Health and Rehabilitation Research Institute and BioDesign Lab, Auckland University of Technology, Auckland, New Zealand.
SMI, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark.
Ann Clin Transl Neurol. 2022 May;9(5):722-733. doi: 10.1002/acn3.51551. Epub 2022 Apr 30.
We propose a novel cue-based asynchronous brain-computer interface(BCI) for neuromodulation via the pairing of endogenous motor cortical activity with the activation of somatosensory pathways.
The proposed BCI detects the intention to move from single-trial EEG signals in real time, but, contrary to classic asynchronous-BCI systems, the detection occurs only during time intervals when the patient is cued to move. This cue-based asynchronous-BCI was compared with two traditional BCI modes (asynchronous-BCI and offline synchronous-BCI) and a control intervention in chronic stroke patients. The patients performed ankle dorsiflexion movements of the paretic limb in each intervention while their brain signals were recorded. BCI interventions decoded the movement attempt and activated afferent pathways via electrical stimulation. Corticomotor excitability was assessed using motor-evoked potentials in the tibialis-anterior muscle induced by transcranial magnetic stimulation before, immediately after, and 30 min after the intervention.
The proposed cue-based asynchronous-BCI had significantly fewer false positives/min and false positives/true positives (%) as compared to the previously developed asynchronous-BCI. Linear-mixed-models showed that motor-evoked potential amplitudes increased following all BCI modes immediately after the intervention compared to the control condition (p <0.05). The proposed cue-based asynchronous-BCI resulted in the largest relative increase in peak-to-peak motor-evoked potential amplitudes(141% ± 33%) among all interventions and sustained it for 30 min(111% ± 33%).
These findings prove the high performance of a newly proposed cue-based asynchronous-BCI intervention. In this paradigm, individuals receive precise instructions (cue) to promote engagement, while the timing of brain activity is accurately detected to establish a precise association with the delivery of sensory input for plasticity induction.
我们提出了一种新的基于线索的异步脑机接口（BCI），通过将内源性运动皮层活动与感觉通路的激活相配对来进行神经调节。
该拟议的 BCI 实时检测单次试验 EEG 信号中的运动意图，但与经典的异步 BCI 系统不同，检测仅在患者被提示运动的时间间隔内进行。该基于线索的异步 BCI 与两种传统 BCI 模式（异步 BCI 和离线同步 BCI）以及慢性中风患者的对照干预进行了比较。在每种干预中，患者在记录其脑信号的同时进行瘫痪肢体的踝关节背屈运动。BCI 干预通过电刺激解码运动尝试并激活传入通路。使用经颅磁刺激在前、干预后即刻和干预后 30 分钟在胫骨前肌中诱发运动诱发电位来评估运动皮质兴奋性。
与之前开发的异步 BCI 相比，所提出的基于线索的异步 BCI 具有显著更少的假阳性/分钟和假阳性/真阳性（%）。线性混合模型显示，与对照条件相比，所有 BCI 模式在干预后即刻运动诱发电位幅度均增加（p <0.05）。与所有干预措施相比，所提出的基于线索的异步 BCI 导致最大的峰峰值运动诱发电位幅度相对增加（141% ± 33%），并且持续 30 分钟（111% ± 33%）。
这些发现证明了新提出的基于线索的异步 BCI 干预的高性能。在这种范式中，个体接收到精确的指令（线索）以促进参与，同时准确检测脑活动的时间以与感觉输入的传递建立精确关联，以诱导可塑性。
