Here are details on the cell topology:
OK, just needed to make sure the model's soma was between the two axons.
Cm = 0.01 for internodes and 1 nodes and soma.
"1 nodes"? Does this mean "node of Ranvier," and if it does, why would any node of Ranvier have the same specific capacitance as the adjacent interndode? Or do you mean "node" in the mathematical sense, i.e. one of the points in space at which NEURON computes membrane potential?
gnabar_hh = 1.2 for nodes and 0.12 for internodes and soma.
The relatively low channel density at the soma may be relevant to one of the observations in your first message.
I used the d_lambda rule with d_lambda = 0.03 according to the recommandations in the ModelView window.
So spatial discretization is more than adequate. If the spatial grid is too coarse, excitability and conduction velocity are both artifactually reduced.
I ran a few more tests to understand what is going on here and I have new insights compared to my previous post.
One of those new insights is probably about this:
I plotted the potential as a function of distance across my cell and it seems that action potentials initiated (IClamp at one node) at the periphery cannot pass the soma.
2/ In the opposite AP initiated in the central axon (IClamp at one central node) propagate in both directions, and antidromic spikes CAN pass the soma.
The peripheral axon is only 1 um in diameter, so it can't generate much depolarizing current. Because the soma is electrically compact and has a very large surface area compared to an identical length of 1 um diameter axon, orthodromic spikes run into a big capacitive load when they hit the soma. That, and the relatively low Na channel density of the soma (which reduces excitability of the soma) may account for conduction failure of orthodromic spikes.
Now, about extracellular stimulation, which can produce puzzling results.
3/ when using extracellular stimulation (which is my objective) it seems that AP are initiated at both extremities resulting in an antidromic central spike and orthodromic peripheral spike both ending at the soma.
You haven't mentioned stimulus waveform or polarity, or whether it is produced by monopolar or bipolar electrodes. Monopolar stimulation is spatially much less selective than bipolar and can produce lots of interesting phenomena. Some spatial configurations of electrode and nerve, and temporal profiles of stimulus current, are more likely to elicit rebound excitation (historically called "anode break excitation") than direct excitation. I'm using the term "direct excitation" to refer to depolarization that occurs while the extracellular current is being applied. Rebound excitation happens in situations where the stimulus current makes membrane hyperpolarize, so that after the current stops the membrane potential springs back toward rest but overshoots and results in a spike. Some spike mechanisms are relatively resistant to rebound excitation. However, the HH mechanism is rather prone to rebound or anode break spiking, because at rest there is a significant activation of gk and inactivation of gna. Hyperpolarization both gna inactivation and gk activation. When the hyperpolarizing current stops, v rises quickly toward rest, na channels open quickly and accelerate this rise, but gk lags well behind--and that can make v overshoot enough to trigger a spike.
It can be useful to examine the temporal evolution of space plots of v, gna, gk, m^3 and h (no need to plot n^4 because gk is proportional to n^4). NEURON's gui makes it very easy to set up such graphs. If you have any problem doing that, let me know.
here is an example I cannot explain:
1/ I place the electrode in front of the most peripheral node => AP is generated at this node propagates through the peripheral axon but cannot pass the soma
2/ my electrode is still in front of that peripheral node but slightly further => I end up with the same AP PLUS another one coming from the other end of the fiber...
This is a perfect situation for demonstrating the utility of having a convenient user interface for interactive simulations. Are you using hoc or Python?