Exploring the role of different cell types on cortical folding in the developing human brain through computational modeling

被引:0
|
作者
Zarzor, Mohammad Saeed [1 ]
Ma, Qiang [2 ]
Almurey, Median [1 ]
Kainz, Bernhard [2 ,3 ]
Budday, Silvia [1 ]
机构
[1] Friedrich Alexander Univ Erlangen Nurnberg, Inst Continuum Mech & Biomech, D-91058 Erlangen, Germany
[2] Imperial Coll London, Dept Comp, London SW7 2AZ, England
[3] Friedrich Alexander Univ Erlangen Nurnberg, Erlangen Grad Sch Adv Opt Technol, D-91052 Erlangen, Germany
来源
SCIENTIFIC REPORTS | 2024年 / 14卷 / 01期
基金
欧洲研究理事会;
关键词
Cortical folding; Human brain development; Outer radial glial cells; Multi-field modeling; Coupled problems; OUTER SUBVENTRICULAR ZONE; HUMAN CEREBRAL-CORTEX; RADIAL GLIA; FINITE GROWTH; EVOLUTION; DIVERSITY; EXPANSION; NEOCORTEX; PATTERNS; DIVISION;
D O I
10.1038/s41598-024-75952-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The human brain's distinctive folding pattern has attracted the attention of researchers from different fields. Neuroscientists have provided insights into the role of four fundamental cell types crucial during embryonic development: radial glial cells, intermediate progenitor cells, outer radial glial cells, and neurons. Understanding the mechanisms by which these cell types influence the number of cortical neurons and the emerging cortical folding pattern necessitates accounting for the mechanical forces that drive the cortical folding process. Our research aims to explore the correlation between biological processes and mechanical forces through computational modeling. We introduce cell-density fields, characterized by a system of advection-diffusion equations, designed to replicate the characteristic behaviors of various cell types in the developing brain. Concurrently, we adopt the theory of finite growth to describe cortex expansion driven by increasing cell density. Our model serves as an adjustable tool for understanding how the behavior of individual cell types reflects normal and abnormal folding patterns. Through comparison with magnetic resonance images of the fetal brain, we explore the correlation between morphological changes and underlying cellular mechanisms. Moreover, our model sheds light on the spatiotemporal relationships among different cell types in the human brain and enables cellular deconvolution of histological sections.
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页数:24
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