July 2018
Volume 59, Issue 9
Free
ARVO Annual Meeting Abstract  |   July 2018
Estimation of visual acuity of the mouse retina in vitro using multi-electrode array recording
Author Affiliations & Notes
  • Darwin Babino
    Ophthalmology, University of Washington School of Medicine, SEATTLE, Washington, United States
  • Tyler Benster
    Stanford University, Stanford, California, United States
  • Larry Bencivengo
    Ophthalmology, University of Washington School of Medicine, SEATTLE, Washington, United States
  • Russell Van Gelder
    Ophthalmology, University of Washington School of Medicine, SEATTLE, Washington, United States
  • Footnotes
    Commercial Relationships   Darwin Babino, None; Tyler Benster, None; Larry Bencivengo, None; Russell Van Gelder, None
  • Footnotes
    Support  NIH Grant R24EY023937
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 5009. doi:
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    • Get Citation

      Darwin Babino, Tyler Benster, Larry Bencivengo, Russell Van Gelder; Estimation of visual acuity of the mouse retina in vitro using multi-electrode array recording. Invest. Ophthalmol. Vis. Sci. 2018;59(9):5009.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The availability of transgenic and knockout techniques has led to the widespread use of the mouse as model for studies on the genetics of normal and disease state visual function as well as studies aiming to restore vision using small molecules, gene therapy, and stem cell approaches. While visual acuity of mouse can be estimated by behavioral testing, these methods often require training phases and are difficult to implement for acute restorative methods such as small molecule photoswitches. Here we describe a method for estimating visual acuity of mouse retina in vitro using multielectrode array (MEA) recording.

Methods : Extracellular recordings of flat-mounted mouse retinas placed ganglion cell layer down, onto an MEA chip (60 channels) were recorded on an MEA 1060-inv-BC system (Multi Channel Systems). Retinas were stimulated with computer-generated movies projected by a DLP LightCrafter 4500 projector in combination with optics focusing stimuli onto retinas. Visually evoked ganglion cell action potentials from static checkerboard patterns, kinetic moving gratings and ETDRS eye chart, all with varying spatial frequencies and contrasts, were used to calculate stimuli classification accuracies using machine learning on population responses. Visual acuities were derived from classification accuracy as a function of spatial frequency. Wild type C57BL/6 retinas and degenerated retinas (rd/rd) with and without application of 100 μM of a synthetic photochromic ligand, PhENAQ, for 10 minutes before visual testing were tested.

Results : Of the four quadrants of the retina tested, highest acuity measurements were achieved from testing in the inferior-nasal sections. In this quadrant, acuity of logMAR 2.2 was measured for both the static and kinetic stimuli in wild-type animals (C57BL/6). Letter classification accuracy of a projected ETDRS eye chart, representing a logMAR of 3.0, on wild type retinas, resulted in perfect recognition for most letters. In rd/rd mice treated with PhENAQ, a logMAR acuity of 3.0 was measured for a static checkerboard stimulus.

Conclusions : This system establishes a novel technique for studying the potential visual acuity of the retina in vitro without assuming a particular neural code or training paradigm. This technique will be applicable to measurement of acuity of mutant retinas as well as blind retinas following vision restoration by a variety approaches.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

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