller, immediate rewards over larger, delayed rewards is known as delay discounting (DD). Developmental deviations in DD may be key in characterizing psychiatric and neurodevelopmental disorders. Recent work empirically supported DD as a transdiagnostic process in various psychiatric disorders. Yet, there is a lack of research relating developmental changes in DD from mid-childhood to adolescence to psychiatric and neurodevelopmental disorders. Additionally, examining the interplay between socioeconomic status/total household income (THI) and psychiatric symptoms is vital for a more comprehensive understanding of pediatric pathology and its complex relationship with DD. METHODS: The current study addresses this gap in a robust psychiatric sample of 1843 children and adolescents aged 5-18 (M = 10.6, SD = 3.17; 1,219 males, 624 females). General additive models (GAMs) characterized the shape of age-related changes in monetary and food reward discounting for nine psychiatric disorders compared with neurotypical youth (NT; n = 123). Over 40% of our sample possessed a minimum of at least three psychiatric or neurodevelopmental disorders. We used bootstrap-enhanced Louvain community detection to map DD-related comorbidity patterns. We derived five subtypes based on diagnostic categories present in our sample. DD patterns were then compared across each of the subtypes. Further, we evaluated the effect of cognitive ability, emotional and behavioral problems, and THI in relation to DD across development. RESULTS: Higher discounting was found in six of the nine disorders we examined relative to NT. DD was consistently elevated across development for most disorders, except for depressive disorders, with age-specific DD differences compared with NTs. Community detection analyses revealed that one comorbidity subtype consisting primarily of Attention-Deficit/Hyperactivity Disorder (ADHD) Combined Presentation and anxiety disorders displayed the highest overall emotional/behavioral problems and greater DD for the food reward. An additional subtype composed mainly of ADHD, predominantly Inattentive Presentation, learning, and developmental disorders, showed the greatest DD for food and monetary rewards compared with the other subtypes. This subtype had deficits in reasoning ability, evidenced by low cognitive and academic achievement performance. For this ADHD-I and developmental disorders subtype, THI was related to DD across the age span such that participants with high THI showed no differences in DD compared with NTs. In contrast, participants with low THI showed significantly worse DD trajectories than all others. Our results also support prior work showing that DD follows nonlinear developmental patterns. CONCLUSIONS: We demonstrate preliminary evidence for DD as a transdiagnostic marker of psychiatric and neurodevelopmental disorders in children and adolescents. Comorbidity subtypes illuminate DD heterogeneity, facilitating the identification of high-risk individuals. Importantly, our findings revealed a marked link between DD and intellectual reasoning, with children from lower-income households exhibiting lower reasoning skills and heightened DD. These observations underscore the potential consequences of compromised self-regulation in economically disadvantaged individuals with these disorders, emphasizing the need for tailored interventions and further research to support improved outcomes.

From urges to tics in children with Tourette syndrome: associations with supplementary motor area GABA and right motor cortex physiology.

Tourette syndrome (TS) is a childhood-onset disorder in which tics are often preceded by premonitory sensory urges. More severe urges correlate with worse tics and can render behavioral therapies less effective. The supplementary motor area (SMA) is a prefrontal region believed to influence tic performance. To determine whether cortical physiological properties correlate with urges and tics, we evaluated, in 8-12-year-old right-handed TS children (n = 17), correlations of urge and tic severity scores and compared both to cortical excitability (CE) and short- and long-interval cortical inhibition (SICI and LICI) in both left and right M1. We also modeled these M1 transcranial magnetic stimulation measures with SMA gamma-amino butyric acid (GABA) levels in TS and typically developing control children (n = 16). Urge intensity correlated strongly with tic scores. More severe urges correlated with lower CE and less LICI in both right and left M1. Unexpectedly, in right M1, lower CE and less LICI correlated with less severe tics. We found that SMA GABA modulation of right, but not left, M1 CE and LICI differed in TS. We conclude that in young children with TS, lower right M1 CE and LICI, modulated by SMA GABA, may reflect compensatory mechanisms to diminish tics in response to premonitory urges.

Biomarkers of tic severity in children with Tourette syndrome: Motor cortex inhibition measured with transcranial magnetic stimulation.

AIM: To compare transcranial magnetic stimulation (TMS)-derived measures of primary motor cortex (M1) physiology between children with and without Tourette syndrome, and to dimensionally analyze TMS measures with Tourette syndrome-related symptom severity. METHOD: We used a cross-sectional experimental design. Sixty 8- to 12-year-old children participated (30 with Tourette syndrome: three females, mean age 10 years 10 months, standard deviation [SD] 1 year 3 months; 30 typically developing children: seven females, mean age 10 years 7 months, SD 1 year 3 months). In the group with Tourette syndrome, 15 (one female, mean age 10 years 11 months, SD 1 year 3 months) had comorbid attention-deficit/hyperactivity disorder (ADHD), rated with the Conners, Third Edition and the parent-reported ADHD rating scales. Tic severity was rated with the Yale Global Tic Severity Scale and urge severity with the Individualized Premonitory Urge for Tics Scale. M1 short-interval cortical inhibition (SICI) and intracortical facilitation were compared between diagnostic groups and, within the group with Tourette syndrome, correlated with symptom severity using linear mixed-effects models for repeated measures. RESULTS: Accounting for ADHD, we found no difference in SICI or intracortical facilitation in those with Tourette syndrome versus typically developing children (p > 0.1). In the group with Tourette syndrome, reduced M1 SICI predicted greater total (p = 0.012) and global (p = 0.002) tic severity. There were no associations with urge severity (p > 0.5). INTERPRETATION: Reduced M1 SICI is robustly associated with increased tic, but not urge, severity. WHAT THIS PAPER ADDS: Increased tic severity is associated with reduced motor cortex short-interval cortical inhibition (SICI). Children with Tourette syndrome with increased urge severity also show increased tic severity. However, reduced motor cortex SICI is associated with tic, but not urge, severity.

Perceptual alterations in the relationship between sensory reactivity, intolerance of uncertainty, and anxiety in autistic children with and without ADHD.

Sensory differences and anxiety disorders are highly prevalent in autistic individuals with and without ADHD. Studies have shown that sensory differences and anxiety are associated and that intolerance of uncertainty (IU) plays an important role in this relationship. However, it is unclear as to how different levels of the sensory processing pathway (i.e., perceptual, affective, or behavioral) contribute. Here, we used psychophysics to assess how alterations in tactile perception contribute to questionnaire measures of sensory reactivity, IU, and anxiety. Thirty-eight autistic children (aged 8-12 years; 27 with co-occurring ADHD) were included. Consistent with previous findings, mediation analyses showed that child-reported IU fully mediated an association between parent-reported sensory reactivity and parent-reported anxiety and that anxiety partially mediated an association between sensory reactivity and IU. Of the vibrotactile thresholds, only simultaneous frequency discrimination (SFD) thresholds correlated with sensory reactivity. Interestingly, we found that sensory reactivity fully mediated an association between SFD threshold and anxiety, and between SFD threshold and IU. Taken together, those findings suggest a mechanistic pathway whereby tactile perceptual alterations contribute to sensory reactivity at the affective level, leading in turn to increased IU and anxiety. This stepwise association can inform potential interventions for IU and anxiety in autism.

ADHD-related sex differences in emotional symptoms across development.

To investigate developmental changes in emotion dysregulation (ED) and associated symptoms of emotional lability, irritability, anxiety, and depression, among girls and boys with and without ADHD from childhood through adolescence. Data were collected from a sample of 8-18-year-old children with (n = 264; 76 girls) and without (n = 153; 56 girls) ADHD, with multiple time-points from a subsample of participants (n = 121). Parents and youth completed rating scales assessing child ED, emotional lability, irritability, anxiety, and depression. Mixed effects models were employed to examine effects and interactions of diagnosis, sex [biological sex assigned at birth], age among boys and girls with and without ADHD. Mixed effects analyses showed sexually dimorphic developmental patterns between boys and girls, such that boys with ADHD showed a greater reduction in ED, irritability, and anxiety with age compared to girls with ADHD, whose symptom levels remained elevated relative to TD girls. Depressive symptoms were persistently elevated among girls with ADHD compared to boys with ADHD, whose symptoms decreased with age, relative to same-sex TD peers. While both boys and girls with ADHD showed higher levels of ED during childhood (compared to their sex-matched TD peers), mixed effects analyses revealed substantial sexually dimorphic patterns of emotional symptom change during adolescence: Boys with ADHD showed robust improvements in emotional symptoms from childhood to adolescence while girls with ADHD continued to show high and/or increased levels of ED, emotional lability, irritability, anxiety and depression.

Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

The exclusion of high-motion participants can reduce the impact of motion in functional Magnetic Resonance Imaging (fMRI) data. However, the exclusion of high-motion participants may change the distribution of clinically relevant variables in the study sample, and the resulting sample may not be representative of the population. Our goals are two-fold: 1) to document the biases introduced by common motion exclusion practices in functional connectivity research and 2) to introduce a framework to address these biases by treating excluded scans as a missing data problem. We use a study of autism spectrum disorder in children without an intellectual disability to illustrate the problem and the potential solution. We aggregated data from 545 children (8-13 years old) who participated in resting-state fMRI studies at Kennedy Krieger Institute (173 autistic and 372 typically developing) between 2007 and 2020. We found that autistic children were more likely to be excluded than typically developing children, with 28.5% and 16.1% of autistic and typically developing children excluded, respectively, using a lenient criterion and 81.0% and 60.1% with a stricter criterion. The resulting sample of autistic children with usable data tended to be older, have milder social deficits, better motor control, and higher intellectual ability than the original sample. These measures were also related to functional connectivity strength among children with usable data. This suggests that the generalizability of previous studies reporting naïve analyses (i.e., based only on participants with usable data) may be limited by the selection of older children with less severe clinical profiles because these children are better able to remain still during an rs-fMRI scan. We adapt doubly robust targeted minimum loss based estimation with an ensemble of machine learning algorithms to address these data losses and the resulting biases. The proposed approach selects more edges that differ in functional connectivity between autistic and typically developing children than the naïve approach, supporting this as a promising solution to improve the study of heterogeneous populations in which motion is common.

Psilocybin induces spatially constrained alterations in thalamic functional organizaton and connectivity.

BACKGROUND: Classic psychedelics, such as psilocybin and LSD, and other serotonin 2A receptor (5-HT2AR) agonists evoke acute alterations in perception and cognition. Altered thalamocortical connectivity has been hypothesized to underlie these effects, which is supported by some functional MRI (fMRI) studies. These studies have treated the thalamus as a unitary structure, despite known differential 5-HT2AR expression and functional specificity of different intrathalamic nuclei. Independent Component Analysis (ICA) has been previously used to identify reliable group-level functional subdivisions of the thalamus from resting-state fMRI (rsfMRI) data. We build on these efforts with a novel data-maximizing ICA-based approach to examine psilocybin-induced changes in intrathalamic functional organization and thalamocortical connectivity in individual participants. METHODS: Baseline rsfMRI data (n=38) from healthy individuals with a long-term meditation practice was utilized to generate a statistical template of thalamic functional subdivisions. This template was then applied in a novel ICA-based analysis of the acute effects of psilocybin on intra- and extra-thalamic functional organization and connectivity in follow-up scans from a subset of the same individuals (n=18). We examined correlations with subjective reports of drug effect and compared with a previously reported analytic approach (treating the thalamus as a single functional unit). RESULTS: Several intrathalamic components showed significant psilocybin-induced alterations in spatial organization, with effects of psilocybin largely localized to the mediodorsal and pulvinar nuclei. The magnitude of changes in individual participants correlated with reported subjective effects. These components demonstrated predominant decreases in thalamocortical connectivity, largely with visual and default mode networks. Analysis in which the thalamus is treated as a singular unitary structure showed an overall numerical increase in thalamocortical connectivity, consistent with previous literature using this approach, but this increase did not reach statistical significance. CONCLUSIONS: We utilized a novel analytic approach to discover psilocybin-induced changes in intra- and extra-thalamic functional organization and connectivity of intrathalamic nuclei and cortical networks known to express the 5-HT2AR. These changes were not observed using whole-thalamus analyses, suggesting that psilocybin may cause widespread but modest increases in thalamocortical connectivity that are offset by strong focal decreases in functionally relevant intrathalamic nuclei.

Covariate Assisted Principal regression for covariance matrix outcomes.

In this study, we consider the problem of regressing covariance matrices on associated covariates. Our goal is to use covariates to explain variation in covariance matrices across units. As such, we introduce Covariate Assisted Principal (CAP) regression, an optimization-based method for identifying components associated with the covariates using a generalized linear model approach. We develop computationally efficient algorithms to jointly search for common linear projections of the covariance matrices, as well as the regression coefficients. Under the assumption that all the covariance matrices share identical eigencomponents, we establish the asymptotic properties. In simulation studies, our CAP method shows higher accuracy and robustness in coefficient estimation over competing methods. In an example resting-state functional magnetic resonance imaging study of healthy adults, CAP identifies human brain network changes associated with subject demographics.

Frequency and Intensity of Premonitory Urges-to-Tic in Tourette Syndrome Is Associated With Supplementary Motor Area GABA+ Levels.

BACKGROUND: Individuals with Tourette syndrome (TS) often report that they express tics as a means of alleviating the experience of unpleasant sensations. These sensations are perceived as an urge to act and are referred to as premonitory urges. Premonitory urges have been the focus of recent efforts to develop interventions to reduce tic expression in those with TS. OBJECTIVE: The aim of this study was to examine the contribution of brain γ-aminobutyric acid (GABA) and glutamate levels of the right primary sensorimotor cortex (SM1), supplementary motor area (SMA), and insular cortex (insula) to tic and urge severity in children with TS. METHODS: Edited magnetic resonance spectroscopy was used to assess GABA+ (GABA + macromolecules) and Glx (glutamate + glutamine) of the right SM1, SMA, and insula in 68 children with TS (MAge = 10.59, SDAge = 1.33) and 41 typically developing control subjects (MAge = 10.26, SDAge = 2.21). We first compared GABA+ and Glx levels of these brain regions between groups. We then explored the association between regional GABA+ and Glx levels with urge and tic severity. RESULTS: GABA+ and Glx of the right SM1, SMA, and insula were comparable between the children with TS and typically developing control subjects. In children with TS, lower levels of SMA GABA+ were associated with more severe and more frequent premonitory urges. Neither GABA+ nor Glx levels were associated with tic severity. CONCLUSIONS: These results broadly support the role of GABAergic neurotransmission within the SMA in the experience of premonitory urges in children with TS. © 2021 International Parkinson and Movement Disorder Society.

The Role of the Cerebellum in Repetitive Behavior Across Species: Childhood Stereotypies and Deer Mice.

Recent studies suggest that the cerebellum may have a significant role in repetitive behaviors. In primary complex motor stereotypies, typically developing children have repetitive movements usually involving rhythmic flapping/waving arm/hand movements. Similarly, the deer mouse animal model exhibits inherited repetitive behaviors, with increased frequencies of spontaneous jumping and rearing. In this study, data from both children with motor stereotypies and deer mice were used to investigate the role of the cerebellum in repetitive behaviors. The 3.0-T MRI volumetric imaging of the cerebellum was obtained in 20 children with primary complex motor stereotypies and 20 healthy controls. In deer mice, cerebellar volume (n = 7/group) and cell counts (n = 9/group) were compared between high- and low-activity animals. Levels of cerebellar neurotransmitters were also determined via HPLC (n = 10/group). In children with stereotypies, (a) there were a statistically significant reduction (compared to controls) in the white matter volume of the posterior cerebellar lobule VI-VII that negatively correlated with motor control and (b) an 8% increase in the anterior vermis gray matter that positively correlated with motor Stereotypy Severity Scores (SSS). In deer mice, (a) there was a significant increase in the volume of the anterior vermal granular cell layer that was associated with higher activity and (b) dentate nucleus cell counts were higher in high activity animals. Similar increases in volume were observed in anterior vermis in children with stereotypies and a deer mouse model of repetitive behaviors. These preliminary findings support the need for further investigation of the cerebellum in repetitive behaviors.

Reduced basal ganglia tissue-iron concentration in school-age children with attention-deficit/hyperactivity disorder is localized to limbic circuitry.

Dopamine-related abnormalities in the basal ganglia have been implicated in attention-deficit/hyperactivity disorder (ADHD). Iron plays a critical role in supporting dopaminergic function, and reduced brain iron and serum ferritin levels have been linked to ADHD symptom severity in children. Furthermore, the basal ganglia is a central brain region implicated in ADHD psychopathology and involved in motor and reward functions as well as emotional responding. The present study repurposed diffusion tensor imaging (DTI) to examine effects of an ADHD diagnosis and sex on iron deposition within the basal ganglia in children ages 8-12 years. We further explored associations between brain iron levels and ADHD symptom severity and affective symptoms. We observed reduced iron levels in children with ADHD in the bilateral limbic region of the striatum, as well as reduced levels of iron-deposition in males in the sensorimotor striatal subregion, regardless of diagnosis. Across the whole sample, iron-deposition increased with age in all regions. Brain-behavior analyses revealed that, across diagnostic groups, lower tissue-iron levels in bilateral limbic striatum correlated with greater ADHD symptom severity, whereas lower tissue-iron levels in the left limbic striatum only correlated with anxious, depressive and affective symptom severity. This study sheds light on the neurobiological underpinnings of ADHD, specifically highlighting the localization of tissue-iron deficiency in limbic regions, and providing support for repurposing DTI for brain iron analyses. Our findings highlight the need for further investigation of iron as a biomarker in the diagnosis and treatment of ADHD and sex differences.

Altered Inferior Parietal Functional Connectivity is Correlated with Praxis and Social Skill Performance in Children with Autism Spectrum Disorder.

Children with autism spectrum disorder (ASD) have difficulties perceiving and producing skilled gestures, or praxis. The inferior parietal lobule (IPL) is crucial to praxis acquisition and expression, yet how IPL connectivity contributes to autism-associated impairments in praxis as well as social-communicative skill remains unclear. Using resting-state functional magnetic resonance imaging, we applied independent component analysis to test how IPL connectivity relates to praxis and social-communicative skills in children with and without ASD. Across all children (with/without ASD), praxis positively correlated with connectivity of left posterior-IPL with the left dorsal premotor cortex and with the bilateral posterior/medial parietal cortex. Praxis also correlated with connectivity of right central-IPL connectivity with the left intraparietal sulcus and medial parietal lobe. Further, in children with ASD, poorer praxis and social-communicative skills both correlated with weaker right central-IPL connectivity with the left cerebellum, posterior cingulate, and right dorsal premotor cortex. Our findings suggest that IPL connectivity is linked to praxis development, that contributions arise bilaterally, and that right IPL connectivity is associated with impaired praxis and social-communicative skills in autism. The findings underscore the potential impact of IPL connectivity and impaired skill acquisition on the development of a range of social-communicative and motor functions during childhood, including autism-associated impairments.

Associations between Task-Related Modulation of Motor-Evoked Potentials and EEG Event-Related Desynchronization in Children with ADHD.

Children with attention-deficit/hyperactivity disorder (ADHD) have previously shown a decreased magnitude of event-related desynchronization (ERD) during a finger-tapping task, with a large between-group effect. Because the neurobiology underlying several transcranial magnetic stimulation (TMS) measures have been studied in multiple contexts, we compared ERD and 3 TMS measures (resting motor threshold [RMT], short-interval cortical inhibition [SICI], and task-related up-modulation [TRUM]) within 14 participants with ADHD (ages 8-12 years) and 17 control children. The typically developing (TD) group showed a correlation between greater RMT and greater magnitude of alpha (10-13 Hz, here) ERD, and there was no diagnostic interaction effect, consistent with a rudimentary model of greater needed energy input to stimulate movement. Similarly, inhibition measured by SICI was also greater in the TD group when the magnitude of movement-related ERD was higher; there was a miniscule diagnostic interaction effect. Finally, TRUM during a response-inhibition task showed an unanticipated pattern: in TD children, the greater TMS task modulation (TRUM) was associated with a smaller magnitude of ERD during finger-tapping. The ADHD group showed the opposite direction of association: Greater TRUM was associated with larger magnitude of ERD. Prior EEG results have demonstrated specific alterations of task-related modulation of cortical physiology, and the current results provide a fulcrum for multimodal study.

Group linear non-Gaussian component analysis with applications to neuroimaging.

Independent component analysis (ICA) is an unsupervised learning method popular in functional magnetic resonance imaging (fMRI). Group ICA has been used to search for biomarkers in neurological disorders including autism spectrum disorder and dementia. However, current methods use a principal component analysis (PCA) step that may remove low-variance features. Linear non-Gaussian component analysis (LNGCA) enables simultaneous dimension reduction and feature estimation including low-variance features in single-subject fMRI. A group LNGCA model is proposed to extract group components shared by more than one subject. Unlike group ICA methods, this novel approach also estimates individual (subject-specific) components orthogonal to the group components. To determine the total number of components in each subject, a parametric resampling test is proposed that samples spatially correlated Gaussian noise to match the spatial dependence observed in data. In simulations, estimated group components achieve higher accuracy compared to group ICA. The method is applied to a resting-state fMRI study on autism spectrum disorder in 342 children (252 typically developing, 90 with autism), where the group signals include resting-state networks. The discovered group components appear to exhibit different levels of temporal engagement in autism versus typically developing children, as revealed using group LNGCA. This novel approach to matrix decomposition is a promising direction for feature detection in neuroimaging.

Children with attention-deficit/hyperactivity disorder spend more time in hyperconnected network states and less time in segregated network states as revealed by dynamic connectivity analysis.

Previous studies in children with attention-deficit/hyperactivity disorder (ADHD) have observed functional brain network disruption on a whole-brain level, as well as on a sub-network level, particularly as related to the default mode network, attention-related networks, and cognitive control-related networks. Given behavioral findings that children with ADHD have more difficulty sustaining attention and more extreme moment-to-moment fluctuations in behavior than typically developing (TD) children, recently developed methods to assess changes in connectivity over shorter time periods (i.e., "dynamic functional connectivity"), may provide unique insight into dysfunctional network organization in ADHD. Thus, we performed a dynamic functional connectivity (FC) analysis on resting state fMRI data from 38 children with ADHD and 79 TD children. We used Hidden semi-Markov models (HSMMs) to estimate six network states, as well as the most probable sequence of states for each participant. We quantified the dwell time, sojourn time, and transition probabilities across states. We found that children with ADHD spent less total time in, and switched more quickly out of, anticorrelated states involving the default mode network and task-relevant networks as compared to TD children. Moreover, children with ADHD spent more time in a hyperconnected state as compared to TD children. These results provide novel evidence that underlying dynamics may drive the differences in static FC patterns that have been observed in ADHD and imply that disrupted FC dynamics may be a mechanism underlying the behavioral symptoms and cognitive deficits commonly observed in children with ADHD.

Increased mirror overflow movements in ADHD are associated with altered EEG alpha/beta band desynchronization.

Children with ADHD show developmentally abnormal levels of mirror overflow-unintentional movements occurring symmetrically opposite of intentional movements. Because mirror overflow correlates with ADHD behavioral symptoms, the study of disinhibition in motor control may shed light on physiologic mechanisms underlying impaired behavioral/cognitive control. This is a case-controlled study of EEG recording from 25 children with ADHD and 25 typically developing (TD) controls performing unilateral sequential finger tapping, with overflow movements measured using electronic goniometers. Consistent with previously published findings, children with ADHD showed increased mirror overflow as compared with TD peers. EEG findings revealed less lateralized alpha modulation (event-related desynchronization; ERD) and decreased magnitude of beta ERD in ADHD; both alpha and beta ERD reflect cortical activation. Moderation analysis revealed a significant association between beta ERD and overflow, independent of diagnosis; and an equivocal (p = .08) effect of diagnosis on the relationship between alpha ERD and overflow, with a significant effect in children with ADHD but not TD children. These results suggest two mechanisms involved with mirror overflow: one reflected in beta ipsilateral to the intentional movement and relevant to both children with ADHD and controls, and the other seemingly more specific to ADHD (alpha, contralateral to movement).

Correcting frequency and phase offsets in MRS data using robust spectral registration.

An algorithm for retrospective correction of frequency and phase offsets in MRS data is presented. The algorithm, termed robust spectral registration (rSR), contains a set of subroutines designed to robustly align individual transients in a given dataset even in cases of significant frequency and phase offsets or unstable lipid contamination and residual water signals. Data acquired by complex multiplexed editing approaches with distinct subspectral profiles are also accurately aligned. Automated removal of unstable lipid contamination and residual water signals is applied first, when needed. Frequency and phase offsets are corrected in the time domain by aligning each transient to a weighted average reference in a statistically optimal order using nonlinear least-squares optimization. The alignment of subspectra in edited datasets is performed using an approach that specifically targets subtraction artifacts in the frequency domain. Weighted averaging is then used for signal averaging to down-weight poorer-quality transients. Algorithm performance was assessed on one simulated and 67 in vivo pediatric GABA-/GSH-edited HERMES datasets and compared with the performance of a multistep correction method previously developed for aligning HERMES data. The performance of the novel approach was quantitatively assessed by comparing the estimated frequency/phase offsets against the known values for the simulated dataset or by examining the presence of subtraction artifacts in the in vivo data. Spectral quality was improved following robust alignment, especially in cases of significant spectral distortion. rSR reduced more subtraction artifacts than the multistep method in 64% of the GABA difference spectra and 75% of the GSH difference spectra. rSR overcomes the major challenges of frequency and phase correction.

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

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.