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Developmental coordination disorder (DCD) presents challenges in motor control. DCD affects tasks such as walking and running and is characterized by poor interlimb coordination and increased spatiotemporal variability compared to typically developing children (TDC). While auditory rhythm synchronization has shown to have benefits for gait performance in adults, its impact on children with DCD during walking and running remains unclear. This study investigated auditory–motor synchronization and interlimb coordination during walking and running in children with and without DCD. Twenty‐one DCD and 23 TDC participants aged 8−12 years walked and ran to two different auditory metronomes (discrete and continuous). Synchronization consistency was the primary outcome, with interlimb coordination and spatiotemporal variability as secondary outcomes. Results showed that children with DCD exhibited significantly lower synchronization consistency than TDC, particularly during running. The metronome structure did not influence synchronization ability. Additionally, interlimb coordination differed significantly between DCD and TDC during running and was not impacted by auditory–motor synchronization. Spatiotemporal variability was higher in DCD during both walking and running than in TDC, and accentuated during running. Variability of cadence was influenced by the use of continuous metronomes, which may offer potential benefits in reducing cadence variability. [ABSTRACT FROM AUTHOR]

Pupil size covaries with the diffusion rate of the cholinergic and noradrenergic neurons throughout the brain, which are essential to arousal. Recent findings suggest that slow pupil fluctuations during locomotion are an index of sustained activity in cholinergic axons, whereas phasic dilations are related to the activity of noradrenergic axons. Here, we investigated movement induced arousal (i.e., by singing and swaying to music), hypothesising that actively engaging in musical behaviour will provoke stronger emotional engagement in participants and lead to different qualitative patterns of tonic and phasic pupil activity. A challenge in the analysis of pupil data is the turbulent behaviour of pupil diameter due to exogenous ocular activity commonly encountered during motor tasks and the high variability typically found between individuals. To address this, we developed an algorithm that adaptively estimates and removes pupil responses to ocular events, as well as a functional data methodology, derived from Pfaffs' generalised arousal, that provides a new statistical dimension on how pupil data can be interpreted according to putative neuromodulatory signalling. We found that actively engaging in singing enhanced slow cholinergic‐related pupil dilations and having the opportunity to move your body while performing amplified the effect of singing on pupil activity. Phasic pupil oscillations during motor execution attenuated in time, which is often interpreted as a measure of sense of agency over movement. [ABSTRACT FROM AUTHOR]

In this perspective paper, we explore the use of haptic feedback to enhance human-human interaction during musical tasks. We start by providing an overview of the theoretical foundation that underpins our approach, which is rooted in the embodied music cognition framework, and by briefly presenting the concepts of action-perception loop, sensorimotor coupling and entrainment. Thereafter, we focus on the role of haptic information in music playing and we discuss the use of wearable technologies, namely lightweight exoskeletons, for the exchange of haptic information between humans. We present two experimental scenarios in which the effectiveness of this technology for enhancing musical interaction and learning might be validated. Finally, we briefly discuss some of the theoretical and pedagogical implications of the use of technologies for haptic communication in musical contexts, while also addressing the potential barriers to the widespread adoption of exoskeletons in such contexts. [ABSTRACT FROM AUTHOR]

Within the broader context of improving interactions between artificial intelligence and humans, the question has arisen regarding whether auditory and rhythmic support could increase attention for visual stimuli that do not stand out clearly from an information stream. To this end, we designed an experiment inspired by pip-and-pop but more appropriate for eliciting attention and P3a-event-related potentials (ERPs). In this study, the aim was to distinguish between targets and distractors based on the subject's electroencephalography (EEG) data. We achieved this objective by employing different machine learning (ML) methods for both individual-subject (IS) and cross-subject (CS) models. Finally, we investigated which EEG channels and time points were used by the model to make its predictions using saliency maps. We were able to successfully perform the aforementioned classification task for both the IS and CS scenarios, reaching classification accuracies up to 76%. In accordance with the literature, the model primarily used the parietal–occipital electrodes between 200 ms and 300 ms after the stimulus to make its prediction. The findings from this research contribute to the development of more effective P300-based brain–computer interfaces. Furthermore, they validate the EEG data collected in our experiment. [ABSTRACT FROM AUTHOR]