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Background: To gain a comprehensive understanding of the altered sensory processing in patients with migraine, in this study, we developed an electroencephalography (EEG) protocol for examining brainstem and cortical responses to sensory stimulation. Furthermore, machine learning techniques were employed to identify neural signatures from evoked brainstem–cortex activation and their interactions, facilitating the identification of the presence and subtype of migraine. Methods: This study analysed 1,000-epoch-averaged somatosensory evoked responses from 342 participants, comprising 113 healthy controls (HCs), 106 patients with chronic migraine (CM), and 123 patients with episodic migraine (EM). Activation amplitude and effective connectivity were obtained using weighted minimum norm estimates with spectral Granger causality analysis. This study used support vector machine algorithms to develop classification models; multimodal data (amplitude, connectivity, and scores of psychometric assessments) were applied to assess the reliability and generalisability of the identification results from the classification models. Results: The findings revealed that patients with migraine exhibited reduced amplitudes for responses in both the brainstem and cortical regions and increased effective connectivity between these regions in the gamma and high-gamma frequency bands. The classification model with characteristic features performed well in distinguishing patients with CM from HCs, achieving an accuracy of 81.8% and an area under the curve (AUC) of 0.86 during training and an accuracy of 76.2% and an AUC of 0.89 during independent testing. Similarly, the model effectively identified patients with EM, with an accuracy of 77.5% and an AUC of 0.84 during training and an accuracy of 87% and an AUC of 0.88 during independent testing. Additionally, the model successfully differentiated patients with CM from patients with EM, with an accuracy of 70.5% and an AUC of 0.73 during training and an accuracy of 72.7% and an AUC of 0.74 during independent testing. Conclusion: Altered brainstem-cortex activation and interaction are characteristic of the abnormal sensory processing in migraine. Combining evoked activity analysis with machine learning offers a reliable and generalisable tool for identifying patients with migraine and for assessing the severity of their condition. Thus, this approach is an effective and rapid diagnostic tool for clinicians. [ABSTRACT FROM AUTHOR]

Emotion dysregulation is one of the challenges that children with autism spectrum disorder (ASD) and their families face. It is unclear whether emotion dysregulation plays a mediating role in the relationship between sensory processing patterns and problem behaviors among these children. This study examined the relations between emotion dysregulation, behavioral problems, and sensory processing patterns among fifty-seven young children with ASD. Behavioral problems and sensory processing patterns were moderately to strongly correlated with emotion dysregulation. The relationship between sensory processing patterns and behavioral problems was significant with emotion dysregulation as a mediator. These findings help identify the relationship between emotion dysregulation, sensory processing patterns, and behavioral problems to facilitate the planning of intervention strategies for young children with ASD. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to investigate the sensory integration and perceptual-motor performances in elementary school children (5– 12 years) with autistic spectrum disorder (ASD) in Taiwan. The impacts of comprehensive body functions on activity participations in ASD were also investigated to provide evidence for clinical applications and further study. Methods: One hundred and seventeen children with ASD (42 females; aged 5– 13 years, average age 8 years 3 months) were recruited. All participants were assessed with standardized measures of body functions and activity participations. The body function measures included Bruininks–Oseretsky of Motor Proficiency – Second Edition, Sensory Profile, Test of Sensory Integration Functions, and Test of Visual Perception Skills – Third Edition. The activity participation measures included the Chinese versions of both Vineland Adaptive Behavior Scale and School Function Assessment. Results: School-aged children with ASD had different levels of impairments on body function measures. Most participant scores fell within the impairment range on 13 to 15 items out of the total 19 sensory and perceptual-motor measure subtests, with worst performance on coordination-related motor task and most sensory integrative dimensions. The results indicated a significant main effect for age and sex on some body functions and activity participations. Correlation analyses indicated strong associations between body function and activity participation across settings in ASD. Conclusion: Our findings characterized the developmental continuum of body functions of school-aged children with ASD and showed their associations with adaptation and participation. While emphasizing the development of functional skills to facilitate age-appropriate activity participation in multiple scenarios, interventions aiming to improve body functions are indispensable. [ABSTRACT FROM AUTHOR]

OBJECTIVE. To compare stance control between children with sensory modulation disorder (SMD) and typically developing children in various visual and somatosensory conditions. METHOD. Thirty-one children participated in this study, including 17 children with SMD and 14 matched typically developing children. The Sensory Profile was used to screen for sensory modulation problems, which were further confirmed by measures of electrodermal response and the Evaluation of Sensory Processing. Stance parameters for an assessment of postural stability were obtained with a dual-axis accelerometer on the lumbar area. RESULTS. The children with SMD presented atypical sensory responses in terms of both electrophysiological and behavioral measures. The results for stance showed a greater body sway in the SMD group than in the control group (p < .05). However, the group difference was not always significant under the conditions of reliable somatosensory input and sway-referenced vision. CONCLUSION. Our findings first confirmed impaired stance control in children with SMD. [ABSTRACT FROM AUTHOR]