Editorial: Chasing brain dynamics at their speed: what can time-varying functional connectivity tell us about brain function?

In the past decades, the growing field of network neuroscience has opened new perspectives on the study of the brain and its function. The integration of tools from network analysis and system neuroscience has allowed researchers to explore the properties of brain networks, offering a valuable alternative to traditional methods based on simple subtraction and mass univariate analysis (Sporns, 2010; Behrens and Sporns, 2012). This has led to an exponential growth of connectivity algorithms and methods designed to capture the intrinsic dynamics of human brain networks, both at rest and during active tasks. As a result, a new research direction has emerged. The quantification of spatio-temporal dynamics of functional connectivity (FC) is offering new means to observe a vast repertoire of brain functions. Despite significant advances in this domain, there are still major challenges to address. This is partly due to the rapid and distributed nature of brain interactions, with large-scale networks that constantly evolve and coordinate activity to produce human perception, cognition, and behavior at sub-second timescales. Additionally, brain network activity can vary widely within and across individuals (Finn et al., 2015; Van De Ville et al., 2021), as well as in clinical conditions and brain disorders (see Miao et al.). Thus, modeling whole-brain network dynamics, accounting for the necessary spatial and temporal resolution at both individual and population levels, remains a crucial goal yet to be fully achieved. The present Research Topic contains a collection of methodological and empirical studies that touch upon some of the main challenges in the field, collectively providing insight into the current state of research and the potential solutions for advancing the field of dynamic network neuroscience in the future.