A Tridomain Model for Potassium Clearance in Optic Nerve
Year: 2020
Type: preprint
Abstract: The accumulation of potassium in the narrow space outside nerve cells is aclassical subject of biophysics that has received much attention recently. It
may be involved in potassium accumulation include spreading depression, perhaps
migraine and some kinds of epilepsy, even (speculatively) learning.
Quantitative analysis is likely to help evaluate the role of potassium
clearance from the extracellular space after a train of action potentials.
Clearance involves three structures that extend down the length of the nerve:
glia, extracellular space, and axon and so need to be described in the
tradition of the 'cable equations' of nerve used to explain nerve conduction
since the work of Hodgkin in 1937. A three-compartment model is proposed here
for the optic nerve and is used to study the accumulation of potassium and its
clearance. The model allows the convection, diffusion, and electrical migration
of water and ions. We depend on the data of Orkand et al to ensure the
relevance of our model and align its parameters with the anatomy and properties
of membranes, channels, and transporters: our model fits their experimental
data quite well. The aligned model shows that glia has an important role in
buffering potassium, as expected. The model shows that potassium is cleared
mostly by convective flow through the syncytia of glia driven by osmotic
pressure differences. A simplified model might be possible, but it must involve
flow down the length of the optic nerve. It is easy for compartment models to
neglect this flow. Our model can be used for structures quite different from
the optic nerve that might have different distributions of channels and
transporters in its three compartments. It can be generalized to include the
fourth compartment to deal with the glymphatic flow into the circulatory
system.
Source: arXiv (Cornell University)
Authors: Yi Zhu, Shixin Xu, Bob Eisenberg, Huaxiong Huang
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W3212818854