As part of the Group Individual Networks (GIN 🍸) team, Anouk and Zarah worked on a project to obtain a snapshot of commonly used methodologies in fMRI network analysis (scoping review) and develop a novel method that takes into account the nested structure of most fMRI studies (methods paper). In the scoping review, we characterized what we consider the fundamental building blocks of network analysis (sample size, network size, association type, edge inclusion strategy, edge weights, and modeling level), highlighting the need for careful consideration and transparent reporting of the used approach. The methods paper presents a Bayesian multilevel network model to jointly estimate individual-level and group-level resting-state fMRI networks, which may provide a solution to disentangle individual and group network topology.
Both preprints are available on PsyArXiv: scoping review and methods paper.