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. 2019 Feb 5;9:1443. doi: 10.1038/s41598-018-37610-7

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© The Author(s) 2019

Open Access 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/.

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A neural model for surround suppression. (a) Tuning curves for a subset of simulated neurons. Green curves represent neurons within a color category (±40°). (b) Tuning curves under a pure FSG modulation. (c) Tuning shift function under the pure FSG condition, which is always zero. (d) Behavioral cueing effect due to FSG (black dots) monotonically decreases and is fitted with a linear function (gray lines). (e) Tuning curves under a hybrid modulation of both FSG and tuning shift. (f) Tuning shift function under the hybrid model. (g) Behavioral cueing effect in the hybrid model exhibits a non-monotonic profile that is better fitted by a Mexican-hat function (black solid line) than a Gaussian function (dark gray solid line). Once outside the suppressive zone, the cueing effect further decreases (light gray solid line).