Abstract

To understand single neuron computation it is desirable that realistic input patterns be given to model neurons in the study of the input-output function. Spike train objects can be used to generate input patterns in place of a full network model, which is often not available. The tutorial describes how spike trains can be generated as probability distributions, or read from experimental data. Correlations between spike trains can be constructed to test temporal coding by neural models. Examples and exercises, including strategies for data analysis will be given.

See the tutorial (Powerpoint format)

See the movie (AVI format - 11 MB)

This video shows 100 msec of simulated cell activity with 20Hz excitation and 2.5 Hz inhibition. It may be viewed on Linux/UNIX systems with the Xine media player.