期刊
NEUROIMAGE
卷 226, 期 -, 页码 -出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2020.117546
关键词
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资金
- Epilepsy Society
- National Institute for Health Research University College London Hospitals Biomedical Research Centre
- UK Biotechnology and Biological Sciences Research Council [BB/H008217/1]
- UK Medical Research Council
- University of Cambridge, UK
- Wellcome Trust [208940/Z/17/Z, 210109/Z/18/Z]
- Reece Foundation
- MRC [G0802012, MR/M00841X/1]
- Fundacao Serrapilheira Institute [Serra-1709-16981]
- CNPq [PQ 2017 312837/2017-8]
- Engineering and Physical Sciences Research Council [EP/M020533/1] Funding Source: researchfish
- EPSRC [EP/M020533/1] Funding Source: UKRI
- MRC [MR/M00841X/1, G0802012] Funding Source: UKRI
- Wellcome Trust [210109/Z/18/Z] Funding Source: Wellcome Trust
Research has shown covariance between cortical morphology measures and introduced new independent measures. Applying these measures can provide new insights, revealing distinct morphological alterations underlying healthy aging and temporal lobe epilepsy.
Quantification of brain morphology has become an important cornerstone in understanding brain structure. Measures of cortical morphology such as thickness and surface area are frequently used to compare groups of subjects or characterise longitudinal changes. However, such measures are often treated as independent from each other. A recently described scaling law, derived from a statistical physics model of cortical folding, demonstrates that there is a tight covariance between three commonly used cortical morphology measures: cortical thickness, total surface area, and exposed surface area. We show that assuming the independence of cortical morphology measures can hide features and potentially lead to misinterpretations. Using the scaling law, we account for the covariance between cortical morphology measures and derive novel independent measures of cortical morphology. By applying these new measures, we show that new information can be gained; in our example we show that distinct morphological alterations underlie healthy ageing compared to temporal lobe epilepsy, even on the coarse level of a whole hemisphere. We thus provide a conceptual framework for characterising cortical morphology in a statistically valid and interpretable manner, based on theoretical reasoning about the shape of the cortex.
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