Functional Network Connectivity in White Matter: A Group Informed ICA-Based Network Approach

White matter (WM) has traditionally been undervalued in functional brain connectivity studies due to its weaker blood-oxygenation-level-dependent (BOLD) signals compared to gray matter (GM). Conventional atlas-based approaches often overlook the individualized aspects of functional networks, limiting their applicability for WM. In this study, we introduce the first WM intrinsic connectivity network (ICN) templates derived from a large dataset of over 100,000 scans, demonstrating the feasibility of estimating individualized WM networks using multivariate-spatially constrained ICA (scICA). By combining WM and GM ICNs, our work provides an expanded framework for evaluating functional network connectivity (FNC) across both tissue types, offering new insights into the integrative role of WM in functional connectivity. This approach holds particular promise for enhancing the understanding of connectivity alterations in clinical populations, such as individuals with schizophrenia.