Effectiveness of motor and prefrontal cortical areas for brain-controlled functional electrical stimulation neuromodulation.

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL Journal of neural engineering Pub Date : 2023-09-26 DOI:10.1088/1741-2552/acfa22
Rizaldi A Fadli, Yuki Yamanouchi, Lazar I Jovanovic, Milos R Popovic, Cesar Marquez-Chin, Taishin Nomura, Matija Milosevic
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Abstract

Objective. Brain-computer interface (BCI)-controlled functional electrical stimulation (FES) could excite the central nervous system to enhance upper limb motor recovery. Our current study assessed the effectiveness of motor and prefrontal cortical activity-based BCI-FES to help elucidate the underlying neuromodulation mechanisms of this neurorehabilitation approach.Approach. The primary motor cortex (M1) and prefrontal cortex (PFC) BCI-FES interventions were performed for 25 min on separate days with twelve non-disabled participants. During the interventions, a single electrode from the contralateral M1 or PFC was used to detect event-related desynchronization (ERD) in the calibrated frequency range. If the BCI system detected ERD within 15 s of motor imagery, FES activated wrist extensor muscles. Otherwise, if the BCI system did not detect ERD within 15 s, a subsequent trial was initiated without FES. To evaluate neuromodulation effects, corticospinal excitability was assessed using single-pulse transcranial magnetic stimulation, and cortical excitability was assessed by motor imagery ERD and resting-state functional connectivity before, immediately, 30 min, and 60 min after each intervention.Main results. M1 and PFC BCI-FES interventions had similar success rates of approximately 80%, while the M1 intervention was faster in detecting ERD activity. Consequently, only the M1 intervention effectively elicited corticospinal excitability changes for at least 60 min around the targeted cortical area in the M1, suggesting a degree of spatial localization. However, cortical excitability measures did not indicate changes after either M1 or PFC BCI-FES.Significance. Neural mechanisms underlying the effectiveness of BCI-FES neuromodulation may be attributed to the M1 direct corticospinal projections and/or the closer timing between ERD detection and FES, which likely enhanced Hebbian-like plasticity by synchronizing cortical activation detected by the BCI system with the sensory nerve activation and movement related reafference elicited by FES.

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运动和前额叶皮层区域对脑控制功能性电刺激神经调控的有效性。
客观的脑机接口(BCI)控制的功能性电刺激(FES)可刺激中枢神经系统,促进上肢运动恢复。我们目前的研究评估了基于运动和前额叶皮层活动的BCI-FES的有效性,以帮助阐明这种神经康复方法潜在的神经调控机制。方法初级运动皮层(M1)和前额叶皮层(PFC)BCI-FES干预在不同的日子进行25分钟,有12名非残疾参与者。在干预期间,来自对侧M1或PFC的单个电极用于检测校准频率范围内的事件相关去同步(ERD)。如果脑机接口系统在运动图像的15秒内检测到ERD,则FES激活腕伸肌。否则,如果脑机接口系统在15秒内没有检测到ERD,则在没有FES的情况下启动后续试验。为了评估神经调控效应,在每次干预前、立即、30分钟和60分钟,使用单脉冲经颅磁刺激评估皮质脊髓兴奋性,并通过运动图像ERD和静息状态功能连接评估皮层兴奋性。主要结果。M1和PFC BCI-FES干预的成功率相似,约为80%,而M1干预在检测ERD活性方面更快。因此,只有M1干预有效地在M1的靶皮质区域周围引起皮质脊髓兴奋性变化至少60分钟,这表明存在一定程度的空间定位。然而,皮层兴奋性测量没有表明M1或PFC BCI-FES后的变化。意义重大。BCI-FES神经调控有效性的神经机制可能归因于M1直接皮质脊髓投射和/或ERD检测与FES之间的更近时间,这可能通过使脑机接口系统检测到的皮层激活与FES引起的感觉神经激活和运动相关再刺激同步来增强Hebbian样可塑性。
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来源期刊
Journal of neural engineering
Journal of neural engineering 工程技术-工程:生物医学
CiteScore
7.80
自引率
12.50%
发文量
319
审稿时长
4.2 months
期刊介绍: The goal of Journal of Neural Engineering (JNE) is to act as a forum for the interdisciplinary field of neural engineering where neuroscientists, neurobiologists and engineers can publish their work in one periodical that bridges the gap between neuroscience and engineering. The journal publishes articles in the field of neural engineering at the molecular, cellular and systems levels. The scope of the journal encompasses experimental, computational, theoretical, clinical and applied aspects of: Innovative neurotechnology; Brain-machine (computer) interface; Neural interfacing; Bioelectronic medicines; Neuromodulation; Neural prostheses; Neural control; Neuro-rehabilitation; Neurorobotics; Optical neural engineering; Neural circuits: artificial & biological; Neuromorphic engineering; Neural tissue regeneration; Neural signal processing; Theoretical and computational neuroscience; Systems neuroscience; Translational neuroscience; Neuroimaging.
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