The ability to synchronize movements with sounds is a complex behavior dependent on predicting the occurrence of future sounds. Simulation theories of musical beat perception posit the motor system contributing predictive information to the processing of auditory streams. In this study, we compared neural responses while subjects drummed or listened to rhythmic hand drumming. It was hypothesized that if the motor system is involved in auditory perception, then a similar pattern of motor system engagement via the beta band (20-30 Hz) of brain oscillations during both movement and listening activities would occur. We found evidence in partial support of the hypothesis, though results must be judged carefully in the context of past work based on finger tapping, given the relative complexity in motor programs for drumming versus tapping. We also found differences in mu rhythm (8-13 Hz) power while drumming, which is associated with drumming expertise. Experienced drummers exhibited a significantly reduced amount of mu power while drumming compared to listening to drums, whereas novice drummers enhanced their mu power while playing drums, relative to listening. This suggests a more efficient use of cortical resources by experienced brains.

How do we can synchronize our movements to sounds? Before a musical ensemble begins, members will often count aloud, or otherwise synchronize their timing. Guitarist duos listening to a metronome before playing demonstrated an increase in inter-brain phase coherence during this synchronizing phase. The auditory system is preferential for synchronizing movements over the visual system and dynamically modulates communication models with the motor system in pianists. Listening to sounds can stimulate movement, even showing increased walking velocity in those with difficulties moving due to Parkinson's disease. Many concert or club goers can attest to the ease which music can stimulate rhythmic movement, from dancing to head nodding and foot tapping. Listening to music without movement can even stimulate activity in motor cortices when listening to familiar action-related sounds sans movement. Given these findings, the motor system may play a role in predicting the occurrence of sounds through a simulation model. Past work demonstrated entrainment of brain waves showing responses to rhythmic sounds, even when an expected sound is omitted. The brain rhythms involved in responses to expected and missing sounds occupy the same frequency range as brain rhythms involved in motor planning and execution in macaques.

Five students from UCSD and five drummers from the San Diego area were recruited for participation (mean age 26.5 years, SD=5.9, five females, two left-handed). All drummers had at least two years of professional experience playing hand drums, and reported previous familiarity with Afro-Brazilian rhythms. Each subject was shown how to play the drum rhythm after initial consent, and had to demonstrate ability to retain the rhythm and play the correct beats with the correct hands after filling out initial questionnaires. Subjects signed consent for procedures that were approved by the UCSD Institutional Review Board. This study used a variation of a hand drum rhythm belonging to a family derived from Yoruban religious rituals called ’Ijexa.’ This rhythm was chosen partially for the ease of play for novice drummers, and also because it includes right and left handed hits, which should aid in identification of motor processes versus auditory processes based on hemispheric differences in the brain responses.

The notes are spaced unevenly which should allow for identification of brainwave components associated with individual drum hits. Little is written about this rhythm as it is part of an oral tradition. This oral method of transmitting the rhythm also results in multiple variations of the rhythm, all using the same name. In this particular instance, subjects would play three drum hits with the right hand, and one hit with the left hand. A ‘differential drum interval’ (DDI) score was calculated for each subject, which was the sum of the absolute value of the difference between the recorded stimulus drum intervals, and the observed drum intervals. This provided a single score for each movement condition (play vs solo) and each trial block (first vs second). A repeated measures ANOVA with factors of condition (2) and trial (2) with between subject factor of drumming experience and Bonferoni Correction revealed a main effect of condition that approached significance (F(1,8)=3.62, p=0.094), but not for trial (F(1,8)=2.35, p=0.16). Subjects drummed with greater accuracy (smaller deviations from expected intervals) during the play along condition with smaller variability (M=41.4, SD=4.2), than during the self-paced solo condition (M=57.9, SD=9.2). Subjects also showed a small improvement in drumming between the first (M=52.7, SD=6.2) and the second block (M=46.6, SD=5.9). While drummers performed better in terms of DDI than inexperienced drummers (M(drummer)=45.9 msec, SD=8.1, M(novice)=53 msec, SD=8.1), the interactions between experience and condition (F(1,8)=0.23, p=0.65), trial (F(1,8)=0.41, p=0.54), and condition*trial (F(1,8)=1.52, p=0.25) were not significant.

Warm Regards,
Joseph Kent
Journal Manager
Journal of Brain Behaviour & Cognitive Sciences