Authors Sheila Nirenberg: Nirenberg lab is part of the department - - PDF document

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Retinal prosthetic strategy with the capacity to restore normal vision Nirenberg, S. and Pandarinath, C. (2012) PNAS

Presented by Aaidt Shah and Connor Orrico April 1, 2012 BIONB 4110 Neuroscience Journal Club

Authors

• Sheila Nirenberg: Nirenberg lab is part of the

department of physiology and biophysics at the Weill Medical College of Cornell University

• f NYC.
• Research Interests
• Recent Publications.

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Chetan Pandarinath

• Postdoctoral Fellow Nirenberg Lab Dept. of

Physiology and Biophysics Weill Medical College of Cornell University

• Ph.D., Electrical Engineering

Cornell University, 2010

• Graduate Research :

The Journal

• The article is from the Proceedings of the

National Academy of Sciences (PNAS) Journal

• f the United States.
• Established in 1914
• One of the world’s most cited multidisciplinary

scientific journals.

• Published daily in online and weekly in print
• Impact factor: 9.681

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Significance of the finding Retinal Prosthetic devices

• New form of Hope to be able

Retinal Prosthetic Devices

HOPE

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The Problem

• About 20-25 million people are affected world

wide from such retinal degenerative diseases.

• Examples of such diseases are

Macular Degeneration Retinitis Pigmentosa.

Normal Vision

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Retinal Degenration: What happens?

Prosthetic Device

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Encoder

• Retinal input/out device.
• Mimics the transformations performed by the

retina

• Converts the visual input into the code used

by the retinal output cells.

• Firing rate at time t of the mth neuron in

response to stimulus λm(t) =Nm((S*Lm)(t))

Encoder

• Encoder is referred to as the complete

encoding device

• Essentially a model retina.
• Arrays of smaller encoders, one for each

ganglion type.

• Example: separate smaller encoder for ON

transient, on sustained etc.

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Stimulator and Transducer

• Stimulator used is the mini DLP
• Converts electrical pulses to light pulses
• Transducer is the light sensitive protein ChR2
• Transducer drives ganglion cells to fire as the

code specifies.

The steps

• Fig. 1 from Nirenberg and Pandarinath (2012)

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Brief Outline

Raw Data Confusion Matrices Image Reconstructions Behavioral Performance

Raw Data

• Presented movies

– Natural, spatiotemporally varying scenes

• Recorded ganglion cell responses using a

multielectrode array

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Functional Assay #1

• Confusion Matrices

– Gives the probability that a neural response to a presented stimulus will be decoded as that stimulus

• Elements on the diagonal indicate correct decoding
• Elements off the diagonal indicate confusion

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Functional Assay #2

• Image Reconstructions

– Image presentation – Ganglion cell responses recorded

• To obtain a large enough dataset for the complete

reconstruction, the image was systemically moved across the region of the retina

Original Image Encoder Encoder & Blind Retina

Blind Retina with standard

• ptogenetic

prosthetic

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Functional Assay #3

• Behavioral Performance on a Optomotor Task

– Animal was head-fixed – Liquid Crystal Display

• LCD used instead of mini-DLP so that the eye-tracking

system could be placed next to the eye

– ISCAN tracking system tracked eye position by measurements of infrared reflections off the cornea

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Conclusions

• “In sum, our results show that incorporating

the code dramatically increases prosthetic

• capabilities. Although increasing resolutions

also improves performance, there is an inherent ceiling on the quality of image this can produce; adding the code breaks through this barrier. The coded output combined with high-resolution stimulation makes natural vision restoration possible.””

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Discussion

• What is the most salient difference between

the prosthetic approach in this paper and

• ther optogenetic approaches?
• Why were 9,800 ganglion cell responses used

in this study?

• In your opinion, how significant are these

findings as related to vision problems in humans?