Differential BOLD fluctuations in brain networks after BCI Training with and without tDCS in Stroke

Submission No:


Submission Type:

Abstract Submission 


Mengjiao Hu1,2, Fang Ji2, Zhongkang Lu3, Weimin Huang3, Reza Khosrowabadi2, Ling Zhao4, Kai Keng Ang3, Kok Soon Phua3, Fatima Ali Nasrallah5, Kai-Hsiang Chuang5,6, Mary C Stephenson7, John Totman7, Xudong Jiang8, Effei Chew4, Cuntai Guan9, Juan Zhou2,7


1Interdisciplinary Graduate School, Nanyang Technological University, Singapore, Singapore, 2Centre for Cognitive Neuroscience, Duke-National University of Singapore Medical School, Singapore, Singapore, 3Institute for Infocomm Research, Agency for Science Technology and Research, Singapore, Singapore, 4Division of Neurology, University Medicine Cluster, National University Health System, Singapore, Singapore, 5Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore, 6Queensland Brain Institute and Centre for Advanced Imaging, the University of Queensland,, Queensland, Australia, 7Clinical Imaging Research Centre, the Agency for Science, Technology and Research, Singapore, Singapore, 8Electrical & Electronic Engineering, Nanyang Technological University, Singapore, Singapore, 9School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore


Mapping the brain alterations post stroke and post intervention is important for rehabilitation therapy development. Previous work has shown changes in functional connectivity based on resting-state fMRI, structural connectivity derived from diffusion MRI, and perfusion as a result of brain-computer interface-assisted motor imagery (MI-BCI) and transcranial direct current stimulation (tDCS) in upper-limb stroke rehabilitation [1, 2, 3]. Besides functional connectivity, regional amplitude of local low frequency fluctuations (ALFF) may provide complementary information on the underlying neural mechanism in disease [4, 5]. Yet, findings on spontaneous brain activity during resting-state in stroke patients after intervention are limited and inconsistent [6, 7]. Here, we sought to investigate the different neuroplasticity induced by tDCS compared to MI-BCI for upper-limb rehabilitation in chronic stroke patients using resting-state fMRI-based ALFF method. We hypothesized that stroke patient would have lower ALFF in the ipsilesional somatomotor network compared to controls at baseline. Increased ALFF both ipsilesional and contralesional somatomotor network and alternations in higher-level cognitive networks such as the default mode (DMN) and salience networks would accompany motor recovery after intervention; though the MI-BCI alone group and MI-BCI combined with tDCS group would exhibit differential patterns.


19 chronic stroke patients were randomized into MI-BCI with tDCS group and MI-BCI with sham-tDCS group. MRI and task-free fMRI were scanned before and 4 weeks after intervention. 11 healthy controls (HC) also underwent brain scans at baseline. Motor function of the affected arm of stroke patients was evaluated by the upper extremity component of the Fugl-Meyer assessment (FMA) before and after intervention. For patients with right hemispheric lesion, we flipped their images for group analysis (i.e., left = ipsilesional). Standard preprocessing and ALFF calculation were performed. After quality control, the whole-brain ALFF maps of 18 patients and 11 HC were compared at baseline. The effect of MI-BCI with and without tDCS were investigated by group and time interaction followed by comparisons before and after intervention for each group separately. Results were reported at the height threshold of p<0.01 and cluster-level of p<0.05, GRF corrected.


At baseline, stroke patients had reduced ALFF in the ipsilesional somatomotor network and increased ALFF in the DMN and anterior cingulate cortex (part of salience network) compared to HC (Fig. 1). After intervention, both patients groups improved motor functions. In parallel, the main effect of time (i.e., after intervention) indicated decreased ALFF in the DMN and increased ALFF in the contralesional somatomotor network. Moreover, though the MI-BCI with and without tDCS groups did not differ in motor recovery, we found significant group and time interactions in the ALFF of the DMN. Post-doc analyses revealed that the observed main effect of intervention above was dominated by the MI-BCI group with sham tDCS, i.e., decreased DMN and increased contralesional somatomotor network ALFF (Fig. 2). In contrast, the MI-BCI with tDCS group did not have any changes in ALFF at the height threshold of p<0.01 and cluster-level of p<0.05 corrected. Interestingly, at a lower threshold of a joint height and cluster threshold of p<0.05 corrected, increased ALFF at the anterior cingulate cortex was found in this group.
Supporting Image: Figure1.PNG
Supporting Image: Figure2.PNG


Our findings demonstrated MI-BCI with and without tDCS intervention exhibited different neuroplasticity mechanism in terms of spontaneous regional activity in stroke patients underlying comparable motor improvement. The effects of MI-BCI and tDCS were not additive but instead might be conflicting. Future work should study the relationship between brain changes and motor recovery for these two intervention strategies in a larger sample of stroke.

Brain Stimulation Methods:

Non-invasive Electrical/tDCS/tACS/tRNS 2

Disorders of the Nervous System:

Stroke 1

Imaging Methods:


Modeling and Analysis Methods:

Task-Independent and Resting-State Analysis

Motor Behavior:

Motor Behavior Other



1|2Indicates the priority used for review