The effects of attention and visual input on the representation of natural speech in EEG

Traditionally, the use of electroencephalography (EEG) to study the neural processing of natural stimuli in humans has been hampered by the need to repeatedly present discrete stimuli. Progress has been made recently by the realization that cortical population activity tracks the amplitude envelope of speech stimuli. This has led to studies using linear regression methods which allow the presentation of continuous speech. One such method, known as stimulus reconstruction, has so far only been utilized in multi-electrode cortical surface recordings and magnetoencephalography (MEG). Here, in two studies, we show that such an approach is also possible with EEG, despite the poorer signal-to-noise ratio of the data. In the first study, we show that it is possible to decode attention in a naturalistic cocktail party scenario on a single trial (≈60 s) basis. In the second, we show that the representation of the envelope of auditory speech in the cortex is more robust when accompanied by visual speech. The sensitivity of this inexpensive, widely-accessible technology for the online monitoring of natural stimuli has implications for the design of future studies of the cocktail party problem and for the implementation of EEG-based brain-computer interfaces.