ABSTRACT
The dynamics of filter response play an important role in neurofeedback. It is not generally possible to determine the important concerns from first principles alone, and the realities of the brain and electroencephalography (EEG) must also be taken into consideration. The importance of the short-term dynamics of the EEG is another reason why visual inspection of EEG waves is important. QEEG analysis tends to obscure short-term variations and hide them behind statistics and static maps. The importance of EEG time dynamics is also reflected in the use of training parameters, such as sustained reward criterion (SRC), refractory period, and averaging windows or damping factors. Digital filtering is another approach to recovering EEG frequency-related information in real time. Modern neurofeedback systems are based upon a computer implementation, most often a general-purpose personal computer (PC). Therefore, the principles of digital sampling and signal processing are applied, and these affect the system capabilities and limitations.
