@article { , title = {Data visualization for inference in tomographic brain imaging}, abstract = {Tomographic brain imaging has a rich iconography. Whilst figures are prepared for scientific communication (i.e., directed to other researchers) they also often end-up on magazine and journal covers (i.e., directed to a lay audience). Scientific figures should however not be just glossy illustrations of what is in the text. One of the primary roles of figures is to carry information that cannot be easily explained in words or summarized in tables (Rougier et al., 2014). Poor scientific figures are figures that not only fail to convey additional information, but also figures that convey or induce incorrect information, especially for non-specialists. Here we provide a guideline on which visual information to display and in which context, to improve information content and minimize false inference. We first discuss the use of slices versus renders and in which situations they should be used. We next reiterate the need for unthresholded statistical maps (Jernigan et al.,2003) along with (i) the highlighting of significant areas on such maps (ii) the necessity to plot results in all regions of interest, and (iii) the choice of colour scales. Together, these measures provide additional contextual information and should prevent readers natural tendency to falsely infer differences in activations or absence of activations. Additional recommendations are also given to convey information about hemispheric asymmetry and effect sizes.}, doi = {10.1111/ejn.14430}, issn = {0953-816X}, issue = {3}, journal = {European Journal of Neuroscience}, note = {This is the peer reviewed version of the following article: Pernet, C.R. and Madan, C.R. (2020), Data visualization for inference in tomographic brain imaging. Eur J Neurosci, which has been published in final form at doi:10.1111/ejn.14430. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.}, pages = {695-705}, publicationstatus = {Published}, publisher = {Wiley}, url = {https://nottingham-repository.worktribe.com/output/1840206}, volume = {51}, keyword = {Beacon - Precision Imaging}, year = {2020}, author = {Pernet, Cyril R and Madan, Christopher R} }