Controversies and progress on standardization of large-scale brain network nomenclature

Progress in scientific disciplines is accompanied by standardization of terminology. Network neuroscience, at the level of macro-scale organization of the brain, is beginning to confront the challenges associated with developing a taxonomy of its fundamental explanatory constructs. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide recommendations on points of consensus, identify open questions, and highlight areas of ongoing debate in the service of moving the field towards standardized reporting of network neuroscience results. The committee conducted a survey to catalog current practices in large-scale brain network nomenclature. A few well-known network names (e.g., default mode network) dominated responses to the survey, and a number of illuminating points of disagreement emerged. We summarize survey results and provide initial considerations and recommendations from the workgroup. This perspective piece includes a selective review of challenges to this enterprise, including 1) network scale, resolution, and hierarchies; 2) inter-individual variability of networks; 3) dynamics and non-stationarity of networks; 4) consideration of network affiliations of subcortical structures; and 5) consideration of multi-modal information. We close with minimal reporting guidelines for the cognitive and network neuroscience communities to adopt.

The idea that the brain is composed of multiple large-scale networks has steadily gained traction over the past decade. Still, the field has not yet reached consensus on key issues regarding terminology. The Workgroup for HArmonized Taxonomy of NETworks (WHATNET) was formed in 2020 as an Organization for Human Brain Mapping (OHBM)-endorsed best practices committee to provide concrete recommendations and reporting guidelines for the scientific community. WHATNET members engaged in regular discussions, conducted a survey to catalog current practices in large-scale brain network nomenclature, identified barriers to progress, and brainstormed tools that could be developed to help standardize reporting in future studies. Here we summarize these activities and provide important considerations and initial recommendations for the network neuroscience community, noting open questions and controversies that require further empirical and theoretical investigation.