EEG training platform: Improving Brain-Computer Interaction and cognitive skills

This work proposes a complete structure of an EEG biofeedback platform focused on an efficient way for its user to learn how to self regulate cortical activity. A longitudinal study of how voluntary training of specific electro cortical activity produces any stable changes in the electroencephalogram is also presented. Correlations of these changes with short term memory are also hypothesized. In this work the human brain was seen as an electrochemical machine capable of receiving stimuli and adapt accordingly. So, only relevant EEG activity was fed back to the trainee by a Brain Computer Interface (BCI) in an intelligible way, allowing the identification of phasic changes in the EEG and what cognitive state caused it. The results from this study showed that it is possible to learn to change some rhythmical activity in the EEG, in this case the alpha activity, after a few feedback sessions. A positive relation between this frequency band and cognitive processes was also observed. These results also indicate that the proposed EEG biofeedback protocol can be shaped as a tool for those who rely on BCI to communicate with the external world as it allows the tracking and training of individual frequency bands.