D
Dov Sagi
Researcher at Weizmann Institute of Science
Publications - 171
Citations - 13098
Dov Sagi is an academic researcher from Weizmann Institute of Science. The author has contributed to research in topics: Perceptual learning & Visual perception. The author has an hindex of 52, co-authored 168 publications receiving 12495 citations. Previous affiliations of Dov Sagi include AT&T & Bell Labs.
Papers
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Journal ArticleDOI
Where practice makes perfect in texture discrimination: evidence for primary visual cortex plasticity
Avi Karni,Dov Sagi +1 more
TL;DR: This work reports remarkable long-term learning in a simple texture discrimination task where learning is specific for retinal input and suggests that learning involves experience-dependent changes at a level of the visual system where monocularity and the retinotopic organization of thevisual input are still retained and where different orientations are processed separately.
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Dependence on REM sleep of overnight improvement of a perceptual skill
TL;DR: Performance of a basic visual discrimination task improved after a normal night's sleep, indicating that a process of human memory consolidation, active during sleep, is strongly dependent on REM sleep.
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Lateral interactions between spatial channels: suppression and facilitation revealed by lateral masking experiments.
Uri Polat,Dov Sagi +1 more
TL;DR: The spatially localized target and masks enabled investigation of space dependent lateral interactions between foveal and neighboring spatial channels, and showed a suppressive region extending to a radius of two wavelengths, in which the presence of the masking signals have the effect of increasing target threshold.
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The time course of learning a visual skill
Avi Karni,Dov Sagi +1 more
TL;DR: Here it is conjecture that some types of perceptual experience trigger permanent neural changes in early processing stages of the adult visual system, which may take many hours to become functional.
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Gabor filters as texture discriminator
TL;DR: The model was found to be in good correlation with known psychophysical characteristics as texton based texture segregation and micropattern density sensitivity, however, this simple model fails to predict human performance in discrimination tasks based on differences in the density of “terminators”.