Biophysical modeling of anatomically realistic prenatal cortical folding development

Area of Science:

• Neuroscience
• Developmental Biology
• Computational Biology

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 aspects of fetal brain development.

Purpose of the Study:

• To develop a biologically interpretable, whole-brain framework for modeling cortical morphogenesis during gestation.
• To integrate region-specific growth laws with realistic anatomical 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 control parameters for folding patterns.

Main Results:

• The developed framework successfully replicated key anatomical landmarks and quantitative morphometrics of human cortical folding.
• Simulated folding patterns closely matched observed patterns in human fetal brain development.
• The model could replicate atypical brain phenotypes like lissencephaly, pachygyria, and polymicrogyria.

Conclusions:

• This framework provides a quantitative foundation for understanding the mechanisms driving typical and atypical fetal brain development.
• It enables biologically interpretable modeling of cortical morphogenesis, linking growth to form.
• The approach offers insights into the genetic and biophysical factors influencing brain structure and cognitive architecture.