Dataset Information

A precision functional atlas of personalized network topography and probabilities.

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.

SUBMITTER: Hermosillo RJM

PROVIDER: S-EPMC11089006 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature

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A precision functional atlas of personalized network topography and probabilities.

Hermosillo Robert J M RJM Moore Lucille A LA Feczko Eric E Miranda-Domínguez Óscar Ó Pines Adam A Dworetsky Ally A Conan Gregory G Mooney Michael A MA Randolph Anita A Graham Alice A Adeyemo Babatunde B Earl Eric E Perrone Anders A Carrasco Cristian Morales CM Uriarte-Lopez Johnny J Snider Kathy K Doyle Olivia O Cordova Michaela M Koirala Sanju S Grimsrud Gracie J GJ Byington Nora N Nelson Steven M SM Gratton Caterina C Petersen Steven S Feldstein Ewing Sarah W SW Nagel Bonnie J BJ Dosenbach Nico U F NUF Satterthwaite Theodore D TD Fair Damien A DA

Nature neuroscience 20240326 5

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 ...[more]

PMID: 38532024

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Project description:BackgroundA key step towards understanding psychiatric disorders that disproportionately impact female mental health is delineating the emergence of sex-specific patterns of brain organization at the critical transition from childhood to adolescence. Prior work suggests that individual differences in the spatial organization of functional brain networks across the cortex are associated with psychopathology and differ systematically by sex.AimsWe aimed to evaluate the impact of sex on the spatial organization of person-specific functional brain networks.MethodWe leveraged person-specific atlases of functional brain networks defined using nonnegative matrix factorization in a sample of n = 6437 youths from the Adolescent Brain Cognitive Development Study. Across independent discovery and replication samples, we used generalized additive models to uncover associations between sex and the spatial layout ("topography") of personalized functional networks (PFNs). Next, we trained support vector machines to classify participants' sex from multivariate patterns of PFN topography. Finally, we leveraged transcriptomic data from the Allen Human Brain Atlas to evaluate spatial correlations between sex differences in PFN topography and gene expression.ResultsSex differences in PFN topography were greatest in association networks including the fronto-parietal, ventral attention, and default mode networks. Machine learning models trained on participants' PFNs were able to classify participant sex with high accuracy. Brain regions with the greatest sex differences in PFN topography were enriched in expression of X-linked genes as well as genes expressed in astrocytes and excitatory neurons.ConclusionsSex differences in PFN topography are robust, replicate across large-scale samples of youth, and are associated with expression patterns of X-linked genes. These results suggest a potential contributor to the female-biased risk in depressive and anxiety disorders that emerge at the transition from childhood to adolescence.

Project description:ImportanceFunctional brain networks are associated with both behavior and genetic factors. To uncover clinically translatable mechanisms of psychopathology, it is critical to define how the spatial organization of these networks relates to genetic risk during development.ObjectiveTo determine the relationship between transdiagnostic polygenic risk scores (PRSs), personalized functional brain networks (PFNs), and overall psychopathology (p-factor) during early adolescence.DesignThe Adolescent Brain Cognitive Development (ABCD) Study is an ongoing longitudinal cohort study of 21 collection sites across the United States. Here, we conduct a cross-sectional analysis of ABCD baseline data, collected 2017-2018.SettingThe ABCD Study ® is a multi-site community-based study.ParticipantsThe sample is largely recruited through school systems. Exclusion criteria included severe sensory, intellectual, medical, or neurological issues that interfere with protocol and scanner contraindications. Split-half subsets were used for cross-validation, matched on age, ethnicity, family structure, handedness, parental education, site, sex, and anesthesia exposure.ExposuresPolygenic risk scores of transdiagnostic genetic factors F1 (PRS-F1) and F2 (PRS-F2) derived from adults in Psychiatric Genomic Consortium and UK Biobanks datasets. PRS-F1 indexes liability for common psychiatric symptoms and disorders related to mood disturbance; PRS-F2 indexes liability for rarer forms of mental illness characterized by mania and psychosis.Main outcomes and measures(1) P-factor derived from bifactor models of youth- and parent-reported mental health assessments. (2) Person-specific functional brain network topography derived from functional magnetic resonance imaging (fMRI) scans.ResultsTotal participants included 11,873 youths ages 9-10 years old; 5,678 (47.8%) were female, and the mean (SD) age was 9.92 (0.62) years. PFN topography was found to be heritable (N=7,459, 57.06% of vertices h 2 p FDR <0.05, mean h 2 =0.35). PRS-F1 was associated with p-factor (N=5,815, r=0.12, 95% CI [0.09-0.15], p<0.001). Interindividual differences in functional network topography were associated with p-factor (N=7,459, mean r=0.12), PRS-F1 (N=3,982, mean r=0.05), and PRS-F2 (N=3,982, mean r=0.08). Cortical maps of p-factor and PRS-F1 regression coefficients were highly correlated (r=0.7, p=0.003).Conclusions and relevancePolygenic risk for transdiagnostic adulthood psychopathology is associated with both p-factor and heritable PFN topography during early adolescence. These results advance our understanding of the developmental drivers of psychopathology.

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A precision functional atlas of personalized network topography and probabilities.

Publications

A precision functional atlas of personalized network topography and probabilities.

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