A network model of glymphatic flow under different experimentally-motivated parametric scenarios

Jeffrey Tithof, Kimberly A.S. Boster, Peter A.R. Bork, Maiken Nedergaard, John H. Thomas, Douglas H. Kelley

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Flow of cerebrospinal fluid (CSF) through perivascular spaces (PVSs) in the brain delivers nutrients, clears metabolic waste, and causes edema formation. Brain-wide imaging cannot resolve PVSs, and high-resolution methods cannot access deep tissue. However, theoretical models provide valuable insight. We model the CSF pathway as a network of hydraulic resistances, using published parameter values. A few parameters (permeability of PVSs and the parenchyma, and dimensions of PVSs and astrocyte endfoot gaps) have wide uncertainties, so we focus on the limits of their ranges by analyzing different parametric scenarios. We identify low-resistance PVSs and high-resistance parenchyma as the only scenario that satisfies three essential criteria: that the flow be driven by a small pressure drop, exhibit good CSF perfusion throughout the cortex, and exhibit a substantial increase in flow during sleep. Our results point to the most important parameters, such as astrocyte endfoot gap dimensions, to be measured in future experiments.

Original languageEnglish (US)
Article number104258
JournaliScience
Volume25
Issue number5
DOIs
StatePublished - May 20 2022

Bibliographical note

Funding Information:
Funding: NIH / National Institute on Aging grant no. RF1AG057575 ( DHK , JHT , MN ) US Army Research Office grant MURI W911NF1910280 ( DHK , JHT , MN ) Career Award at the Scientific Interface from Burroughs Wellcome Fund (JT)

Publisher Copyright:
© 2022 The Author(s)

Keywords

  • In silico biology
  • Neuroscience
  • Systems neuroscience

Fingerprint

Dive into the research topics of 'A network model of glymphatic flow under different experimentally-motivated parametric scenarios'. Together they form a unique fingerprint.

Cite this