Two-component spatiotemporal template for activation-inhibition of speech in ECoG
Eric Easthope

TL;DR
This study identifies a two-component spatiotemporal pattern of activation and inhibition in sensorimotor cortex during speech, using principal component analysis of high-density ECoG data to reveal distinct neural dynamics.
Contribution
It introduces a novel two-component model of speech-related ECoG activity, highlighting the complex interplay of activation and inhibition in sensorimotor regions during speech production.
Findings
Two principal components capture speech-related activity in SMC
Distinct activation-inhibition patterns are observed during speech
Third component shows insignificant correlation, indicating sufficiency of two components
Abstract
I compute the average trial-by-trial power of band-limited speech activity across epochs of multi-channel high-density electrocorticography (ECoG) recorded from multiple subjects during a consonant-vowel speaking task. I show that previously seen anti-correlations of average beta frequency activity (12-35 Hz) to high-frequency gamma activity (70-140 Hz) during speech movement are observable between individual ECoG channels in the sensorimotor cortex (SMC). With this I fit a variance-based model using principal component analysis to the band-powers of individual channels of session-averaged ECoG data in the SMC and project SMC channels onto their lower-dimensional principal components. Spatiotemporal relationships between speech-related activity and principal components are identified by correlating the principal components of both frequency bands to individual ECoG channels over time…
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Taxonomy
TopicsSpeech Recognition and Synthesis
