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Hi!

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

Best regards,
Hans

--
Dr. Hans Ekkehard Plesser
Associate Professor

Dept. of Mathematical Sciences and Technology
Norwegian University of Life Sciences

Phone +47 6496 5467
Fax +47 6496 5401
Email hans.ekkehard.plesser at umb.no
Home http://arken.umb.no/~plesser

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• [cellml-discussion] Using CellML for simplified neuron models?, Dr. Hans Ekkehard Plesser, 05/30/2009

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