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. 2017 Dec 19;7:17765. doi: 10.1038/s41598-017-18130-2

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© The Author(s) 2017

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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Multiple regression analysis (MRA) for circadian and sleep predictors over behavioral measures. MRAs are plotted for multiple behaviors in LD (upper panels, (a,b)) and DD (lower panels, (d,e)) and for wild-type (left panels, (a,d)) mice and Afh (right panels, (b,e)) mutants. Predictor 1 (circadian nose poking activity) and different sleep measures as predictor 2 were used. The color intensity reflects the R² value of MRA corresponding to the best lag condition. The proportion of MRAs in which a single regressor was needed to predict the behavior in LD (c) and DD (f) condition.