Abstract
Objective: To determine whether changes in sensorimotor control resulting from speaking conditions that induce fluency in people who stutter (PWS) can be measured using electroencephalographic (EEG) mu rhythms in neurotypical speakers.Methods: Non-stuttering (NS) adults spoke in one control condition (solo speaking) and four experimental conditions (choral speech, delayed auditory feedback (DAF), prolonged speech and pseudostuttering). Independent component analysis (ICA) was used to identify sensorimotor μ components from EEG recordings. Time-frequency analyses measured μ-alpha (8–13 Hz) and μ-beta (15–25 Hz) event-related synchronization (ERS) and desynchronization (ERD) during each speech condition.Results: 19/24 participants contributed μ components. Relative to the control condition, the choral and DAF conditions elicited increases in μ-alpha ERD in the right hemisphere. In the pseudostuttering condition, increases in μ-beta ERD were observed in the left hemisphere. No differences were present between the prolonged speech and control conditions.Conclusions: Differences observed in the experimental conditions are thought to reflect sensorimotor control changes. Increases in right hemisphere μ-alpha ERD likely reflect increased reliance on auditory information, including auditory feedback, during the choral and DAF conditions. In the left hemisphere, increases in μ-beta ERD during pseudostuttering may have resulted from the different movement characteristics of this task compared with the solo speaking task. Relationships to findings in stuttering are discussed.Significance: Changes in sensorimotor control related feedforward and feedback control in fluency-enhancing speech manipulations can be measured using time-frequency decompositions of EEG μ rhythms in neurotypical speakers. This quiet, non-invasive, and temporally sensitive technique may be applied to learn more about normal sensorimotor control and fluency enhancement in PWS.
Highlights
Sensorimotor control for speech production is achieved via the integration of feedback and feedforward control mechanisms (Houde and Jordan, 1998; Jones and Munhall, 2005; Purcell and Munhall, 2006; Bauer et al, 2007)
independent component analyses (ICA) successfully unmixed raw EEG data collected during speech production to identify sensorimotor μ components
Subsequent time-frequency analyses of μ component clusters revealed oscillatory changes in μ-alpha and μ-beta bands which were indicative of real-time adjustments in sensorimotor control that were differentiated by speaking condition
Summary
Sensorimotor control for speech production is achieved via the integration of feedback and feedforward control mechanisms (Houde and Jordan, 1998; Jones and Munhall, 2005; Purcell and Munhall, 2006; Bauer et al, 2007). Feedforward control is associated with the activation of speech motor programs in ventral premotor areas in the left frontal lobe. Activation of a motor program engages feedback controllers for speech via projections to auditory and somatosensory association areas. These projections encode forward models that transform the current motor commands into the desired or expected sensory outcomes. Comparisons between desired and actual feedback allow for monitoring the accuracy of speech output. Discrepancies between these signals generate an error signal, the magnitude and direction of which are mapped onto corrective motor commands via projections from auditory and somatosensory areas to frontal speech motor areas. A similar hemispheric differentiation between feedforward and feedback control has been identified for limb movements (Grafton et al, 2008)
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