Multisensory BCI promotes motor recovery via high-order network-mediated interhemispheric integration in chronic stroke

Abstract

Background: Chronic stroke patients often experience persistent motor impairments, and current rehabilitation therapies rarely achieve substantial functional recovery. Sensory feedback during movement plays a pivotal role in driving neuroplasticity. This study introduces a novel multi-modal sensory feedback brain-computer interface (Multi-FDBK-BCI) system that integrates proprioceptive, tactile, and visual stimuli into motor imagery-based training. We aimed to explore the potential therapeutic efficacy and elucidate its neural mechanisms underlying motor recovery.

Methods: Thirty-nine chronic stroke patients were randomized to either the Multi-FDBK-BCI group (n = 20) or the conventional motor imagery therapy group (n = 19). Motor recovery was assessed using the Fugl-Meyer Assessment (primary outcome), Motor Status Scale, Action Research Arm Test, and surface electromyography. Functional MRI was used to examine brain activation patterns during upper limb tasks, while Granger causality analysis and machine learning evaluated inter-regional connectivity changes and their predictive value for recovery.

Results: Multi-FDBK-BCI training led to significantly greater motor recovery compared to conventional therapy. Functional MRI revealed enhanced activation of high-order transmodal networks-including the default mode, dorsal/ventral attention, and frontoparietal networks-during paralyzed limb movement, with activation strength positively correlated with motor improvement. Granger causality analysis identified a distinct information flow pattern: signals from the lesioned motor cortex were relayed through transmodal networks to the intact motor cortex, promoting interhemispheric communication. These functional connectivity changes not only supported motor recovery but also served as robust predictors of therapeutic outcomes.

Conclusions: Our findings highlight the Multi-FDBK-BCI system as a promising strategy for chronic stroke rehabilitation, leveraging activity-dependent neuroplasticity within high-order transmodal networks. This multi-modal approach holds significant potential for patients with limited recovery options and sheds new light on the neural drivers of motor restoration, warranting further investigation in clinical neurorehabilitation.

Trial registration: All data used in the present study were obtained from a research trial registered with the ClinicalTrials.gov database (ChiCTR-ONC-17010739, registered 26 February 2017, starting from 10 January 2017).

Keywords: Brain pasticity; Brain-computer interface; Hemiplegia; Multi-modal sensory feedback; Stroke.

Fig. 1

Diagram of study design. A Flow chart of the study protocol. Patients who meet the inclusion criteria underwent behavioral, electrophysiological and fMRI assessment. Then they were randomized into two groups, either received classical motor imagery therapy or Multi-FDBK-BCI therapy. When all the interventions were finished after 20 days, all the participants were reassessed. FMA, Fugl-Meyer assessment; sEMG, surface electromyography; ARAT, action research arm test; MSS, motor status scale. B Flow diagram of participant recruitment and participation in the study. C Demographic and clinical description of including participants at baseline

Fig. 2

Multi-FDBK-BCI therapy improved motor functions than motor imagery in chronic stroke patients. A Schematic of the experimental setup of Multi-FDBK-BCI therapy, including visual, tactile and proprioceptive feedbacks. B-E Significant enhancement of motor functions after Multi-FDBK-BCI therapy (N = 20) compared to those after motor imagery therapy (N = 19), including FMA (B) and sEMG (C). No significant changes were observed in the MSS (D) and ARAT (E) function for chronic stroke patients. Statistical significance was determined using the (B-D) two sample t-test (two tails) or (E) Mann-Whitney U test for inter-group comparison depending on the distribution of the data. FMA, Fugl-Meyer assessment; sEMG, surface electromyography; ARAT, action research arm test; MSS, motor status scale. Each dot represented an individual patient. The box showed the first and third quartiles; inner line was the median over sessions; whiskers represented minimum and maximum values

Fig. 3

Significant activations in human transmodal regions evoked by impaired hand movement after Multi-FDBK-BCI therapy for chronic stroke patients. A Schematic setup of fMRI task. L, left hand movement; R, right hand movement. B No significant difference (post- v.s. pre- Multi-FDBK-BCI therapy) of whole-brain activations under healthy hand movement (FDR corrected p < 0.05). N = 20 patients. C As in (B) but for impaired hand movement. Significant BOLD activations were observed in transmodal brain regions (FDR corrected p < 0.05). D Functional parcels based on Yeo et. al. [74] seven cortical networks. E Quantitative comparison of BOLD signal changes between pre- and post- Multi-FDBK-BCI therapy across somatomotor, dorsal attention, ventral attention, frontoparietal and default mode networks in both lesion and healthy hemispheres. Error bar, standard error of the mean (SEM). N = 20 patients. Statistical significance was determined by one-way ANOVA with Tukey-Kramer's test for post hoc multiple comparisons. *, p < 0.05; n.s., no significance

Fig. 4

Significant correlations between BOLD responses and motor function recovery after Multi-FDBK-BCI therapy for chronic stroke patients. A Correlation between impaired hand movements evoked BOLD responses and behavioral changes after Multi-FDBK-BCI therapy. Red lines were scaled according to the Pearson’s correlation coefficients between behavioral (upper) and BOLD signal (lower) changes with threshold p < 0.05. B-G Scatter plot for BOLD signal and sEMG changes (post- v.s. pre- Multi-FDBK-BCI therapy). Each dot indicated an individual chronic stroke patient (N = 20). The red lines represented the best linear fit. Scatter plots for BOLD signal and FMA (or MSS) changes were shown in Supplementary Figure 3

Fig. 5

Multi-FDBK-BCI therapy strengthened the functional compensation of ipsi-lateral motor cortex through transmodal regions for chronic stroke patients. A Computational pipeline of granger causality changes across human functional networks between post- and pre- multi-FDBK-BCI therapy for chronic stroke patients’ impaired hand movement. B Significant difference of granger causalities between post- and pre- Multi-FDBK-BCI therapy for chronic stroke patients’ lesion hand movements (paired t-test, two tails). C Mechanism summary of motor function recovery for chronic stroke patients after multi-FDBK-BCI therapy. For impaired hand movement, multi-FDBK-BCI therapy enhanced the information interaction among transmodal regions and thus achieved the motor function compensation of ipsilateral motor cortex

Fig. 6

Δ Granger causality had utility in predicting subject-level motor function recovery. A Schematic illustrating the ‘leave-one-subject-out’ procedure for predicting single-patient behavioral changes of motor function. Models were fit using the Δ Granger causality and behavioral changes from n-1 subjects to predict the behavioral change for the remaining 1 subject. B No significant difference between empirical and model predicted behavioral changes, illustrating the robustness of the model. N = 20 subjects; paired t-test, two tails. FMA, Fugl-Meyer assessment; sEMG, surface electromyography; MSS, motor status scale