Although ear canal electroencephalogram (EEG) recording has received interest from basic
and applied research communities, evidence on how it can be implemented in practice is …

Abstract Machine learning techniques have proven to be a useful tool in cognitive
neuroscience. However, their implementation in scalp‐recorded electroencephalography …

Dynamics of electroencephalographic (EEG) activity during auditory information processing
were evaluated in response to changes in stimulus complexity, stimulus discriminability and …

The goal of describing how the human brain responds to complex acoustic stimuli has
driven auditory neuroscience research for decades. Often, a systems-based approach has …

Source localization of electrical activity in the brain can be greatly improved by testing the
experimental variability in the signals being localized. The most widely used method for …

Middle components (la6tency 8–50 msec) of the averaged auditory electroencephalic
response (AAER), evoked by brief duration tone bursts, were recorded from 11 normal …

Objective. Conventional, multi-channel scalp electroencephalography (EEG) allows the
identification of the attended speaker in concurrent-listening ('cocktail party') scenarios. This …

This study analyzed relationships among co-existent EEG frequency responses during
passive auditory stimulus processing. By applying quantifiers based on wavelet entropy, it is …

Sensory stimuli produce phase-locked and non-phase-locked changes in brain activity as
indexed by EEG and MEG. Time-frequency methods such as wavelets, when carefully …

Objectives In recent years, there has been significant interest in recovering the temporal
envelope of a speech signal from the neural response to investigate neural speech …