Mantziaris, C. | bioRxiv Science

bioRxiv2022

Network architecture producing swing to stance transitions in an insect walking system

The walking system of the stick insect is one of the most thoroughly described invertebrate systems. We know a lot about the role of sensory input in the control of stepping of a single leg. However, the neuronal organization and connectivity of the central neural networks underlying the rhythmic activation and coordination of leg muscles still remain elusive. It is assumed that these networks can couple in the absence of phasic sensory input due to the observation of spontaneous recurrent patterns (SRPs) of coordinated motor activity equivalent to fictive stepping-phase transitions. Here we sought to quantify the phase of motor activity within SRPs in the isolated and interconnected meso- and metathoracic ganglia. We show that SRPs occur not only in the meso-, but also in the metathoracic ganglia of the stick insect, discovering a qualitative difference between them. We construct a network based on neurophysiological data capable of reproducing the measured SRP phases to investigate this difference. By comparing network output to the biological measurements we confirm the plausibility of the architecture and provide a hypothesis to account for these qualitative differences. The neural architecture we present couples individual central pattern generators to reproduce the fictive stepping-phase transitions observed in deafferented stick insect preparations after pharmacological activation, providing insights into the neural architecture underlying coordinated locomotion.

neuroscience↗

bioRxiv2018

Unraveling intra- and intersegmental neuronal connectivity between central pattern generating networks in a multi-legged locomotor system

Animal walking results from a complex interplay of central pattern generating networks (CPGs), local sensory signals expressing position, velocity and forces generated in the legs, and coordinating signals between neighboring ones. In the stick insect, in particular, intra- and intersegmental coordination is conveyed by these sensory signals. The rhythmic activity of the CPGs, hence of the legs, can be modified by the aforementioned sensory signals. However, the precise nature of the interaction between the CPGs and these sensory signals has remained largely unknown. Experimental methods aiming at finding out details of these interactions, often apply the muscarinic acetylcholine receptor agonist, pilocarpine in order to induce rhythmic activity in the CPGs, hence in the motoneurons of the segmental ganglia. Using this general approach, we removed the influence of sensory signals and investigated the putative connections between CPGs associated with the coxa-trochanter (CTr)-joint in the different segments (legs) in more detail. The experimental data underwent phase-difference analysis and Dynamic Causal Modelling (DCM). These methods can uncover the underlying coupling structure and strength between pairs of segmental ganglia (CPGs). We set up different coupling schemes (models) for DCM and compared them using Bayesian Model Selection (BMS). Models with contralateral connections in each segment and ipsilateral connections on both sides, as well as the coupling from the meta- to the ipsilateral prothoracic ganglion were preferred by BMS to all other types of models tested. Moreover, the intrasegmental coupling strength in the mesothoracic ganglion was the strongest and most stable in all three ganglia.

neuroscience↗