The Research Landscape of Dynamic Functional Connectivity in Parkinson's Disease: Systematic Review and Interactive Tool

Abstract

Dynamic functional connectivity (dFC) analysis of functional Magnetic Resonance Imaging (fMRI) data has emerged as a powerful framework for characterizing the time-varying network disintegration and topological transitions underlying Parkinsons disease (PD). However, the rapid expansion of this field introduces methodological heterogeneity, creating a fragmented landscape that complicates knowledge synthesis and informed decision-making for future study designs. To address this, we performed a scoping review to map the conceptual and methodological diversity of dFC research in PD. Beyond a traditional static synthesis, we developed DynaPD, an open-source interactive application that allows researchers to dynamically explore study designs, analytical pipelines, and reported findings. Our synthesis of 37 eligible studies reveals divergence in preprocessing strategies but a convergence on core analytical pipelines, notably sliding-window techniques coupled with k-means clustering. Empirically, studies converge on the importance of neural flexibility assessed via dwell times and topological transitions between strongly and sparsely connected states. However, specific network interpretations remain variable. Common limitations included cross-sectional designs, limited spatial resolution for subcortical networks, and short scan duration. By providing a scoping evidence synthesis and a living interactive tool, this work functions as a decision-support resource to consolidate the literature and guide the methodological design of future studies.