Abstract

Objective: Brain-computer interface (BCI) training is becoming increasingly popular in neurorehabilitation. However, around one third subjects have difficulties in controlling BCI devices effectively, which limits the application of BCI training. Furthermore, the effectiveness of BCI training is not satisfactory in stroke rehabilitation. Intermittent theta burst stimulation (iTBS) is a powerful neural modulatory approach with strong facilitatory effects. Here, we investigated whether iTBS would improve BCI accuracy and boost the neuroplastic changes induced by BCI training.Methods: Eight right-handed healthy subjects (four males, age: 20–24) participated in this two-session study (BCI-only session and iTBS+BCI session in random order). Neuroplastic changes were measured by functional near-infrared spectroscopy (fNIRS) and single-pulse transcranial magnetic stimulation (TMS). In BCI-only session, fNIRS was measured at baseline and immediately after BCI training. In iTBS+BCI session, BCI training was followed by iTBS delivered on the right primary motor cortex (M1). Single-pulse TMS was measured at baseline and immediately after iTBS. fNIRS was measured at baseline, immediately after iTBS, and immediately after BCI training. Paired-sample t-tests were used to compare amplitudes of motor-evoked potentials, cortical silent period duration, oxygenated hemoglobin (HbO2) concentration and functional connectivity across time points, and BCI accuracy between sessions.Results: No significant difference in BCI accuracy was detected between sessions (p > 0.05). In BCI-only session, functional connectivity matrices between motor cortex and prefrontal cortex were significantly increased after BCI training (p's < 0.05). In iTBS+BCI session, amplitudes of motor-evoked potentials were significantly increased after iTBS (p's < 0.05), but no change in HbO2 concentration or functional connectivity was observed throughout the whole session (p's > 0.05).Conclusions: To our knowledge, this is the first study that investigated how iTBS targeted on M1 influences BCI accuracy and the acute neuroplastic changes after BCI training. Our results revealed that iTBS targeted on M1 did not influence BCI accuracy or facilitate the neuroplastic changes after BCI training. Therefore, M1 might not be an effective stimulation target of iTBS for the purpose of improving BCI accuracy or facilitate its effectiveness; other brain regions (i.e., prefrontal cortex) are needed to be further investigated as potentially effective stimulation targets.

Highlights

  • Brain computer interface (BCI) can directly translate brain activities reflecting the subject’s intention into motor commands for controlling an external device (Abiri et al, 2019)

  • The increased BCI accuracy cannot be transferred to improved effectiveness of BCI training in motor recovery following stroke (Ang et al, 2015; KasashimaShindo et al, 2015; Hong et al, 2017); this is possibly because anodal transcranial direct current stimulation (tDCS) could not facilitate neuroplastic changes induced by BCI training

  • We investigated how Intermittent thetaburst stimulation (TBS) (iTBS) targeted on primary motor cortex (M1) influenced BCI accuracy and neuroplastic changes induced by BCI training

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Summary

Introduction

Brain computer interface (BCI) can directly translate brain activities reflecting the subject’s intention into motor commands for controlling an external device (Abiri et al, 2019). With BCI, stroke survivors are able to control external devices bypassing the damaged physiological motor output system (Daly and Wolpaw, 2008), including those with severe hemiparesis who cannot actively participate in traditional motor training (Ramos-Murguialday et al, 2013). The closedloop BCI system provides stroke survivors with a chance to actively participate in motor training and activate their motorrelated cortices (Pichiorri et al, 2015). The effectiveness of BCI training on motor recovery following stroke has been reported in several clinical studies (Teo and Chew, 2014; Pichiorri et al, 2015; Sun et al, 2017; Wu et al, 2019)

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