www-from-model/content/publications/15f6113f-8ef6-403c-9618-0b35dc436866/_index.md

title	persons	topics	params
The role of auxiliary parameters in evaluating voxel-wise encoding models for 3T and 7T BOLD fMRI data	michael-hanke moritz-boos	neuroimaging predictive-data-analysis	graphRootNodePID pid doi date title description kind author topic xyzrins:publications/15f6113f-8ef6-403c-9618-0b35dc436866 xyzrins:publications/15f6113f-8ef6-403c-9618-0b35dc436866 10.1101/2020.04.07.029397 2020-04-08 The role of auxiliary parameters in evaluating voxel-wise encoding models for 3T and 7T BOLD fMRI data In neuroimaging, voxel-wise encoding models are a popular tool to predict brain activity elicited by a stimulus. To evaluate the accuracy of these predictions across multiple voxels, one can choose between multiple quality metrics. However, each quality metric requires specifying auxiliary parameters such as the number and selection criteria of voxels, whose influence on model validation is unknown. In this study, we systematically vary these parameters and observe their effects on three common quality metrics of voxel-wise encoding models in two open datasets of 3- and 7-Tesla BOLD fMRI activity elicited by musical stimuli. We show that such auxiliary parameters not only exert substantial influence on model validation, but also differ in how they affect each quality metric. Finally, we give several recommendations for validating voxel-wise encoding models that may limit variability due to different numbers of voxels, voxel selection criteria, and magnetic field strengths. bibo:AcademicArticle pid given_name family_name xyzrins:persons/michael-hanke Michael Hanke pid given_name family_name xyzrins:persons/moritz-boos Moritz Boos pid display_label xyzrins:topics/neuroimaging Neuroimaging pid display_label xyzrins:topics/predictive-data-analysis Predictive data analysis