Precompute initial stabilization phase of RMP
Posted: Tue May 19, 2020 2:10 pm
Hi,
Is there a way to precompute a given time period of an axon model in resting state and then use the result to set initial conditions for a separate run of the same model?
This question is with respect to the model from Gaines et al. (2018) published under http://modeldb.yale.edu/243841.
When running the model as downloaded, it goes through an initial phase of instability in the resting membrane potential (RMP). A delay of 50ms before the onset of the extracellular stimulus is implemented, during which the RMP stabilizes.
The authors of the model have confirmed to me that providing time for stabilization was indeed the reason for the implementation of this rather large delay and that they did not have a solution without it.
My issue here is that I would like to use the model at a large scale for the simulation of extracellular current injections. More specifically I'm using a set of about 100 nerve fiber types, on which I intend to apply about 200'000 different extracellular stimulus configurations. The fiber types differ in terms of parameters like diameter etc., whereas the extracellular stimuli are taken from a FEM potential distribution and then applied to the fiber's nodes and myelin sections. In all of these runs I only need to know one thing: whether or not the stimulus evokes an action potential (AP) in the chosen fiber type.
This means that the initial 50ms for stabilization are independent of the extracellular stimulus, and only depend on the predefined fiber types. Running the model for the entire duration before every stimulus would mean a lot of redundant computation, which I need to avoid at this scale. It seems to me now that ideally I would be able to run the stabilization phase just once for each fiber type and then use the end state of that run to parametrize the model for the beginning of each current injection. In other words the model would be frozen at 50ms for every fiber type, so that in every stimulation run I could just access my "stable state freezer", get the model for the adequate fiber type at t=50ms and inject the stimulus right away.
So far, I haven't found a way to do this. A last resort would be to try and adjust the model parameters until the instability is removed sufficiently, but that would raise new questions of validity.
I am new to NEURON, any help is appreciated.
Is there a way to precompute a given time period of an axon model in resting state and then use the result to set initial conditions for a separate run of the same model?
This question is with respect to the model from Gaines et al. (2018) published under http://modeldb.yale.edu/243841.
When running the model as downloaded, it goes through an initial phase of instability in the resting membrane potential (RMP). A delay of 50ms before the onset of the extracellular stimulus is implemented, during which the RMP stabilizes.
The authors of the model have confirmed to me that providing time for stabilization was indeed the reason for the implementation of this rather large delay and that they did not have a solution without it.
My issue here is that I would like to use the model at a large scale for the simulation of extracellular current injections. More specifically I'm using a set of about 100 nerve fiber types, on which I intend to apply about 200'000 different extracellular stimulus configurations. The fiber types differ in terms of parameters like diameter etc., whereas the extracellular stimuli are taken from a FEM potential distribution and then applied to the fiber's nodes and myelin sections. In all of these runs I only need to know one thing: whether or not the stimulus evokes an action potential (AP) in the chosen fiber type.
This means that the initial 50ms for stabilization are independent of the extracellular stimulus, and only depend on the predefined fiber types. Running the model for the entire duration before every stimulus would mean a lot of redundant computation, which I need to avoid at this scale. It seems to me now that ideally I would be able to run the stabilization phase just once for each fiber type and then use the end state of that run to parametrize the model for the beginning of each current injection. In other words the model would be frozen at 50ms for every fiber type, so that in every stimulation run I could just access my "stable state freezer", get the model for the adequate fiber type at t=50ms and inject the stimulus right away.
So far, I haven't found a way to do this. A last resort would be to try and adjust the model parameters until the instability is removed sufficiently, but that would raise new questions of validity.
I am new to NEURON, any help is appreciated.