selective attention

In this accepted paper in Scientific Reports, we present a novel dataset and accompanying analysis enabling the first direct comparison between scalp, around-ear, and in-ear electroencephalography (EEG) for neural selective auditory attention decoding to speech.

In this preprint, we present efficient unsupervised training algorithms for EEG-based auditory attention decoding that have no initialization bias.

In this article, we present a new end-to-end deep learning model, AADnet, for auditory attention decoding from EEG in multi-talker scenarios.

In this preprint, we present analysis of a conversation tracking paradigm with 2 or 3 conversations during selective auditory attention decoding from EEG.

In this article, we present a new experiment in which participants attend on of two superimposed video, and we show that we can decode their attention from EEG and gaze data.

In this article, presented at EUSIPCO 2025, we present a novel method to model the performance curve of EEG-based AAD algorithms starting from a single decision window length.