Stimulation of the nervous system with neurotechnology has opened up new avenues for treating human disorders, such as prosthetic arms and legs that restore the sense of touch in amputees, prosthetic fingertips that provide detailed sensory feedback with varying touch resolution and intraneural stimulation to help the blind by giving sensations of sight.
A collaboration between SISSA, EPFL and Scuola Superiore Sant’Anna has shown that optic nerve stimulation is a promising way for developing personalized visual signals to help the blind. In a study recently published in Patterns, the protocol has been tested for the moment on artificial neural networks known to simulate the entire visual system, called convolutional neural networks (CNN) usually used in computer vision for detecting and classifying objects.
The idea is to stimulate the optic nerve through intraneural electrodes, ones that pierce through the nerve instead of being wrapped around it. Tuning this stimulation is a major challenge and this work is the first to feature automatic optimization of optic nerve stimulation protocols.
“Our study shows that it is possible to elicit desired activity patterns in deep layers of a CNN that simulate cortical visual areas. The next step is to understand what patterns should be evoked in order to induce percepts of arbitrary visual objects,” explains Davide Zoccolan, Professor of Neurophysiology and Head of SISSA Visual Neuroscience Lab. “To meet this challenge, we are now working on building predictive models of neuronal responses based on CNNs. These models will learn the 'tuning' of visual cortical neurons based on their responses to a battery of visual images, thus uncovering the mapping between image space and response space that is central for sight restoration.”
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