Biophysical modeling of anatomically realistic prenatal cortical folding development

Area of Science:

• Developmental neuroscience
• Computational biology
• Human neuroimaging

Background:

• Cortical folding is crucial for human cognition, but its developmental mechanisms are not fully understood.
• Existing biophysical models lack anatomical realism and fail to capture key features of human brain development.

Purpose of the Study:

• To develop a biologically interpretable, whole-brain developmental framework for modeling cortical morphogenesis.
• To integrate region-specific growth laws with realistic cortical geometry for accurate simulation.

Main Methods:

• Utilized large-scale prenatal magnetic resonance imaging (MRI) data to derive region-specific growth fields.
• Integrated heterogeneous growth data into an anatomically realistic cortical geometry framework.
• Performed systematic perturbations to identify key parameters influencing folding patterns.

Main Results:

• The framework successfully replicated key anatomical landmarks and quantitative morphometrics of human cortical folding.
• Simulated folding patterns closely matched those observed in typical fetal brain development.
• The model accurately reproduced atypical brain phenotypes, including lissencephaly, pachygyria, and polymicrogyria.

Conclusions:

• This data-driven computational framework provides a quantitative foundation for understanding typical and atypical fetal brain development.
• The model elucidates the mechanisms underlying cortical morphogenesis and its variability.
• Offers insights into the origins of neurodevelopmental disorders affecting brain structure.