Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Adaptation Dependent Sensitivity Losses: Implications for cone receptor involvement in RP

Not Accessible

Your library or personal account may give you access

Abstract

The assessment of a sensitivity loss in patients with retinal disease is often performed in the presence of a background. Marré and Marré1, for example, have devised a technique based on Wald's version of Stiles' two-color threshold technique to measure the relative loss in three "basic cone mechanisms", each mechanism is isolated with a single chromatic background. Other investigators have argued for a selective sensitivity loss of a blue cone mechanism or a chromatic mechanism based upon data also collected at one or two adapting field intensities. The implicit assumption is that sensitivity loss of a particular cone mechanism is independent of the level of adaptation. This paper has two goals. First, we review evidence indicating that sensitivity loss is not independent of the level of adaptation in patients with RP, and we propose that models of sensitivity loss must incorporate a model of adaptation2. Second, we apply the model of adaptation proposed by Hood and Greenstein3 to assess whether the tvi data from RP patients support the hypothesis that RP primarily affects the receptors.

© 1988 Optical Society of America

PDF Article
More Like This
The effect of background luminance on Cone Sensitivity Functions

Tsaiyao Yeh, Joel Pokorny, and Vivianne C. Smith
TuA3 Noninvasive Assessment of the Visual System (NAVS) 1988

Increment Threshold (tvi) Data and the Site of Disease Action

D.C. Hood and V.C. Greenstein
TuA1 Noninvasive Assessment of the Visual System (NAVS) 1988

Adaptation of human cone receptors: Recordings of cone a-waves

Donald C. Hood and David G. Birch
FA4 Advances in Color Vision (ACV) 1992

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.