Diffusion in Brain Extracellular Space

Diffusion in Brain Extracellular Space

2008 October | Eva Syková and Charles Nicholson
Diffusion in the brain extracellular space (ECS) is constrained by volume fraction and tortuosity, with a modified diffusion equation describing transport. Deviations from this equation indicate loss of molecules via the blood-brain barrier, cellular uptake, or binding. Early methods used radiolabeled tracers, while modern techniques like real-time iontophoresis (RTI) and integrative optical imaging (IOI) measure diffusion in small ions and macromolecules. Theoretical models explore ECS geometry, dead-space microdomains, and extracellular matrix (ECM) interactions. Studies show ECS volume fraction is ~20% and tortuosity ~1.6, varying regionally and with development/aging. Diffusion properties are studied in brain stimulation, osmotic challenges, and disease models. These studies enhance understanding of ECS structure and roles of glia and ECM in modulating the ECS microenvironment. Knowledge of ECS diffusion is valuable for understanding extrasynaptic volume transmission and drug delivery. The ECS is a fluid-filled space between cells, with a volume fraction of 15-30% in normal brain tissue. It facilitates ion transport, chemical signaling, and substance movement between blood vessels and cells. ECS width varies, with recent studies indicating an average of 38-64 nm. Tortuosity, a measure of diffusion hindrance, is influenced by geometric path length, dead-space microdomains, ECM viscosity, and molecular interactions. The effective diffusion coefficient (D*) is related to free diffusion (D) by D* = D/λ², where λ is tortuosity. Factors like molecular size, charge, and ECM composition affect diffusion. Bulk flow, though debated, may occur in perivascular spaces. The diffusion equation in the ECS accounts for volume fraction, tortuosity, and other factors, with Monte Carlo simulations and theoretical models providing insights into ECS structure and diffusion behavior. These studies highlight the complexity of ECS diffusion and its implications for brain function and disease.Diffusion in the brain extracellular space (ECS) is constrained by volume fraction and tortuosity, with a modified diffusion equation describing transport. Deviations from this equation indicate loss of molecules via the blood-brain barrier, cellular uptake, or binding. Early methods used radiolabeled tracers, while modern techniques like real-time iontophoresis (RTI) and integrative optical imaging (IOI) measure diffusion in small ions and macromolecules. Theoretical models explore ECS geometry, dead-space microdomains, and extracellular matrix (ECM) interactions. Studies show ECS volume fraction is ~20% and tortuosity ~1.6, varying regionally and with development/aging. Diffusion properties are studied in brain stimulation, osmotic challenges, and disease models. These studies enhance understanding of ECS structure and roles of glia and ECM in modulating the ECS microenvironment. Knowledge of ECS diffusion is valuable for understanding extrasynaptic volume transmission and drug delivery. The ECS is a fluid-filled space between cells, with a volume fraction of 15-30% in normal brain tissue. It facilitates ion transport, chemical signaling, and substance movement between blood vessels and cells. ECS width varies, with recent studies indicating an average of 38-64 nm. Tortuosity, a measure of diffusion hindrance, is influenced by geometric path length, dead-space microdomains, ECM viscosity, and molecular interactions. The effective diffusion coefficient (D*) is related to free diffusion (D) by D* = D/λ², where λ is tortuosity. Factors like molecular size, charge, and ECM composition affect diffusion. Bulk flow, though debated, may occur in perivascular spaces. The diffusion equation in the ECS accounts for volume fraction, tortuosity, and other factors, with Monte Carlo simulations and theoretical models providing insights into ECS structure and diffusion behavior. These studies highlight the complexity of ECS diffusion and its implications for brain function and disease.
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