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      Mapping the Contrast Sensitivity of the Visual Field With Bayesian Adaptive qVFM

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          Abstract

          Current clinical evaluation, which focuses on central vision, could be improved through characterization of residual vision with peripheral testing of visual acuity, contrast sensitivity, color vision, crowding, and reading speed. Assessing visual functions in addition to light sensitivity, a comprehensive visual field map (VFM) would be valuable for detecting and managing eye diseases. In a previous study, we developed a Bayesian adaptive qVFM method that combines a global module for preliminary assessment of the VFM's shape and a local module for assessment at individual retinal locations. The method was validated in measuring the light sensitivity VFM. In this study, we extended the qVFM method to measure contrast sensitivity across the visual field. In both simulations and psychophysics, we sampled 64 visual field locations (48 x 48 deg) and compared the qVFM method with a procedure that tested each retinal location independently (qFC; Lesmes et al., 2015). In each trial, subjects were required to identify a single optotype (size: 2.5 x 2.5 deg), one of 10 filtered Sloan letters. To compare the accuracy and precision of the two methods, three simulated eyes were tested in 1,280 trials with each method. In addition, data were collected from 10 eyes (5 OS, 5 OD) of five normal observers. For simulations, the average RMSE of the estimated contrast sensitivity with the qVFM and qFC methods were 0.057 and 0.100 after 320 trials, and 0.037 and 0.041 after 1,280 trials [all in log10 units, represent as log(sensitivity)], respectively. The average SD of the qVFM and qFC estimates were 0.054 and 0.096 after 320 trials, and 0.032 and 0.041 after 1,280 trials, respectively. The within-run variability (68.2% HWCIs) were comparable to the cross-run variability (SD). In the psychophysics experiment, the average HWCI of the estimated contrast sensitivity from the qVFM and qFC methods across the visual field decreased from 0.33 on the first trial to 0.072 and 0.16 after 160, and to 0.060 and 0.10 after 320 trials. The RMSE between the qVFM and qFC estimates started at 0.26, decreased to 0.12 after 160 and to 0.11 after 320 qVFM trials. The qVFM provides an accurate, precise, and efficient mapping of contrast sensitivity across the entire visual field. The method might find potential clinical applications in monitoring vision loss, evaluating therapeutic interventions, and developing effective rehabilitation for visual diseases.

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          Most cited references103

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          Peripheral vision and pattern recognition: a review.

          We summarize the various strands of research on peripheral vision and relate them to theories of form perception. After a historical overview, we describe quantifications of the cortical magnification hypothesis, including an extension of Schwartz's cortical mapping function. The merits of this concept are considered across a wide range of psychophysical tasks, followed by a discussion of its limitations and the need for non-spatial scaling. We also review the eccentricity dependence of other low-level functions including reaction time, temporal resolution, and spatial summation, as well as perimetric methods. A central topic is then the recognition of characters in peripheral vision, both at low and high levels of contrast, and the impact of surrounding contours known as crowding. We demonstrate how Bouma's law, specifying the critical distance for the onset of crowding, can be stated in terms of the retinocortical mapping. The recognition of more complex stimuli, like textures, faces, and scenes, reveals a substantial impact of mid-level vision and cognitive factors. We further consider eccentricity-dependent limitations of learning, both at the level of perceptual learning and pattern category learning. Generic limitations of extrafoveal vision are observed for the latter in categorization tasks involving multiple stimulus classes. Finally, models of peripheral form vision are discussed. We report that peripheral vision is limited with regard to pattern categorization by a distinctly lower representational complexity and processing speed. Taken together, the limitations of cognitive processing in peripheral vision appear to be as significant as those imposed on low-level functions and by way of crowding. © ARVO
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            Adaptive procedures in psychophysical research.

            R Leek (2001)
            As research on sensation and perception has grown more sophisticated during the last century, new adaptive methodologies have been developed to increase efficiency and reliability of measurement. An experimental procedure is said to be adaptive if the physical characteristics of the stimuli on each trial are determined by the stimuli and responses that occurred in the previous trial or sequence of trials. In this paper, the general development of adaptive procedures is described, and three commonly used methods are reviewed. Typically, a threshold value is measured using these methods, and, in some cases, other characteristics of the psychometric function underlying perceptual performance, such as slope, may be developed. Results of simulations and experiments with human subjects are reviewed to evaluate the utility of these adaptive procedures and the special circumstances under which one might be superior to another.
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              Enhancing the contrast sensitivity function through action video game training.

              The contrast sensitivity function (CSF) is routinely assessed in clinical evaluation of vision and is the primary limiting factor in how well one sees. CSF improvements are typically brought about by correction of the optics of the eye with eyeglasses, contact lenses or surgery. We found that the very act of action video game playing also enhanced contrast sensitivity, providing a complementary route to eyesight improvement.
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                Author and article information

                Contributors
                Journal
                Front Neurosci
                Front Neurosci
                Front. Neurosci.
                Frontiers in Neuroscience
                Frontiers Media S.A.
                1662-4548
                1662-453X
                07 July 2020
                2020
                : 14
                : 665
                Affiliations
                [1] 1College of Optometry, The Ohio State University , Columbus, OH, United States
                [2] 2Adaptive Sensory Technology, Inc. , San Diego, CA, United States
                [3] 3Division of Arts and Sciences, NYU Shanghai , Shanghai, China
                [4] 4Center for Neural Science and Department of Psychology, New York University , New York, NY, United States
                [5] 5NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai , Shanghai, China
                Author notes

                Edited by: Christopher DiMattina, Florida Gulf Coast University, United States

                Reviewed by: Woojae Kim, Howard University, United States; Jenny C. A. Read, Newcastle University, United Kingdom

                *Correspondence: Zhong-Lin Lu zhonglin@ 123456nyu.edu

                This article was submitted to Perception Science, a section of the journal Frontiers in Neuroscience

                Article
                10.3389/fnins.2020.00665
                7358309
                9441a6af-b7c2-4fef-a8e9-5b9140f2a362
                Copyright © 2020 Xu, Lesmes, Yu and Lu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 14 February 2020
                : 29 May 2020
                Page count
                Figures: 8, Tables: 2, Equations: 10, References: 117, Pages: 15, Words: 9527
                Funding
                Funded by: National Eye Institute 10.13039/100000053
                Award ID: EY021553
                Award ID: EY025658
                Categories
                Neuroscience
                Original Research

                Neurosciences
                bayesian adaptive testing,automated perimetry,visual-filed map,peripheral vision,contrast sensitivity,active learning,sloan letters

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