Training the brain to time: the effect of neurofeedback of SMR-Beta1 rhythm on time perception in healthy adults.

The timing ability plays an important role in everyday activities and is influenced by several factors such as the attention and arousal levels of the individuals. The effects of these factors on time perception have been interpreted through psychological models of time, including Attentional Gate Model (AGM). On the other hand, research has indicated that neurofeedback (NFB) training improves attention and increases arousal levels in the clinical and healthy population. Regarding the link between attentional processing and arousal levels and NFB and their relation to time perception, this study is a pilot demonstration of the influence of SMR-Beta1 (12-18 Hz) NFB training on time production and reproduction performance in healthy adults. To this end, 12 (9 female and 3 males; M = 26.3, SD = 3.8) and 12 participants (7 female and 5 males; M = 26.9, SD = 3.1) were randomly assigned into the experimental (with SMR-Beta1 NFB) and control groups (without any NFB training), respectively. The experimental group underwent intensive 10 sessions (3 days a week) of the 12-18 Hz up-training. Time production and reproduction performance were assessed pre and post NFB training for all participants. Three-way mixed ANOVA was carried out on T-corrected scores of reproduction and production tasks. Correlation analysis was also performed between SMR-Beta1 and time perception. While NFB training significantly influenced time production (P < 0.01), no such effect was observed for the time reproduction task. The results of the study are finally discussed within the frameworks of AGM, dual-process and cognitive aspects of time perception. Overall, our results contribute to disentangling the underlying mechanisms of temporal performance in healthy individuals.

EEG Biofeedback for Treatment of Psychogenic Non-Epileptic Seizures (PNES) in Multiple Sclerosis: A Case Report.

The objective of the present study was to evaluate the effectiveness of EEG biofeedback for treatment of psychogenic non-epileptic seizures (PNES) in a patient with multiple sclerosis. The patient was a 47-year-old female who has been experiencing several PNES types after being diagnosed with multiple sclerosis. She underwent 16 sessions of the EEG biofeedback over a period of two months. Following EEG biofeedback, the patient reported that her PNES attacks had stopped and the treatment resulted in significant abatement in her clinical seizure symptoms. The analysis of sensorimotor rhythm (SMR) values revealed reduction of psychogenic non-epileptic seizure. The Beck Anxiety Inventory (BAI) and Word Health Organization Quality of Life Questionnaire (WHOQOL) were used before and after treatment. Decreased anxiety as well as increased quality of life was observed after treatment. Generally, the results indicated that EEG biofeedback was a useful procedure in treating PNES, promoting quality of life and reducing anxiety in our patient with multiple sclerosis.