Discussion and Conclusion
We hypothesised that participants with better working memory are less affected by delayed auditory feedback during musical performance. Our results tentatively support our hypothesis. A moderate negative correlation was found between DAF effect and N-back task accuracy which was significant at p = .044. Moreover, a multiple linear regression with DAF effect as the dependent variable found that N-back task accuracy was the predictor with the greatest effect size and the only predictor to reach statistical significance with p = .029, although the model itself was not significant. N-back reaction time, by contrast, did not appear to exhibit a relationship with DAF effect, nor did any of our other recorded variables (sex, dominant hand, ability to read music, piano playing, years of musical instruction, reference tempo).
Although our results certainly point towards a relationship between working memory and DAF effect, it is disappointing that many of our main findings did not reach significance at p < .05. Owing to the Covid-19 pandemic of 2020, we had access to a limited participant pool, resulting in N = 23, of which only half were piano players. To the best of our knowledge, all prior studies utilising a DAF-piano paradigm recruited only experienced piano players, for instance “students majoring in instrumental music education” (Havlicek, 1968, p. 311). Although we attempted to design a musical performance task suitable for complete novices, we cannot rule out a learning effect that may have interacted with our experiment, nor can we rule out a three-way interaction between DAF effect, prior piano playing ability, and working memory. Indeed, as a post hoc analysis, we ran a correlation between DAF effect and N-back accuracy separately for pianists and non-pianists. Both the correlation coefficient and significance level were weaker for non-pianists than for pianists (rpianists = -.46, rnon-pianists = -.21; ppianists = .068, pnon-pianists = .264), and it is regrettable that more pianists were not available for recruitment to this study. Moreover, the inclusion of both pianists and non-pianists meant that performance tempo was highly variable, ranging from 60 to 110 beats per minute. Finney and Warren (2002) found that the maximal impairment delay is dependent on performance rate; however, the present study takes 250 ms to be the peak impairment interval for all participants.
It is also interesting to note that DAF effect correlated significantly with N-back accuracy but not with N-back reaction time, despite both purporting to be measures of working memory. Although researchers have been using the N-back test extensively as a working memory paradigm since the 1960s, more recent validation studies have cast doubt on the N-back test as a measure of individual differences in working memory (Jaeggi et al., 2010).
Our results are in line with previous research indicating a relationship between working memory and sensorimotor integration of speech production (e.g. Guo et al., 2017; Li et al., 2015). However, ours is the first study to investigate working memory and sensorimotor integration with a DAF-musical performance paradigm. The results appear to support the model proposed by Guo et al. (2017) whereby working memory exerts a top-down influence on sensorimotor integration, possibly by facilitating the processing of feedback errors and inhibiting compensatory adjustments to altered feedback. That being said, it is not a given that the mechanisms and pathways of sensorimotor integration of speech production correspond to that of musical performance. For one, musical performance also relies on visual and tactile feedback, although the available research does indicate that the auditory system is dominant in this regard (Comstock et al., 2018). Nevertheless, the interactions between auditory, visual, and tactile systems on the sensorimotor integration of musical performance is underexplored, and further research in this area is needed to answer these questions.