Biology subjects

Mostofsky, S. H.

Publications and source records attributed to Mostofsky, S. H..

8 recordsLinked to original sources

bioRxiv2025

Mapping brain function underlying naturalistic motor observation and imitation using high-density diffuse optical tomography

BackgroundAutism spectrum disorder (ASD), a condition defined by deficits in social communication, restricted interests, and repetitive behaviors, is associated with early impairments in motor imitation that persist through childhood and into adulthood. Alterations in the mirror neuron system (MNS), crucial for interpreting and imitating actions, may underlie these ASD-associated differences in motor imitation. High-density diffuse optical tomography (HD-DOT) overcomes logistical challenges of functional magnetic resonance imaging to enable identification of neural substrates of naturalistic motor imitation. ObjectiveWe aim to investigate brain function underlying motor observation and imitation in autistic and non-autistic adults. We hypothesize that HD-DOT will reveal greater activation in regions associated with the MNS during motor imitation than motor observation, and that MNS activity will negatively correlate with autistic traits and motor fidelity. MethodsWe imaged brain function using HD-DOT in N = 100 participants as they engaged in observing or imitating a sequence of arm movements. Additionally, during imitation, participant movements were simultaneously recorded with 3D cameras for computer-vision-based assessment of motor imitation (CAMI). Cortical responses were estimated using general linear models, and multiple regression was used to test for associations with autistic traits, assessed via the Social Responsiveness Scale-2 (SRS), and imitation fidelity, assessed via CAMI. ResultsBoth observing and imitating motor movements elicited significant activations in higher-order visual and MNS regions, including the inferior parietal lobule, superior temporal gyrus, and inferior frontal gyrus. Imitation additionally exhibited greater activation in the superior parietal lobule, primary motor cortex, and supplementary motor area. Notably, the right temporal-parietal junction exhibited activation during observation but not during imitation. Higher autistic traits were associated with increased activation during motor observation in the right superior parietal lobule. No significant correlation between brain activation and CAMI scores was observed. ConclusionsOur findings provide robust evidence of shared and task-specific cortical responses underlying motor observation and imitation, emphasizing the differential engagement of MNS regions during motor observation and imitation.

neuroscience↗

bioRxiv2023

Brain Glutathione and GABA+ levels in autistic children

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered neurometabolite levels, including glutathione (GSH) and gamma-aminobutyric acid (GABA), have been proposed as potential contributors to the biology underlying ASD. This study investigated whether cerebral GSH or GABA levels differ between a large cohort of children aged 8-12 years with ASD (n=52) and typically developing children (TDC, n=49). A comprehensive analysis of GSH and GABA levels in multiple brain regions, including the primary motor cortex (SM1), thalamus (Thal), medial prefrontal cortex (mPFC), and supplementary motor area (SMA), was conducted using single-voxel HERMES MR spectroscopy at 3T. The results revealed no significant differences in cerebral GSH or GABA levels between the ASD and TDC groups across all examined regions. These findings suggest that the concentrations of GSH (an important antioxidant and neuromodulator) and GABA (a major inhibitory neurotransmitter) do not exhibit marked alterations in children with ASD compared to TDC. A statistically significant positive correlation was observed between GABA levels in the SM1 and Thal regions with ADHD inattention scores. No significant correlation was found between metabolite levels and hyper/impulsive scores of ADHD, measures of core ASD symptoms (ADOS-2, SRS-P) or adaptive behavior (ABAS-2). While both GSH and GABA have been implicated in various neurological disorders, the current study provides valuable insights into the specific context of ASD and highlights the need for further research to explore other neurochemical alterations that may contribute to the pathophysiology of this complex disorder. Lay summaryAutism spectrum disorder (ASD) is a neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Altered glutathione (GSH, an important antioxidant and neuromodulator) and gamma-aminobutyric acid (GABA, a major inhibitory neurotransmitter) levels have been proposed as potential contributors to the biology underlying ASD. Here, we used advanced edited Magnetic Resonance Spectroscopy (MRS) to measure levels of these low-concentration metabolites in four brain regions of a pediatric cohort. Contrary to our hypothesis, no significant difference was found between ASD and control subjects in either GSH or GABA levels in any brain region.

neuroscience↗

bioRxiv2022

Psilocybin induces spatially constrained alterations in thalamic functional organization and connectivity

BackgroundSerotonin 2A receptor (5-HT2AR) agonist psychedelics including psilocybin and LSD ("classic" psychedelics) evoke acute alterations in perception and cognition. Altered thalamocortical connectivity has been proposed to underlie these effects, which is supported by some functional MRI (fMRI) studies. Likely due to sample size limitations, 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 employed to generate functional subdivisions of the thalamus from resting state fMRI (rsfMRI) data. This report utilizes a novel data-sparing ICA approach in order to examine psilocybin-induced changes in intrathalamic functional organization and thalamocortical connectivity. MethodsBaseline rsfMRI data (n=38) was utilized to generate a template, which 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 a smaller sample (n=18). Correlations with subjective reports of drug effect and comparisons with a previously reported analytic approach (treating the thalamus as a single functional unit) were conducted. ResultsSeveral intrathalamic components showed significant psilocybin-induced alterations in intrathalamic spatial organization, largely localized to the mediodorsal and pulvinar nuclei, and correlated with reported subjective effects. These same components demonstrated alterations 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. ConclusionsUtilization of a novel analytic approach demonstrated changes in intra- and extra-thalamic functional organization and connectivity of intrathalamic nuclei and cortical networks known to express the 5-HT2AR. Given that these changes were not observed using whole-thalamus analyses, it seems that psilocybin may cause widespread but modest increases in thalamocortical connectivity that are offset by strong focal decreases in functionally relevant intrathalamic nuclei.

neuroscience↗

bioRxiv2022

Accounting for motion in 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 naive 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 naive approach, supporting this as a promising solution to improve the study of heterogeneous populations in which motion is common.

neuroscience↗

bioRxiv2021

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 TMS measures have been studied in multiple contexts, we compared ERD and three TMS measures (Resting Motor Threshold [RMT], Short-Interval Cortical Inhibition [SICI] and Task-Related Up-Modulation [TRUM]) within 14 participants with ADHD (ages 8-12y) and 17 control children. The TD group showed a correlation between greater RMT and greater magnitude of alpha (10-13Hz, 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 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.

neuroscience↗

bioRxiv2021

Beyond massive univariate tests: Covariance regression reveals complex patterns of functional connectivity related to attention-deficit/hyperactivity disorder, age, sex, and response control

We applied a novel Covariate Assisted Principal (CAP) whole-matrix regression approach to identify resting-state functional connectivity (FC) brain networks associated with attention-deficit/hyperactivity disorder (ADHD) and response control. Participants included 8-12 year-old children with ADHD (n=115, 29 girls) and typically developing controls (n=102, 35 girls) with a resting-state fMRI scan and go/no-go task behavioral data. We modeled three sets of covariates to identify resting-state networks associated with ADHD, age, sex, and response control. Four networks were identified across models revealing complex interactions between subregions of cognitive control, default mode, subcortical, visual, and somatomotor networks that relate to age, response control, and a diagnosis of ADHD among girls and boys. Unique networks were also identified in each of the three models suggesting some specificity to the covariates of interest. These findings demonstrate the utility of our novel covariance regression approach to studying functional brain networks relevant for development, behavior, and psychopathology.

neuroscience↗

bioRxiv2018

Parsing heterogeneity in autism spectrum disorder and attention-deficit/hyperactivity disorder with individual connectome mapping

Traditional diagnostic systems for mental illnesses define diagnostic categories that are heterogeneous in behavior and underlying neurobiological alterations. The goal of this study was to parse heterogeneity in a core executive function, cognitive flexibility, in children with a range of abilities (N=132; children with autism spectrum disorder [ASD], attention deficit/hyperactivity disorder [ADHD], and typically developing [TD] children) using directed functional connectivity profiles derived from resting-state fMRI data. Brain regions activated in response to a cognitive flexibility task in adults were used guide region-of-interest (ROI) selection to estimate individual connectivity profiles in this study. We expected to find at least three subgroups of children who differed in their network connectivity metrics and symptom measures. Unexpectedly, we did not find a stable or valid subgrouping solution, which suggests that categorical models of the neural substrates of cognitive flexibility in children may be invalid. Results shed light on the validity of conceptualizing the neural substrates of cognitive flexibility categorically in children. Ultimately, this work may provide a foundation for the development of a revised nosology focused on neurobiological substrates of mental illness as an alternative to traditional symptom-based classification systems.

neuroscience↗

bioRxiv2018

Investigating functional brain network integrity using a traditional and novel diagnostic system for neurodevelopmental disorders

BackgroundCurrent diagnostic systems for neurodevelopmental disorders do not have clear links to underlying neurobiology, limiting their utility in identifying targeted treatments for individuals. Several factors contribute to this issue, including the use of small samples in neuroimaging research and heterogeneity within diagnostic categories. Here, we aimed to investigate differences in functional brain network integrity between traditional diagnostic categories (autism spectrum disorder [ASD], attention-deficit/hyperactivity disorder [ADHD], typically developing [TD]) and carefully consider the impact of comorbid ASD and ADHD on functional brain network integrity in a large sample. We also assess the neurobiological validity of a novel, potential alternative nosology based on behavioral measures of executive function.\n\nMethodFive-minute resting-state fMRI data were obtained from 168 children (128 boys, 40 girls) with ASD, ADHD, comorbid ASD and ADHD, and TD children. Independent component analysis and dual regression were used to compute within- and between-network functional connectivity metrics at the individual level.\n\nResultsNo significant group differences in within- nor between-network functional connectivity were observed between traditional diagnostic categories (ASD, ADHD, TD) even when stratified by comorbidity (ASD+ADHD, ASD, ADHD, TD). Similarly, subgroups classified by executive functioning levels showed no group differences.\n\nConclusionsUsing clinical diagnosis and behavioral measures of executive function, no group differences were observed among the categories examined. Therefore, we suggest that brain imaging metrics may more effectively define clinical subgroups than behavioral metrics, and may contribute to the establishment of a neurobiologically valid nosology for neurodevelopmental disorders.

neuroscience↗