May 2007
Volume 48, Issue 13
ARVO Annual Meeting Abstract  |   May 2007
Simulated Object Recognition with a Cortical Visual Prosthesis
Author Affiliations & Notes
  • D. Bradley
    University of Chicago, Chicago, Illinois
  • M. Lusignan
    University of Chicago, Chicago, Illinois
  • P. Troyk
    Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois
  • S. Cogan
    EIC, Chicago, Illinois
  • D. McCreery
    HMRI, Pasadena, California
  • E. Schmidt
    NIH, Bethesda, Maryland
  • M. Bak
    Microprobe, Bethesda, Maryland
  • R. Erickson
    University of Chicago, Chicago, Illinois
  • D. Curry
    University of Chicago, Chicago, Illinois
  • L. Towle
    University of Chicago, Chicago, Illinois
  • Footnotes
    Commercial Relationships D. Bradley, None; M. Lusignan, None; P. Troyk, None; S. Cogan, None; D. McCreery, None; E. Schmidt, None; M. Bak, None; R. Erickson, None; D. Curry, None; L. Towle, None.
  • Footnotes
    Support NIH Grant NS40690-01A1, Brain Research Foundation
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 2346. doi:
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      D. Bradley, M. Lusignan, P. Troyk, S. Cogan, D. McCreery, E. Schmidt, M. Bak, R. Erickson, D. Curry, L. Towle; Simulated Object Recognition with a Cortical Visual Prosthesis. Invest. Ophthalmol. Vis. Sci. 2007;48(13):2346.

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

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Purpose:: Cortical visual prostheses hold the promise of restoring basic vision to patients blinded by retinal malfunction or optic nerve damage. Recent animal work has shown that stimulating implants with 250 or more electrodes are possible. To assess the potential benefit of an array this size, we simulated an object recognition task where sensory input was derived solely from microstimulation currents.

Methods:: The hypothetical experiment involved a subject facing a screen and a camera that transformed visual signals into a distribution of stimulation currents. These were delivered through an electrode array implanted in striate cortex (V1). Each electrode was assumed to activate a cluster of neurons with overlapping receptive fields. These fields were modeled as Gaussian functions with SD equal to published field widths. Each Gaussian was used as a kernel to integrate luminance on the screen; in turn, current was sent through the corresponding electrode with magnitude proportional to the integrated luminance. The subject was assumed to make 5 saccades such that the distribution of receptive fields (Gaussians) relative to the object being displayed was variable. This effectively increased the size of the array. In the simulation, the distribution of input "luminances" (microstimulation strengths) was compared to a learned distribution, and a Bayesian rule was used to determine which of 8 objects in memory best matched the current input.

Results:: Model performance was 49%, substantially and significantly greater than the 13% expected for guessing (p<.001).

Conclusions:: Based on currently feasible technology and reasonable assumptions, it appears that a cortical visual prosthesis could provide at least rudimentary visual capability.

Keywords: visual cortex • visual impairment: neuro-ophthalmological disease • space and scene perception 

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