Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; Monash Data Futures Institute, Monash University, Melbourne, Australia
Aurina Arnatkevičiūtė
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia
Eugene McTavish
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; Healthy Brain and Mind Research Centre, Faculty of Health Sciences, Australian Catholic University, Fitzroy, Australia
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; Department of Psychology, Yale University, New Haven, United States
Chao Suo
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; BrainPark, Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia
Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia; Monash Biomedical Imaging, Monash University, Melbourne, Australia; School of Physics, University of Sydney, Sydney, Australia; Center of Excellence for Integrative Brain Function, University of Sydney, Sydney, Australia; BrainKey Inc, San Francisco, United States
for the Alzheimer's Disease Neuroimaging Initiative
Asymmetries of the cerebral cortex are found across diverse phyla and are particularly pronounced in humans, with important implications for brain function and disease. However, many prior studies have confounded asymmetries due to size with those due to shape. Here, we introduce a novel approach to characterize asymmetries of the whole cortical shape, independent of size, across different spatial frequencies using magnetic resonance imaging data in three independent datasets. We find that cortical shape asymmetry is highly individualized and robust, akin to a cortical fingerprint, and identifies individuals more accurately than size-based descriptors, such as cortical thickness and surface area, or measures of inter-regional functional coupling of brain activity. Individual identifiability is optimal at coarse spatial scales (~37 mm wavelength), and shape asymmetries show scale-specific associations with sex and cognition, but not handedness. While unihemispheric cortical shape shows significant heritability at coarse scales (~65 mm wavelength), shape asymmetries are determined primarily by subject-specific environmental effects. Thus, coarse-scale shape asymmetries are highly personalized, sexually dimorphic, linked to individual differences in cognition, and are primarily driven by stochastic environmental influences.
