Active dendrites and spike propagation in a hippocampal interneuron (Saraga et al 2003)

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We create multi-compartment models of an Oriens-Lacunosum/Moleculare (O-LM) hippocampal interneuron using passive properties, channel kinetics, densities and distributions specific to this cell type, and explore its signaling characteristics. We find that spike initiation depends on both location and amount of input, as well as the intrinsic properties of the interneuron. Distal synaptic input always produces strong back-propagating spikes whereas proximal input could produce both forward and back-propagating spikes depending on the input strength. Please see paper for more details.
1 . Saraga F, Wu CP, Zhang L, Skinner FK (2003) Active dendrites and spike propagation in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons. J Physiol 552:673-89 [PubMed]
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): Hippocampus CA1 interneuron oriens alveus cell;
Channel(s): I Na,t; I A; I K; I h;
Gap Junctions:
Receptor(s): AMPA;
Simulation Environment: NEURON;
Model Concept(s): Action Potential Initiation; Dendritic Action Potentials; Active Dendrites; Influence of Dendritic Geometry; Detailed Neuronal Models; Action Potentials;
Implementer(s): Saraga, Fernanda [Fernanda.Saraga at];
Search NeuronDB for information about:  Hippocampus CA1 interneuron oriens alveus cell; AMPA; I Na,t; I A; I K; I h;
load_file(1, "Case2.hoc")
access soma

objref nclist, SG[3], syn[3]

load_file(1, "")
proc con(){
	nclist = new List()
	SG[0] = SpikeGenerator[0]
	SG[1] = SpikeGenerator[1]
	SG[2] = SpikeGenerator[2]
	syn[0] = AMPA_S[0]
	syn[1] = AMPA_S[1]
	syn[2] = AMPA_S[2]
	nclist.append(new NetCon(SG[0], syn[0], -20, 0, 1))
	nclist.append(new NetCon(SG[1], syn[1], -20, 0, 1))
	nclist.append(new NetCon(SG[2], syn[2], -20, 0, 1))

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