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bioRxiv · 10.1101/2022.04.07.487473

Unmasking hidden changes in intrinsic properties in neurons that coordinate oscillatory networks

Abstract

2.Neurons utilize gain control to efficiently encode shifting inputs with maximum sensitivity. While gain control is present in a multitude of neurons, research on the underlying mechanisms is still sparse. We focused on one coordinating neuron (ASCE) in the crayfish swimmeret system that is both necessary and sufficient to coordinate distributed motor circuits. This neuron encodes properties of the motor activity in its home ganglion and sends the information as burst of spikes to its anterior target ganglia. Previous research has shown that ASCE encodes the strength of the motor activity by its spike number, and that the range of the number of spikes per burst adapts to the average motor activity. In turn, the motor activity can be activated and modulated via cholinergic pathways. We explored ASCEs response to changing levels of motor system excitation, which was induced with cholinergic agonists, both when the neuron was part of the full swimmeret systems circuit and when it was isolated from the network. The cholinergic agonist carbachol directly depolarized ASCEs membrane potential via nicotinic receptors when the neuron was isolated. In the intact circuit, ASCEs membrane potential did not change but its input resistance decreased. This indicated an additional indirect action of carbachol, presumably via presynaptic central pattern generating neurons at the core of each motor circuit. The balance of direct and indirect effects could allow ASCE to match its spiking range to the systems excitation level. 1. Summary statementA balance of direct and indirect cholinergic effects precisely controls the membrane potential, and therefore the gain, of a neuron that is involved in the coordination of distributed motor circuits.

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BibTeXRIS

Schneider, A. C., Smarandache-Wellmann, C. R.. 2022-04-10. Unmasking hidden changes in intrinsic properties in neurons that coordinate oscillatory networks. https://doi.org/10.1101/2022.04.07.487473

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