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Problems with stimulating current

Posted: Wed Jul 15, 2015 8:08 pm
by mganguly
Hi

I am having trouble with inserting stimulating currents. I am using IClamp for standalone current pulse and IPulse2.mod for periodic pulses. The axon continues to spike and shows no changes with change in the stimulation current amplitude or frequency and behaves as if the stimulation current was ON for the entire time. Even decreasing the current amplitude all the way to zero doesn't seem to affect the axon.

I am using NEURON with Python and have written a lot of code scenarios successfully until suddenly I observed this.

Thanks,

Mohit

Re: Problems with stimulating current

Posted: Wed Jul 15, 2015 11:32 pm
by ted
What have you done to debug the simulations? What happens if you eliminate the IClamp and IPulse2? Have you verified that there is a close match between the anatomical and biophysical properties of your conceptual model and those of the model that is set up by your code? Does the global parameter celsius have the correct value?

Re: Problems with stimulating current

Posted: Thu Jul 16, 2015 12:15 pm
by mganguly
Thanks for the reply.

So I had made some changes to the original "hh.mod" to account for spatial temperature distribution. (by changing GLOBAL celcius to LOCAL localtemp). However, it did run successfully until yesterday.

Changing the mechanism from the modified hh to original hh solves the stimulation current problem. Not sure whats wrong with the modified mechanism.

Thanks,

Mohit

Re: Problems with stimulating current

Posted: Thu Jul 16, 2015 7:07 pm
by ted
mganguly wrote:I had made some changes to the original "hh.mod" to account for spatial temperature distribution. (by changing GLOBAL celcius to LOCAL localtemp).
Two comments. First, NEURON's built in temperature parameter is called celsius. Second, a LOCAL is not what you need to be able to specify different temperatures in different compartment. All you need is make a copy of every original mod file that uses celsius, then revise the copy by declaring a new RANGE variable called mytemp, inserting the statement
mytemp = 25 (degC) : or use a different default value if you prefer
in the PARAMETER block,
and in the rest of the file comment out every statement that involves celsius and replace it with a copy that uses mytemp instead. Then you need to test your revised code by running two simulations and comparing their results. The first simulation should use the original code, with celsius set to some reasonable value T. The second simulation should use your revised code, with mytemp set to T in all compartments of all sections. These two simulations should produce identical results. If the results differ, figure out why and fix the problem. Have you done such a test?
it did run successfully until yesterday.

Changing the mechanism from the modified hh to original hh solves the stimulation current problem. Not sure whats wrong with the modified mechanism.
Code that "runs successfully" isn't necessarily producing correct results. The hardest bugs to diagnose are the ones that don't cause a crash and produce no error messages, not least because they can remain undetected for a long time. Suggest starting with the original, "pre-LOCAL" code, revising that to use "mytemp" as described above, and running the test described above. That may fix the "spontaneous activity" problem.

Re: Problems with stimulating current

Posted: Thu Jul 16, 2015 8:12 pm
by mganguly
So, in my previous message instead of LOCAL, I was using RANGE. ( Sorry about that !)

I figured out that I had accidentally changed the coefficient of alpha for the 'm' system from 0.1 to 0.12 and (maybe) that had led to these abnormal results. Changing it back to the original value of 0.1 corrected the problem. All is well.

Thanks again for the responses. Couldn't imagine how such a small change to such 'devastating' results.

Mohit

Re: Problems with stimulating current

Posted: Mon Jul 20, 2015 2:14 am
by ted
Yes, imagination is not always a reliable predictor of the response of even a slightly complex system to small parameter changes. Unexpected findings are one of the benefits of computational modeling.

One might ask if this is an example of a result that is too critically dependent on a particular parameter value to be entirely plausible. Someone who is familiar with the literature on neuronal homeostasis (see Turrigiano et. al dating back to the 1990s) might suggest that, in an organism that depends on proper functioning of axons, a 20% increase of sodium channel density might be accompanied by a compensatory increase of leak conductance or of a potassium channel such as a delayed rectifier, which would tend to stabilize the axon so that spontaneous spiking would not occur. Individual organisms that lacked the ability to compensate in this way would simply die, removing that particular disability from the gene pool (or simply eliminating the species) in a generation or two.