Motor Imagery-Based Neurofeedback in Physiotherapy Practice

Abstract

Neurofeedback (NFB) is a closed-loop technique in which the patient receives feedback on brain activity to encourage voluntary control of brain activity. NFB promotes neuroplasticity and changes the brain functionally and structurally. Motor imagery-based NFB (MI-NFB) can improve motor imagery ability by providing feedback on brain activity during motor imagery, thereby showing effectiveness in performance and motor learning. Furthermore, the effects of MI-NFB are further enhanced when it is combined with noninvasive brain stimulation and motor exercise. Therefore, MI-NFB is used in the physiotherapy of patients with neurological diseases, such as stroke and Parkinson disease, as well as children with attention deficit-hyperactivity disorder and elderly people. This chapter reviews MI-NFB in physiotherapy practice, thus contributing to the development of effective evidence-based physiotherapy.

1. Introduction

Neurofeedback (NFB) is a technique that promotes voluntary control of brain activity by providing feedback on brain activity to the participant [1]. Kamiya found that electroencephalography (EEG) can be used to notice changes in brain states [2] and that it can be controlled spontaneously by feeding back activity in the α-frequency band [3]. These research results were the first step to developing NFB, which has been widely used to treat psychiatric disorders [4], improve cognitive function [5], enhance motor performance [6], and so on. In NFB, brain activity is measured mainly by EEG [7], functional magnetic resonance imaging (fMRI) [8], and functional near-infrared spectroscopy [9], and feedback on the activity in the targeted brain regions is provided to the participant to facilitate self-regulation of the participant’s brain activity. The methods used to provide feedback include visual feedback [10], in which brain activity is projected on a monitor, and auditory feedback [11], which uses sound stimuli of different frequencies. These methods are used to encourage participants to voluntarily adjust their brain activity.

Although many neural mechanisms underlying the effects of NFB are still unclear, several potential mechanisms have been proposed [12, 13, 14], one of which is the induction of neuroplasticity through NFB. In addition to changing motor performance and brain activity, NFB has also been shown to alter the structure of white matter [15]. For these reasons, neuroplasticity, which causes changes in brain structure, has been proposed to be a mechanism underlying the effects of NFB. The second potential mechanism involves changing the connectivity of the brain. The neural network associated with NFB can be divided into control, learning, and forward-processing networks [16]. The control network is composed of the frontoparietal control network, which consists of the dorsolateral frontal and posterior parietal cortices, with the participation of brain regions related to the processing of feedback stimuli, such as the lateral occipital cortex and thalamus. The dorsolateral frontal and posterior parietal cortices are associated with the execution of imagery and other processes [17] and may be important in the mental processes that control brain activity. The learning network consists of the dorsal striatum, which has been shown to be associated with motor control and learning based on procedural memory [18] and may be involved in learning to coordinate neural activity in NFB. Finally, the reward-processing network consists of the anterior insula, anterior cingulate cortex, and ventral striatum. The anterior insula [19] and anterior cingulate cortex [20] are associated with a conscious perception of reward, whereas the ventral striatum is associated with an unconscious perception of reward [21, 22]. The reward-processing network has been reported to be activated by the NFB [23], which is also known to regulate brain activity. Thus, the knowledge of results (KR) for regulating brain activity conferred by the NFB may be involved in the process of recognizing the accomplishment of the task, and these neural networks have been proposed to be related to NFB.

In addition to the NFB-related networks described above, NFB alters the connectivity of the language network and visual network, which are involved in internal reception [24]. NFB has also been reported to alter connectivity not only within the cerebrum but also between the primary motor cortex and the cerebellum [25], and NFB may produce its effects by altering connectivity between these brain regions. As described above, NFB has been suggested to cause functional and structural changes in the brain. This chapter reviews the NFB to motor imagery frequently used in physiotherapy practice.

2. Motor imagery-based neurofeedback

Recently, the effect of NFB on motor imagery has attracted much attention. This approach is called motor imagery-based NFB (MI-NFB). Motor imagery is a cognitive process of imagining what it is like to exercise without actual movement [26]. Motor imagery can be divided into myosensory first-person imagery and visual third-person imagery, and previous studies have reported individual differences in motor imagery ability [27, 28]. Motor imagery is known to improve performance [29] and has a motor-learning effect [30] even when the participant does not actually exercise. In addition, motor imagery has been supported from a neurological aspect, as there are areas where brain activity similar to that of actual exercise is observed [31], and resting EEG is altered by motor imagery [32]. On the basis of these background characteristics, motor imagery has been used in sports training for athletes [33] and in rehabilitation for stroke patients [34, 35]. However, one limitation of motor imagery is that the participant cannot understand the accuracy of the imagery because the actual movement does not occur [36]. NFB can be used to solve this problem. MI-NFB provides real-time feedback on brain activity during motor imagery to the participant and improves the accuracy of imagery by activating brain regions related to motor imagery [37]. In this section, the mechanism and effects of MI-NFB are explained on the basis of the results of studies conducted in healthy individuals.

MI-NFB has been reported to provide feedback on activity in the primary motor cortex (M1) [38, 39] and supplementary motor area (SMA) [40, 41] in many studies. These areas are activated by motor imagery and have been reported to be related to the accuracy of motor imagery [31]. The blood oxygen-level dependent (BOLD) signal in fMRI [40, 41] and the event-related desynchronization (ERD) of EEG β-rhythms [42] and μ-rhythms [43] are mainly used as feedback stimuli for MI-NFB. In this approach, the ERD reflects a decrease in the EEG signal caused by the occurrence of an event [44]. Control of these parameters related to motor imagery is then encouraged to improve the accuracy of motor imagery and motor performance (Figure 1).

Figure 1.

MI-NFB system using EEG. EEG is measured during motor imagery, and μERD data are used to provide feedback to the patients, including visual feedback using bar graphs or auditory feedback using sound stimuli. This system promotes voluntary control of EEG during motor imagery.

MI-NFB has been proposed to facilitate motor learning by providing KR [45]. KR is one of the basic principles underlying motor learning, and if motor learning involves actual exercise, the results are automatically returned as feedback by behavioral indicators and sensory stimuli, and motor learning is based on this information [46]. In contrast, motor imagery does not provide feedback on KR such as behavioral indices and sensory stimuli because it is not accompanied by actual movement. In this context, MI-NFB provides brain activity as KR, and motor learning is facilitated based on this information.

MI-NFB has been shown to alter brain activity and improve motor imagery ability [37]. Hwang et al. tested the effects of MI-NFB with visual stimuli in healthy young individuals [47]. In their study, right- or left-hand movements were used as the imagery task, the μ activity in the sensorimotor area was displayed on a monitor, and the participants received visual feedback regarding brain activity. The findings showed that this system facilitated control of brain activity during motor imagery. Their results indicated that MI-NFB enabled the control of μ activity, potentially indicating an improvement in motor imagery ability. Additionally, Grigorev et al. examined the effects of MI-NFB with vibrotactile stimulation in healthy young individuals [48]. In their study, the imagery task consisted of right- or left-handed movements. Vibration actuators were attached to the bilateral forearms and behind the neck and set to vibrate when μ-rhythmic ERD occurred, providing vibrotactile brain activity feedback (Figure 2). Their results showed that MI-NFB produced significantly greater ERD for non-dominant hand motor imagery, but it had no significant difference for dominant hand motor imagery. Since non-dominant hand movements require higher brain activity than dominant hand movements [49], the present results may modulate the brain activity mobilized for these non-dominant hand movements. Although MI-NFB has been suggested to enable the control of brain activity and improve the accuracy of motor imagery, as shown in the above study [48], the effect of MI-NFB varies depending on the conditions. Moreover, the effects of MI-NFB are not consistent in relation to the participant’s characteristics [50] and the difficulty of the task [51]. Therefore, improving the accuracy of MI-NFB and evaluating its responsiveness are future research topics.

Figure 2.

Experimental setup of MI-NFB using vibrotactile stimulation [48]. EEG was measured during motor imagery, and brain activity was returned as feedback to the participant in real time through a vibration actuator. The participant then had to imagine the hand movement to generate more vibration.

In this section, the basic mechanisms and effects of MI-NFB are described on the basis of previous studies. MI-NFB provides the participant KR in motor imagery accuracy, encouraging the participant to control brain activity related to motor imagery. This process improves the accuracy of motor imagery. Therefore, MI-NFB may be effective in addressing participants’ inability to understand whether their motor imagery is good or poor. However, the effectiveness of MI-NFB varies depending on the difficulty of the task and the participants’ characteristics; hence, more accurate MI-NFB is required in the future.

3. Combination of neurofeedback with other techniques

With the evolving usage of stimulators in physiotherapy [52], it is becoming increasingly clear that MI-NFB should not be used alone; rather, it should be used in combination with some other interventions to further amplify its effects. This section describes the use of MI-NFB in combination with other techniques.

3.1 Combination of neurofeedback with transcranial stimulation

Recent studies have begun examining the efficacy of transcranial stimulation combined with MI-NFB. Transcranial stimulation is classified into transcranial direct current stimulation (tDCS), transcranial alternating current stimulation, and transcranial magnetic stimulation [53]. These stimuli are used to promote brain plasticity and alter cognitive and mental functions [54], and their effects have attracted much attention. The effects of transcranial stimulation on motor imagery have been validated, with tDCS [55, 56], transcranial alternating current stimulation [56, 57], and transcranial magnetic stimulation [58] all shown to improve the accuracy of motor imagery. However, the effects of combining transcranial stimulation with MI-NFB are largely unclear.

In a study examining the effects of tDCS on MI-NFB [59], participants were divided into NFB and NFB + tDCS groups, and MI-NFB for left wrist dorsiflexion was performed. For the NFB + tDCS group, tDCS was performed before imaging. During NFB, EEG measurements were obtained, and the ERD of the μ-rhythm in M1 was projected on the monitor (Figure 3). In tDCS, the anode was placed on C4 and the cathode on the right upper arm, and anodal stimulation was administered to increase the activity of C4, which corresponds to the sensorimotor area of the left hand (Figure 4). The participants performed a motor imagery task without NFB before and after MI-NFB, and the EEG results obtained during the task were compared between the groups. The results showed that the ERD of the μ-rhythm in the NFB + tDCS group was significantly higher than that in the NFB group. This result indicates that the effect of MI-NFB alone, as well as the combination of MI-NFB and tDCS, can amplify the effect of MI-NFB. Both MI-NFB [37] and tDCS [55, 56] have been shown to improve MI accuracy, but the processes underlying their effects are different. Therefore, the effects of MI-NFB and tDCS do not appear to overlap, indicating the possibility of a synergistic effect.

Figure 3.

Experimental setup [59]. The participant sat in a chair and mentally imagined a dorsiflexion movement of the left wrist joint. During the imagery, EEG was measured, and the ERD of the μ-rhythm was represented as a bar graph on the monitor.

Figure 4.

tDCS setup [59]. A tDCS electrode was placed targeting C4, which corresponds to the sensorimotor area of the left hand. Anodal stimulation was applied to increase activity in this region.

As shown above, the efficacy of MI-NFB combined with tDCS has been demonstrated. Other electrical and magnetic stimuli also have similar mechanisms of action to tDCS, and their use in combination with MI-NFB may amplify the effects of MI-NFB. Intervention methods that combine such techniques are still in their infancy and require further study. In addition, noninvasive brain stimulation methods such as tDCS are not yet commonly used in physiotherapy practice. With advancements in brain science and engineering, physiotherapy using these devices will become widespread and provide effective rehabilitation.

3.2 Combination of neurofeedback with action observation or motor execution

Action observation and motor execution are often compared with motor imagery, and the accuracy of motor imagery and motor performance are improved when action observation and motor execution are combined with motor imagery [60, 61]. The effects of MI-NFB have also been shown to be improved by combining it with action observation and motor execution.

Action observation is a cognitive process of observing a scene in motion without moving [62]. Action observation and motor imagery have both been used in conjunction with motor execution to support motor learning, but both are different techniques, and it was believed that action observation and motor imagery cannot be used together. However, studies elucidating the neural bases and effects of these techniques have clarified that the combination of motor imagery and action observation improves the accuracy of motor imagery and motor performance [63]. Moreover, the effectiveness of the combination of action observation and MI-NFB has been verified in recent studies. Friesen et al. [64] used a handshake task to examine the effects of MI-NFB in combination with action observation. In their study, participants were divided into two groups: an NFB group, which received EEG feedback during the task, and a sham group, which received false stimulus feedback. The participants were required to watch a video of a complex handshake and simultaneously imagine the action (Figure 5). The ERD of μ-rhythms in the sensorimotor area was then measured, and the NFB group received visual feedback of brain activity by changing the saturation of the handshake video. Specifically, a vivid movie was displayed when a sufficient ERD was generated, and a monochrome movie was displayed when the ERD was insufficient (Figure 6). A comparison of ERD between groups showed that the NFB group had significantly higher ERD than the sham group, indicating an improvement in the accuracy of motor imagery when NFB is used in combination with action observation and motor imagery. The combination of motor imagery and action observation has been shown to increase cortical excitability [65] and activate motor-related networks [66]. In contrast, the results of this study showed that the combination of motor imagery and action observation did not have the greatest effect but that the effect was further enhanced when NFB was used in combination.

Figure 5.

Action observation of a handshake [64]. The participant was asked to imagine the motion while watching a video of a complex handshake.

Figure 6.

Providing NFB when action observation and MI-NFB are combined [64]. The participant performed action observation and motor imagery simultaneously, during which EEG measurements were obtained. Then, the handshake video was set to become vivid with the ERD of the μ-rhythm, providing visual feedback on brain activity.

Ono et al. [67] examined the combined effects of MI-NFB and action observation using proprioceptive NFB. In their study, participants were divided into an NFB group and a control group in which random feedback was provided, and training was conducted using a combination of action observation and motor imagery. A ball-gripping task was used in this study, and participants imagined the motion while watching a video of themselves gripping a ball. An exoskeleton robot was attached to the hand and set to passively generate finger-flexion movements when ERD with a sufficient μ-rhythm was generated during the task. This task was performed six times at 2-week intervals, and the ERD during motor imagery was continuously evaluated. The results showed a significant increase in the ERD in the NFB group in comparison with the control group. These results indicate that the combination of MI-NFB using proprioceptive and behavioral observations can improve the accuracy of motor imagery. Motor imagery and action observation may have activated motor-related areas, which were further modified by NFB. Similar to the findings of the study by Friesen et al. [64], this study showed that the combination of MI-NFB and action observation was effective. Furthermore, since proprioceptive feedback has been reported to be more effective than visual feedback in MI-NFB [68], the feedback system used in this study may have maximized the effects of motor imagery, action observation, and NFB, respectively. As shown in the above studies, the effectiveness of using MI-NFB in combination with action observation is being verified, and more effective methods of motor imagery training are being developed. Action observation is often used in physiotherapy practice, wherein patients observe the actions of physical therapists. Therefore, the results of these studies can be applied to physiotherapy practice to provide effective rehabilitation.

Motor execution generates myosensory and superficial sensory information that does not occur in motor imagery [69], which is thought to support motor imagery as KR [70]. In addition, motor execution has a neural mechanism that is partially similar to motor imagery [31]. For these reasons, the effects of training with motor execution and motor imagery have been examined [71]. The effects of combining MI-NFB and motor execution have been initially verified in recent studies. In one study, the authors examined the effects of combining MI-NFB and motor execution using a standing postural-control task [72]; the participants in this study were divided into the MIME group, which alternated between motor imagery and motor execution, and the MIME + NFB group, in which NFB was added to the motor imagery at that time. The task consisted of an actual exercise, in which the participant stood on an unstable board and kept the board horizontal, and a phase in which the participant imagined the exercise (Figure 7). The imagery of the exercise was performed in the resting sitting position, and the participants in the MIME + NFB group received ERD feedback of μ-rhythms in the motor-related regions during the imagery. The feedback method was auditory feedback, wherein higher-frequency sound stimuli were provided as the ERD increased. Performance on the standing postural-control task before and after training was compared between groups. The results showed significantly better standing postural control performance in the MIME + NFB group than in the MIME group. These results indicate that the combination of MI-NFB and motor execution improves the accuracy and performance of motor imagery. NFB provided KR of motor imagery from the neural activity aspect, and motor execution provided KR of motor imagery from the superficial and proprioceptive aspects, and their combined use may have improved the accuracy and effectiveness of motor imagery. Thus, the initial studies on the effects of combining MI-NFB and motor execution have suggested that this approach may improve the accuracy of motor imagery. Since there are many situations in physiotherapy practice where actual exercise and motor imagery are used together, the results of these studies can be applied to clinical treatment.

Figure 7.

A standing postural-control task combining MI-NFB and motor execution [72]. The participant stood on an unstable board and maintained the board in horizontal position. In the motor imagery task, the participant was asked to mentally imagine this standing postural-control task in a resting sitting position. Feedback regarding the ERD of the μ-rhythm during motor imagery was provided by auditory stimuli.

3.3 Summary

This section described the effects of using MI-NFB in combination with other techniques. The use of noninvasive brain stimulation methods that alter brain states similar to NFB as well as the addition of action observation and motor execution, which are comparable to motor imagery, to MI-NFB can improve its effectiveness. However, further research is needed to provide more effective MI-NFB, since many aspects of this technique remain to be verified, including the effects of the area to be stimulated and the intensity of the stimulation. In physiotherapy practice, motor imagery shows individual differences in its effectiveness [36]. Thus, combining it with the other techniques described above could solve this problem and facilitate effective exercise imagery training for all patients, thereby establishing evidence-based motor imagery and MI-NFB.

4. Neurofeedback in physiotherapy practice

MI-NFB has been validated not only in healthy individuals but also in patients with neurological diseases. This section presents clinical studies of MI-NFB in patients with neurological disorders and describes the physiotherapy practice of MI-NFB.

4.1 Neurofeedback for patients with stroke

The hemiplegia and motor impairment caused by stroke necessitate physical therapy [73]. In particular, stroke patients have reduced motor imagery ability [74, 75], and MI-NFB is used to improve the effectiveness of motor imagery training [76]. Moreover, upper limb function is less likely to recover after stroke than lower limb function [77], and MI-NFB has attracted attention as a new and effective intervention method.

Pichiorri et al. [78] examined the effects of MI-NFB on upper limb movement in patients with subacute stroke. In their study, participants were divided into a control group, which performed motor imagery without NFB, and an MI-NFB group, which performed motor imagery with NFB. EEG measurements were obtained during imaging, and the ERD of the β-rhythm was evaluated. In the MI-NFB group, the virtual hand on the monitor moved to provide visual feedback on brain activity. In this study, participants underwent regular rehabilitation, including physical therapy and occupational therapy for 3 hours a day, and motor imagery training was conducted in addition to these sessions. In a comparison of the control and MI-NFB groups, the MI-NFB group showed a significantly higher ERD of the β-rhythm during imagery, and this phenomenon occurred mainly in the impaired hemisphere. This result suggests that MI-NFB may have enhanced the accuracy of motor imagery by facilitating recruitment of the impaired hemisphere during motor imagery. In addition, an intergroup comparison of the functional connectivity of the resting brain after training showed that the MI-NFB group had significantly increased connectivity between hemispheres in high-frequency bands such as β. The details of this phenomenon are not yet clear, but it is suggested to be related to the compensatory functions of the brain. The injured hemisphere and the unaffected hemisphere may be tightly connected, and bilateral activity may have produced the motor imagery. Interhemispheric connectivity was also observed after imagery training, indicating that it may contribute to brain reorganization. In addition, MI-NFB improved motor function as assessed by the arm section of the Fugl-Meyer Assessment (FMA), the upper limb section of the Medical Research Council scale for muscle strength, and the National Institute of Health Stroke Scale. In particular, the FMA score improved by more than a minimal clinically important difference only in the MI-NFB group. These improvements in brain and motor function indicate that MI-NFB is effective in physiotherapy practice for upper limb function in stroke patients. Zich et al. [79] also examined the effects of frequent MI-NFB on home treatment of chronic stroke patients and presented case reports of three chronic stroke patients more than 6 months after stroke onset, one with mild upper limb paralysis and two with severe upper limb paralysis. In MI-NFB, the participants imagined hand movements and received visual feedback of β-rhythm ERDs assessed from EEG. After 4 weeks of home training with MI-NFB, all participants showed cortical activation in motor-related areas. In addition, upper limb motor function improved in participants who showed mild paralysis. This patient clearly showed functional and structural recovery of the central nervous system after the training. This study did not show motor function or structural brain changes in patients with severe paralysis but showed changes in patients with mild paralysis. These findings indicate that MI-NFB may be effective even in patients with chronic stroke. Future studies should continue to validate MI-NFB in chronic stroke patients, allowing for more widespread use of MI-NFB in physiotherapy practice.

MI-NFB has been examined not only for upper limb function but also for gait function. Mihara et al. [41] performed motor imagery training of gait in patients with gait disorders due to subcortical stroke. During the imagery training, frontal functional near-infrared spectroscopy measurements were obtained to provide visual feedback on blood flow in the SMA associated with the motor imagery. The participants were divided into two groups: the MI-NFB group, which received cerebral blood flow feedback, and the sham group, which received sham feedback. The MI-NFB group showed a significant increase in SMA blood flow in comparison with the sham group. In addition to changes in brain function, the MI-NFB group’s score on the Timed Up and Go test, a gait evaluation method, was significantly better after training. The results show that MI-NFB can effectively improve brain and motor function in gait, indicating that MI-NFB can be widely used in physiotherapy practice for stroke patients.

MI-NFB has been shown to improve upper limb and gait functions in stroke patients and may be an effective approach in physiotherapy practice. However, stroke symptoms vary according to the region of injury, and detailed classification of participants and investigation of interventional methods on the basis of the region of injury will contribute to the development of more effective MI-NFB. Conversely, a standard MI-NFB approach for stroke patients could be developed through large-scale studies that are not limited to the region of injury. Further research is needed to establish MI-NFB in physiotherapy practice for stroke patients.

4.2 Neurofeedback for patients with Parkinson disease

Parkinson disease (PD) is a neurological disorder whose main symptoms are resting tremors, muscle stiffness, immobility, and postural dysreflexia [80]. Motor imagery has been shown to be effective in treating these symptoms [81, 82], and MI-NFB is used to improve the effectiveness of motor imagery training. PD patients show decreased motor imagery ability [75, 83], and MI-NFB may contribute to symptom improvement in PD patients.

Subramanian et al. [84] examined the efficacy of MI-NFB in patients with Hoehn and Yahr stage I–III PD. The participants were divided into NFB and control groups and were required to imagine finger-tapping movements of the left hand. fMRI was measured during the imagery, and the BOLD signal of the SMA was returned as feedback to the NFB group. Next, the finger-tapping test and the fMRI BOLD signal during imagery were evaluated before and after training. The finger-tapping test involves tapping the thumb and index finger at maximum speed and reflects the immobility of PD patients [85]. The results showed upregulated SMA brain activity and greater finger-tapping speed in the NFB group in comparison with the control group. The results indicate that MI-NFB modulates brain activity in regions related to PD symptoms and improves immobility. A compensatory network involving the basal ganglia and thalamus is activated in PD as symptoms progress [86]. In addition, SMA projects to the globus pallidus internus of the basal ganglia and thalamus [87, 88], suggesting that MI-NFB may activate the compensatory network. As reported in the above studies, MI-NFB has been shown to be effective in treating motor symptoms in PD patients. Additionally, Subramanian et al. [89] examined the effect of combining exercise therapy and MI-NFB in PD patients. In their study, participants with Hoehn and Yahr stage I–III PD were divided into two groups: the EX group, which received exercise therapy, and the NF group, which received MI-NFB in addition to exercise therapy, and trained for 10 weeks. The EX group performed finger-tapping and postural-control tasks using a virtual reality game device as exercise therapy. In contrast, the NF group performed finger-tapping motor imagery and postural-control tasks. The motor score of the Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) [90] was performed before and after training. The MDS-UPDRS consists of four items: daily motor experiences, daily non-motor experiences, motor tests, and motor complications. In addition, the MDS-UPDRS and other PD symptom scales were assessed before, during, and after the 4-week intervention. The results showed that the motor examination score of MDS-UPDRS significantly improved in the NF group in comparison with the EX group in the unmedicated condition. However, the MDS-UPDRS scores with medication did not show significant group differences for any of the items (Figure 8). This result indicates that MI-NFB may contribute to the recovery of basal ganglia function. In the on-medication condition, PD patients are treated with levodopa and other common PD medications that affect the basal ganglia. However, the findings of the study described above showed a difference in motor function with MI-NFB only in the off-medication condition, suggesting that MI-NFB may be an alternative to pharmacotherapy. Thus, MI-NFB has been shown to influence task performance reflecting motor symptoms as well as a general scale assessing the severity of PD. However, MI-NFB did not improve motor function in the on-medication condition. Since most patients with PD are on medication, the clinical usefulness of MI-NFB requires investigation of approaches to improve motor symptoms while on medication.

Figure 8.

Effects of MI-NFB combined with exercise therapy in PD patients [89]. (A) The motor examination score of the MDS-UPDRS in the off-medication condition was significantly better in the NF group than in the EX group. (B–D) However, the overall, non-motor experience or motor experience MDS-UPDRS scores with medication showed no significant group differences.

In physiotherapy practice, MI-NFB may be an effective approach to improve motor symptoms such as immobility in PD patients. Since the basal ganglia, which are impaired by PD, are connected to the SMA, which is activated by MI-NFB, MI-NFB can improve symptoms via the SMA. However, the effectiveness of MI-NFB depends on the medication conditions, and further validation is needed to devise an effective MI-NFB protocol. In addition to motor symptoms, PD often presents with non-motor symptoms such as autonomic and psychiatric symptoms. Therefore, the potential effects of non-motor symptoms on the effectiveness of MI-NFB also require consideration.

4.3 Summary

This section presented information regarding the physiotherapy practice of MI-NFB on the basis of its effects on stroke and PD patients; MI-NFB may be effective for stroke and PD caused by brain damage because it encourages the voluntary regulation of brain activity. However, MI-NFB is not always effective for these neurological diseases because their symptoms differ among patients. The findings also indicate the need to develop a method for selecting patients for whom MI-NFB is indicated as well as new MI-NFB protocol that demonstrates a certain level of effectiveness regardless of the characteristics of the patients. With the establishment of additional evidence, MI-NFB may emerge as a standard approach in physiotherapy practice.

5. Conclusion

This chapter described MI-NFB findings from basic studies in healthy individuals and clinical studies in patients with neurological diseases. Many studies have shown that MI-NFB facilitates voluntary control of brain activity and improves motor performance. The use of MI-NFB in combination with other techniques such as transcranial stimulation and action observation has been shown to further enhance its effects. Although clinical studies on patients are still scarce, a certain level of effectiveness has been demonstrated. Therefore, MI-NFB may be an effective approach in the practice of physiotherapy. However, further evidence needs to be developed for the widespread use of MI-NFB; controlling the brain with MI-NFB may raise the level of physiotherapy practice.

Acknowledgments

This work was supported by JSPS KAKENHI (grant number JP23K10417). We would like to thank Editage (www.editage.com) for English language editing.

Conflict of interest

The authors declare no conflict of interest.

Appendices and nomenclature

NFB	neurofeedback
EEG	electroencephalography
fMRI	functional magnetic resonance imaging
MI-NFB	motor imagery-based neurofeedback
M1	primary motor cortex
SMA	supplementary motor area
ERD	event-related desynchronization
KR	knowledge of result
tDCS	transcranial direct current stimulation
ME	motor execution
FMA	Fugl-Meyer assessment
MDS-UPDRS	Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale