Biology subjects

Mostofsky, S.

Publications and source records attributed to Mostofsky, S..

3 recordsLinked to original sources

bioRxiv2021

Altered Cortical Activation Associated with Mirror Overflow Driven by Non-Dominant Hand Movement in Attention-Deficit/Hyperactivity Disorder

Mirror overflow is involuntary movement that accompanies unilateral voluntary movement on the opposite side of the body, and is commonly seen in Attention-Deficit/Hyperactivity Disorder (ADHD). Children with ADHD show asymmetry in mirror overflow between dominant and non-dominant hand, yet there are competing mechanistic accounts of why this occurs. Using EEG during a sequential, unimanual finger-tapping task, we found that children with ADHD exhibited significantly more mirror overflow than typically developing (TD) controls, especially during the tapping of the non-dominant hand. Furthermore, source-level EEG oscillation analysis revealed that children with ADHD showed decreased alpha (8-12 Hz) event-related desynchronization (ERD) compared with controls in both hemispheres, but only during tapping of the non-dominant hand. Moreover, only the ERD ipsilateral to the mirror overflow during non-dominant hand movement correlated with both magnitude of overflow movements and higher ADHD symptom severity (Conners ADHD Hyperactivity/Impulsiveness scale) in children with ADHD. TD controls did not show these relationships. Our findings suggest that EEG differences in finger-tapping in ADHD are related primarily to voluntary movement in the non-dominant hand. Our results are also consistent with the Ipsilateral Corticospinal Tract (CST) Hypothesis, which posits that the atypical persistence of mirror overflow in ADHD may originate in the sensorimotor areas ipsilateral to mirror overflow and be transmitted via non-decussating CST fibers.

neuroscience↗

bioRxiv2020

Mimicry is associated with procedural learning, not social bonding, neural systems in autism

Mimicry facilitates social bonding throughout the lifespan. Mimicry impairments in autism spectrum conditions (ASC) are widely reported, including differentiation of the brain networks associated with its social bonding and learning functions. This study examined associations between volumes of brain regions associated with social bonding versus procedural skill learning, and mimicry of gestures during a naturalistic interaction in ASC and neurotypical (NT) children. Consistent with predictions, results revealed reduced mimicry in ASC relative to the NT children. Mimicry frequency was negatively associated with autism symptom severity. Mimicry was predicted predominantly by the volume of procedural skill learning regions in ASC, and by bonding regions in NT. Further, bonding regions contributed significantly less to mimicry in ASC than in NT, while the contribution of learning regions was not different across groups. These findings suggest that associating mimicry with skill learning, rather than social bonding, may partially explain observed communication difficulties in ASC.

neuroscience↗

bioRxiv2018

Covariate Assisted Principal Regression for Covariance Matrix Outcomes

Modeling variances in data has been an important topic in many fields, including in financial and neuroimaging analysis. We consider the problem of regressing covariance matrices on a vector covariates, collected from each observational unit. The main aim is to uncover the variation in the covariance matrices across units that are explained by the covariates. This paper introduces Covariate Assisted Principal (CAP) regression, an optimization-based method for identifying the components predicted by (generalized) linear models of the covariates. We develop computationally efficient algorithms to jointly search the projection directions and regression coefficients, and we establish the asymptotic properties. Using extensive simulation studies, our method shows higher accuracy and robustness in coefficient estimation than competing methods. Applied to a resting-state functional magnetic resonance imaging study, our approach identifies the human brain network changes associated with age and sex.

neuroscience↗