The neural response to the temporal fine structure of continuous musical pieces is not affected by selective attention

Abstract

Speech and music are spectro-temporally complex acoustic signals that a highly relevant for humans. Both contain a temporal fine structure that is encoded in the neural responses of subcortical and cortical processing centres. The subcortical response to the temporal fine structure of speech has recently been shown to be modulated by selective attention to one of two competing voices. Music similarly often consists of several simultaneous melodic lines, and a listener can selectively attend to a particular one at a time. However, the neural mechanisms that enable such selective attention remain largely enigmatic, not least since most investigations to date have focussed on short and simplified musical stimuli. Here we study the neural encoding of classical musical pieces in human volunteers, using scalp electroencephalography (EEG) recordings. We presented volunteers with continuous musical pieces composed of one or two instruments. In the latter case, the participants were asked to selectively attend to one of the two competing instruments and to perform a vibrato identification task. We used linear encoding and decoding models to relate the recorded EEG activity to the stimulus waveform. We show that we can measure neural responses to the temporal fine structure of melodic lines played by one single instrument, at the population level as well as for most individual subjects. The neural response peaks at a latency of 7.6 ms and is not measurable past 15 ms. When analysing the neural responses elicited by competing instruments, we find no evidence of attentional modulation. Our results show that, much like speech, the temporal fine structure of music is tracked by neural activity. In contrast to speech, however, this response appears unaffected by selective attention in the context of our experiment.

A Novel Computationally Efficient Approach for Exploring Neural Entrainment to Continuous Speech Stimuli Incorporating Cross-Correlation

“…These results indicated that the detrended cross-correlation can also effectively and comparably capture neural responses to long continuous speech. Recently, SI methods have been applied to investigate the neural source dynamics in response to continuous stimuli [38,39] and the neural response to the temporal fine structure of continuous stimuli [40]. However, the computational demands of these methods increase due to the significant large quantity of cortices at the source level or the necessity of a high sampling rate for temporal fine structure analysis.…”