<p>If there is literature that you are building off of or comparing your approach to, I would look in their papers to see what values they used and use the same. This is the standard approach, as it yields easily comparable experimental results.</p>

<p>If you are just looking for some ballpark numbers for less formal research, <a href="http://www.cns.nyu.edu/~eorhan/notes/lif-neuron.pdf">these guys</a> used 1 mΩ, <a href="http://icwww.epfl.ch/~gerstner/SPNM/node26.html">these guys</a> did the same, and <a href="http://neuroscience.ucdavis.edu/goldman/Tutorials_files/Integrate%26Fire.pdf">these guys</a> say they use 10 MΩ (I think they might mean mΩ). If you want, you can also tune the model by altering this parameter until it yields expected behaviors you are looking for under conditions where you know how the model performs. Different kinds of neurons have different resistance. It's hard to be more specific without knowing more details about what you want to do.</p>

CC BY-SA 3.0
2016-07-10T23:10:59.307Z
2016-07-10T23:10:59.307Z
Larry Muhlstein
<p>I am about to simulate a neuron activity with the "Leaky Integrate and Fire" neuron model. But for that I need the membrane resistance. I was really looking a lot online, but I just cant find a value.
Does anybody know the measured resistance value, or the value usually used in this model?</p>

CC BY-SA 3.0
2016-07-06T17:42:03.670Z
Welcome to cogsci.SE!  More information, about both your question and what you've done to try to answer it, would help people answer you--simulate using what tools and for what goal? where did you look?
Krysta
CC BY-SA 3.0
2016-07-06T17:44:49.710Z
I am doing it for a university project, and I am simulating it with my own C++ program via the Runge Kutta 4 Algorithm.
Luca Thiede
CC BY-SA 3.0
2016-07-06T22:00:36.363Z
Membrane resistance depends on the state of the neuron (in rest-high; excited-low; inhibited-very high?) - it's a dynamic thing, *i.e.,* there does not exist something as *the* resistance
AliceD
CC BY-SA 3.0
2016-07-07T05:55:40.317Z
But in this Leaky Integration Model you assume the resistance as a constant (it is a very strongly simplified Model). So what is commonly used there? Probably something like the average resistance when the Neuron is not firing. Does somebody have a value for that? Or at least a order of magnitude?
Luca Thiede
CC BY-SA 3.0
2016-07-09T19:44:39.843Z
It depends on the neuron you want to model.  It varies enormously depending on the neuron.
TheBlackCat
<neuroscience><electrophysiology>
Membrane resistance of a neuron
Luca Thiede
# Membrane resistance of a neuron

(Asked by: username_0 on 2016-07-06)

I am about to simulate a neuron activity with the "Leaky Integrate and Fire" neuron model. But for that I need the membrane resistance. I was really looking a lot online, but I just cant find a value.
Does anybody know the measured resistance value, or the value usually used in this model?

**Tags:** neuroscience, electrophysiology

> **Comments:**
> **username_1**: Welcome to cogsci.SE!  More information, about both your question and what you've done to try to answer it, would help people answer you--simulate using what tools and for what goal? where did you look?  
> **username_0**: I am doing it for a university project, and I am simulating it with my own C++ program via the Runge Kutta 4 Algorithm.  
> **username_2**: Membrane resistance depends on the state of the neuron (in rest-high; excited-low; inhibited-very high?) - it's a dynamic thing, *i.e.,* there does not exist something as *the* resistance  
> **username_0**: But in this Leaky Integration Model you assume the resistance as a constant (it is a very strongly simplified Model). So what is commonly used there? Probably something like the average resistance when the Neuron is not firing. Does somebody have a value for that? Or at least a order of magnitude?  
> **username_3**: It depends on the neuron you want to model.  It varies enormously depending on the neuron.  

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## 1 answers

### Answer by username_4 on 2016-07-10. Score: 6

If there is literature that you are building off of or comparing your approach to, I would look in their papers to see what values they used and use the same. This is the standard approach, as it yields easily comparable experimental results.

If you are just looking for some ballpark numbers for less formal research, [these guys](http://www.cns.nyu.edu/~eorhan/notes/lif-neuron.pdf) used 1 mΩ, [these guys](http://icwww.epfl.ch/~gerstner/SPNM/node26.html) did the same, and [these guys](http://neuroscience.ucdavis.edu/goldman/Tutorials_files/Integrate%26Fire.pdf) say they use 10 MΩ (I think they might mean mΩ). If you want, you can also tune the model by altering this parameter until it yields expected behaviors you are looking for under conditions where you know how the model performs. Different kinds of neurons have different resistance. It's hard to be more specific without knowing more details about what you want to do.


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