Gap junctions desynchronize a neural circuit to stabilize insect flight

Silvan Hürkey, Nelson Niemeyer, Jan-Hendrik Schleimer, Stefanie Ryglewski, Susanne Schreiber () and Carsten Duch ()
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Silvan Hürkey: Johannes Gutenberg-University Mainz
Nelson Niemeyer: Humboldt-Universität zu Berlin
Jan-Hendrik Schleimer: Humboldt-Universität zu Berlin
Stefanie Ryglewski: Johannes Gutenberg-University Mainz
Susanne Schreiber: Humboldt-Universität zu Berlin
Carsten Duch: Johannes Gutenberg-University Mainz

Nature, 2023, vol. 618, issue 7963, 118-125

Abstract: Abstract Insect asynchronous flight is one of the most prevalent forms of animal locomotion used by more than 600,000 species. Despite profound insights into the motor patterns1, biomechanics2,3 and aerodynamics underlying asynchronous flight4,5, the architecture and function of the central-pattern-generating (CPG) neural network remain unclear. Here, on the basis of an experiment–theory approach including electrophysiology, optophysiology, Drosophila genetics and mathematical modelling, we identify a miniaturized circuit solution with unexpected properties. The CPG network consists of motoneurons interconnected by electrical synapses that, in contrast to doctrine, produce network activity splayed out in time instead of synchronized across neurons. Experimental and mathematical evidence support a generic mechanism for network desynchronization that relies on weak electrical synapses and specific excitability dynamics of the coupled neurons. In small networks, electrical synapses can synchronize or desynchronize network activity, depending on the neuron-intrinsic dynamics and ion channel composition. In the asynchronous flight CPG, this mechanism translates unpatterned premotor input into stereotyped neuronal firing with fixed sequences of cell activation that ensure stable wingbeat power and, as we show, is conserved across multiple species. Our findings prove a wider functional versatility of electrical synapses in the dynamic control of neural circuits and highlight the relevance of detecting electrical synapses in connectomics.

Date: 2023
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DOI: 10.1038/s41586-023-06099-0

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