Tutorial given at GUM*02
Nov. 8-10, 2002
San Antonio, TX

Parameter Searching tools in GENESIS

Michael Vanier, California Institute of Technology


This tutorial will describe the process of fitting optimal parameters to single neuron models using parameter search techniques. Different methods will be compared with an emphasis on stochastic methods useful for ragged parameter landscapes. Different parameter searching methods, including genetic algorithms, simulated annealing, and conjugate gradient descent will be discussed using both simple models and models taken from research projects. Software tools, in particular the GENESIS "param" library, will be described in some detail Limitations of parameter searching techniques and future directions will also be considered.

See the tutorial (paramsearch.ppt) (Powerpoint version)

See the tutorial (HTML format)

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