AUTHOR=Soekadar Surjo R., Witkowski Matthias , Garcia Cossio Eliana , Birbaumer Niels , Cohen Leonardo TITLE=Learned EEG-based brain self-regulation of motor-related oscillations during application of transcranial electric brain stimulation: feasibility and limitations JOURNAL=Frontiers in Behavioral Neuroscience VOLUME=Volume 8 - 2014 YEAR=2014 URL=https://www.frontiersin.org/journals/behavioral-neuroscience/articles/10.3389/fnbeh.2014.00093 DOI=10.3389/fnbeh.2014.00093 ISSN=1662-5153 ABSTRACT=Objective: Transcranial direct current stimulation (tDCS) improves motor learning and can influence emotional processing or attention. However, it remained unclear whether learned electroencephalography (EEG)-based brain-machine interface (BMI) control during tDCS is feasible and how application of transcranial electric currents during BMI control would interfere with feature-extraction of physiological brain signals. Here we tested this combination and evaluated stimulation-dependent artifacts across different EEG frequencies and stability of motor imagery-based BMI control. Approach: Ten healthy volunteers were invited to two BMI-sessions, each comprising two 60-trial blocks. During the trials, modulation of mu-rhythms (8-15Hz) associated with motor imagery recorded over C4 was translated into online cursor movements on a computer screen. During block 2, either sham (session A) or anodal tDCS (session B) was applied at 1mA with the stimulation electrode placed 1cm anterior of C4. Main results: tDCS was associated with a significant signal power increase in the lower frequencies most evident in the signal spectrum of the EEG channel closest to the stimulation electrode. Stimulation-dependent signal power increase exhibited a decay of 12dB per decade, leaving frequencies above 9Hz unaffected. Analysis of BMI control performance did not indicate a difference between blocks and tDCS conditions. Conclusion: Application of tDCS during learned EEG-based self-regulation of brain oscillations above 9Hz is feasible and safe, and might improve applicability of BMI systems in patient populations.