PT - JOURNAL ARTICLE AU - Ross D. Markello AU - Justine Y. Hansen AU - Zhen-Qi Liu AU - Vincent Bazinet AU - Golia Shafiei AU - Laura E. Suárez AU - Nadia Blostein AU - Jakob Seidlitz AU - Sylvain Baillet AU - Theodore D. Satterthwaite AU - M. Mallar Chakravarty AU - Armin Raznahan AU - Bratislav Misic TI - neuromaps: structural and functional interpretation of brain maps AID - 10.1101/2022.01.06.475081 DP - 2022 Jan 01 TA - bioRxiv PG - 2022.01.06.475081 4099 - http://biorxiv.org/content/early/2022/01/06/2022.01.06.475081.short 4100 - http://biorxiv.org/content/early/2022/01/06/2022.01.06.475081.full AB - Imaging technologies are increasingly used to generate high-resolution reference maps of brain structure and function. Modern scientific discovery relies on making comparisons between new maps (e.g. task activations, group structural differences) and these reference maps. Although recent data sharing initiatives have increased the accessibility of such brain maps, data are often shared in disparate coordinate systems (or “spaces”), precluding systematic and accurate comparisons among them. Here we introduce the neuromaps toolbox, an open-access software package for accessing, transforming, and analyzing structural and functional brain annotations. We implement two registration frameworks to generate high-quality transformations between four standard coordinate systems commonly used in neuroimaging research. The initial release of the toolbox features >40 curated reference maps and biological ontologies of the human brain, including maps of gene expression, neurotransmitter receptors, metabolism, neurophysiological oscillations, developmental and evolutionary expansion, functional hierarchy, individual functional variability, and cognitive specialization. Robust quantitative assessment of map-to-map similarity is enabled via a suite of spatial autocorrelation-preserving null models. By combining open-access data with transparent functionality for standardizing and comparing brain maps, the neuromaps software package provides a systematic workflow for comprehensive structural and functional annotation enrichment analysis of the human brain.Competing Interest StatementThe authors have declared no competing interest.