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. 2018 Apr 30;8:6732. doi: 10.1038/s41598-018-24703-6

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© The Author(s) 2018

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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Factorial model space and Bayesian Information Criterion (BIC) for the joint analysis of experiment 1 and experiment 2. 3 (combination of fixed effects predictors) x 2 (probability values in predictors: linear vs. log-transformed) model space. Predictors included in i. conventional Model 1: attention, spatial signal probability and attention x spatial signal probability interaction, ii. Model 2: attention, general response probability and spatially selective response probability, iii. Model 3: attention, spatial signal probability, general response probability and spatially selective response probability. To account for potential non-linear relationship between probabilities and response times, the probabilities predicted response times in a linear or a log-transformed fashion. The matrix shows the Bayesian Information Criterion (BIC) of the 6 models (smaller BIC, i.e. darker shade, indicates better model).