Tell me why? A scoping review on the fundamental building blocks of fMRI networks

This review explores the current landscape of network estimation methods in the context of fMRI-based network neuroscience, focusing on static undirected network analysis. We focused on papers published in a single year (2022), and characterised what we consider the fundamental building blocks of network analysis: sample size, network size, association type, edge inclusion strategy, edge weights, and modelling level. We find that most similar across all included studies (n=191) was the use of pairwise correlations to estimate the associations between brain regions (79.6%) and the estimation of the network at the individual level (86.9%) as opposed to at the group level. Importantly, a substantial number of studies lacked comprehensive reporting on their methodological choices, hindering the synthesis of research findings within the field. This review underscores the critical need for careful consideration and transparent reporting of fMRI network estimation methodologies to advance our understanding of complex brain-behaviour relationships. We hope to facilitate integration between network neuroscience and network psychometrics when studying complex brain-behaviour relations.