Literature DB >> 10341976

Position jitter and undersampling in pattern perception.

D M Levi1, S A Klein, V Sharma.   

Abstract

The present paper addresses whether topographical jitter or undersampling might limit pattern perception in foveal, peripheral and strabismic amblyopic vision. In the first experiment, we measured contrast thresholds for detecting and identifying the orientation (up, down, left, right) of E-like patterns comprised of Gabor samples. We found that detection and identification thresholds were both degraded in peripheral and amblyopic vision; however, the orientation identification/detection threshold ratio was approximately the same in foveal, peripheral and amblyopic vision. This result is somewhat surprising, because we anticipated that a high degree of uncalibrated topographical jitter in peripheral and amblyopic vision would have affected orientation identification to a greater extent than detection. In the second experiment, we investigated the tolerance of human and model observers to perturbation of the positions of the samples defining the pattern when its contrast was suprathreshold, by measuring a 'jitter threshold' (the amount of jitter required to reduce performance from near perfect to 62.5% correct). The results and modeling of our jitter experiments suggest that pattern identification is highly robust to positional jitter. The positional tolerance of foveal, peripheral and amblyopic vision is equal to about half the separation of the features and the close similarity between the three visual systems argues against extreme topographical jitter. The effects of jitter on human performance are consistent with the predictions of a 'template' model. In the third experiment we determined what fraction of the 17 Gabor samples are needed to reliably identify the orientation of the E-patterns by measuring a 'sample threshold' (the proportion of samples required for 62.5% correct performance). In foveal vision, human observers are highly efficient requiring only about half the samples for reliable pattern identification. Relative to an ideal observer model, humans perform this task with 85% efficiency. In contrast, in both peripheral vision and strabismic amblyopia more samples are required. The increased number of features required in peripheral vision and strabismic amblyopia suggests that in these visual systems, the stimulus is underrepresented at the stage of feature integration.

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Mesh:

Year:  1999        PMID: 10341976     DOI: 10.1016/s0042-6989(98)00125-4

Source DB:  PubMed          Journal:  Vision Res        ISSN: 0042-6989            Impact factor:   1.886


  14 in total

1.  Amblyopes see true alignment where normal observers see illusory tilt.

Authors:  A V Popple; D M Levi
Journal:  Proc Natl Acad Sci U S A       Date:  2000-10-10       Impact factor: 11.205

2.  Global contour processing in amblyopia.

Authors:  Dennis M Levi; Cong Yu; Shu-Guang Kuai; Elizabeth Rislove
Journal:  Vision Res       Date:  2007-01-16       Impact factor: 1.886

3.  Scale-dependent loss of global form perception in strabismic amblyopia.

Authors:  Elizabeth M Rislove; Elaine C Hall; Kara A Stavros; Lynne Kiorpes
Journal:  J Vis       Date:  2010-10-22       Impact factor: 2.240

4.  Sensitivity to synchronicity of biological motion in normal and amblyopic vision.

Authors:  Jennifer Y Luu; Dennis M Levi
Journal:  Vision Res       Date:  2013-03-06       Impact factor: 1.886

5.  Image segregation in strabismic amblyopia.

Authors:  Dennis M Levi
Journal:  Vision Res       Date:  2007-04-17       Impact factor: 1.886

6.  Bayesian integration of position and orientation cues in perception of biological and non-biological forms.

Authors:  Steven M Thurman; Hongjing Lu
Journal:  Front Hum Neurosci       Date:  2014-02-24       Impact factor: 3.169

7.  Covert spatial attention is functionally intact in amblyopic human adults.

Authors:  Mariel Roberts; Rachel Cymerman; R Theodore Smith; Lynne Kiorpes; Marisa Carrasco
Journal:  J Vis       Date:  2016-12-01       Impact factor: 2.240

8.  A Weber-like law for perceptual learning.

Authors:  Andrew T Astle; Roger W Li; Ben S Webb; Dennis M Levi; Paul V McGraw
Journal:  Sci Rep       Date:  2013-01-29       Impact factor: 4.379

9.  Is the Cortical Deficit in Amblyopia Due to Reduced Cortical Magnification, Loss of Neural Resolution, or Neural Disorganization?

Authors:  Simon Clavagnier; Serge O Dumoulin; Robert F Hess
Journal:  J Neurosci       Date:  2015-11-04       Impact factor: 6.167

Review 10.  Perceptual learning as a potential treatment for amblyopia: a mini-review.

Authors:  Dennis M Levi; Roger W Li
Journal:  Vision Res       Date:  2009-02-27       Impact factor: 1.886

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