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Yi-Zhong Wang, Petra Kozma, Elaine Wilson; Effects of disrupting local orientation and position features on the detection of orientation-defined shape difference. Journal of Vision 2004;4(8):669. doi: 10.1167/4.8.669.
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Purpose: Orientation and position of local contour elements are two fundamental features to global shape integration. In this study we investigated the impact of disrupting local orientation and position features on the detection of orientation-defined shape difference. Methods: Stimuli were Gabor patch-sampled radial frequency (GSRF) patterns. Orientation-defined shape differences (orientation GSRF patterns) were generated by placing Gabor patches at zero-crossings of sinusoidal radial modulation, so that changing radial modulation results in changes in the local orientation but not the position of the patches. The disruption of local features was introduced by adding Gaussian jitter to either carrier orientation or patch position. Thresholds for detecting the radial modulation were estimated by a maximum likelihood procedure. Results: The mean threshold modulation of three normal subjects for detecting un-jittered orientation GSRF patterns (mean radius of 1.6 deg, radial frequency of 4 cyc/360 deg) was 0.49±0.10(SD)%. While disrupting either local orientation or position feature affected the detection of shape difference, orientation jitter had much bigger impact than position jitter. Orientation jitters larger than the threshold modulation (SD of orientation jitter > 1 deg) significantly elevated the detection threshold. In comparison, position jitter less than 3 times the threshold modulation had no effect on the detection threshold. When the jitter was 6 times the threshold modulation, the detection threshold was elevated 4 times by orientation jitter and was only elevated 1.5 times by position jitter. Conclusions: The perception of orientation-defined shape is affected differentially by the disruption of local orientation and position features. These results suggest that orientation and position GSRF patterns may be used as effective tools to probe the deficits in local feature analysis caused by visual disorders such as amblyopia and macular degeneration.
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