UC Santa Barbara Researchers Use AI to Improve Visual Cortex Prosthesis Stimulation
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- ScienceDaily.com
Researchers from three institutions, including UC Santa Barbara, demonstrated that a deep learning system can improve the precision of an experimental visual prosthesis and help predict the visual sensations it produces. The system developed electrical stimulation patterns for electrodes temporarily implanted in the visual cortex, then analyzed brain responses to give researchers greater control over neural activity. The proof-of-concept study was published online in Neuron.
Visual cortical prostheses deliver electrical signals directly to the visual cortex rather than relying on the eyes or optic nerves. The approach could potentially help people whose visual pathways are damaged but whose visual cortex remains responsive, including some people who lost vision after strokes, neurodegenerative diseases, or traumatic brain injuries. The findings suggest that adapting stimulation to an individual’s brain responses may improve on predetermined settings, although the study does not establish a clinical treatment or demonstrate restored functional vision.
In 2024, researchers from Beyeler’s Bionic Vision Lab traveled to Spain to test whether their computer models could improve an implant’s performance in an experimental study. The source does not disclose the outcome of that test or a timeline for further development. The research builds on computational work supported by Beyeler’s 2022 NIH Director’s New Innovator Award, a five-year, $2 million grant.
Original report
AI-powered bionic eye breakthrough could help the blind see again
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