WhiFuN: A toolbox to map the white matter functional networks of the human brain

Functional connectivity (FC) computed using functional magnetic resonance imaging (fMRI) of the gray matter (GM) regions of the human brain has been successfully used to find reliable markers of healthy and clinical populations. Approximately 50% of the human brain consists of white matter (WM), and previous studies have shown the presence of blood oxygen level-dependent (BOLD) signals in the WM. However, current FC analysis by researchers is limited to GM regions of the brain, and fMRI data from WM are typically not analyzed. Here, we present the White Matter Functional Networks (WhiFuN) Toolbox specifically designed for WM-FC analysis, incorporating preprocessing steps that minimize signal contamination due to GM, optimized methods for extracting meaningful WM signals, and dedicated statistical and visualization tools for WM-FC. WhiFuN is based on SPM12 preprocessing and contains statistical tools for group-level analyses. WhiFuN provides an intuitive graphical user interface allowing users to execute all steps from preprocessing to final group-level analyses and does not require prior knowledge of computer programming. To demonstrate the features and capabilities of WhiFuN, 98 healthy controls from the publicly available HCP 100 unrelated dataset were used to identify sex differences in WM-FC. We found significant WM-FC sex differences between the left body of the corpus callosum (CC) and the WM-FN that included the left and right posterior corona radiata and the left and right posterior thalamic region. WhiFuN will provide a platform for the neuroimaging community, offering new dimensions to elucidate human brain function as an integrated system of both GM and WM.