Estimating Use-Dependent Synaptic Gain in Autonomic Ganglia by Computational Simulation and Dynamic-Clamp Analysis

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Abstract
Biological gain mechanisms regulate the sensitivity and dynamics of signaling pathways at the systemic, cellular, and molecular levels. In the sympathetic nervous system, gain in sensory-motor feedback loops is essential for homeostatic regulation of blood pressure and body temperature. 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. The simulations also showed that postsynaptic refractory periods serve to limit synaptic gain and alter postsynaptic spike timing. Synaptic gain was measured by stimulating dissociated bullfrog sympathetic neurons with 1–10 virtual synapses using a dynamic clamp. As in simulations, the threshold synaptic conductance for nicotinic excitation of firing was typically 10–15 nS, and synaptic gain increased with higher levels of nicotinic convergence. Unlike the model, gain in neurons sometimes declined during stimulation. This postsynaptic effect was partially blocked by 10 μM Cd2+, which inhibits voltage-dependent calcium currents. These results support a general model in which the circuit variations observed in parasympathetic and sympathetic ganglia, as well as other neural relays, can enable functional subsets of neurons to behave either as 1:1 relays, variable amplifiers, or switches.