Arif Sinan Uslu: The effect of self-paced neurofeedback on EEG learning: An experimental setup

Machine Learning Seminar presentation

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

Speaker: Arif Sinan Uslu, FHSE, University of Luxembourg

Time: Wednesday, 2021.01.27, 10:00 CET

How to join: Please contact Jakub Lengiewicz

Abstract:

Neurofeedback refers to the regulation of brain activity via a brain-computer interface. In a feedback loop, the brain activity is recorded, analyzed, and fed back to the user. 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.

Additional material:

[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 (edited)