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This study proposes a quantitative evaluation support system for infant motor development and uses the system to analyze hands-and-knees creeping and belly crawling. This system measures movements using two video cameras and extracts movement features via background and inter-frame subtractions of original images. Eight evaluation indices for each crawling cycle are calculated, enabling markerless movement analysis of infants. Cross-sectional analysis of 16 10-month-olds confirmed significant differences between hands-and-knees creeping and belly crawling in five of the eight indices, demonstrating the system capability to quantitatively differentiate between creeping and crawling. Longitudinal analysis of one infant (aged 7–10 months) also suggested that the proposed quantitative indices can follow changes in crawling characteristics and evaluate infants’ motor development process. The results from the experiments suggest that the proposed system may enable diagnosis support in clinical practice.

Various attempts have been made to elucidate the development patterns in the spontaneous movements of infants through longitudinal evaluations. Movement complexity has been found to demonstrate u-shaped changes in the measurements focusing on limb movements. However, researchers have not yet clarified how other characteristics, besides movement complexity, change over time. This paper presents a longitudinal evaluation of spontaneous movements in infants using evaluation indices calculated through markerless video analysis. Nine infants with corrected ages from $$-1$$ - 1 to 15 weeks participated in the experiments. We confirmed the change in indices over time using statistical methods. Index changes can be classified as positively correlated, u-shaped, inverted u-shaped, and uncorrelated. We also confirmed that the u-shaped and inverted u-shaped indices are negatively correlated. Furthermore, the principal component analysis revealed that the first principal component had the inverted u-shaped changes with the corrected age. These results suggest that it is important to synchronize the inverted u-shaped variations in the movement and velocity with the u-shaped changes in the movement complexity for infant development.

Increasing evidence suggests that epigenetic mechanisms play a role in the etiology of autism spectrum disorder (ASD). To date, several studies have attempted to identify epigenetic biomarkers for ASD. However, reliable markers remain to be established and most of these studies have focused on pediatric patients with ASD. In this study, we sought to find an epigenetic DNA methylation biomarker from peripheral blood for adult patients with high-functioning ASD. DNA methylation profiles were analyzed using the Illumina 450 K methylation array. To identify robust candidate markers, we employed two types of machine-learning algorithms for marker selection. We identified a potential marker (cg20793532) for which is the AUC value was 0.79. Notably, cg20793532 was annotated to the PPP2R2C gene, which was hypermethylated and down-regulated in blood from ASD patients compared to that in the controls. Although requiring careful interpretation, this pilot study seems to provide a potential blood biomarker for identifying individuals with high-functioning ASD.

Autism is characterized by two primary characteristics: deficits in social interaction and repetitive behavioral patterns. Because interpersonal communication is extremely complicated, its underlying brain mechanisms remain unclear. Here we showed that both characteristics can be explained by a unifying underlying mechanism related to difficulties with irregularities. To address the issues, we measured electroencephalographm during a cooperative tapping task, which required participants to tap a key alternately and synchronously with constant rhythmic a PC program, a variable rhythmic PC program, or a human partner. We found that people with autism had great difficulty synchronizing tapping behavior with others, and exhibited greater than normal theta-wave (6 Hz) activity in the frontal cortex during the task, especially when their partner behaved somewhat irregularly (i.e. a variable rhythmic PC program or a human partner). Importantly, the higher theta-wave activity was related to the severity of autism, not the performance on the task. This indicates that people with autism need to use intense cognition when trying to adapt to irregular behavior and can easily become overtaxed. Difficulty adapting to irregular behavior in others is likely related to their own tendencies for repetitive and regular behaviors. Thus, while the two characteristics of autism have been comprehended separately, our unifying theory makes understanding the condition and developing therapeutic strategies more tractable., 自閉スペクトラム症者のコミュニケーション障害に関する新たな視点 --最新の脳波技術を用いた科学的根拠による理解の促進--. 京都大学プレスリリース. 2017-11-10.