Sympathetic neuron (Wheeler et al 2004)

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.

Model Type: Neuron or other electrically excitable cell

Currents: I Na,t; I K; I M; I CNG

Receptors: Nicotinic

Model Concept(s): Activity Patterns; Synaptic Convergence

Simulation Environment: MATLAB (web link to model); MATLAB

Implementer(s): Wheeler, Diek W [wheeler at]


Wheeler DW, Kullmann PH, Horn JP. (2004). Estimating use-dependent synaptic gain in autonomic ganglia by computational simulation and dynamic-clamp analysis. Journal of neurophysiology. 92 [PubMed]

Kullmann PH, Wheeler DW, Beacom J, Horn JP. (2004). Implementation of a fast 16-Bit dynamic clamp using LabVIEW-RT. Journal of neurophysiology. 91 [PubMed]

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