Feasibility of clinical EEG for music recognition in children aged 1-12 years

Musicality is an innate capability and the fundamental architectures necessary for music processing are present from birth. However, there is a notable gap in pediatric specific music neuroscience research and research that employs ecologically valid musical stimuli.

This pragmatic feasibility study aimed to assess the utility of EEG collected via pre-existing clinical monitoring to describe the processing of familiar song as an ecologically valid stimulus, in the underrepresented pediatric population. Three comparative auditory conditions (song, speech, and noise) were utilized to assess the changes in EEG across these conditions compared to a baseline silence.

Analysis of EEG data from a pilot sample of four children revealed distinct changes in the underlying frequency components of the EEG during the song condition that were not observed in either the speech or noise conditions. To extend this analysis, a uniquely hypothesis-driven, multivariate statistical analysis method (generalized eigendecomposition [GED]) was employed, however in this study we did not isolate a consistent source responsible for the observed changes in the frequency components of the EEG during the song condition.

The study is limited by the small sample size but nevertheless demonstrated feasibility of collecting EEG data in the imperfect auditory environment of an acute clinical setting to describe a response to an ecologically valid stimulus in the underrepresented pediatric population. Further research with a more restrictive study design and greater participant numbers is needed to extend these preliminary findings.