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Optimal spatial localization is limited by contrast sensitivity. | LitMetric

AI Article Synopsis

Article Abstract

Bisection is one of several spatial localization tasks that achieve hyperacuity performance levels. We find that optimal bisection thresholds, and hyperacuity tasks in general, are no better than might be expected from simple contrast detection and discrimination performance. The three-line bisection task can be described in terms of the test-pedestal paradigm where the test pattern is a horizontal dipole and the pedestal is a horizontal three-line pattern with equal spacing between the lines. When the dipole test is added to the center line, the line shifts up or down, depending on the test polarity. For low contrast pedestal lines at the optimal separation, the bisection threshold falls between the observer's own dipole contrast detection threshold and the bottom of the dipole contrast discrimination dipper function. At higher pedestal strengths performance degrades with a slope of about 0.5-0.7, similar to that found in contrast discrimination tasks. Therefore, bisection performance is compatible with expectations based on contrast discrimination data. At large pedestal line separations (> 10 min) bisection thresholds in min are about 1/60 the separation and relatively independent of pedestal strength. These findings are consistent with the idea that two processes are involved in limiting bisection performance; the first limit is based on contrast sensitivity of the system and the second limit to performance is based on a local sign or position tag processing. Finally, when bisection is compared with Vernier acuity and blur resolution tasks, where the test is also a dipole, bisection performance falls roughly midway, better than Vernier acuity but worse than blur resolution.

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http://dx.doi.org/10.1016/s0042-6989(98)00121-7DOI Listing

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