Variational relevance evaluation of individual fMRI data enables deconstruction of task-dependent neural dynamics

Abstract

In neuroimaging research, univariate analysis has always been used to localize "representations" at the microscale, whereas network approaches have been applied to characterize transregional "operations". How are representations and operations linked through dynamic interactions? We developed the variational relevance evaluation (VRE) method to analyze individual task fMRI data, which selects informative voxels during model training to localize the "representation", and quantifies the dynamic contributions of single voxels across the whole-brain to different cognitive functions to characterize the "operation". Using 15 individual fMRI data files for higher visual area localizers, we evaluated the characterization of selected voxel positions of VRE and revealed different object-selective regions functioning in similar dynamics. Using another 15 individual fMRI data files for memory retrieval after offline learning, we found similar task-related regions working in different neural dynamics for tasks with diverse familiarities. VRE demonstrates a promising horizon in individual fMRI research.