Decoding saccadic eye movements from brain signals using an endovascular neural interface.

IF 3.8
Suleman Rasheed, James Bennett, Peter E Yoo, Anthony N Burkitt, David B Grayden
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Abstract

Objective: An Oculomotor Brain-Computer Interface (BCI) records neural activity from brain regions involved in planning eye movements and translates this activity into control commands. While previous successful studies have relied on invasive implants in non-human primates or electrooculography (EOG) artefacts in human electroencephalogram (EEG) data, this study aimed to demonstrate the feasibility of an oculomotor BCI using a minimally invasive endovascular StentrodeTM device implanted near the supplementary motor area of a patient with Amyotrophic Lateral Sclerosis (ALS). Approach. One participant performed self-paced visually-guided and free-viewing saccade tasks in four directions (left, right, up, down) while endovascular EEG and eye gaze recordings were collected. Visually-guided saccades were cued with visual stimuli, whereas free-viewing saccades were self-directed without explicit cues. Brain signals were pre-processed to remove cardiac artefacts, downsampled, and classified using a Random Forest algorithm. For saccade onset classification (fixation vs. saccade), features in time and frequency domains were extracted after xDAWN denoising, while for saccade direction classification, the downsampled time series were classified directly without explicit feature extraction. Main results. The neural responses of visually-guided saccades overlapped with cue-evoked potentials, while free-viewing saccades exhibited saccade-related potentials that began shortly before eye movement, peaked approximately 50 ms after saccade onset, and persisted for around 200 ms. In the frequency domain, these responses appeared as a low-frequency synchronisation below 15 Hz. Saccade onset classification was robust, achieving mean area under the receiver operating characteristic curve (AUC) scores of 0.88 within sessions and 0.86 across sessions. Saccade direction decoding yielded within-session AUC scores of 0.67 for four-class decoding and up to 0.75 for the best performing binary comparisons (left vs. up and left vs. down). Significance. This proof-of-concept study demonstrates the feasibility of an endovascular oculomotor BCI in a patient with ALS, establishing a foundation for future oculomotor BCI studies in human subjects.

利用血管内神经接口从大脑信号中解码跳眼运动。
目的:眼动脑机接口(BCI)记录参与眼球运动规划的脑区神经活动,并将该活动转化为控制命令。虽然之前成功的研究依赖于非人类灵长类动物的侵入性植入物或人类脑电图(EEG)数据中的眼电图(EOG)假影,但本研究旨在证明在肌萎缩性侧索硬化症(ALS)患者的辅助运动区附近植入微创血管内StentrodeTM装置来实现动眼肌脑机接口的可行性。一名参与者在四个方向(左、右、上、下)进行自定节奏的视觉引导和自由观看扫视任务,同时收集血管内脑电图和眼睛注视记录。视觉引导的扫视是在视觉刺激的提示下进行的,而自由观看的扫视是在没有明确提示的情况下进行的。对大脑信号进行预处理,去除心脏伪影,下采样,并使用随机森林算法进行分类。对于扫视开始分类(注视与扫视),xDAWN去噪后提取时间域和频域特征,而对于扫视方向分类,下采样时间序列直接分类,不进行显式特征提取。& # xD;主要结果。视觉引导扫视的神经反应与线索诱发电位重叠,而自由视视的扫视表现出与扫视相关的电位,这些电位在眼球运动之前开始,在扫视开始后约50 ms达到峰值,并持续约200 ms。在频域中,这些响应表现为低于15 Hz的低频同步。眼跳开始分类是稳健的,受试者工作特征曲线下的平均面积(AUC)得分在疗程内为0.88,在疗程间为0.86。对于四类解码,眼动方向解码产生的会话内AUC得分为0.67,对于表现最佳的二进制比较(左与上,左与下),AUC得分高达0.75。这项概念验证研究证明了血管内动眼肌脑机接口在ALS患者中的可行性,为未来在人类受试者中进行动眼肌脑机接口研究奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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