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Hi Hans,

> We are looking for a good way to describe and share neuron models, and
> CellML appears a good
> candidate. The neuron models we are interested in consist mostly of a
> single compartment,
> possibly of a small number of compartments.
>
> As far as I can see, CellML appears well suited to describe the so-called
> subthreshold dynamics
> of model neurons. But I am wondering if CellML can also capture (or be
> extended to capture) the
> threshold operation present in most simplified neuron models. Briefly, the
> model dynamics are
> integrated according to a set of differential equations. When the membrane
> potential of the
> neuron crosses a certain threshold, the neuron is said to "fire": the
> membrane potential is
> reset to a certain value instantaneuously, and often clamped at that value
> for a certain period
> of time afterwards (refractory period); also, an output signal is
generated.
> In simple
> pseudocode, this would look like:
>
> while ( simulation time not up )
>
> process input
> update dynamics according to ODE
>
> if ( neuron is refractory )
> V_m = V_reset
> count down "refractoriness"
>
> if ( V_m > Threshold )
> V_m = V_reset
> emit output signal
>
> count up time

I believe this could easily be done, as long as you are OK with the
following:
- this would require integrating the model using an integration technique
that relies on a fixed time step. In my experience, anything will make your
resetting of Vm difficult.
- your output signal (Vm?) will always be generated.

Attached is a very simple CellML file (based on the van der Pol model) that
illustrates the kind of thing I think you are after. You want to plot the x
and y parameters (see attached screenshot).

Alan
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• [cellml-discussion] Using CellML for simplified neuron models?, Alan Garny, 06/01/2009
  • <Possible follow-up(s)>
  • [cellml-discussion] Using CellML for simplified neuron models?, James Lawson, 06/02/2009

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