A computational model of hemodynamic parameters in cortical capillary networks

Area of Science:

• Neuroscience
• Biophysics
• Computational Biology

Background:

• Analysis of cerebral capillary hemodynamics and functional reactivity remains debated.
• Understanding blood flow in the brain's microvasculature is crucial for neurological health.

Purpose of the Study:

• To develop and utilize a generic computational model of the cortical capillary network.
• To assess hemodynamic parameters and blood flow distribution within varying capillary densities of the human cortex.

Main Methods:

• A 2D Voronoi tessellation model was created, representing capillary segments.
• Morphometric data from the human cortex informed the model's geometric and physiological parameters.
• Numerical simulations incorporated blood viscosity, phase separation, and plasma skimming effects.

Main Results:

• Hemodynamic parameters were analyzed for capillary networks with differing densities.
• Hematocrit, flow rates, and velocities showed variations in heterogeneity and mean values between models.
• Blood flow distribution supported the hypothesis that all cortical capillaries are recruited at rest.

Conclusions:

• The study provides key hemodynamic insights into cortical capillary networks.
• Network resistance discrepancies were observed between models with different capillary densities.
• The findings contribute to a better understanding of cerebral blood flow regulation.