Functionally-Adaptive Gray and White Matter Structural Basis Sets via Dynamic Fusion of Multimodal MRI Data

The exact nature of the coupling of brain structure and function has long been an open area of research. Often, this question is approached by first defining a single structural basis set, and then estimating functional brain activation time courses as a linear combination of these structural bases. However, knowing that functional brain activity and connectivity vary over time, so might the nature of these structural/functional couplings. Thus, a single rigidly defined, "functionally unaware" structural manifold may be insufficient to describe structure/function linkages across a whole functional time series. Here, we introduce dynamic fusion, an ICA-based symmetric fusion, and show evidence that challenges current approaches and suggests time-resolved structural basis sets can better represent changing functional manifolds. We perform dynamic fusion using measures of both gray matter (GM) and white matter (WM) structure and present results that may indicate a stronger link between WM structure and dynamic brain function than in GM.