The long range goal of our research program is to develop a quantitative understanding of the mechanisms of visual processing that underlie spatial vision and adaptation in the cone and rod systems. Our primary research strategy has been to work out, in quantitative detail, the constraints on visual performance imposed by anatomical and physiological mechanisms, and to carry out psychophysical tests to determine what aspects of human performance might be accounted for by these mechanisms. The present proposal is to continue this research strategy to the study of spatial-, temporal- and contrast-discrimination performance. One line of research will be to develop and test multiple-channels models of visual adaptation. Much recent research on visual adaptation has involved measuring sensitivity for stimuli with fixed spatial configurations in the flash-on-flash paradigm. This research has been very useful for finding and quantifying the properties of the adaptation mechanism. However, for simplicity, spatial variables have largely been avoided. On the other hand, spatial-vision studies and associated models have largely avoided the transient conditions that most clearly reveal the adaptation mechanisms. Several experiments are proposed to fill this gap and to test models that simultaneously deal with both adaptation and spatial-vision phenomena. These experiments will measure threshold for detection of Gabor patches (of a special type) on transient backgrounds under various adaptation conditions. A second line of proposed research will be to continue the ideal-observer analysis developed in the previous project period, and to extend the analysis to the rod system and to higher levels of visual processing. In the previous project period, we developed an ideal-observer model for the preneural mechanisms up to the level of photon absorption in the cone system, and applied it (with useful results) to a wide range of spatial-, chromatic-and intensity-discrimination tasks. Most of present experiments will be directed at determining what aspects of temporal threshold data might be accounted for by the physical and physiological factors prior to and including the transduction process in the photoreceptors. To analyze the data, we will extend the earlier ideal-observer model to the level of internal-transmitter concentration in the photoreceptor. Finally, a somewhat more exploratory series of studies will attempt to develop an ideal-observer analysis that is appropriate for measuring the information transmitted by single neurons in discrimination tasks. Of particular interest will be the measurement of the information carried in the temporal pattern of the responses.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Research Project (R01)
Project #
5R01EY002688-14
Application #
3257039
Study Section
Visual Sciences A Study Section (VISA)
Project Start
1981-12-01
Project End
1994-11-30
Budget Start
1991-12-01
Budget End
1992-11-30
Support Year
14
Fiscal Year
1992
Total Cost
Indirect Cost
Name
University of Texas Austin
Department
Type
Schools of Arts and Sciences
DUNS #
City
Austin
State
TX
Country
United States
Zip Code
78712
Benvenuti, Giacomo; Chen, Yuzhi; Ramakrishnan, Charu et al. (2018) Scale-Invariant Visual Capabilities Explained by Topographic Representations of Luminance and Texture in Primate V1. Neuron 100:1504-1512.e4
Paulun, Vivian C; Schütz, Alexander C; Michel, Melchi M et al. (2015) Visual search under scotopic lighting conditions. Vision Res 113:155-68
Bradley, Chris; Abrams, Jared; Geisler, Wilson S (2014) Retina-V1 model of detectability across the visual field. J Vis 14:
Michel, Melchi M; Chen, Yuzhi; Geisler, Wilson S et al. (2013) An illusion predicted by V1 population activity implicates cortical topography in shape perception. Nat Neurosci 16:1477-83
Geisler, Wilson S (2011) Contributions of ideal observer theory to vision research. Vision Res 51:771-81
Michel, Melchi; Geisler, Wilson S (2011) Intrinsic position uncertainty explains detection and localization performance in peripheral vision. J Vis 11:18
Najemnik, Jiri; Geisler, Wilson S (2009) Simple summation rule for optimal fixation selection in visual search. Vision Res 49:1286-94
Sit, Yiu Fai; Chen, Yuzhi; Geisler, Wilson S et al. (2009) Complex dynamics of V1 population responses explained by a simple gain-control model. Neuron 64:943-56
Najemnik, Jiri; Geisler, Wilson S (2008) Eye movement statistics in humans are consistent with an optimal search strategy. J Vis 8:4.1-14
Geisler, Wilson S (2008) Visual perception and the statistical properties of natural scenes. Annu Rev Psychol 59:167-92

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