The "sensory processing disorder" (SPD) refers to brain's inability to organize sensory input for appropriate use. In this study, we determined the diffusion tensor imaging (DTI) microstructural and connectivity correlates of SPD, and apply machine learning algorithms for identification of children with SPD based on DTI/tractography metrics. A total of 44 children with SPD and 41 typically developing children (TDC) were prospectively recruited and scanned.
View Article and Find Full Text PDFBackground: Sensory processing difficulties are common across neurodevelopmental disorders. Thus, reliable measures are needed to understand the biological underpinnings of these differences. This study aimed to define a scoring methodology specific to auditory (AOR) and tactile (TOR) over-responsivity.
View Article and Find Full Text PDFPrior neuroimaging studies have reported white matter network underconnectivity as a potential mechanism for autism spectrum disorder (ASD). In this study, we examined the structural connectome of children with ASD using edge density imaging (EDI), and then applied machine-learning algorithms to identify children with ASD based on tract-based connectivity metrics. Boys aged 8-12 years were included: 14 with ASD and 33 typically developing children.
View Article and Find Full Text PDFBackground: In children with sensory processing dysfunction (SPD), who do not meet criteria for autism spectrum disorder (ASD) or intellectual disability, the contribution of de novo pathogenic mutation in neurodevelopmental genes is unknown and in need of investigation. We hypothesize that children with SPD may have pathogenic variants in genes that have been identified as causing other neurodevelopmental disorders including ASD. This genetic information may provide important insight into the etiology of sensory processing dysfunction and guide clinical evaluation and care.
View Article and Find Full Text PDFObjective: Children with autism spectrum disorders (ASD) and sensory processing dysfunction (SPD) are reported to show difficulties involving cognitive and visuomotor control. We sought to determine whether performance on computerized, behavioral measures of cognitive control aimed at assessing selective attention, as well as visuomotor abilities differentiated children with ASD (n = 14), SPD (n = 14) and typically developing controls (TDC; n = 28).
Method: Cognitive control differences were measured by assessing selective attention-based abilities both with and without distracting stimuli, and visuomotor differences were measured by characterizing visuomotor tracking and tracing skills.
Children with Sensory Processing Dysfunction (SPD) experience incoming information in atypical, distracting ways. Qualitative challenges with attention have been reported in these children, but such difficulties have not been quantified using either behavioral or functional neuroimaging methods. Furthermore, the efficacy of evidence-based cognitive control interventions aimed at enhancing attention in this group has not been tested.
View Article and Find Full Text PDFSensory processing disorders (SPDs) affect up to 16% of school-aged children, and contribute to cognitive and behavioral deficits impacting affected individuals and their families. While sensory processing differences are now widely recognized in children with autism, children with sensory-based dysfunction who do not meet autism criteria based on social communication deficits remain virtually unstudied. In a previous pilot diffusion tensor imaging (DTI) study, we demonstrated that boys with SPD have altered white matter microstructure primarily affecting the posterior cerebral tracts, which subserve sensory processing and integration.
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