m,h states don't change in each time step

[GTR]

Dear Ted,

I have a Na mechanism in my neuron model with activation m and inactivation state h respectively.
My aim is to simulate a resting action potential and spontaneous resting activity where NaP channel is the responsible mechanism for these.
But instead of this,when I try to run my model I get no resting action potential.
I was instructed to go to DistributedMechanisms/Viewers/ShapeName
and select Type/alltypes to see how the variables of my model are changing during each single time step.
I observed that m and h states remain stable in the course of time( h=1 and m=2.8148e-09).So no resting action potential generation with this invariable behaviour of states.

Code: Select all

 TITLE HH fast acting sodium channel
: Hodgkin - Huxley squid sodium channel
NEURON {
	SUFFIX Na
	USEION na READ ena WRITE ina
	RANGE gNabar,gNaPbar,ina
}

UNITS {
	(mA) = (milliamp)
	(mV) = (millivolt)
        (mS)=(millisiemens)
	}
PARAMETER {
	gNabar=1.48e-2 (mS/cm2) 
        gNaPbar=1.11e-5 (mS/cm2) 
                v (mV)
	
}
INITIAL{ 
  settables(v)
  m = malpha/(malpha+mbeta)
  h = halpha/(halpha+hbeta)
  }  

STATE {
	m h
}

ASSIGNED {
	
                ena (mV)
	ina (mA/cm2)
	malpha
        halpha
        mbeta
        hbeta
}
BREAKPOINT {
	ina= (0.001)*(gNabar*m^2*h+gNaPbar)*(v-ena) 
}

DERIVATIVE states {
	settables(v)
	m' = (malpha*(1-m))-(mbeta*m)
	h' = (halpha*(1-h))-(hbeta*h)
}
UNITSOFF
PROCEDURE settables(v(mV)){
TABLE malpha, mbeta, halpha, hbeta FROM -100 TO 100 WITH 200
malpha=0.32*(13.1-v)/(exp((13.1-v)/4)-1)
mbeta=0.28*(v-40.1)/(exp(v-40.1)-1)
halpha=0.128*exp((17-v)/18)
hbeta=4/(exp((40-v)/5)+1)
}
UNITSON

I have Ina as a disrtibution of conductances gNa and gNaP Ina=(gNabar*m^2*h+gNaPbar)*(v-ena)
Does this play role to my problem?
Is it better to split this current equation into two seperate .mod files?

[ted]

So you expect spontaneous spiking but didn't see it? What makes you think it should
happen with the parameters you are using, in particular the conductance densities?
Have you tried changing the density of the persistent gna?

I was instructed to go to DistributedMechanisms/Viewers/ShapeName
and select Type/alltypes to see how the variables of my model are changing during each single time step.

You might find it helpful to plot the state variables vs. time.

[GTR]

I am trying to reproduce a subthalamic neuron behaviour which exhibits rhythmic firing during resting state.

You might find it helpful to plot the state variables vs. time.

If I do this with the state plot I suppose that I will get a straight line vs. time for h having a constant value of 1 and the same for m with a value near to zero.
Is it better to inrease gNaP value?

[ted]

I meant simply: plot the state variables as functions of time. x axis is time, y axis is each
of the state variables.