Applications of Spiking Neural Network in Brain Computer Interface

Spiking neural network (SNN) is regarded as the third generation of the artificial neural network, which takes biologically plausible spiking neurons as the basic computing unit. Due to its ability to capture the rich dynamics of biological neurons and to represent and integrate different information dimensions, such as time, frequency and phase, SNN provides a powerful tool for modeling complex information processing in the brain. EEG can help us better understand brain activity and structure, and shows great potential in implementing Brain-Computer Interface (BCI). In this review, we mainly summarize the application of the SNN model in EEG signal processing. These applications are grouped into four categories, each of which is further explored using examples from previous studies.