Brainstem speech encoding is dynamically shaped online by fluctuations in cortical α state

•Arousal state can be indexed by cortical α band.•Speech-evoked FFRs during low α are smaller compared to high α (in noise).•FFR F0 amplitude predicts perceptual response time during low cortical α.•Speech stimuli are more accurately decoded from low-α-FFRs. Experimental evidence in animals demonstr...

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Veröffentlicht in:NeuroImage (Orlando, Fla.) Fla.), 2022-11, Vol.263, p.119627-119627, Article 119627
Hauptverfasser: Lai, Jesyin, Price, Caitlin N., Bidelman, Gavin M.
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Sprache:eng
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Zusammenfassung:•Arousal state can be indexed by cortical α band.•Speech-evoked FFRs during low α are smaller compared to high α (in noise).•FFR F0 amplitude predicts perceptual response time during low cortical α.•Speech stimuli are more accurately decoded from low-α-FFRs. Experimental evidence in animals demonstrates cortical neurons innervate subcortex bilaterally to tune brainstem auditory coding. Yet, the role of the descending (corticofugal) auditory system in modulating earlier sound processing in humans during speech perception remains unclear. Here, we measured EEG activity as listeners performed speech identification tasks in different noise backgrounds designed to tax perceptual and attentional processing. We hypothesized brainstem speech coding might be tied to attention and arousal states (indexed by cortical α power) that actively modulate the interplay of brainstem-cortical signal processing. When speech-evoked brainstem frequency-following responses (FFRs) were categorized according to cortical α states, we found low α FFRs in noise were weaker, correlated positively with behavioral response times, and were more ”decodable” via neural classifiers. Our data provide new evidence for online corticofugal interplay in humans and establish that brainstem sensory representations are continuously yoked to (i.e., modulated by) the ebb and flow of cortical states to dynamically update perceptual processing.
ISSN:1053-8119
1095-9572
DOI:10.1016/j.neuroimage.2022.119627