How to model a net that involves an inhibitory neuron

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ted
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How to model a net that involves an inhibitory neuron

Post by ted » Tue May 24, 2005 8:43 pm

On 2/15/2005 a NEURON user wrote:
> I'm looking for, ideally, a model of an inhibitory neuron that both functions on its own

You may find some in ModelDB. Check out the link to ModelDB on NEURON's
home page www.neuron.yale.edu. We try to ensure that all NEURON models
in the database will run and produce "correct results" (i.e. reproduce at least
one figure from the published paper). However, NEURON has undergone many
changes in the time since many of those models were published, so some of them
are likely to contain instances of obsolete usage, especially with regard to network
modeling. The readings recommended below demonstrate the preferred strategies
and syntax for new model development.

> and that is also able to inhibit a connected excitatory neuron

If all you need is a source of inhibitory input, the best thing to do is to attach an
ExpSyn or Exp2Syn to your target neuron, assign the synaptic mechanism an
appropriate time course and reversal potential, and drive it with spike events
generated by a NetStim and conducted by a NetCon.

If you need a presynaptic neuron model that is itself driven by afferent synaptic
inputs, then instead of a NetStim you may be able to get all the functionality
you need from an IntFire, IntFire2, or IntFire4 artificial spiking cell.

That's much easier than it sounds. You'll want to read chapter 10 of the
NEURON book
http://www.neuron.yale.edu/ftp/ted/book ... xedref.pdf
and work through the Network Builder tutorial, which is available on the
Documentation page of NEURON's WWW site
http://www.neuron.yale.edu/neuron/docs

If you need to build a big net, you'll probably also want to read chapter 11.
http://www.neuron.yale.edu/ftp/ted/book ... xedref.pdf

Some of the readings make extensive use of object oriented programming.
Chapter 12
http://www.neuron.yale.edu/ftp/ted/book ... xedref.pdf
contains a good general discussion of programming in hoc, and chapter 13
http://www.neuron.yale.edu/ftp/ted/book ... xedref.pdf
covers object oriented programming in hoc.

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