Over the years, multiple “brain maps” have emerged, each focusing on different brain processes, from metabolism to cognitive function. While these maps are important, using them in isolation limits the discoveries researchers can make from them.

Now a team from Montreal Neurological Institute and other researchers has brought together more than forty existing brain maps in one place. The database, called neuromaps, is expected to help scientists find correlations between patterns across different brain regions, spatial scales, modalities, and brain functions.

The database provides a standardized space to view each map in comparison to each other, and assesses the statistical significance of these comparisons, to help researchers distinguish a meaningful correlation from a random pattern. The neuromaps database also helps standardize the code across maps, to improve reproducibility of results.

The scientists published the study “neuromaps: structural and functional interpretation of brain maps” in Nature Methods and made their data open access on github.

Sampling of some of the brain maps included in neuromaps. [Montreal Neurological Institute]
“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,” write the investigators.

“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.”

“Ultimately, we hope that neuromaps will add a spark to the analysis of human brain maps and increase accessibility of data and software tools to people with diverse research interests,” says Justine Hansen, a PhD student and the paper’s co-first author. “As the rate at which new brain maps are generated in the field continues to grow, we hope that neuromaps will provide researchers with a set of standardized workflows for better understanding what these data can tell us about the human brain.”

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