Awareness and filling-in of the human blind spot: linking psychophysics with retinal topography

To link psychophysical thresholds for blind spot awareness and filling-in with early neural components that underpin these perceptions. Blind spot dimensions were quantified, after which an intrinsic stimulus (i.e., a rectangular bar of varying length centered within the blind spot) was used to dete...

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Veröffentlicht in:Investigative ophthalmology & visual science 2011-01, Vol.52 (1), p.541-548
Hauptverfasser: Abadi, Richard V, Jeffery, Glen, Murphy, Jonathan S
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Sprache:eng
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Zusammenfassung:To link psychophysical thresholds for blind spot awareness and filling-in with early neural components that underpin these perceptions. Blind spot dimensions were quantified, after which an intrinsic stimulus (i.e., a rectangular bar of varying length centered within the blind spot) was used to determine blind spot awareness and filling-in for five subjects. Histologic examination of six human retinas at 20-μm intervals from the temporal and nasal neural rims of the optic nerve head out to 1040 μm allowed the quantification of outer nuclear layer thickness, a direct correlate of photoreceptor density. Blind spot awareness was reported for bar extensions beyond 0.4° to 0.8° from the edge of the blind spot. Partial and total blind spot filling-in were reported between 1.1° and 1.3° and beyond 1.5°, respectively. Histologic measures of ONL thickness were correlated with previously published data of photoreceptor spatial density to determine the percentage of photoreceptor density required to trigger a 75% probability response. Blind spot awareness was achieved by stimulating 43% to 70% of the maximum photoreceptor density. Partial and total filling-in of the blind spot required between 78% and 83% and more than 85% photoreceptor spatial densities, respectively. A novel intrinsic stimulus has been used to concurrently investigate blind spot awareness and blind spot filling-in. Retinal neural correlates of each visual experience have been quantified. Future computational models will have to integrate bottom-up constraints with long-range cortical receptive field activity and higher order cognitive factors.
ISSN:1552-5783
1552-5783
DOI:10.1167/iovs.10-5910