Martin Spüler

This study identifies EEG correlates of decision confidence across different phases of a recognition memory task, showing confidence is most reflected during feedback processing.

This paper introduces a BCI system combining EEG2Code with deep learning, achieving high information transfer rates and accurate decoding of visual stimuli from EEG signals.

This paper introduces an asynchronous high-speed BCI speller with robust non-control state detection, achieving an average information transfer rate of 122.7 bit/min.

This paper critiques two studies claiming to enable communication in complete locked-in state patients, showing methodological flaws and irreproducibility of their results.

This paper uses machine learning to analyze EEG data and finds distinct and shared neural correlates for the executive functions updating and inhibition.

This paper introduces a method to model brain responses to arbitrary visual stimuli using EEG, enabling flexible and high-speed brain-computer interfaces with increased information transfer rates.