Potential movement biomarkers for autism in children and adolescents

Background -- While social communication deficits are the hallmark of autism spectrum disorders (ASD), motor deficits are known to be common in this population as well. Recently, members of our research team showed that kinematic markers collected by playing a tablet game may be a promising biomarker for identification of ASD as compared to a typically developing population (TD) in children ages 3-6 years old (Anzulewicz et al, 2016). To our knowledge, no one has replicated this finding in an older population. Purpose -- To replicate and extend previous findings of kinematic differences in children with ASD to an older population of children (9-14 years old). Methods -- Four TD children and 5 children with ASD (aged 9-12) played an iPad drawing game (Anzulewicz et al, 2016) that measured gesture kinematics and gesture force using inertial sensors and touch screen touch displacements. 212 features were calculated from the inertial sensor and touch screen data (ibid). A Kolmogorov-Smirnov (K-S) test was run to identify motor features distinct between ASD and TD children. Results -- K-S test identified seven significantly different features (JerkMagnitudeMax, JerkMin_y, JerkRange_y, AttitudeRange_y, RotationRMS_x, RotationStdDev_x, JerkZeroCrossing_x) between ASD and TD groups that represented differences in acceleration of finger movements and the displacement of the iPad during movements. Conclusions -- Results demonstrated inertial movement sensor parameter differences are key identifiers between 8-12 year old ASD and TD children, common to children 3-6 years old. Contact forces and the distribution of forces during coloring may serve as important identifiers of ASD irrespective of age during childhood, while other parameters may be age-dependent. Research Support NIH R01 (1R01HD079432-01A1

Brainstem morphometric differences in children with autism spectrum disorder, developmental coordination disorder, and those typically developing

Background: The brainstem is a neglected topic in autism research, despite major lines of evidence indicating its active involvement in sensory, motor, affect, arousal, and social regulation (Dadalko & Travers, 2018). It is the substrate of what affective neuroscience identifies as the ‘Core Self’ (Alcaro, Carta, & Panksepp, 2017), and disruption to its growth and function appears to disturb core conscious experience in autism (Delafield-Butt & Trevarthen, 2017; Trevarthen & Delafield-Butt, 2013). Yet, although evidence indicates brainstem growth is disrupted in early childhood (Bosco et al., 2018), how these growth differences compare to closely related neurodevelopmental disorders, such a Developmental Coordination Disorder (DCD), is not yet understood. Objectives: To determine brainstem morphometric differences between children with ASD, DCD, and those typically developing (TD). Methods: Study participants were 87 youths ages 8 to 17 assigned to the ASD (n = 30, 7 female), DCD (n =24, 12 female) or TD (n = 33, 12 female) group. Exclusion criteria for all groups included IQ <80. TD were excluded if they had any neuropsychological or psychopathological disorder. DCD eligibility additionally included performance 16th percentile on the MABC-2 and no concern about an ASD diagnosis. ASD participants had a previous clinical diagnosis confirmed by ADOS-2 and ADI-R. Individuals were excluded if they had another neuropsychological disorder, except attention deficit or anxiety disorder. T1-weighted MPRAGE (1mm isotropic resolution) MRI data were acquired on a 3T MAGNETOM Prisma (Siemens). Brainstem morphology was analysed using SPHARM-MAT (http://lishenlab.com/spharm/), a 3D Fourier surface representation method¬¬¬. A typical surface was calculated for the TD group, and distances from this norm computed for each vertex. Mean distances at each vertex were computed for each group (ASD, DCD, TD) and compared, taking into account age, gender and supratentorial volume as covariates. Results: Significant brainstem morphological differences were identified between all three (TD, ASD and DCD; Figure 1). Significant differences between TD and ASD (p<0.01) were identified in a large region of the anterior-most surface, extending caudally along the right posterior surface. Differences between TD and DCD groups were similar with reduced significance (p0.01), and the pattern diverged with more inclusion of the anterior ventricular surface and less pronouncement at the right anterior border. Finally, significant differences were found between ASD and DCD groups (p<0.01), specifically at the anterior midline either side of the ventricular surface, and especially in two long anteroposterior columns on the left side adjacent and parallel to the fourth ventricle. Conclusions: Surface morphology differences indicate alterations in local nuclei and/or tract growth within the brainstem, especially approaching the anterior surface in ASD and DCD children, and differentially between them at the ventricular surface. The former may relate to specific nerve growth of the pons, and the latter to cerebellar peduncle connectivity differences, superficial nuclei growth such as the hypoglossal, intercalatus, or vagus and associated tracts, or deeper nuclei such as the inferior olivary nucleus. Brainstem structural differences likely disturbs the integrative function of the Core Self. Higher resolution 7T MRI is required to resolve the underlying differential composition

Impact of Motor Stroke on Novel and Conventional Action Metaphor Comprehension

Previous studies indicate that damage to motor brain regions impacts comprehension of literal action-related language. However, whether such damage also impacts comprehension of action-metaphors remains unknown. Such a finding would support the notion that metaphors are grounded in sensorimotor representations. Here we tested this hypothesis by comparing comprehension of novel, conventional, and frozen action and non-action metaphors in 14 right-handed adults with right-sided mild to moderate paresis following left hemisphere motor stroke and 23 neurotypical participants. Consistent with our hypothesis, results indicated that only in the stroke group, accuracy for action metaphors was significantly lower than for non-action metaphors. Further, in the stroke group, accuracy was significantly worse in the following pattern: novel&nbsp;&lt;&nbsp;conventional&nbsp;&lt;&nbsp;frozen action metaphors. These results strongly support the notion that motor-related brain regions are important not only for literal action-related language comprehension, but also for action-related metaphor comprehension, especially for less familiar metaphors

Decoding Autism (vs. TD and DCD)

Test whether sensory and motor features improve upon original RDoC constructs in decoding youth with ASD from typically developing controls and those with motor deficits

Motor signature differences between autism spectrum disorder and developmental coordination disorder, and their neural mechanisms

Purpose: Autism spectrum disorder (ASD) and Developmental Coordination Disorder (DCD) are distinct clinical groups with overlapping motor features. We attempted to 1) differentiate children with ASD from those with DCD, and from those typically developing (TD) (ages 8-17; 18 ASD, 16 DCD, 20 TD) using a 5-minute coloring game on a smart tablet and 2) identify neural correlates of these differences. Methods: We utilized standardized behavioral motor assessments (e.g. fine motor, gross motor, and balance skills) and video recordings of a smart tablet task to capture any visible motor, behavioral, posture, or engagement differences. We employed machine learning analytics of motor kinematics during a 5-minute coloring game on a smart tablet. Imaging data was captured using functional magnetic resonance imaging (fMRI) during action production tasks. Results: While subject-rated motor assessments could not differentiate the two clinical groups, machine learning computational analysis provided good predictive discrimination: between TD and ASD (76% accuracy), TD and DCD (78% accuracy), and ASD and DCD (71% accuracy). Two kinematic markers which strongly drove categorization were significantly correlated with cerebellar activity. Conclusion: Findings demonstrate unique neuromotor patterns between ASD and DCD relate to cerebellar function and present a promising route for computational techniques in early identification. These are promising preliminary results that warrant replication with larger samples

Sensory Modulation in Children with Developmental Coordination Disorder Compared to Autism Spectrum Disorder and Typically Developing Children

Developmental Coordination Disorder (DCD) is one of the least studied and understood developmental disorders. One area that has been minimally investigated in DCD is potential issues with sensory modulation. Further, in other neurodevelopmental disorders (e.g., autism spectrum disorder (ASD)) sensory modulation is related to many other challenges (e.g., social issues, repetitive behaviors, anxiety); however, such potential relationships in children with DCD have been largely unexplored. The purpose of this study is to explore sensory modulation differences in DCD and to understand the relationships between sensory modulation and social emotional measures, behavior, and motor skills in DCD in comparison to ASD and typically developing (TD) peers. Participants (aged 8&ndash;17) and their caregivers (DCD, N = 26; ASD, N = 57; and TD, N = 53) completed behavioral and clinical measures. The results indicated that 31% of the DCD group showed sensory modulation difficulties, with the DCD group falling between the ASD and TD groups. In the DCD group, sensory modulation was significantly associated with anxiety, empathic concern, repetitive behaviors, and motor skills. Data are compared to patterns seen in ASD and TD groups and implications for interventions are discussed

Factors Influencing Receipt and Type of Therapy Services in the NICU

Understanding the type and frequency of current neonatal intensive care unit (NICU) therapy services and predictors of referral for therapy services is a crucial first step to supporting positive long-term outcomes in very preterm infants. This study enrolled 83 very preterm infants (<32 weeks, gestational age mean 26.5 ± 2.0 weeks; 38 male) from a longitudinal clinical trial. Race, neonatal medical index, neuroimaging, and frequency of therapy sessions were extracted from medical records. The Test of Infant Motor Performance and the General Movement Assessment were administered. Average weekly sessions of occupational therapy, physical therapy, and speech therapy were significantly different by type, but the magnitude and direction of the difference depended upon the discharge week. Infants at high risk for cerebral palsy based on their baseline General Movements Assessment scores received more therapy sessions than infants at low risk for cerebral palsy. Baseline General Movements Assessment was related to the mean number of occupational therapy sessions but not physical therapy or speech therapy sessions. Neonatal Medical Index scores and Test of Infant Motor Performance scores were not predictive of combined therapy services. Medical and developmental risk factors, as well as outcomes from therapy assessments, should be the basis for referral for therapy services in the neonatal intensive care unit

Effect of a NICU to Home Physical Therapy Intervention on White Matter Trajectories, Motor Skills, and Problem-Solving Skills of Infants Born Very Preterm: A Case Series

Infants born very preterm (VPT; &le;29 weeks of gestation) are at high risk of developmental disabilities and abnormalities in neural white matter characteristics. Early physical therapy interventions such as Supporting Play Exploration and Early Development Intervention (SPEEDI2) are associated with improvements in developmental outcomes. Six VPT infants were enrolled in a randomised clinical trial of SPEEDI2 during the transition from the neonatal intensive care unit to home over four time points. Magnetic resonance imaging scans and fixel-based analysis were performed, and fibre density (FD), fibre cross-section (FC), and fibre density and cross-section values (FDC) were computed. Changes in white matter microstructure and macrostructure were positively correlated with cognitive, motor, and motor-based problem solving over time on developmental assessments. In all infants, the greatest increase in FD, FC, and FDC occurred between Visit 1 and 2 (mean chronological age: 2.68&ndash;6.22 months), suggesting that this is a potential window of time to optimally support adaptive development. Results warrant further studies with larger groups to formally compare the impact of intervention and disparity on neurodevelopmental outcomes in infants born VPT