neuromaps: structural and functional interpretation of brain maps
By Ross D. Markello, J. Hansen, Zhen-Qi Liu, Vincent Bazinet, G. Shafiei, Laura E. Suárez, Nadia Blostein, J. Seidlitz, Sylvain Baillet, T. Satterthwaite and 3 more. bioRxiv, 2022
433 citations recorded by the source corpus.
Imaging technologies are increasingly used to generate high-resolution reference maps of brain structure and function. Comparing experimentally generated maps to these reference maps facilitates cross-disciplinary scientific discovery. Although recent data sharing initiatives increase the accessibility of brain maps, data are often shared in disparate coordinate systems, precluding systematic and accurate comparisons. Here we introduce neuromaps, a toolbox for accessing, transforming and analyzing structural and functional brain annotations. We implement functionalities for generating high-quality transformations between four standard coordinate systems. The toolbox includes curated reference maps and biological ontologies of the human brain, such as molecular, microstructural, electrophysiological, developmental and functional ontologies. Robust quantitative assessment of map-to-map similarity is enabled via a suite of spatial autocorrelation-preserving null models. neuromaps combines open-access data with transparent functionality for standardizing and comparing brain maps, providing a systematic workflow for comprehensive structural and functional annotation enrichment analysis of the human brain. neuromaps is a toolbox for accessing, transforming and comparing human neuroimaging data.
Subfields: Cognitive Neuroscience, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/f8734292a35badebb013a9213b12a52f35b02a91
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cognitive Neuroscience
Citations in the corpus
- Top-down selection of visual working memory contents is supported by alpha-band phase-synchronized oscillatory networks (2025, unknown): “Advances in brain network analysis ( Markello et al., 2022; Shafiei et al., 2023), especially at the edge-(connection) level ( Betzel et al., 2023; Faskowitz et al., 2022), provide a new way to chart neuronal architectures.”
- A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment (2022, background): “Current atlases of cognitive (Varoquaux et al., 2018; Bueichekú et al., 2020; Markello et al., 2022), neurochemical (Seidlitz et al., 2020) and neurogenetic (Seidlitz et al., 2020) distributions also allow for coordination of EEG data with multi-level brain function.”