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. 2017 Jul 18;7:5677. doi: 10.1038/s41598-017-05888-8

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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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Bayesian model reduction for the driving input of imagery. P: perception, I: imagery. The mean of the group level parameter estimates after BMR are shown. The estimated parameters have a multivariate normal distribution, specified by their means (gray bars) and covariance. We transformed the estimated variance of the parameters to 95% confidence intervals, which are displayed as the pink bars. The results show that the driving input during imagery can be best modelled as targeting both IFG and OCC.