Predicting “When” Using the Motor System’s Beta-Band Oscillations

Abstract

Anticipating future sensory events is one keystone of adaptive behavior. This notion is at the origin of recent theories suggesting perception and action control rely on internal models that are constantly tested and updated as a function of incoming sensory inputs. These hierarchical models (predictive coding and other generative models based on the notion of inference) suggest that neural responses reflect the difference between top-down expectations (or priors) and incoming feed-forward sensory inputs (Rao and Ballard, 1999; Friston, 2005). Priors are formed via the extraction of statistical regularities and can therefore relate to many different dimensions of a sensory event (e.g., spatial, spectral, temporal…; Arnal and Giraud, 2012). In the temporal domain, isochronous rhythm arguably constitutes the most basic regularity that can be used to anticipate the occurrence of an event. Consistent with such a notion of predictive timing, temporally anticipating a sound in an isochronous stream reduces the uncertainty about its occurrence (Rohenkohl et al., 2012) and therefore leads to a decrease of the amplitude of electrophysiological responses in the auditory cortex (Costa-Faidella et al., 2011). The neural origin and computations supporting predictive timing remain unclear, but a new study by Fujioka et al. (2012) raises a potential function of sensorimotor beta-band oscillations in the control of temporal anticipation during beat perception. The authors recorded neuromagnetic activity in participants that passively listened to isochronous (2.5, 1.7, and 1.3 Hz) or anisochronous (randomly spaced) tone sequences presented in four different blocks. Importantly, subjects’ attention was engaged in viewing a silent movie, and they were explicitly asked to ignore the sounds. Using a dipole source model of auditory responses, the authors first focused on the time-frequency profiles in response to these sequences in the auditory cortex. Consistent with previous findings, they observed transient increases of low ( 30 Hz) power, time-locked to the stimulus. More interestingly, while beta-band activity (13–25 Hz) consistently decreased after stimulus onset in every condition, the following beta rebound (beta resynchronization) increased differentially as a function of beat patterns. By evaluating the rising slope of the beta rebound for each condition, they found that beta rebound is fast and transient during aperiodic stimulation whereas it increased progressively to reach a maximum at the occurrence of the subsequent sound in the isochronous conditions. They also observed that the magnitude of the post-stimulus beta decrease co-varies with the frequency of stimulation (i.e., the slower the rhythm, the larger the beta decrease). Based on these findings, the authors suggest that beta rebound tracks the tempo of stimulation in the auditory cortex and can be used to maintain predictive timing. Because beta-band activity is classically considered as being related to motor functions (Engel and Fries, 2010), the authors extended their investigation to whole-brain beta activity using a spatio-temporal principal component analysis. In addition to auditory regions, they identified a large network of sensorimotor regions implicated in the tracking of beat tempo. This suggests that the motor system is recruited during the passive perception of rhythms, even in the absence of any intention to move in synchrony with the beat. One might interpret this result as the passive, rhythmic entrainment of auditory, and motor systems. In that case, though, it would be unlikely to observe tempo-dependent beta rebounds following post-stimulus beta suppression. The fact that the beta rebound progressively increases and is maximal at the onset of upcoming sounds more likely supports an active, predictive timing account. These results suggest that (i) the motor system is automatically recruited during passive listening to anticipate forthcoming sounds, (ii) predictive timing allows to control neural activity in sensory regions, and (iii) beta-band oscillations play an instrumental role in predictive timing. By examining in more detail the interactions between auditory and motor systems, the authors determined that post-stimulus event-related beta-coherence varied in an opposite way between these two systems. While beta-coherence decreased after stimulus onset in auditory regions, it simultaneously increased in motor areas. This may suggest that beta oscillations are used to control predictive timing via sensorimotor loops between auditory and motor systems. This interpretation must be viewed with caution in light of the absence of a clear causal relationship between the time courses of beta activity in these regions. However, these results converge to support a functional role of beta activity in the predictive modulation of auditory activity by the motor system.