Results from the present study demonstrated that the NIRS system can be used to detect real-time task-related hemoglobin signal changes, and this system can be reliably used as a neurofeedback tool. During motor learning processes, correct information feedback about performance (“knowledge of result”) is known to be effective in healthy subjects and in stroke patients 
. For tasks related to motor imagery, difficulty of objective evaluation has traditionally hampered collection and dissemination of correct information pertaining to task performance. However, results from the present study suggested that neurofeedback methods could provide important information about local brain activity associated with motor imagery.
Results from Experiment 1 revealed that hemoglobin signal changes were detected by the sliding-window GLM analysis with a hemodynamic delay of several seconds. Results from real-time processing in this system represented task-related cortical hemoglobin signal changes. Compared with other neuroimaging modalities, the NIRS-mediated neurofeedback system exhibits several advantages for clinical application, including relative robustness of subject motion, shorter attachment time, and less subject constraint. However, one main technical flaw of the NIRS measurements is the delay of several seconds between neuronal activation and hemoglobin signal changes. Simultaneous measurement of NIRS and EEG, which measures direct neuronal activation and has greater temporal resolution, could be a possible solution for methodological limitations 
, because these techniques produce a complementary effect. However, the combination of EEG and NIRS requires longer experimentation time and could reduce feasibility in a clinical setting.
The present results demonstrated that OxyHb was more robust under real-time assessment conditions for task-related cortical activation. However, it remains to be determined which hemoglobin parameters are more suitable for measuring cortical activation. Although the current theoretical framework for blood level-dependent (BOLD) signals in fMRI suggests that decreased DeoxyHb concentrations correlate with greater BOLD signals 
, some studies have reported greater correlations between BOLD and OxyHb signals 
. OxyHb signals have also been shown to be sensitive to changes, but DeoxyHb signals are more selective and localized 
. Lower sensitivity and greater spatial selectivity for DeoxyHb signal changes could explain the present results. In addition, wavelength selection could affect sensitivity of Oxy- and DeoxyHb signals. The NIRS system utilized three wavelengths (780 nm, 805 nm, and 830 nm). However, several studies have reported that the 782–830 nm pair results in less SNR than the 692–830 nm pair 
. In addition, the 790–825 nm pair results in less separation of OxyHb and DeoxyHb signals compared to the 710–905 nm pair 
. These results suggest that wavelength selection in the current system could result in reduced sensitivity for DeoxyHb signal changes.
Results from Experiment 2 demonstrated that NIRS-mediated neurofeedback enhanced motor imagery-related cortical activation in the contralateral premotor cortex. These findings were consistent with previous findings from a fMRI-mediated neurofeedback study, which showed rostral enlargement of motor imagery-related motor cortical activation 
. Other studies have also suggested that the premotor cortex is a crucial region for the generation of motor imagery 
, and subjects with good motor imagery skills exhibit enhanced activation in the lateral premotor cortex compared to those with poor motor imagery skills 
. These results suggest that the premotor cortex could be a candidate for neurofeedback information in the motor imagery task. Further studies are needed to determine which cortical area is most effective as a neurofeedback for motor imagery augmentation.
Results from the present study also demonstrated significantly greater cortical activation in the parietal association cortex under sham feedback conditions. Previous studies have suggested that the medial parietal association cortex is involved in memory-related visual imagery 
and visuospatial imagery 
. In addition, activation in the medial parietal association cortex is increased during visual imagery compared with kinesthetic imagery of body part movement 
. Under sham conditions, the subjects could feel uncertain and lose confidence in kinesthetic imagery with incorrect feedback, which could mislead the subjects, because visual imagery would feel more familiar with healthy subjects and require less effort than kinesthetic imagery 
. This could be responsible for enhanced activation in the medial parietal association cortex under sham conditions. In this study, subjects improved their kinesthetic motor imagery by trial-and-error. Under real feedback conditions, the feedback signals increased if the subjects activated motor-related cortex areas during the task condition and relaxed during the rest condition. This effect helped to learn how to perform proper kinesthetic imagery. However, that was not the case under sham feedback conditions; the subjects could feel unsure of their kinesthetic motor imagery. This could be responsible for the small and non-significant correlation between self-assessment scores of kinesthetic motor imagery and average feedback height in this study. A previous study using NIRS showed that positive and negative feedback increases motor imagery-related cortical activation 
, which suggests that it is not greater feedback, but rather appropriate feedback, of motor imagery performance that is most helpful for improved motor imagery. Further studies are needed to determine the most effective feedback method for improving behavioral performance.
Bilateral prefrontal cortex and right premotor cortex were activated by the motor imagery task, regardless of type of provided feedback (real or sham). Because motor imagery requires much attention and concentration, prefrontal activation could be related to cognitive processes involved in motor imagery. Indeed, previous reports have consistently documented greater cortical activation in the bilateral premotor cortex and prefrontal cortex during motor imagery tasks compared with motor execution tasks 
Because cognitive processes, including planning, inhibition, and motor imagery, could evoke changes in heart and respiratory rate 
, it is possible that a systemic vascular response via
the autonomic nervous system, which was evoked by motor imagery, could have affected the task-related hemoglobin signal changes. However, the focal activation patterns were different between feedback conditions and were unlikely to be the result of extracerebral contamination. Previous studies have introduced techniques to eliminate the effect of systemic vascular changes on NIRS signals 
, which should be adopted in the case of extracerebral signal contamination. Further development of systems to adopt these methodologies would help to improve task flexibility.
Sham information served as feedback information for the control condition. In previous neurofeedback studies, several kinds of signals, including background signals with random fMRI noise 
, signals from different brain lesions 
, signal from other subjects 
, and signals from different region in the previous session 
were used as controls. The widespread cortical area includes the premotor and sensorimotor cortex, as well as the supplementary motor area, prefrontal cortex, and the parietal cortex 
. In the present study, the NIRS system measured activation only from the fronto-parietal cortical area. Therefore, all available channels could have been activated by the motor imagery task. For this reason, the randomized value was utilized for control (sham) feedback.
There were several limitations in this study. First, because the study included only healthy subjects, the effect of neurofeedback on stroke patients remains unclear. Although motor imagery in stroke patients is generally not impaired 
, the impairment level depends on site and extent of lesion 
. Accuracy and temporal coupling of motor imagery can be disrupted in some stroke patients, and further studies are needed to validate the effect of neurofeedback on motor imagery in stroke patients. Second, the long-term effect of neurofeedback on motor imagery and related cortical activation was not analyzed. A long-term effect of neurofeedback on motor imagery-related cortical activation of up to two weeks has been previously described in fMRI-mediated neurofeedback systems 
. However, a NIRS-mediated system should be tested for long-term use in clinical applications. Third, differences in pace and complexity of imagery could have affected cortical activations between the two feedback conditions 
. Although the subjects were asked to imagine movement in a similar manner and at similar pace as was physically performed, it is possible that greater activation would result from faster or more complex finger imagery. Finally, only visual inspection was performed to detect overt finger movements during motor imagery without EMG monitoring. The subject finger was not constrained to avoid isometric muscle contraction, and subjects with overt finger movements were excluded. However, it could be possible that minimal muscle activation was evoked during imagery. Although marginal muscle activation was not excluded, it was assumed that these activities would not significantly differ between the feedback conditions. Comparison of timeline analysis and second-level imaging analysis under both feedback conditions revealed comparable activation in channels covering the sensorimotor cortex (channel 4). Previous results revealed that motor execution involves the limited area of the sensorimotor cortex 
. Therefore, taking the poor spatial resolution of NIRS into consideration, it was assumed that the effect of subliminal EMG activation remained limited in this study.
In conclusion, results from the present study demonstrated the feasibility of a NIRS-mediated neurofeedback system and revealed the modulative effect of this system on motor imagery-related cortical activation. Results suggested that neurofeedback could facilitate individual skills for kinesthetic motor imagery. The NIRS-mediated neurofeedback system could be a promising tool, which could be applied in widespread areas, including neurorehabilitation. However, further clinical trials are needed to determine whether this system could enhance mental practice in stroke patients.