Miguel Hernández University

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   Deep learning personalizes visual-cortex stimulation in early human trial

   Researchers from the University of California, Santa Barbara, ETH Zurich, and Miguel Hernández University used deep learning to personalize electrical stimulation delivered through a temporary 96-electrode array implanted in a participant's visual cortex. According to cnBeta, the optimized patterns more accurately activated targeted neural responses while requiring less current, and recorded brain activity predicted the participant's reported phosphenes better than electrode parameters alone. The paper was published in Neuron on August 7, 2026.

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