The impact of imitation on engagement in minimally verbal children with autism during improvisational music therapy

A review of artificial intelligence methods enabled music-evoked EEG emotion recognition and their applications

Music is an archaic form of emotional expression and arousal that can induce strong emotional experiences in listeners, which has important research and practical value in related fields such as emotion regulation. Among the various emotion recognition methods, the music-evoked emotion recognition method utilizing EEG signals provides real-time and direct brain response data, playing a crucial role in elucidating the neural mechanisms underlying music-induced emotions. Artificial intelligence technology has greatly facilitated the research on the recognition of music-evoked EEG emotions. AI algorithms have ushered in a new era for the extraction of characteristic frequency signals and the identification of novel feature signals. The robust computational capabilities of AI have provided fresh perspectives for the development of innovative quantitative models of emotions, tailored to various emotion recognition paradigms. The discourse surrounding AI algorithms in the context of emotional classification models is gaining momentum, with their applications in music therapy, neuroscience, and social activities increasingly coming under the spotlight. Through an in-depth analysis of the complete process of emotion recognition induced by music through electroencephalography (EEG) signals, we have systematically elucidated the influence of AI on pertinent research issues. This analysis offers a trove of innovative approaches that could pave the way for future research endeavors.

Integrated parent-child music classes for preschoolers with and without autism: Parent expectations and experiences

Integrated recreational programs designed to support neurodiverse children and their families are important vehicles for community participation. In this mixed-methods study, we investigated the mechanisms by which parent-child music classes for autistic and neurotypical children can support community participation. Parents of autistic (n = 33) and typically developing (TD; n = 28) preschoolers were interviewed about their expectations for and experiences of participating in a 12-week psychoeducational parent-child music program. Parents completed ratings of momentary affect and social connection, and researchers coded children's behavioral engagement during classes at multiple time points throughout the program. Primary motivations for enrolling in an integrated music class included children's interest in music and opportunities for child socialization. Parent-focused reasons were less frequently endorsed as primary motivations for participation. Yet, momentary ratings indicated that music classes supported parents' affect regulation and social connection with other parents at the level of individual classes and across the program. These in-class experiences were echoed by interviews following program completion, which additionally highlighted the use of new parenting strategies through the musical activities. Since parental emotional experiences of activities, supportive community relationships, and parenting confidence are all linked with increased community participation, integrated music classes may support participation and satisfaction with community experiences.