  In recent years, neural networks showed unprecedented growth that ultimately
influenced dozens of different industries, including signal processing for the
electroencephalography (EEG) process. Electroencephalography, although it
appeared in the first half of the 20th century, was not changed the physical
principles of work to this day. But signal processing technology made
significant progress in this area through the use of neural networks. But many
different models of neural networks complicate the process of understanding the
real situation in this area. This manuscript summarizes the current state of
knowledge on this topic, summarizes and describes the most significant
achievements in various fields of application of neural networks for processing
EEG signals. We discussed in detail the results presented in recent research
papers for various fields in which EEG signals have been involved. We also
examined in detail the process of extracting features from EEG signals using
neural networks. In conclusion, we have provided recommendations for the
correct demonstration of research results in manuscripts on the subject of
neural networks and EEG.
