Detecting cortical responses to continuous running speech using EEG data from only one channel

Abstract

Objective To explore the detection of cortical responses to continuous speech using a single EEG channel. Particularly, to compare detection rates and times using a cross-correlation approach and parameters extracted from the temporal response function (TRF). Design EEG from 32-channels were recorded whilst presenting 25-min continuous English speech. Detection parameters were cross-correlation between speech and EEG (XCOR), peak value and power of the TRF filter (TRF-peak and TRF-power), and correlation between predicted TRF and true EEG (TRF-COR). A bootstrap analysis was used to determine response statistical significance. Different electrode configurations were compared: Using single channels Cz or Fz, or selecting channels with the highest correlation value. Study sample Seventeen native English-speaking subjects with mild-to-moderate hearing loss. Results Significant cortical responses were detected from all subjects at Fz channel with XCOR and TRF-COR. Lower detection time was seen for XCOR (mean = 4.8 min) over TRF parameters (best TRF-COR, mean = 6.4 min), with significant time differences from XCOR to TRF-peak and TRF-power. Analysing multiple EEG channels and testing channels with the highest correlation between envelope and EEG reduced detection sensitivity compared to Fz alone. Conclusions Cortical responses to continuous speech can be detected from a single channel with recording times that may be suitable for clinical application.