Beta bursts carry a graded signal of semantic updating during naturalistic narrative comprehension
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Comprehending a narrative requires continuously updating a model of the discourse, and beta-band activity is thought to signal when that model should be held versus changed. Whether beta also grades how much to update, and whether that index is carried by discrete bursts beyond sustained power, is unknown for naturalistic comprehension. We recorded MEG from 61 human participants (22 men, 39 women) while they listened to naturalistic Hebrew narratives, detected beta bursts in the continuous signal, and quantified the semantic shift between successive sentences from sentence embeddings. Beta burst rate decreased after sentence boundaries, and regression-based deconvolution separated a pre-onset maintenance phase from a graded post-onset response whose magnitude scaled with semantic shift (peak ∼0.9 s). This response was independent of lexical surprisal, the acoustic envelope, and referent introduction, largely robust to dependency structure, though it shared variance with propositional quantity. Burst occurrence carried a component of the effect beyond the accompanying amplitude change: applying that change as a pure gain to each participant’s envelope and re-running the identical detection predicts only 75% of the observed burst-rate reduction (excess p = .038), the effect survived an amplitude-invariant threshold, and a Poisson model reproduced it as a graded reduction in burst-initiation rate. The effect held in both participant groups, which heard differently framed narratives, and was decisively supported (BF10 > 250). Beta bursts thus provide a graded signal of semantic updating during continuous comprehension, expressed in the rate of burst occurrence over and above the accompanying change in sustained power.
Significance Statement
Comprehending speech requires continuously updating an internal model of the unfolding discourse, but how the brain signals how much to update is unclear. Beta activity is thought to maintain the current cognitive state; we show that during natural story listening, the rate of brief beta bursts decreases at sentence transitions in proportion to how much the meaning shifts, consistent with a graded “how-much-to-update” signal rather than a binary boundary flag. Converging analyses show the effect is expressed in how often bursts occur, by more than the accompanying change in sustained beta power can explain, extending the transient-beta-burst framework to naturalistic language. The signal appears automatic and tied to linguistic structure rather than to subjective event segmentation.