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Related Concept Videos

Vision01:24

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

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

Suleman Rasheed1,2,3, James Bennett3,4, Peter E Yoo3,4

  • 1Department of Biomedical Engineering, The University of Melbourne, Melbourne, Australia.

Journal of Neural Engineering
|October 3, 2025
PubMed
Summary
This summary is machine-generated.

This study shows an endovascular oculomotor brain-computer interface (BCI) is feasible in an ALS patient, decoding eye movements using a Stentrode device for potential communication restoration.

Keywords:
ALSBMIStentrodeendovascularintravascularoculomotor BCIsaccade

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Rehabilitation Technology

Background:

  • Oculomotor brain-computer interfaces (BCIs) translate neural activity into control commands for eye movements.
  • Previous BCI research often required invasive implants in animals or used artifactual EEG data in humans.
  • Amyotrophic lateral sclerosis (ALS) patients experience progressive motor neuron loss, impacting communication abilities.

Purpose of the Study:

  • To demonstrate the feasibility of a minimally invasive endovascular oculomotor BCI in a patient with ALS.
  • To utilize a Stentrode device implanted near the supplementary motor area for neural signal acquisition.
  • To decode saccade onset and direction for potential communication restoration in ALS.

Main Methods:

  • Recorded endovascular EEG and eye gaze data from one ALS participant performing saccade tasks (visually-guided and free-viewing).
  • Pre-processed neural signals to remove artifacts and downsampled data.
  • Classified saccade onset and direction using a Random Forest algorithm with time/frequency domain features and raw time series data.

Main Results:

  • Identified distinct neural responses related to free-viewing saccades, appearing as low-frequency synchronization below 15 Hz.
  • Achieved robust saccade onset classification with Area Under the Curve (AUC) scores of 0.88 (within-session) and 0.86 (across-session).
  • Demonstrated saccade direction decoding with within-session AUC scores up to 0.75 for binary comparisons.

Conclusions:

  • This proof-of-concept study validates the feasibility of an endovascular oculomotor BCI in an ALS patient.
  • The findings establish a foundation for developing advanced oculomotor BCIs for human subjects.
  • This technology holds promise for restoring communication and control for individuals with severe motor impairments.