Neurofeedback Using Real-Time Near-Infrared Spectroscopy Enhances Motor Imagery Related Cortical Activation

Accumulating evidence indicates that motor imagery and motor execution share common neural networks. Accordingly, mental practices in the form of motor imagery have been implemented in rehabilitation regimes of stroke patients with favorable results. Because direct monitoring of motor imagery is difficult, feedback of cortical activities related to motor imagery (neurofeedback) could help to enhance efficacy of mental practice with motor imagery. To determine the feasibility and efficacy of a real-time neurofeedback system mediated by near-infrared spectroscopy (NIRS), two separate experiments were performed. Experiment 1 was used in five subjects to evaluate whether real-time cortical oxygenated hemoglobin signal feedback during a motor execution task correlated with reference hemoglobin signals computed off-line. Results demonstrated that the NIRS-mediated neurofeedback system reliably detected oxygenated hemoglobin signal changes in real-time. In Experiment 2, 21 subjects performed motor imagery of finger movements with feedback from relevant cortical signals and irrelevant sham signals. Real neurofeedback induced significantly greater activation of the contralateral premotor cortex and greater self-assessment scores for kinesthetic motor imagery compared with sham feedback. These findings suggested the feasibility and potential effectiveness of a NIRS-mediated real-time neurofeedback system on performance of kinesthetic motor imagery. However, these results warrant further clinical trials to determine whether this system could enhance the effects of mental practice in stroke patients

Association between aphasia severity and brain network alterations after stroke assessed using the electroencephalographic phase synchrony index

Abstract Electroencephalographic synchrony can help assess brain network status; however, its usefulness has not yet been fully proven. We developed a clinically feasible method that combines the phase synchrony index (PSI) with resting-state 19-channel electroencephalography (EEG) to evaluate post-stroke motor impairment. In this study, we investigated whether our method could be applied to aphasia, a common post-stroke cognitive impairment. This study included 31 patients with subacute aphasia and 24 healthy controls. We assessed the expressive function of patients and calculated the PSIs of three motor language-related regions: frontofrontal, left frontotemporal, and right frontotemporal. Then, we evaluated post-stroke network alterations by comparing PSIs of the patients and controls and by analyzing the correlations between PSIs and aphasia scores. The frontofrontal PSI (beta band) was lower in patients than in controls and positively correlated with aphasia scores, whereas the right frontotemporal PSI (delta band) was higher in patients than in controls and negatively correlated with aphasia scores. Evaluation of artifacts suggests that this association is attributed to true synchrony rather than spurious synchrony. These findings suggest that post-stroke aphasia is associated with alternations of two different networks and point to the usefulness of EEG PSI in understanding the pathophysiology of aphasia

Configuration and testing of the neurofeedback system using NIRS.

<p><b><i>A,</i></b> Representation of time course of the experiment. Subjects were asked to perform 15 repetitions of a 5-s task with randomized inter-task rest periods between 8–15 s. The total length of one experimental session was no longer than 250 s. <b><i>B,</i></b> Schematic figure of the NIRS-mediated neurofeedback system. Task-related cortical hemoglobin signal changes were transferred to a data-processing computer, and the evaluated cortical activation was visually fed back in real-time. Cortical activation was represented by bar height and color. <b><i>C,</i></b> The NIRS-mediated neurofeedback system in use. Subjects were seated in an armchair, and the heads were fixed to the headrest to avoid excessive head movement during experimentation.</p

DeoxyHb signal-based cortical mapping analysis for motor imagery with feedback.

<p>CH: channel number; BA: Brodmann area; SPL: superior parietal lobule.</p

Correlation analysis between t-values calculated from task-by-task analyses (T_Ref) and t-values calculated from sliding-window GLM analyses (T_SWA).

<p>Correlation analysis between t-values calculated from task-by-task analyses (T_Ref) and t-values calculated from sliding-window GLM analyses (T_SWA).</p

Individual self-assessment scores from 21 participants.

<p>M: male F: female.</p

Design matrices for real-time processing and off-line processing.

<p><b><i>A,</i></b> The design matrix for real-time sliding-window GLM analysis. The time window was 80 data points wide. The matrix consisted of one constant column, three columns for task and rest phases, respectively, and one linear term (L). Task-related signal changes were estimated as a beta value, comparing task data with resting data. <b><i>B,</i></b> The design matrix for off-line task-by-task GLM analysis. The matrix consisted of a constant column, columns for each task, and a high-pass filter with a cut-off frequency of 0.0125 Hz.</p