Lindsey Power

Predictive speech processing relies on oscillatory dynamics in the auditory and higher order language regions, with theta (4-8 Hz) oscillations tracking syllabic rhythms and supporting auditory signalling, and beta (15-30 Hz) oscillations mediating top-down inhibitory control and prediction. These signals often manifest as transient bursts with precise temporal characteristics offering insight into neural timing. However, the functional roles of bursts in continuous, natural speech processing remain unresolved. Our work investigates the role of beta and theta bursts in naturalistic speech processing using MEG data obtained from 11 healthy participants presented with TED talk recordings. Throughout natural speech, beta and theta bursts showed changes in response to auditory input, with beta bursting increasing during pauses between phrases and theta increasing during word presentation. Furthermore, the uncertainty and surprisal of presented words modulated the bursting response. Our results shed light on the temporal dynamics of speech processing, demonstrating the complementary roles of beta and theta bursting in signalling predictive speech features. Further, these findings may have clinical relevance for disorders such as psychosis, which impair language processing in the brain.

Lindsey Power is a post-doctoral researcher working with electrophysiological markers of aging, neuropathology, and cognition. Over the years, she has studied healthy aging processes and a variety of complex clinical cases (including epilepsy, dementia, and psychosis) using an equally varied number of signaling methods and analyses (notably functional neuroimaging and machine learning). She received a BSc in Neuroscience in 2019, and a PhD in Biomedical Engineering in 2024 from Dalhousie University. Currently, she is studying the relationship between magnetoencephalography (MEG) signals and language processing at the Montreal Neurological Institute.

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