Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/28937
Appears in Collections:Psychology Journal Articles
Peer Review Status: Refereed
Title: Speed tuning properties of mirror symmetry detection mechanisms
Author(s): Sharman, Rebecca
Gheorghiu, Elena
Issue Date: 5-Mar-2019
Date Deposited: 5-Mar-2019
Citation: Sharman R & Gheorghiu E (2019) Speed tuning properties of mirror symmetry detection mechanisms. Scientific Reports, 9, Art. No.: 3431. https://doi.org/10.1038/s41598-019-39064-x
Abstract: The human visual system is often tasked with extracting image properties such as symmetry from rapidly moving objects and scenes. The extent to which motion speed and symmetry processing mechanisms interact is not known. Here we examine speed-tuning properties of symmetry detection mechanisms using dynamic dot-patterns containing varying amounts of position and local motion-direction symmetry. We measured symmetry detection thresholds for stimuli in which symmetric and noise elements either drifted with different relative speeds, were relocated at different relative temporal frequencies or were static. We also measured percentage correct responses under two stimulus conditions: a segregated condition in which symmetric and noise elements drifted at different speeds, and a non-segregated condition in which the symmetric elements drifted at two different speeds in equal proportions, as did the noise elements. We found that performance (i)improved gradually with increasing the difference in relative speed between symmetric and noise elements, but was invariant across relative temporal frequencies/lifetime duration differences between symmetric and noise elements, (ii)was higher in the segregated compared to non-segregated conditions, and in the moving compared to the static conditions. We conclude that symmetry detection mechanisms are broadly tuned to speed, with speed-selective symmetry channels combining their outputs by probability summation.
DOI Link: 10.1038/s41598-019-39064-x
Rights: This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Licence URL(s): http://creativecommons.org/licenses/by/4.0/

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