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Lookup NU author(s): Professor Yujiang WangORCiD, Joe NecusORCiD, Professor Marcus Kaiser
This is the authors' accepted manuscript of an article that has been published in its final definitive form by National Academy of Sciences, 2016.
For re-use rights please refer to the publisher's terms and conditions.
The folding of the cortex in mammalian brains across species has recently been shown to follow a universal scaling law that can be derived from a simple physics model. However, it was yet to be determined whether this law also applies to the morphological diversity of different individuals in a single species, in particular with respect to factors such as age, gender and disease.To this end, we derived and investigated the cortical morphology from magnetic resonance imaging (MRI) of over 1000 healthy human subjects from three independent public databases.Our results show that all three MRI datasets follow the scaling law obtained from the comparative neuroanatomical data, which strengthens the case for the existence of a common mechanism for cortical folding. Additionally, for comparable age groups, both male and female brains scale in exactly the same way, despite systematic differences in size and folding. Furthermore, age introduces a systematic shift in the offset of the scaling law. In the model, this can be interpreted as changes in the mechanical forces acting on the cortex. We also applied this analysis to a dataset derived from comparable cohorts of Alzheimer's patients and healthy subjects of similar age. We demonstrate a systematically lower offset, and a possible change in the exponent for Alzheimer's subjects compared to the control cohort.Finally, we discuss implications of the changes in offset and exponent in the data, and relate it to existing literature. We thus provide a possible mechanistic link between previously independent observations.
Author(s): Wang Y, Necus J, Kaiser M, Mota B
Publication type: Article
Publication status: Published
Journal: Proceedings of the National Academy of Sciences of the USA
Year: 2016
Volume: 113
Issue: 45
Pages: 12820-12825
Print publication date: 08/11/2016
Online publication date: 24/10/2016
Acceptance date: 13/09/2016
Date deposited: 03/10/2016
ISSN (print): 0027-8424
ISSN (electronic): 1091-6490
Publisher: National Academy of Sciences
URL: http://dx.doi.org/10.1073/pnas.1610175113
DOI: 10.1073/pnas.1610175113
Data Access Statement: http://dx.doi.org/10.17634/122519-1
PubMed id: 27791126
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