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Journal of NeurophysiologyNeurosciencePeer-reviewed journal article

M-current regulates firing mode and spike reliability in a collision detecting neuron

Richard Burkett DewelliD, Fabrizio GabbianiiD

PDFDOIPreprint

Abstract

All animals must detect impending collisions to escape them, and they must reliably discriminate them from non-threatening stimuli to prevent false alarms. Therefore, it is no surprise that animals have evolved highly selective and sensitive neurons dedicated to such tasks. We examined a well-studied collision detection neuron in the grasshopper Schistocerca americana using in vivo electrophysiology, pharmacology, and computational modeling. This lobula giant movement detector (LGMD) neuron is excitable by inputs originating from each ommatidia of the compound eye, and it has many intrinsic properties that increase its selectivity to objects approaching on a collision course, including switching between burst and non-burst firing. Here, we demonstrate that the LGMD neuron exhibits a large M current, generated by non-inactivating K+ channels, that narrows the window of dendritic integration, regulates a firing mode switch between burst and isolated spiking, increases the precision of spike timing, and increases the reliability of spike propagation to downstream motor centers. By revealing how the M current increases the LGMDs ability to detect impending collisions our results suggest that it may play an analogous role in other collision detection circuits.\n\nNew & NoteworthyThe ability to reliably detect impending collisions is a critical survival skill. The nervous systems of many animals have developed dedicated neurons for accomplishing this task. We used a mix of in vivo electrophysiology and computational modeling to investigate the role of M potassium channels within one such collision detecting neuron and showed that through regulation of burst firing and increasing spiking reliability the M current increases the ability to detect impending collisions.

Citations
10
FWCI
0.36
Field percentile
top 44%

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Richard Burkett Dewell, Fabrizio Gabbiani·Journal of Neurophysiology·Jul 3, 2019· 17 citations