Sympathetic neuron (Wheeler et al 2004)

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Accession:44972
This study shows how synaptic convergence and plasticity can interact to generate synaptic gain in autonomic ganglia and thereby enhance homeostatic control. Using a conductance-based computational model of an idealized sympathetic neuron, we simulated the postganglionic response to noisy patterns of presynaptic activity and found that a threefold amplification in postsynaptic spike output can arise in ganglia, depending on the number and strength of nicotinic synapses, the presynaptic firing rate, the extent of presynaptic facilitation, and the expression of muscarinic and peptidergic excitation. See references for details.
References:
1 . Wheeler DW, Kullmann PH, Horn JP (2004) Estimating use-dependent synaptic gain in autonomic ganglia by computational simulation and dynamic-clamp analysis. J Neurophysiol 92:2659-71 [PubMed]
2 . Kullmann PH, Wheeler DW, Beacom J, Horn JP (2004) Implementation of a fast 16-Bit dynamic clamp using LabVIEW-RT. J Neurophysiol 91:542-54 [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):
Channel(s): I Na,t; I K; I M; I CNG;
Gap Junctions:
Receptor(s): Nicotinic;
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB (web link to model); MATLAB;
Model Concept(s): Activity Patterns;
Implementer(s): Wheeler, Diek W [wheeler at mpih-frankfurt.mpg.de];
Search NeuronDB for information about:  Nicotinic; I Na,t; I K; I M; I CNG;
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sympathetic
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