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The Effects of Attention and Visual Input on the Representation of Natural Speech in EEG

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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 magneto-encephalography (MEG). In this talk I will present data from two studies showing that such an approach is also possible with EEG . In the first study, I will present data showing that it is possible to decode attention in a naturalistic cocktail party scenario on a single trial (≈60 s) basis. In the second, I will present results showing that the representation of the envelope of auditory speech in the cortex is earlier and more robust when accompanied by visual speech. The sensitivity of the stimulus reconstruction approach has implications for the design of future EEG studies into the ongoing dynamics of cognition and for research aimed at identifying biomarkers of clinical disorders.

This talk is part of the Centre for Neuroscience in Education (CNE) series.

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