A precision functional atlas of personalized network topography and probabilities

Robert J.M. Hermosillo, Lucille A. Moore, Eric Feczko, Óscar Miranda-Domínguez, Adam Pines, Ally Dworetsky, Gregory Conan, Michael A. Mooney, Anita Randolph, Alice Graham, Babatunde Adeyemo, Eric Earl, Anders Perrone, Cristian Morales Carrasco, Johnny Uriarte-Lopez, Kathy Snider, Olivia Doyle, Michaela Cordova, Sanju Koirala, Gracie J. GrimsrudNora Byington, Steven M. Nelson, Caterina Gratton, Steven Petersen, Sarah W. Feldstein Ewing, Bonnie J. Nagel, Nico U.F. Dosenbach, Theodore D. Satterthwaite, Damien A. Fair

Research output: Contribution to journalArticlepeer-review

Abstract

Although the general location of functional neural networks is similar across individuals, there is vast person-to-person topographic variability. To capture this, we implemented precision brain mapping functional magnetic resonance imaging methods to establish an open-source, method-flexible set of precision functional network atlases—the Masonic Institute for the Developing Brain (MIDB) Precision Brain Atlas. This atlas is an evolving resource comprising 53,273 individual-specific network maps, from more than 9,900 individuals, across ages and cohorts, including the Adolescent Brain Cognitive Development study, the Developmental Human Connectome Project and others. We also generated probabilistic network maps across multiple ages and integration zones (using a new overlapping mapping technique, Overlapping MultiNetwork Imaging). Using regions of high network invariance improved the reproducibility of executive function statistical maps in brain-wide associations compared to group average-based parcellations. Finally, we provide a potential use case for probabilistic maps for targeted neuromodulation. The atlas is expandable to alternative datasets with an online interface encouraging the scientific community to explore and contribute to understanding the human brain function more precisely.

Original languageEnglish (US)
Pages (from-to)1000-1013
Number of pages14
JournalNature neuroscience
Volume27
Issue number5
DOIs
StatePublished - May 2024

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© The Author(s) 2024.

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