Dataset Information

Retinal prosthetic strategy with the capacity to restore normal vision.

ABSTRACT: Retinal prosthetics offer hope for patients with retinal degenerative diseases. There are 20-25 million people worldwide who are blind or facing blindness due to these diseases, and they have few treatment options. Drug therapies are able to help a small fraction of the population, but for the vast majority, their best hope is through prosthetic devices [reviewed in Chader et al. (2009) Prog Brain Res 175:317-332]. Current prosthetics, however, are still very limited in the vision that they provide: for example, they allow for perception of spots of light and high-contrast edges, but not natural images. Efforts to improve prosthetic capabilities have focused largely on increasing the resolution of the device's stimulators (either electrodes or optogenetic transducers). Here, we show that a second factor is also critical: driving the stimulators with the retina's neural code. Using the mouse as a model system, we generated a prosthetic system that incorporates the code. This dramatically increased the system's capabilities--well beyond what can be achieved just by increasing resolution. Furthermore, the results show, using 9,800 optogenetically stimulated ganglion cell responses, that the combined effect of using the code and high-resolution stimulation is able to bring prosthetic capabilities into the realm of normal image representation.

SUBMITTER: Nirenberg S

PROVIDER: S-EPMC3443127 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

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Retinal prosthetic strategy with the capacity to restore normal vision.

Nirenberg Sheila S Pandarinath Chethan C

Proceedings of the National Academy of Sciences of the United States of America 20120813 37

Retinal prosthetics offer hope for patients with retinal degenerative diseases. There are 20-25 million people worldwide who are blind or facing blindness due to these diseases, and they have few treatment options. Drug therapies are able to help a small fraction of the population, but for the vast majority, their best hope is through prosthetic devices [reviewed in Chader et al. (2009) Prog Brain Res 175:317-332]. Current prosthetics, however, are still very limited in the vision that they prov ...[more]

PMID: 22891310

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Project description:Objective. Patients with photovoltaic subretinal implant PRIMA demonstrated letter acuity ∼0.1 logMAR worse than sampling limit for 100μm pixels (1.3 logMAR) and performed slower than healthy subjects tested with equivalently pixelated images. To explore the underlying differences between natural and prosthetic vision, we compare the fidelity of retinal response to visual and subretinal electrical stimulation through single-cell modeling and ensemble decoding.Approach. Responses of retinal ganglion cells (RGCs) to optical or electrical white noise stimulation in healthy and degenerate rat retinas were recorded via multi-electrode array. Each RGC was fit with linear-nonlinear and convolutional neural network models. To characterize RGC noise, we compared statistics of spike-triggered averages (STAs) in RGCs responding to electrical or visual stimulation of healthy and degenerate retinas. At the population level, we constructed a linear decoder to determine the accuracy of the ensemble of RGCs onN-way discrimination tasks.Main results. Although computational models can match natural visual responses well (correlation ∼0.6), they fit significantly worse to spike timings elicited by electrical stimulation of the healthy retina (correlation ∼0.15). In the degenerate retina, response to electrical stimulation is equally bad. The signal-to-noise ratio of electrical STAs in degenerate retinas matched that of the natural responses when 78 ± 6.5% of the spikes were replaced with random timing. However, the noise in RGC responses contributed minimally to errors in ensemble decoding. The determining factor in accuracy of decoding was the number of responding cells. To compensate for fewer responding cells under electrical stimulation than in natural vision, more presentations of the same stimulus are required to deliver sufficient information for image decoding.Significance. Slower-than-natural pattern identification by patients with the PRIMA implant may be explained by the lower number of electrically activated cells than in natural vision, which is compensated by a larger number of the stimulus presentations.

Dataset Information

Retinal prosthetic strategy with the capacity to restore normal vision.

Publications

Retinal prosthetic strategy with the capacity to restore normal vision.

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