ArticleFrontiers in neuroscience2022
Establishing a Baseline for Human Cortical Folding Morphological Variables: A Multisite Study.
Article in Frontiers in neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Dissecting causal relationships between cortical morphology and neuropsychiatric disorders: a bidirectional Mendelian randomization study.Nature. Mental health · 2025Article
- SAN: Mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites.Human brain mapping · 2024Article
- SAN: mitigating spatial covariance heterogeneity in cortical thickness data collected from multiple scanners or sites.bioRxiv : the preprint server for biology · 2024Article
- Prognostic associations of cortical gyrification in minimally medicated schizophrenia in an early intervention setting.Schizophrenia (Heidelberg, Germany) · 2022Article
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Authors and funding
4 authors.
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Abstract
Differences in the way human cerebral cortices fold have been correlated to health, disease, development, and aging. However, to obtain a deeper understanding of the mechanisms that generate such differences, it is useful to derive one's morphometric variables from the first principles. This study explores one such set of variables that arise naturally from a model for universal self-similar cortical folding that was validated on comparative neuroanatomical data. We aim to establish a baseline for these variables across the human lifespan using a heterogeneous compilation of cross-sectional datasets as the first step to extending the model to incorporate the time evolution of brain morphology. We extracted the morphological features from structural MRI of 3,650 subjects: 3,095 healthy controls (CTL) and 555 patients with Alzheimer's Disease (AD) from 9 datasets, which were harmonized with a straightforward procedure to reduce the uncertainty due to heterogeneous acquisition and processing. The unprecedented possibility of analyzing such a large number of subjects in this framework allowed us to compare CTL and AD subjects' lifespan trajectories, testing if AD is a form of accelerated aging at the brain structural level. After validating this baseline from development to aging, we estimate the variables' uncertainties and show that Alzheimer's Disease is similar to premature aging when measuring global and local degeneration. This new methodology may allow future studies to explore the structural transition between healthy and pathological aging and may be essential to generate data for the cortical folding process simulations.
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