Differential motor system entrainment to auditory and visual rhythms.

Abstract

Perception of, and synchronization to, auditory rhythms is known to be more accurate than with flashing visual rhythms. The motor system is known to play a role in the processing of timing information for auditory rhythm perception, but it is unclear if the motor system plays the same role for visual rhythm perception. One demonstrated component of auditory rhythm perception is neural entrainment at the frequency of the auditory rhythm. In this study, we use EEG to measure the entrainment of both auditory and visual rhythms from the motor cortex while subjects either tapped in synchrony with or passively attended to the presented rhythms. To isolate activity from motor cortex, we used independent component analysis to first separate out neural sources, then selected components using a combination of component topography, dipole location, mu activation, and beta modulation. This process took advantage of the fact that tapping activity results in reduced mu power, and characteristic beta modulation, which helped select motor components. Our findings suggest neural entrainment in motor components was stronger for visual rhythms than auditory rhythms and strongest during the tapping conditions for both modalities. We also find mu power increased in response to both auditory and visual rhythms. These findings indicate that the generally greater rhythm perception capabilities of the auditory system over the visual system may not depend entirely on neural entrainment in the motor system, but rather how the motor system is able to use the timing information made available to it. NEW & NOTEWORTHY We investigated neural entrainment in the motor system for both auditory and visual isochronous rhythms using electroencephalogram. Counter to expectations, our findings suggest stronger entrainment for visual rhythms than for auditory rhythms. Motor system activity was isolated with a novel procedure using independent component analysis as a means of blind source separation, along with known markers of mu activity from the motor system to identify motor components.