The role of brain oscillations in predicting self-generated sounds

Abstract

Being able to predict self-generated sensory consequences is an important feature of normal brain functioning. In the auditory domain, self-generated sounds lead to smaller brain responses (e.g., auditory evoked responses) compared to externally generated sounds, which is usually referred to as the sensory attenuation effect. Here we investigated the role of brain oscillations underlying this effect. With magnetoencephalography, we show that self-generated sounds are associated with increased pre-stimulus alpha power and decreased post-stimulus gamma power and alpha/beta phase locking in auditory cortex. All these oscillatory changes are correlated with changes in evoked responses, suggesting a tight link between these oscillatory events and sensory attenuation. Furthermore, the pre- and post- oscillatory changes correlate with each other across participants, supporting the idea that they constitute a neural information processing sequence for self-generated sounds. In line with findings of alpha oscillations reflecting feedback and gamma oscillations feedforward processes and models of predictive coding, we suggest that pre-stimulus alpha power represent prediction and post-stimulus gamma power represent prediction error, which is further processed with post-stimulus alpha/beta phase resetting. The correlation between these oscillatory events is further validated with cross-trial analysis, which provides additional support for the proposed information processing sequence that might reflect a general mechanism for the prediction of self-generated sensory input.

Beta‐band oscillations play an essential role in motor–auditory interactions

“…This result is consistent with previous studies and demonstrates how actions can modulate auditory processing (Cao, Thut, & Gross, ; Cao, Veniero, et al, ; Hughes, Desantis, & Waszak, ; Martikainen et al, ; Schneider & Mooney, ). The term sensory attenuation has been used for the M100 amplitude suppression for a long time (Cao, Thut, & Gross, ; Cao, Veniero, et al, ; Hughes et al, ; Wolpe et al, ). One possible function of neurons generating M100 is to call attention to the availability of stimulus information (Näätänen & Picton, ).…”

“…Our results also demonstrate functional connectivity from motor to auditory cortex in alpha range before the stimulus onset for active condition. This result extends previous observations that prestimulus changes in alpha oscillations in auditory cortex during movement preparation (Cao, Thut, & Gross, ; Cao, Veniero, et al, ; Müller, Leske, Hartmann, Szebényi, & Weisz, ; Stenner, Bauer, Haggard, Heinze, & Dolan, ) shape the processing of incoming sensory stimuli. In fact, Granger causality from motor to LAC (Figure ) suggests a spectral connectivity pattern that shifts from alpha frequencies before tone onset to beta frequencies just after tone onset.…”

“…We report significant beta power decrease in left and right auditory cortex following stimulus onset in the active condition compared to the passive condition. This replicates a similar finding in right auditory cortex in a similar task (Cao, Thut, & Gross, ; Cao, Veniero, et al, ) and suggests an interaction between motor and auditory cortex in this frequency band. Indeed, we observed two interactions.…”

“…While further work is needed to corroborate this finding, it might indicate different stages of motor–auditory interactions. Prestimulus motor–auditory alpha connectivity could represent an unspecific downregulations of auditory excitability (consistent with the prestimulus alpha increase observed in Cao, Thut, and Gross () and Cao, Veniero, et al ()) followed by motor–auditory beta connectivity that could represent more specific information based on the motor efference copy.…”

“…Cao et al demonstrated a correlation between the prestimulus alpha increase in auditory cortex and the magnitude of sensory attenuation indicating a downregulation of auditory excitability when predicted self‐generated sensory input is expected (Cao, Thut, & Gross, ; Cao, Veniero, Thut, & Gross, ). In line with the above‐mentioned functional differentiation between different oscillations, gamma‐band changes in response to self‐generated stimuli seem to reflect prediction errors (Buchholz, David, Sengelmann, & Engel, ; Cao, Thut, & Gross, ; Cao, Veniero, et al, ; Flinker et al, ). These prediction errors are computed by comparing real sensory input and the sensory input that is predicted on the basis of the motor command by the internal forward model.…”