Mapping function onto neuronal morphology (Stiefel and Sejnowski 2007)

"... 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. ..."

Model Type: Neuron or other electrically excitable cell

Model Concept(s): Influence of Dendritic Geometry; Methods; Unsupervised Learning

Simulation Environment: NEURON

Implementer(s): Stiefel, Klaus [stiefel at]


Stiefel KM, Sejnowski TJ. (2007). Mapping function onto neuronal morphology. Journal of neurophysiology. 98 [PubMed]

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