Decoding Saccadic Eye Movements from Brain Signals Using an Endovascular Neural Interface
Suleman Rasheed, James Bennett, Peter E. Yoo, Anthony N. Burkitt, David B. Grayden

TL;DR
This study demonstrates the feasibility of decoding eye movements from brain signals using a minimally invasive endovascular neural interface in an ALS patient, paving the way for future oculomotor BCIs.
Contribution
First to show that an endovascular Stentrode device can record saccadic eye movement signals for BCI applications in humans.
Findings
High accuracy in classifying fixations vs. saccades (AUC ~0.87)
Distinct neural potentials identified for free-viewing saccades
Feasibility established for endovascular oculomotor BCI in ALS
Abstract
An Oculomotor Brain-Computer Interface (BCI) records neural activity from regions of the brain involved in planning eye movements and translates this activity into control commands. While previous successful oculomotor BCI studies primarily relied on invasive microelectrode implants in non-human primates, this study investigates the feasibility of an oculomotor BCI using a minimally invasive endovascular Stentrode device implanted near the supplementary motor area in a patient with amyotrophic lateral sclerosis (ALS). To achieve this, self-paced visually-guided and free-viewing saccade tasks were designed, in which the participant performed saccades in four directions (left, right, up, down), with simultaneous recording of endovascular EEG and eye gaze. The visually guided saccades were cued with visual stimuli, whereas the free-viewing saccades were self-directed without explicit cues.…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces · Gaze Tracking and Assistive Technology · Neuroscience and Neural Engineering
MethodsAdaptive Label Smoothing
