Evaluating potential EEG-indicators for auditory attention to speech in realistic environmental noise

The human brain is remarkably capable of perceiving relevant sounds in noisy environments but the underlying interplay of neurophysiology and acoustics is still being investigated. Cortical processing of these sounds in the brain depends on attentional demand. One of the most important issues is how to identify whether a person is paying attention to the relevant sounds or not. The aim of this study was to explore the potential of single-trial electroencephalography (EEG) indicators to distinguish the cortical representation of three sequential tasks — attentive listening to lectures in background noise, attentive and inattentive listening to background noise alone. Three types of environmental noise, including multi-talker babble, fluctuating traffic and highway sounds were employed as the background during the first task and the stimulus during the second and third tasks. 23 healthy volunteers were exposed to these three tasks while 64-channels EEG signals were recorded. Alpha-band spectral characteristics (peak frequency and power) were investigated as potential indicators of attention and cortical inhibition. Furthermore, based on the hypothesis of self-similarity as excitation-inhibition balance, long-range temporal correlation of alpha-band activity was quantified based on detrended fluctuation analysis. Finally, the hypothesis of speech envelope entrainment of brain activity motivated to estimate the delta absolute power for investigating the attended sound. Considering the participant as a random factor, a linear mixed-effect regression was employed to model the estimated indicators as a function of listening task, EEG channel cluster, and background noise. Strong significant differences were found that support our hypotheses that auditory attention to speech can be observed via EEG-indicators.