May 2007
Volume 48, Issue 13
ARVO Annual Meeting Abstract  |   May 2007
Accessing the Cortical Response to Macular Disease via a Large-Scale Spiking Neuron Model of V1
Author Affiliations & Notes
  • P. Sajda
    Columbia University, New York, New York
    Biomedical Engineering,
  • J. Wielaard
    Columbia University, New York, New York
    Biomedical Engineering,
  • J. Shi
    Columbia University, New York, New York
    Biomedical Engineering,
  • R. T. Smith
    Columbia University, New York, New York
  • Footnotes
    Commercial Relationships P. Sajda, None; J. Wielaard, None; J. Shi, None; R.T. Smith, None.
  • Footnotes
    Support NEI RO1 EY015520 HIGHWIRE EXLINK_ID="48:5:2347:1" VALUE="EY015520" TYPEGUESS="GEN" /HIGHWIRE
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 2347. doi:
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      P. Sajda, J. Wielaard, J. Shi, R. T. Smith; Accessing the Cortical Response to Macular Disease via a Large-Scale Spiking Neuron Model of V1. Invest. Ophthalmol. Vis. Sci. 2007;48(13):2347.

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

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Purpose:: Current efforts for assessing macular disease have focused on the retina, for instance quantitation of drusen distributions. Retinal imaging, however, does not provide a complete picture of the nature of the expected vision loss. Important to consider is how the visual cortex responds to the resulting scotomata and distortion of the retinal input.

Methods:: In this study we used an anatomically and physiologically detailed spiking neuron model of V1 (Wielaard and Sajda, Cerebral Cortex. 2006 16(11) 1531-1545) to investigate the effect of macular disease on cortical activity, tuning, and selectivity. We segmented fundus images and use them as ``masks" for input to our cortical simulations. The model was probed using simulated drifting sinusoidal grating stimuli. All simulations were done using monocular input. We analyzed the firing rates and orientation selectivity of cells in parvocellular (4Cß) and magnocellular (4Cα) versions of the cortical model as a function of normal and abnormal retinal input. To analyze orientation selectivity we computed the circular variance (CV) across the population of cells.

Results:: We found for the magnocellular model an overall reduction of firing rates of all cortical neurons. However there were no obvious "holes" of activity indicative of clusters of inactive neurons whose spatial position could be correlated with the spatial distribution of drusen. Analysis of orientation selectivity showed a dramatic reduction in selectivity for the normal vs abnormal cases. For the abnormal cases there was a shift of the CV distribution toward 1.0, indicating poorer orientation selectivity of the cells in 4Cα. For 4Cß the results are somewhat different. Unlike the magnocellular model, the parvocellular model showed clusters of inactivity which correlated with the spatial distribution of drusen. However the orientation selectivity was not significantly affected, with distributions between normal and abnormal cases being indistinguishable.

Conclusions:: The magno system appears to fill-in spatial information though at the cost of a loss of orientation selectivity, were as the parvo system maintains orientation selectivity however with scotoma present in the cortical activity. This analysis is only "first order" in that drusen are treated purely as masking out the visual input, when in fact their effect on retinal ganglion cell activity can be more complex. Nonetheless, the simulations offer some insight into how responses of cortical neurons are affected by retinal disease.

Keywords: visual cortex • age-related macular degeneration • computational modeling 

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