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Software System to Improve the Function of Retinal Implants

ranslated by the Retina Encoder and subsequently forwarded to a kind of "virtual central visual system." This simulation mimics the brain function for the interpretation of the converted camera data.

Initially, the Retina Encoder does not know which language the virtual central visual system speaks. Therefore the software translates the original picture - for example a ring - in different, randomly selected "dialects". This way, variations of the picture emerge, which are more or less similar to a ring. The volunteer sees these variations on a small screen that is integrated in a frame of glasses. By means of head movements, the person selects those variations that appear most similar to a ring. From these choices, the learning software draws conclusions how to improve the translation. In the next learning cycle, several new picture variations are being presented, which look already more similar to the original: during this process, the Retina Encoder becomes adapted step-by-step to the language of the virtual central visual system. In the current tests it works very well; however, the scientists have not yet tested their system in patients. The scientists emphasize that in principle, the Retina Encoder could be integrated in implanted visual prostheses within a few months.

In normally sighted humans, a kind of natural Retina Encoder is already integrated in the retina: specifically, four layers of nerve cells are positioned in front of the photoreceptor cells. "The retina is a transparent biocomputer," Eckmiller says. "It transforms the electrical signals of rod and cone photoreceptors into a complex signal." This signal reaches the brain via the optic nerve.

In the brain, the complex information is being decoded. The brain acquires the corresponding ability within the first months of life. During this time, the central visual system becomes individually adjusted to the retinal signals: the brain learns how to interpret the data
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