Neurofeedback and physical balance in Parkinson's patients
Introduction
Over the past 60 years, it has been discovered that it is possible to reconstruct and retrain brainwave patterns [1]. Brainwave training, called EEG biofeedback or neurofeedback training (NFT), can help in the treatment of many diseases that originate in the brain [2]. Neurofeedback is a kind of biofeedback in which people receive feedback of input signals that are related to their subconscious neural activities [3]. A patient who observes their brainwaves on a computer screen can control these waves and change them based on requirements. This leads to the patient learning to subconsciously control their brainwaves in the other conditions of life [3]. Neurofeedback can regulate brain function and has been successfully used to treat balance problems in some diseases, such as attention deficit hyperactivity disorder (ADHD), fibromyalgia, and chronic stroke [1], [2]. Hammond [4] reported on the successful treatment of balance problems in four clinical patients utilizing a specific protocol. Recent research by Thornton and Carmody [5] suggests that neurofeedback can often produce significant improvement, even many years after a head injury. Parkinson's disease (PD) is a particularly suitable target for such neurofeedback intervention because imbalance between cortical and subcortical motor circuits is at the heart of pathophysiological models [6]. Because balance and gait in Parkinson's disease are attention process demands, any improvement in the patient's attention can lead to an increase in the maintenance of balance [7], [8]. Several studies have shown that NFT can alter the beta frequencies that influence participants’ attentional processing. Rasey et al. [9] reported on 20 training sessions to enhance beta (16–22 Hz) and inhibit high theta (4–8 Hz) in the CPz–PCz. Egner and Gruzelier [10] trained 22 participants to enhance low beta and inhibit theta. They concluded that a successful enhancement of attentional performance in healthy volunteers through EEG-operant conditioning techniques can be achieved. Others studies reported that neurofeedback training to enhance beta activity may influence semantic working memory performance. Vernon et al. [11], [12] suggested that enhancing 12–15 Hz helps the maintenance of the working memory representation utilized in semantic working memory. Egner et al. [13] reported that enhancing low beta and beta1 may have differential effects on attentional processing. In a subsequent study, they found [14] that focusing on beta1 enhancement can improve musical performance. However, the effectiveness of neurofeedback training in these waves is not limited to attentional processing or working memory [4]. Furthermore, it should be noted that treatment of patients with motor deficiencies has been considered by researchers as another application of neurofeedback training [15]. Since there is a relationship between specific patterns of cortical activity and particular levels of performance, the use of neurofeedback to train patients with motor deficiencies to recreate patterns of cortical activity can result in enhanced performance [16]. This study can be considered proof of concept for the application of neurofeedback for patients with a neurodegenerative disorder. We furthermore wanted to assess whether neurofeedback provides clinical benefits to patients with early-stage PD. However, to the best of our knowledge, the treatment of PD patients with balance problems has not been investigated previously and the main purpose of this study is to evaluate the effects of neurofeedback training on both dynamic and static balance in Parkinson's patients.
Section snippets
Participants
The participants of the current study were 16 PD patients in stage 1.5–2 on the Hoehn and Yahr scale [17]. The participants were selected using purposive sampling, and they provided informed consent to participate in the research. They were randomly divided into experimental and control groups. Each group consisted of eight patients (four women and four men). All participants lived at home and were tested while on medication. Levodopa-equivalent dosages were calculated to express dose intensity
Results
Repeated measures ANOVA for static and dynamic balance scores indicated that differences between factors and conditions were statistically significant (Table 2). Specifically, in the experimental group, static and dynamic balance scores improved (p ≤ 0.001).
The mean amplitude for the training frequencies across the eight sessions is shown in Fig. 2. The experimental group showed an increase in beta1 mean and decrease in theta mean from session one to eight. Table 3 shows beta and theta wave
Discussion
In this study, we examined the effect of neurofeedback training on PD patient's balance. The results provided evidence that 30 min of NFT inhibit 4–7 Hz while reinforcing 15–18 Hz activity over eight sessions. This can contribute, at least temporarily, to the improvement in both static and dynamic balance of PD patients. Previous studies have shown the effect of neurofeedback balance training on patients with Parkinson's disease [21]. They reported that neurofeedback balance training could reduce
Conclusion
In this study, the effects of neurofeedback on balance of patients with Parkinson disease were successfully verified. The results showed that this method can be effective for improving the dynamic and static balance of PD patients. The research concluded that during NFT, subjects can learn to selectively control their brain waves. These results confirm previous studies that claimed that neurofeedback could treat other kinds of diseases. The results also demonstrated that NFT can complement
Limitations and perspectives
The research showed that NFT can improve PD patient balance, but much more work remains. The present intervention was brief and not intensive. Also a lack of follow-up measurements was a limitation of this study. It would be interesting to investigate the effects of longer-term or more intensive NFT on PD patients as well as long-term effects of neurofeedback. In the current study, the number of participants was low and disease severity was mild, without cognitive decline. We suggest that
Conflict of interest statement
We confirm that this study has not any financial and personal relationships with other people or organizations that could inappropriately influence (bias) our work. Also there is not any potential conflicts of interest include employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, and grants or other funding.
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2020, Biomedical Signal Processing and ControlCitation Excerpt :The reason for this choice was that the efficiency and effectiveness of the training course would be further enhanced if the neurofeedback training protocol had been specifically designed based on the differences of the brain signals in the target group and the training one. In most research studies in the field of neurofeedback, a constant scoring method had been employed [7,12,47,51–55,78,79,84]. Accordingly, one point could be added to the total scores obtained by subjects based on their success rates and they could be encouraged with the same audio or video feedback.