Wen-Che Tsai

The deficit in social interaction skills among individuals with autism spectrum disorder (ASD) is strongly influenced by personal experiences and social environments. Neuroimaging studies have previously highlighted the link between social impairment and brain activity in ASD. This study aims to develop a method for assessing and identifying ASD using a social cognitive game-based paradigm combined with electroencephalography (EEG) signaling features. Typically developing (TD) participants and autistic preadolescents and teenagers were recruited to participate in a social game while 12-channel EEG signals were recorded. The EEG signals underwent preprocessing to analyze local brain activities, including event-related potentials (ERPs) and time-frequency features. Additionally, the global brain network's functional connectivity between brain regions was evaluated using phase-lag indices (PLIs). Subsequently, machine learning models were employed to assess the neurophysiological features. Results indicated pronounced ERP components, particularly the late positive potential (LPP), in parietal regions during social training. Autistic preadolescents and teenagers exhibited lower LPP amplitudes and larger P200 amplitudes compared to TD participants. Reduced theta synchronization was also observed in the ASD group. Aberrant functional connectivity within certain time intervals was noted in the ASD group. Machine learning analysis revealed that support-vector machines achieved a sensitivity of 100%, specificity of 91.7%, and accuracy of 95.8% as part of the performance evaluation when utilizing ERP and brain oscillation features for ASD characterization. These findings suggest that social interaction difficulties in autism are linked to specific brain activation patterns. Traditional behavioral assessments face challenges of subjectivity and accuracy, indicating the potential use of social training interfaces and EEG features for cognitive assessment in ASD.

Evaluation of cognitive function of autistic children after early intervention has become important for providing promising biomarkers to assess the improvement after cognitive intervention. In this study, we have developed a game-based platform with electroencephalography (EEG) signal recording to investigate gaze following in children. Typically developing (TD) children and children with autism spectrum disorder (ASD) were recruited to participate in the gaze-following game with 12-channel EEG signal recording; the corresponding brain oscillations, event-related potentials (ERP), and event-related spectral perturbations were analyzed. Brain functional connections were also evaluated with phase-lag indices (PLIs). The results showed that, relative to the TD children, autistic children had smaller N170, P3a, and late positive potential (LPP) during gaze following, suggesting that they ignored low-level features of social information. Further, autistic children showed increased alpha and beta desynchronization and decreased theta synchronization and functional connectivity. With the development of human-computer interface, physiological signals are essential in future implementation of game-based interfaces to further investigate underlying mechanisms and effective biomarkers. We have demonstrated the possibility of incorporating EEG signals measured by portable applications to evaluate cognitive and social performance in autistic children. This approach has superior flexibility compared with other neuroimaging techniques.

The design goals of recently developed serious games are to improve attention, affective recognition, and social interactions among individuals with autism. However, most previous studies on serious games used behavioral questionnaires to evaluate their effectiveness. The cognitive assessment of individuals with autism after behavioral intervention or drug treatment has become important because it provides promising biomarkers to assess improvement after cognitive intervention. In this study, we developed a game-based social interaction platform incorporating an eye-tracking system for children and preadolescents with autism. Three modules (focusing on gaze following, facial emotion recognition, and social interaction skills) are included in the platform; participants with autism learn these according to their cognitive abilities. The eye-tracking results showed decreased fixation durations when autistic children looked at positive emotional expressions and focused on multiple targets. Prolonged saccade durations and shorter fixation times for social-related facial emotion expressions were also found in preadolescents and teenagers with autism. Our findings suggest that these atypical gaze patterns are reliable biomarkers for evaluating the social and cognitive functions of autistic individuals while playing serious games. The proposed platform’s game-based modules and the findings regarding aberrant gaze patterns in autistic individuals demonstrate the possibility of evaluating cognitive functions and intervention effectiveness by using eye-tracking signals in a serious game or real-life environment.

We compared the maternal reports on mothering and family processes between 160 youth with autism spectrum disorder (ASD) and 160 age and gender-matched typically developing (TD) youth stratified by personal characteristics from Taiwan. The ASD groups consisted of 51 ‘typical autism’ (TA), 52 ‘high-functioning autism’ (HFA), and 57 ‘Asperger syndrome (AS).’ Maternal reports showed that youth with ASD obtained less affection and more protection from the mother, and had less active mother-child interactions and more behavioral problems at home. Their mothers perceived less family support when compared to mothers of TD youth. Moreover, both TA and AS groups had more maternal protection and less maternal perceived family support, whereas HFA and co-occurring ADHD were only associated with more behavioral problems at home. The maternal and family process may vary across different ASD subgroups.

Objectives: This study investigated the associations of cognitive status with specific/overall health-related quality of life (HRQoL) in older stroke survivors in Taiwan. Method: A subsample of 592 older stroke survivors in a nationwide population-based survey of cognitive-dysfunction prevalencewas analyzed. HRQoL was assessed using the EuroQol five-dimension questionnaire (EQ-5D). Results: Stroke survivors with dementia were 5.60 times more likely to have mobility problems, 12.20 times to have self-care problems, 16.61 times to have problems in usual activities, 4.31 times to have pain/discomfort, and 3.28 times to have anxiety/depression than stroke survivors with normal cognitive function. Stroke survivors with mild cognitive dysfunction (MCD) were 2.57 times more likely to have mobility problems, 3.17 times to have self-care problems, 3.31 times to have problems in usual activities, 2.11 times to have pain/discomfort, and 2.35 times to have anxiety/depression than those with normal cognitive function. Both dementia (b = −15.13, p < .001) and MCD (b = −6.24, p < .001) significantly contributed to lower EQ-5D VAS; both dementia (b = −.15, p < .001) and MCD (b = −.10, p < .001) significantly contributed to lower EQ-5D index. Conclusion: Dementia and MCD strongly predicted worse overall and specific HRQoL dimensions, especially self-care and usual activities for older stroke survivors.

Rare genomic copy number variations (CNVs) (frequency <1%) contribute a part to the genetic underpinnings of autism spectrum disorders (ASD). The study aimed to understand the scope of rare CNV in Taiwanese patients with ASD. We conducted a genome-wide CNV screening of 335 ASD patients (299 males, 36 females) from Taiwan using Affymetrix Genome-Wide Human SNP Array 6.0 and compared the incidence of rare CNV with that of 1093 control subjects (525 males, 568 females). We found a significantly increased global burden of rare CNVs in the ASD group compared to the controls as a whole or when the rare CNVs were classified by the size and types of CNV. Further analysis confirmed the presence of several rare CNVs at regions strongly associated with ASD as reported in the literature in our sample. Additionally, we detected several new private pathogenic CNVs in our samples and five patients carrying two pathogenic CNVs. Our data indicate that rare genomic CNVs contribute a part to the genetic landscape of our ASD patients. These CNVs are highly heterogeneous, and the clinical interpretation of the pathogenic CNVs of ASD is not straightforward in consideration of the incomplete penetrance, varied expressivity, and individual genetic background.