RESUMEN
Aim: Autism spectrum disorder (ASD) is a neurodevelopmental disorder that is thought to involve a variety of neurophysiological characteristics. Event-related potentials (ERPs) reflect cognitive functions in the brain's cognitive processing. In this study, we investigated differences in P300 and N100 of ERPs between ASD and typically developing groups and focused on the relationship between the components of ERPs and measures of autistic traits and sensory processing characteristics. Methods: ERPs were measured in 96 subjects in the ASD group and 62 subjects in the age- and sex-adjusted typically developing group. Correlations between each component and the scores of the Autism-Spectrum Quotient Japanese version (AQ-J) and the Adolescent and Adult Sensory Profile (AASP) were also evaluated. Results: The ASD group showed a significant decrease in the amplitude of N100 at C3. Furthermore, a negative correlation was found between lower amplitude at C3 of N100 and low registered sensory scores in both groups. Conclusion: Our findings imply that the N100 amplitude at C3 could be a potential indicator for examining the neurophysiological traits of ASD; however, these results should be interpreted with caution due to their preliminary nature. These tentative insights into sensory processing anomalies may be discernible in specific subsets of the ASD population, providing a foundation for future investigative pathways.
RESUMEN
BACKGROUND: Schizophrenia is a complex mental disorder characterized by significant cognitive and neurobiological alterations. Impairments in cognitive function and eye movement have been known to be promising biomarkers for schizophrenia. However, cognitive assessment methods require specialized expertise. To date, data on simplified measurement tools for assessing both cognitive function and eye movement in patients with schizophrenia are lacking. OBJECTIVE: This study aims to assess the efficacy of a novel tablet-based platform combining cognitive and eye movement measures for classifying schizophrenia. METHODS: Forty-four patients with schizophrenia, 67 healthy controls, and 41 patients with other psychiatric diagnoses participated in this study from 10 sites across Japan. A free-viewing eye movement task and 2 cognitive assessment tools (Codebreaker task from the THINC-integrated tool and the CognitiveFunctionTest app) were used for conducting assessments in a 12.9-inch iPad Pro. We performed comparative group and logistic regression analyses for evaluating the diagnostic efficacy of the 3 measures of interest. RESULTS: Cognitive and eye movement measures differed significantly between patients with schizophrenia and healthy controls (all 3 measures; P<.001). The Codebreaker task showed the highest classification effectiveness in distinguishing schizophrenia with an area under the receiver operating characteristic curve of 0.90. Combining cognitive and eye movement measures further improved accuracy with a maximum area under the receiver operating characteristic curve of 0.94. Cognitive measures were more effective in differentiating patients with schizophrenia from healthy controls, whereas eye movement measures better differentiated schizophrenia from other psychiatric conditions. CONCLUSIONS: This multisite study demonstrates the feasibility and effectiveness of a tablet-based app for assessing cognitive functioning and eye movements in patients with schizophrenia. Our results suggest the potential of tablet-based assessments of cognitive function and eye movement as simple and accessible evaluation tools, which may be useful for future clinical implementation.