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Poster Session C: Friday, August 15, 2:00 – 5:00 pm, de Brug & E‑Hall

Modelling Demonstrates Phase-Reset is an Important Feature of Neural Speech Processing

Andrew Shannon¹, Martin Homer, David A.W. Barton¹, Conor Houghton¹; ¹University of Bristol

Presenter: Andrew Shannon

Syllable segregation and source separation are foundational components of neural speech processing, yet consensus on their underlying mechanism remains elusive. Several hypotheses have been proposed, suggesting that the brain may align its activity to incoming linguistic stimuli via evoked responses, entrainment of endogenous oscillations, or some combination of the two. We investigate the origin of oscillatory behaviour in syllable segregation by modelling the dynamical response to periodic linguistic stimuli. We compare a biophysically accurate neural mass model and a phase-resetting oscillator with prior experimental EEG data. We find that a correlation between neural activity entrainment strength and the sharpness of incoming phonemes, identified in the EEG experiment, is readily reproduced by both the neural mass model and the oscillator. However, when the phase-resetting dynamics are removed, the oscillator fails to reproduce the correlation. This demonstrates that phase-resetting is required for sharpness specific tuning of neural entrainment to speech. Identifying the neural correlates of this phenomenon may be possible through interrogation of the biophysical features of the neural mass model.

Topic Area: Language & Communication

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