Predictive Neural Dynamics for Musical Beat Perception
A central focus of this work is on understanding how and why human brain networks used for control of body movements are affected by and involved with sound perception. We explore the role of prediction and motor simulation in musical rhythm perception and test the proposed networks for predictive timing perception in humans. Our data support that the dorsal auditory stream, connecting premotor to auditory cortex through parietal projections, is critically involved in accurate phase timing when listening to music.
 Ross, J.M., Comstock, D., Iversen, J.R., Makeig, S., & Balasubramaniam, R. (2022). Cortical mu rhythms during action and passive music listening. Journal of Neurophysiology, 127, 213-224.
 Comstock, D., Ross, J., & Balasubramaniam, R. (2021). Modality-specific frequency band activity during neural entrainment to auditory and visual rhythms. European Journal of Neuroscience, 54(2), 4649-4669.
 Ross, J.M. & Balasubramaniam, R. (2022). Time perception for musical rhythms: sensorimotor perspectives on entrainment, simulation and prediction. Frontiers in Integrative Neuroscience, 16:916220. doi: 10.3389/fnint.2022.916220
 Ross, J.M., Iversen, J.R., & Balasubramaniam, R. (2018). The role of posterior parietal cortex in beat-based timing perception: A continuous theta-burst stimulation study. Journal of Cognitive Neuroscience, 30(5), 634-643.
 Ross, J.M., Iversen, J.R., & Balasubramaniam, R. (2016). Motor simulation theories of musical beat perception. Neurocase, 22(6).
 Ross, J.M., & Balasubramaniam, R. (2014). Physical and neural entrainment to rhythm: human sensorimotor coordination across tasks and effector systems. Front. Hum. Neurosci., 8:576.
Figure 1. Listening to music induces phase-alignment in motor network oscillations.
(A) Schematic showing phase-alignment in motor-related oscillatory brain activity to the predicted musical beat times. (B,C) Signatures of covert motor engagement in electrophysiological recordings–spectral power changes (B, schematic) and time-frequency dynamics [C, in this example to rhythmic auditory events during passive listening as described by Comstock et al., 2021, Eur. J. Neurosci.]. Event-related spectral perturbation (ERSP) is used to observe averaged dynamic changes in amplitude of the broad band frequency spectrum as a function of time and captures phase shifts in ongoing oscillatory activity. Inter-trial coherence (ITC) describes how consistent oscillatory phase is across trials and can be used to quantify phase locking to an event. If the time course of averaged ERSP and ITC is the same, then the event is phase locking oscillations consistently across trials. Ross & Balasubramaniam, 2014, Front. Hum. Neurosci.; Ross, Iversen, & Balasubramaniam, 2016, Neurocase; Figure adapted from Ross & Balasubramaniam, 2022, Front. Hum. Neurosci.
Figure 2. Mu (µ) synchronization occurs during passive music listening, localizes to premotor and motor cortices (bilaterally and on the midline), and reflects overt motor inhibition.
Mu rhythms are cortical field phenomena associated with the somatomotor system that appear over sensorimotor cortex and are thought to reflect motor inhibition. We recorded 32-channel EEG (n = 17) during silence without movement, overt movement (foot/hand), and music listening without movement. Using an independent component analysis-based source equivalent dipole clustering technique, we identified three mu-related clusters, localized to left primary motor and right and midline premotor cortices. Right foot tapping was accompanied by mu enhancement in the left lateral source cluster, replicating previous work. Music listening was accompanied by similar mu enhancement in the left, as well as midline, clusters. We are the first to report, and also to source-resolve, music-related mu modulation in the absence of overt movements. Figure adapted from Ross et al., 2022, J. Neurophysiol.
Figure 3. Beta band phase-alignment occurs to musical rhythms, localizes to sensorimotor, occipital, parietal and frontal networks, and the networks engaged depends on the stimulus properties.
We show evidence for beta phase alignment in a slope analysis of pre- to post-beat change in event-related spectral perturbation (ERSP; S), peak time of beta phase alignment (T), and change in peak power of beta (P). Using an ICA-based spatial clustering analysis, we found evidence for auditory and visual evoked beta alignment in the parietal and right frontal regions, auditory-specific beta alignment in bilateral sensorimotor regions, and visually-specific beta alignment in midline central, and bilateral temporal/parietal regions. Overall, this work shows phase alignment using sensory stimuli across multiple brain networks and provides a time course of phase-alignment to musical events. Figure adapted from Comstock et al., 2021, Eur. J. Neurosci.
Figure 4. The dorsal auditory stream plays an essential role in accurate musical phase perception, shown using downregulatory TMS.
There is growing interest in how the brain’s motor systems contribute to the perception of musical rhythms. The Action Simulation for Auditory Prediction hypothesis proposes that the dorsal auditory stream is involved in bidirectional interchange between auditory perception and beat-based prediction in motor planning structures via parietal cortex (Patel & Iversen, 2014). We use a TMS protocol, continuous theta burst stimulation (cTBS), that is known to down-regulate cortical activity for up to 60 min following stimulation to test for causal contributions to beat-based timing perception. cTBS target areas include the left posterior parietal cortex (lPPC), which is part of the dorsal auditory stream, and the left SMA (lSMA). We show that cTBS down-regulation of lPPC does interfere with beat-based timing ability, but only the ability to detect shifts in beat phase, not changes in tempo. Downregulation of lSMA, in contrast, does not interfere with beat-based timing. As expected, absolute interval timing ability was not impacted by the down-regulation of lPPC or lSMA. We find no evidence of an essential role of parietal cortex or SMA in interval timing. Ross, Iversen, & Balasubramaniam, 2018, J. Cogn. Neurosci.