Cortical Morphometry in Neuroimaging and Neurodegeneration
Summary
Cortical morphometry encompasses quantitative measurement of cortical architecture, capturing features such as thickness, surface area and folding patterns via high-resolution MRI. Automated pipelines have matured to facilitate large-scale studies spanning health and disease, offering insights into normal development, ageing and pathology. Cortical thickness quantifies the distance between white matter and pial surfaces, while surface area reflects the expanse of cortical tissue; gyrification indices assess folding complexity. Voxel-based and surface-based methods complement each other by focusing on tissue concentration versus anatomical geometry. Harmonised acquisition protocols and advanced segmentation tools improve reproducibility, enabling longitudinal tracking of subtle changes. In Alzheimer’s, Parkinson’s and frontotemporal dementia, region-specific thinning and atrophy progress in characteristic patterns, serving as biomarkers for early diagnosis, prognosis and therapeutic monitoring. Emerging approaches include fractal-based multiscale descriptors of folding, rapid imaging protocols that reduce motion artefacts, and standardisation efforts for multicentre cohorts. By refining sensitivity and reliability, these developments extend the translational potential of cortical morphometry, informing global efforts in neurodegenerative disease research and clinical application.
Research from Nature Portfolio
No recent Nature Portfolio content available.
Cortical Morphometry in Neuroimaging and Neurodegeneration publication trend
The graph below shows the total number of articles in cortical morphometry in neuroimaging and neurodegeneration across all publications each year (not limited to Nature Index journals).
Technical terms
Cortical thickness: Distance between the white matter boundary and pial surface of the cerebral cortex.
Cortical surface area: Total area of the cerebral cortex reflecting the extent of the cortical sheet.
Gyrification: Measure of the complexity of cortical folding patterns.
Voxel-based morphometry (VBM): Voxel-wise statistical analysis of local tissue volume or density in MRI scans.
Surface-based morphometry (SBM): Analysis of cortical metrics derived from reconstructed cortical surfaces.
References
- Neuro-evolutionary evidence for a universal fractal primate brain shape. eLife (2024).
- Brain morphometry in older adults with and without dementia using extremely rapid structural scans. NeuroImage (2023).
- Influence of Processing Pipeline on Cortical Thickness Measurement. Cerebral Cortex (2020).
- Cortical Thickness Estimations of FreeSurfer and the CAT12 Toolbox in Patients with Alzheimer's Disease and Healthy Controls. Journal of Neuroimaging (2018).
- A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging. NeuroImage (2009).
About these summaries
This Nature Research Intelligence Topic summary is created with the cited references and a large language model. We take care to ground generated text with facts, and have systems in place to gain human feedback on the overall quality of the process in line with our AI principles. We strive to create accurate and useful summaries for people unfamiliar with the research topic and that supports this goal. These pages are a beta release and will be updated as we learn how best to help people gain value from a research topic summary.
Turn complex research questions into confident strategic decisions
When you're under pressure to set direction, justify investment, or understand your competitive position, you need more than raw data — you need trusted insights you can act on.
Benchmark your performance against global peers using robust, methodologically sound analysis.
Combine quantitative metrics with qualitative expert insight to uncover strengths, gaps and emerging opportunities.
Gain tailored, decision-ready recommendations aligned to your strategic priorities.
Talk to us to learn more about our data dashboards and bespoke strategy reports.
Grow research skills, confidence and careers with training built for every stage of the research lifecycle.
Developed with Nature Portfolio journal Editors and internationally renowned experts. Discover three ways to learn:
Self-paced, online courses in convenient bite-sized units, covering key skills across scientific writing, publishing, grant writing, data analysis, and more.
Expert trainer-led workshops with hands-on exercises and real-time feedback across core research skills, delivered via interactive group sessions.
Editor-led workshops combining core principles in writing and publishing, personalised 1:1 feedback from Nature Portfolio Editors and hands-on exercises.
Explore course catalogues and workshop agendas, enquire about the options or request institutional pricing.