Audio-Vocal Monitoring System Revealed by Mu-Rhythm Activity

Abstract

Understanding the neural mechanisms underlying speech production has a number of potential practical applications. Speech production involves multiple feedback loops. An audio-vocal monitoring system plays an important role in speech production, based on auditory feedback about the speaker’s own voice. Here we investigated the mu-rhythm activity associated with speech production by examining event-related desynchronization and synchronization in conditions of delayed auditory feedback (DAF) and noise feedback (Lombard). In Experiment 1, we confirmed that the mu-rhythms were detectable for a conventional finger-tapping task, and vocalization. In Experiment 2, we examined the mu-rhythms for imagined speech production. We tested whether the same motor-related mu-rhythm activity was exhibited while participants listened to their own voice, and while reading. The mu-rhythms were observed for overt vocalization and covert reading, while listening to simulated auditory feedback of the participants’ own voice reading text. In addition, we found that the mu-rhythm associated with listening was boosted and attenuated under the DAF and Lombard conditions, respectively. This is consistent with the notion that auditory feedback is important for the audio-vocal monitoring system in speech production. This paradigm may help clarify the way in which auditory feedback supports motor planning, as indexed by the motor-related mu-rhythm.

Speech motor learning changes the neural response to both auditory and somatosensory signals

“…Mu rhythms are observed in the electrodes over sensorimotor areas corresponding to leg, arm and facial motion 18 27 28 , which is consistent with our observation. Mu rhythm activity is also observed in speech production with delayed auditory feedback or with noise 20 . All of these results suggest that the mu rhythms reflect sensorimotor processing.…”

“…For somatosensory analyses, and in particular the time-frequency analysis, we focus on activity over orofacial sensorimotor regions. Previous studies 18 19 20 have documented mu rhythms (11–13 Hz cortical oscillations) over these sites. We find that adaptation results in changes to sensory evoked potentials.…”

The interpretation of mu suppression as an index of mirror neuron activity: past, present and future

“…Although Tamura et al . [36] argued that their results demonstrated mu suppression during imagined speech production, suppression was not specific either to the central sites or to the stimulation period, and again, the process for selecting the frequency band for analysis from the baseline period would be likely to create some false positives. A further limitation of this study is that production and perception conditions were in two separate studies—a crucial test of mirror neuron functioning would be demonstrating mu suppression both during perception and production of the same stimuli within the same study.…”

EEG Mu ( µ ) rhythm spectra and oscillatory activity differentiate stuttering from non-stuttering adults

“…Though they can be observed in various regions of the cortex (Schnitzler et al, 2000;Hauswald et al, 2013;Kodama et al, 2016), the primary sources of μ rhythms lie within anterior regions of the dorsal stream (e.g., premotor and primary motor cortices). Within sensorimotor μ rhythms, activity in the β band is thought to encode motor information (Pfurtscheller, 1981;Toro et al, 1994;Seeber et al, 2014), and activity within the α band is thought to encode somatosensory and auditory feedback (Cheyne et al, 2003;Gaetz and Cheyne, 2006;Tamura et al, 2012;Sebastiani et al, 2014;Peled-Avron et al, 2016). Thus, if stuttering is associated with reduced capacity for generating forward models in motor regions, μ spectral differences, particularly in β frequencies, might be expected when comparing PWS to non-stuttering groups.…”