{"title":"Feature-invariant processing of spatial segregation based on temporal asynchrony.","authors":"Yen-Ju Chen, Zitang Sun, Shin'ya Nishida","doi":"10.1167/jov.24.5.15","DOIUrl":null,"url":null,"abstract":"<p><p>Temporal asynchrony is a cue for the perceptual segregation of spatial regions. Past research found attribute invariance of this phenomenon such that asynchrony induces perceptual segmentation regardless of the changing attribute type, and it does so even when asynchrony occurs between different attributes. To test the generality of this finding and obtain insights into the underlying computational mechanism, we compared the segmentation performance for changes in luminance, color, motion direction, and their combinations. Our task was to detect the target quadrant in which a periodic alternation in attribute was phase-delayed compared to the remaining quadrants. When stimulus elements made a square-wave attribute change, target detection was not clearly attribute invariant, being more difficult for motion direction change than for luminance or color changes and nearly impossible for the combination of motion direction and luminance or color. We suspect that waveform mismatch might cause anomalous behavior of motion direction since a square-wave change in motion direction is a triangular-wave change in the spatial phase (i.e., a second-order change in the direction of the spatial phase change). In agreement with this idea, we found that the segregation performance was strongly affected by the waveform type (square wave, triangular wave, or their combination), and when this factor was controlled, the performance was nearly, though not perfectly, invariant against attribute type. The results were discussed with a model in which different visual attributes share a common asynchrony-based segmentation mechanism.</p>","PeriodicalId":49955,"journal":{"name":"Journal of Vision","volume":"24 5","pages":"15"},"PeriodicalIF":2.0000,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11146091/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Vision","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1167/jov.24.5.15","RegionNum":4,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Temporal asynchrony is a cue for the perceptual segregation of spatial regions. Past research found attribute invariance of this phenomenon such that asynchrony induces perceptual segmentation regardless of the changing attribute type, and it does so even when asynchrony occurs between different attributes. To test the generality of this finding and obtain insights into the underlying computational mechanism, we compared the segmentation performance for changes in luminance, color, motion direction, and their combinations. Our task was to detect the target quadrant in which a periodic alternation in attribute was phase-delayed compared to the remaining quadrants. When stimulus elements made a square-wave attribute change, target detection was not clearly attribute invariant, being more difficult for motion direction change than for luminance or color changes and nearly impossible for the combination of motion direction and luminance or color. We suspect that waveform mismatch might cause anomalous behavior of motion direction since a square-wave change in motion direction is a triangular-wave change in the spatial phase (i.e., a second-order change in the direction of the spatial phase change). In agreement with this idea, we found that the segregation performance was strongly affected by the waveform type (square wave, triangular wave, or their combination), and when this factor was controlled, the performance was nearly, though not perfectly, invariant against attribute type. The results were discussed with a model in which different visual attributes share a common asynchrony-based segmentation mechanism.
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