Dynamic Co-Modulation (DyCoM): A Unified Operator Framework for Time-Varying Interactions

Abstract

Dynamic connectivity is central to understanding time-varying interactions between brain regions. Despite decades of methodological development, approaches to measuring dynamic connectivity remain fragmented, leading to inconsistent findings, limited comparability across studies, and difficulty attributing observed effects to computational choices. Here, we introduce dynamic co-modulation (DyCoM), a compact operator-level framework that expresses dynamic connectivity estimators as compositions of a small set of fundamental signal processing operations. Using simulations and resting-state fMRI data, we show that DyCoM disentangles previously conflated findings by revealing that lower-order sensory and higher-order executive control neurobiological signatures, state-transition sensitivity, and medication-linked clinical associations arise from distinct operator choices within a single unified framework. Together, these results establish DyCoM as a unifying foundation for dynamic interaction analysis, revealing how differences in estimator design give rise to divergent biological interpretations and offering a principled and extensible framework for coherence, interpretability, and estimator development.