gabrielggn wrote: ↑Thu Aug 22, 2024 5:36 amif anybody reads this post, I suggest the following for discussion about this topic and other interesting ones: 10.1016/j.jphysparis.2011.10.003
An excellent suggestion. For those who don't immediately recognize the DOI, the citation is
Joucla S, Yvert B. Modeling extracellular electrical neural stimulation: from basic understanding to MEA-based applications. Journal of Physiology, Paris 106: 146–158, 2012.
In another paper, these authors proposed a somewhat different approach for predicting and understanding the effects of extracellular fields on cells, which has some advantages over the activating function approach. It should be kept in mind that all methods for predicting excitation of cells by extracellular fields, including multicompartmental computational modeling, are based on assumptions and approximations, and therefore have their own strengths, weaknesses, and domains in which they are "good enough for the purpose at hand."
The limitations are such as only the polarization due to the onset of the pulse is properly represented by the AF estimate
and as Joucla and Yvert (and others) note, "onset of the pulse" means "within a very short interval" (on the scale of microseconds) after the start of the extracellular stimulus.
and only if the electrotonic length is small enough to neglect longitudinal currents.
which raises the question: how applicable is the AF approximation to axons with diameters on the order of microns, and lengths on the order of centimeters? It's OK as long as the extracellular field is "spatially compact" e.g. what you'd get in the near neighborhood of a small monopolar or bipolar stimulating electrode, but it won't work for a field that produces an extensive region (on the scale of hundreds of microns or more) in which extracelluar potential has a significant gradient, as might be produced between a parallel pair of plates driven by different voltages, or between a high voltage power line and ground.
The thing that I do not understand is more about the mathematical translation of the HH equations with extracellular term within NEURON. Indeed, the differences that is represented by the second partial derivative of the extracellular potential is still zero even without taking the limit dx->0. Therefore I don't see how a linear gradient can affect the membrane potential.
Theory is powerful, theory is impressive, but sometimes it is useful to consider a simplified practical example.
Suppose you have a neurite with spatially uniform anatomical and biophysical properties. Let it be so short that it can be represented by three compartments of identical size, as in this crude diagram
Code: Select all
Compartment
A B C
+--ra--+--ra--+
| | |
RC RC RC
| | |
G G G
where + is the center of a compartment, -- and | are merely "wires", G means ground, RC is a resistor in parallel with a capacitor, and ra is the longitudinal cytoplasmic resistance between the centers of adjacent compartments.
The initial conditions are:
At t==0 the extracellular potential is 0 everywhere, and the charge on all capacitors is 0 so the potential difference between each + and G is 0.
At t==1, an extracellular stimulus is applied that leaves compartment B's extracelluar potential == 0, but makes the extracellular potentials for compartments A and C jump to -1 and +1, respectively. (a nice linear gradient)
What happens to the membrane potentials of these three compartments?
And what happens after the stimulus ends, so that the extracellular potentials fall back to 0?
For convenience, assume that all R == 1, C == 1, and ra == 1.
For compatibility with NEURON, you may assume the following units
time ms
potential mV
resistance megohm
capacitance nanofarad
but you're free to use whatever consistent set of units that you like.
Hint: you could build the circuit and run the simulation with NEURON's Linear Circuit Builder