A Convolutional Neural Network for Enhancing the Detection of SSVEP in the Presence of Competing Stimuli.

Stimulus proximity has been shown to have an influence on the classification performance of a steady-state visual evoked potential based brain-computer interface (SSVEP-BCI). Multiple visual stimuli placed close to each other compete for neural representations leading to the effect of competing stimuli. In this study, we propose a convolutional neural network (CNN) based classification method to enhance the detection accuracy of SSVEP in the presence of competing stimuli.