Subject-level measurement of local cortical coupling
Open accessAbstract
The human cortex is highly folded to allow for a massive expansion of surface area. Notably, the thickness of the cortex strongly depends on cortical topology, with gyral cortex sometimes twice as thick as sulcal cortex. We recently demonstrated that global differences in thickness between gyral and sulcal cortex continue to evolve throughout adolescence. However, human cortical development is spatially heterogeneous, and global comparisons lack power to detect localized differences in development or psychopathology. Here we extend previous work by proposing a new measure - local cortical coupling - that is sensitive to differences in the localized topological relationship between cortical thickness and sulcal depth. After estimation, subject-level coupling maps can be analyzed using standard neuroimaging analysis tools. Capitalizing on a large cross-sectional sample (n=932) of youth imaged as part of the Philadelphia Neurodevelopmental Cohort, we demonstrate that local coupling is spatially heterogeneous and exhibits nonlinear development-related trajectories. Moreover, we uncover sex differences in coupling that indicate divergent patterns of cortical topology. Developmental changes and sex differences in coupling support its potential as a neuroimaging phenotype for investigating neuropsychiatric disorders that are increasingly conceptualized as disorders of brain development. R code to estimate subject-level coupling maps from any two cortical surfaces generated by FreeSurfer is made publicly available along with this manuscript.
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Our results do not contradict previous reports of age-related patterns in the coupling between cortical thickness and sulcal depth (Vandekar et al. 2016).
“Our results do not contradict previous reports of age-related patterns in the coupling between cortical thickness and sulcal depth (Vandekar et al. 2016); however, this relationship does not drive higher rejection rate for detection of age when jointly analyzing the two modalities.”
From Similarity-based multimodal regression (2024) · cites this paper as Vandekar et al. 2016
Previous studies of the PNC have demonstrated coupling between cortical thickness and sulcal depth.
“andthecouplingbetweencorticalthicknessandsulcaldepth(Vandekar et al. 2016)”
From Similarity-based multimodal regression (2024) · cites this paper as Vandekar et al. 2016
Modalities with weak associations can reduce power of a multimodal analysis, even when the correlation between modalities is known to be important.
“We also observe through our application to PNC cortical structure that modalities with weak associations can reduce power of a multimodal analysis, even when the correlation between modalities is known to be important (Vandekar et al. 2016).”
From Similarity-based multimodal regression (2024) · cites this paper as Vandekar et al. 2016
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Similarity-based multimodal regression
Chen, A. A., Weinstein, S. M., Adebimpe, A., Gur, R. C., Gur, R. E., Merikangas, K. R., Satterthwaite, T. D., Shinohara, R. T., & Shou, H. (2024) · Biostatistics · doi:10.1093/biostatistics/kxad033 · Cited by 6 · see citing works
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- Authors
- Vandekar, S. N., Shinohara, R. T., Raznahan, A., Hopson, R. D., Roalf, D. R., Ruparel, K., Gur, R. C., Gur, R. E., & Satterthwaite, T. D.
- Affiliations
- University of Pennsylvania (US)
- National Institutes of Health (US)
- Philadelphia VA Medical Center (US)
- Corresponding author
- Vandekar, Simon N.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2016-06
- Volume
- 133
- Pages
- 88-97
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4889557
- OpenAlex
- W2291533047
- Cited by
- 27
- References
- 47
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 9 · 2023: 2 · 2022: 4 · 2021: 2 · 2020: 1 · 2019: 3 · 2018: 2 · 2017: 1
- FWCI
- 1.73
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- NeuroImage (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (MH089983, MH089924)
- Center for Biomedical Computing and Image Analysis (K23MH098130, R01MH107703, R01NS085211, K01MH10260, T32MH065218-11)
- Dowshen Program for Neuroscience
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- cortical thickness, sulcal depth, cortical development, adolescence, sex differences, neuroimaging phenotypes, Philadelphia Neurodevelopmental Cohort
- MeSH terms
- Adolescent, Cerebral Cortex, Child, Female, Humans, Male, Nerve Net, Neural Pathways, Neuronal Plasticity, Sensitivity and Specificity, Reproducibility of Results, Young Adult, Diffusion Tensor Imaging, Connectome
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