2.4. SMR Training Neurofeedback

We run a single neurofeedback session training SMR on Cz. To train SMR we used BrainAvatar 4.6.4 and Atlantis I amplifier (BrainMaster Technologies, Inc.). Usually, the clinician sets the amplitude thresholds so that irrespective of the selected frequency band, the software algorithm allows the patient to receive feedback. The goal is to ensure the reinforcement to the patient 50% of the time, although the literature specifies this percentage ranging between 20–70% [35]. We set up an auto-thresholding protocol that auto-adjusts the level of voltage to be achieved by SMR to get the feedback, the criterium to get the feedback was to put SMR voltage above the threshold, and the threshold was auto-adjusted to provide feedback 50% of the time. When more than one frequency band is being reinforced and/or inhibited, all set thresholds must be within the range that was set to receive feedback [36]. SMR amplitude was quantified by using digital filter and the update rate was 32 milliseconds on the feedback.

For the NF-selected group, a dimmer was placed in front of the video screen that offered sharpness when the patient met the criterium (put SMR voltage above the threshold) or became opaque, preventing the video from being viewed, when the criterium was not met (Figure 1).

The NF-sham group also was offered to choose both the form and type of the reinforcer, but we used an EEG simulation—a playback of a real EEG from a healthy individual—to run the session irrespective of the participants actual EEG.