NEURON files from the paper: Learning mechanism for column formation in the olfactory bulb by M. Migliore, Carlo Inzirillo, Gordon M. Shepherd, Front. Integr. Neurosci. (2007) 1:12. doi:10.3389/neuro.07.012.2007 In the olfactory bulb, the processing units for odor discrimination are believed to involve dendrodendritic synaptic interactions between mitral and granule cells. There is increasing anatomical evidence that these cells are organized in columns, and that the columns processing a given odor are arranged in widely distributed arrays. Experimental evidence is lacking on the underlying learning mechanisms for how these columns and arrays are formed. We have used a simplified realistic circuit model to test the hypothesis that distributed connectivity can self-organize through an activity-dependent dendrodendritic synaptic mechanism. The results point to action potentials propagating in the mitral cell lateral dendrites as playing a critical role in this mechanism, and suggest a novel and robust learning mechanism for the development of distributed processing units in a cortical structure. The traces shown in Fig.2 of the paper are produced by running 2mc-w05-w00-e2i3-int220.hoc. However, because the simulation is quite long, the output files are included in the distribution and read by plasticity-disp.hoc, that also allows the display of the time course for all dendrodendritic synapses. After the fig 2 button is pressed and the simulations have completed, the windows can have there axes adjusted similarly to the figures: Under unix systems: to compile the mod files use the command nrnivmodl and run the simulation hoc file with the command nrngui mosinit.hoc Under Windows systems: to compile the mod files use the "mknrndll" command. A double click on the simulation file mosinit.hoc will open the simulation window. Under MAC OS X: Drag and drop the plast folder onto the mknrndll icon in the NEURON application folder. When the mod files are finished compiling drag and drop the mosinit.hoc file onto the nrngui icon. Questions on how to use this model should be directed to michele.migliore@pa.ibf.cnr.it