Mapping function onto neuronal morphology (Stiefel and Sejnowski 2007)

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Accession:93398
"... We used an optimization procedure to find neuronal morphological structures for two computational tasks: First, neuronal morphologies were selected for linearly summing excitatory synaptic potentials (EPSPs); second, structures were selected that distinguished the temporal order of EPSPs. The solutions resembled the morphology of real neurons. In particular the neurons optimized for linear summation electrotonically separated their synapses, as found in avian nucleus laminaris neurons, and neurons optimized for spike-order detection had primary dendrites of significantly different diameter, as found in the basal and apical dendrites of cortical pyramidal neurons. ..."
Reference:
1 . Stiefel KM, Sejnowski TJ (2007) Mapping function onto neuronal morphology. J Neurophysiol 98:513-26 [PubMed]
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Model Information (Click on a link to find other models with that property)
Model Type: Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s):
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: NEURON;
Model Concept(s): Influence of Dendritic Geometry; Methods; Unsupervised Learning;
Implementer(s): Stiefel, Klaus [stiefel at salk.edu]; 
create dummy
objref stimulator[100]

// inserts a NetStim into a dummy section
proc makestimulators() {
	for mm = 0, $1-1 {
		access dummy
		L = 0.1
		diam = 0.1
		stimulator[mm] = new NetStim(.5)
		stimulator[mm].number = 1 
		stimulator[mm].start =  10
		}
}