space plot and axial resistance

[thats_karlo]

Hi,

How we can use space plot to see how axial resistance vary vs. distance from soma? do you think the following code will give me a good answer?

soma distance()
forsec "list1" {for (x) print distance(x)," ",ri(x)}

[ted]

How we can use space plot to see how axial resistance vary vs. distance from soma?

ri() is not a range variable. It is a function. Furthermore, its value is entirely "accidental" by
which I mean that it is not determined solely by the anatomy and biophysical properties of
the model, but also by the spatial discretization paramter. So it doesn't really tell you anything
about how the anatomy and biophysical properties affect the function of a neuron, and its
variation with distance from the soma will not have any particular biological "meaning."

[thats_karlo]

Thanks Ted,

let me ask 2 more questions:

its value is entirely "accidental" by which I mean that it is not determined solely by the anatomy and biophysical properties of the model, but also by the spatial discretization parameter.

1- if spatial discretization parameter means nseg, i agree for different nseg the ri() gets new value but if we keep nseg constant, say nseg=17, then ri() depends on the cell's anatomy, ,say diameter of the sections, am i right?

2-for constant nseg, i consider ri() as a function of geometry and cytoplasmic resistance. is it ture? or it also depends on other parameters?

Thanks in advance

[ted]

1- if spatial discretization parameter means nseg, i agree for different nseg the ri() gets new value but if we keep nseg constant, say nseg=17, then ri() depends on the cell's anatomy, ,say diameter of the sections, am i right?

2-for constant nseg, i consider ri() as a function of geometry and cytoplasmic resistance. is it ture?

Yes, and yes. But why do you care about ri()? What insight regarding neuronal function are
you trying to gain from the value returned by ri()?

[ted]

Of course, it turns out that the user is interested in the effect of a synaptic input at one point
on membrane potential at some other point, and how the shape of the cell influences this
effect.

I think the only things that change by geometry is the input resistance of the cell and the axial resistance.
. . . then the attenuation of amplitude depends on the axial resistance in the way to the soma.

ri() is only the axial resistance between two adjacent nodes. It isn't the axial resistance
between the synaptic location and the spike trigger zone (or any other location you might
be interested in). More importantly, it does not tell you anything at all about how much signal
current leaks out the membrane between the nodes, or how much escapes into any other
branch that might be attached to the "upstream" node, or even what the signal current does
to membrane potential at the downstream node.

The best predictor of the effect of subthresold synaptic inputs on membrane potential is
the transfer impedance between the synaptic location and the location at which you
observe the psp. Read about this in
David B. Jaffe and Nicholas T. Carnevale
Passive Normalization of Synaptic Integration Influenced by Dendritic Architecture
J Neurophysiol, Dec 1999; 82: 3268 - 3285.
which you can get for free from Journal of Neurophysiology
http://jn.physiology.org/
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