Tutorial 1 : Fitting a function to data

Suppose we have measured the time course of a synaptic conductance.

Horizontal axis is in milliseconds.

This particular data trace was produced by a simulation.
The implementational details of the model that was used
are not strictly relevant to this tutorial, but some of you
will have to know, so here they are.

Our goal is to approximate this conductance transient with a function of the form

A (e- k1 t - e- k2 t )

Before we start, it is useful to outline a strategy of how to proceed.


Step 1. Bring up a Multiple Run Fitter

This is a "data-driven" problem, so it makes sense at this point to load our experimental data into the Multiple Run Fitter.

Step 2. Load the Experimental Data into the Multiple Run Fitter

Step 3. Specify the function we want to optimize

Step 4. Specify the parameters that will be adjusted

Step 5. Specify the criteria we want the function to satisfy

Step 6. Perform the optimization

Go back to the main page ("Using NEURON's Optimization Tools") to try the second tutorial.

Copyright © 2004 by N.T. Carnevale and M.L. Hines, All Rights Reserved.