The effect of self-paced neurofeedback on EEG learning: An experimental setup.

Speaker: Arif Sinan Uslu (Faculty of Humanities, Education and Social Sciences; University of Luxembourg)
Title: The effect of self-paced neurofeedback on EEG learning: An experimental setup
Time: Wednesday, 2021.01.27, 10:00 a.m. (CET)
Place: fully virtual (contact Dr. Jakub Lengiewicz to register)
Format: 30 min. presentation + 30 min. discussion

Abstract: 

Neurofeedback refers to the regulation of brain activity via a brain-computer interface. In a feedback-loop, the brain activity is recorded, analysed and fed back to the user. An iterative and dynamic feedback enables the user to learn whether or not the recorded brain activity meets a pre-specified threshold. Research in the field of cognitive electrophysiology suggests that the regulation of brain rhythms is associated with changes in cognitive functions [1,2]. However, these associations frequently apply to subgroup of participants who were able to regulate their brain activity [2,3,4]. Up until now, most studies on EEG neurofeedback applied a block design during training during which participants receive the same timed neurofeedback training blocks (e.g. 5 minutes) interspersed by rest periods. To my knowledge, there has been no study investigating the effect of self-paced neurofeedback on learning outcome although the factor of training frequency and duration has been discussed as an indicator of training success. In the current study I will investigate how self-paced neurofeedback influences the activity of alpha frequency compared to classical externally-paced neurofeedback and a control group receiving sham-neurofeedback.

In my presentation I will give a brief theoretical introduction to the matter and focus later on the technical implementation of my experimental setup and the type of data that is being recorded. Although a data-driven methodology is not implemented for this experiment, I would very much like to take this opportunity to discuss possibilities to include data-driven methods that could be applied to the data from this experiment or a modified version of this experiment.

[1] Escolano, C., Navarro-Gil, M., Garcia-Campayo, J. et al. The Effects of a Single Session of Upper Alpha Neurofeedback for Cognitive Enhancement: A Sham-Controlled Study. Appl Psychophysiol Biofeedback 39, 227–236 (2014). https://doi.org/10.1007/s10484-014-9262-9
[2] Hanslmayr, S., Sauseng, P., Doppelmayr, M., Schabus, M., & Klimesch, W. (2005). Increasing individual upper alpha power by neurofeedback improves cognitive performance in human subjects. Applied psychophysiology and biofeedback, 30(1), 1–10. https://doi.org/10.1007/s10484-005-2169-8
[3] Nan, W., Rodrigues, J. P., Ma, J., Qu, X., Wan, F., Mak, P. I., Mak, P. U., Vai, M. I., & Rosa, A. (2012). Individual alpha neurofeedback training effect on short term memory. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 86(1), 83–87. https://doi.org/10.1016/j.ijpsycho.2012.07.182
[4] Kober, S. E., Witte, M., Ninaus, M., Neuper, C., & Wood, G. (2013). Learning to modulate one’s own brain activity: the effect of spontaneous mental strategies. Frontiers in human neuroscience, 7, 695. https://doi.org/10.3389/fnhum.2013.00695