Changes in EEG spectral characteristics in the course of neurofeedback training

Abstract

Spectral power (SP) ratios of the EEG α and β frequencies were used as neurofeedback (NFB) for ten apparently healthy subjects (university students) to control a computer cursor in a graphic interface in three scenarios. The results showed that the scenario that used the SP ratio of the α and β 2 frequencies pro vided for the highest accuracy and best speed of task performance. The ratios including the β 1 frequency were found to be less efficient because an increase or a decrease in its SP could occur together with an increase or a decrease of the SPs of the α and β 2 frequencies. However, the subjects acquired the skill of controlling the cursor with an efficiency of 81%, which gradually grew during learning, after a relatively short period of time (5 training sessions within 2 weeks).

Discriminative Frequencies and Temporal EEG Segmentation in the Motor Imagery Classification Approach

“…Although we have previously identified the most significant frequency ranges (such as µ (10-13 Hz), β (13-25 Hz), and γ (30-70 Hz)) reliable for the classification of MI-related EEG patterns [3], we assume that the most effective frequency band of the EEG and its severity are determined by the individual characteristics of the subject [20]. It has also been shown that the ability of a person, in principle, to voluntarily induce patterns of brain activity, for example, when mentally performing a movement with a certain limb, is purely individual [21][22][23]. Therefore, the BCI user is not always able to operate with the set of control commands offered to them.…”