Self-Paced Online vs. Cue-Based Offline Brain–Computer Interfaces for Inducing Neural Plasticity

Abstract

Brain–computer interfaces (BCIs), operated in a cue-based (offline) or self-paced (online) mode, can be used for inducing cortical plasticity for stroke rehabilitation by the pairing of movement-related brain activity with peripheral electrical stimulation. The aim of this study was to compare the difference in cortical plasticity induced by the two BCI modes. Fifteen healthy participants participated in two experimental sessions: cue-based BCI and self-paced BCI. In both sessions, imagined dorsiflexions were extracted from continuous electroencephalogram (EEG) and paired 50 times with the electrical stimulation of the common peroneal nerve. Before, immediately after, and 30 min after each intervention, the cortical excitability was measured through the motor-evoked potentials (MEPs) of tibialis anterior elicited through transcranial magnetic stimulation. Linear mixed regression models showed that the MEP amplitudes increased significantly (p < 0.05) from pre- to post- and 30-min post-intervention in terms of both the absolute and relative units, regardless of the intervention type. Compared to pre-interventions, the absolute MEP size increased by 79% in post- and 68% in 30-min post-intervention in the self-paced mode (with a true positive rate of ~75%), and by 37% in post- and 55% in 30-min post-intervention in the cue-based mode. The two modes were significantly different (p = 0.03) at post-intervention (relative units) but were similar at both post timepoints (absolute units). These findings suggest that immediate changes in cortical excitability may have implications for stroke rehabilitation, where it could be used as a priming protocol in conjunction with another intervention; however, the findings need to be validated in studies involving stroke patients.

A Systematic Review of Paired Associative Stimulation (PAS) to Modulate Lower Limb Corticomotor Excitability: Implications for Stimulation Parameter Selection and Experimental Design

“…Any disagreement was discussed with a third reviewer (DT) until consensus was achieved. All reviewers have experience in the application of TMS and experimental neurophysiological research methods in both healthy and stroke populations (Lewis et al, 2014; Jochumsen et al, 2016, 2019; Olsen et al, 2018).…”

Induction of Neural Plasticity Using a Low-Cost Open Source Brain-Computer Interface and a 3D-Printed Wrist Exoskeleton

“…Brain-computer interfaces (BCIs) have over the past years been proposed also as a tool for motor rehabilitation after neural injuries, such as spinal cord injury or stroke [ 1 , 2 , 3 , 4 , 5 , 6 ]. It is well-established that BCIs can be used for inducing neural plasticity [ 7 , 8 , 9 , 10 , 11 ], which is believed to be the underlying mechanism of motor learning/recovery [ 12 ]. These neuroplastic changes are induced in the brain by pairing the movement-related activity of the brain with the inflow of congruent somatosensory feedback from, e.g., electrical stimulation [ 7 ], rehabilitation robots, or exoskeletons [ 8 ].…”

“…Both of these movement types are important to train during stroke rehabilitation. It has been shown previously that neural plasticity, when quantified with transcranial magnetic stimulation (TMS), can be induced using BCI-triggered electrical stimulation and passive movements from rehabilitation robots/exoskeletons for the cortical projections of the lower limb muscles [ 7 , 8 , 9 , 10 , 11 ], but this has not been shown for the cortical projections of the upper limb muscles, although functional improvements in stroke patients have been reported for the upper limbs (see, e.g., Refs. [ 4 , 5 , 27 , 28 ]).…”

Development of a brain-computer interface for patients in the critical care setting

“…Self-paced BCI systems, however, possess their own set of challenges. Due to the large amount of data continuously processed over time, self-paced BCI systems must rely on high true positive rates and a low number of false positive detections [ 14 ].…”