Theoretical and experimental investigations of intra- and inter-segmental control networks and their application to locomotion of insects and crustaceans

Movements of the walking legs in terrestrial animals have to be coordinated continuously in order to produce successful locomotion. Walking is a cyclic process: A single step consists of a stance phase and a swing phase. In the stance phase, the leg muscles provide propulsion of the animal’s body. During the swing phase, the leg is positioned to the starting position of the next stance phase. Sensory input, arising from sensory organs in the legs, modulates the rhythmic motoneuronal activity and therefore the rhythmic activity of the antagonistic muscles pairs in a leg. The coordination of leg joints, and thus of the respective muscle pairs, is called intra-segmental coordination. For coordinated walking not only the proper coordination of one leg is important, but also the coordination of contralateral and ipsilateral legs. The latter is called inter-segmental coordination and also strongly depends on sensory feedback. In this thesis I present three publications (Grabowska et al., 2012; Toth et al., 2013; Grabowska et al., in rev.) and results of an experimental study focusing on different aspects of intra- and inter-segmental coordination. Starting with experimental data on the stick insect Carausius morosus, a well studied model organism for locomotion, I analyzed inter-segmental coordination of legs during walking behavior of stick insects by video analysis. I also performed electrophysiological experiments that provide insight into the inter-segmental connections of different thoracic segments. Furthermore, experimental results were summarized in mathematical models in order to reproduce stick insect locomotion and to provide new hypotheses about so far unknown neuronal controlling processes. First, a study of the walking behavior of the stick insect is introduced (Grabowska et al., 2012). For this purpose, walking sequences of adult animals, walking straight on surfaces with increasing and decreasing slopes, were recorded. Depending on the slope, the animals used different coordination patterns. Subsequent, walking patterns of animals with amputated front, hind or middle legs were analyzed. It became evident that the resulting coordination patterns were regular or maladapted, depending on the amputated leg pairs. We therefore assumed that afferent information from walking front, middle, and hind legs contribute differently to coordination. The second part presents a neuromechanical model that describes starting and stopping of a stick insect leg during walking (Tóth et al., 2013). An existing model of the intra-segmental neuronal network of the stick insect leg was extended by a model of its musculo-skeletal system. The focus of the model was on the neuronal control of slow and fast muscle fiber activity of the three proximal leg muscle groups at start and stop of a leg within a stepping cycle. Using the effects of sensory signals that encode position and velocity of the leg joints like the temporal components of activated muscles during start and stop, observed in experiments, as well as the timing of starting and stopping processes within a step cycle, the simulation results were in good agreement with the observed data of the stick insect. Therefore, this model can be regarded as physiologically relevant and leads to hypotheses about the neuronal control of the musculo-skeletal system that can reveal details of stop and starting in the walking animals. In the third part of this thesis the above mentioned 3-CPG-MN network model, which has been developed based on stick insect data, was extended to serve as a basic module for eight-legged locomotion in walking crustaceans (Grabowska et al., in rev.). For this purpose, the existing 3-CPG-MN network model was extended by an additional segmental module. The basic properties of the 3-CPG-MN network modules remained unchanged. By testing two different network topologies of the new 4-CPG-MN network model, specific walking behavior (coordination patterns, stepping frequency, and transitions) of crustaceans could be replicated by only changing the timing of the inter-segmental excitatory sensory input on the influenced segment. Considering the topology of the 3-CPG-MN network model, namely a caudal-rostral inter-segmental connection connecting every second CPG, the 4-CPG-MN network model was able to reproduce all kinds of walking behavior of forward walking crabs and crayfish. This network stresses the importance of the timing of excitatory signals that are provided by inter-segmental pathways in animals with eight walking legs and four thoracic segments, and proposes possible inter-segmental sensory pathways. Finally, results of experimental data are introduced showing that the rhythm of protractor/retractor central pattern generating networks (thorax-coxa joint) in the prothoracic ganglion can be influenced by a stepping ipsilateral hind leg of the stick insect. This inter-segmental pathway was hypothesized in the 3-CPG-MN network model of Daun-Gruhn and Tóth (2011) for stick insect walking. The experiments showed that a pilocarpine-induced rhythm in the prothoracic protractor and retractor motoneurons could be entrained by an intact forward or backward walking hind leg. In stick insects, this is the evidence for a long range ipsilateral inter-segmental connection that mediates sensory information from a stepping hind leg to the prothoracic CPGs

Encoding of Coordinating Information in a Network of Coupled Oscillators

Animal locomotion is driven by cyclic movements of the body or body appendages. These movements are under the control of neural networks that are driven by central pattern generators (CPG). In order to produce meaningful behavior, CPGs need to be coordinated. The crayfish swimmeret system is a model to investigate the coordination of distributed CPGs. Swimmerets are four pairs of limbs on the animal’s abdomen, which move in cycles of alternating power-strokes and return-strokes. The swimmeret pairs are coordinated in a metachronal wave from posterior to anterior with a phase lag of approximately 25% between segments. Each swimmeret is controlled by its own neural microcircuit, located in the body segment’s hemiganglion. Three neurons per hemiganglion are necessary and sufficient for the 25% phase lag. ASCE DSC encode information about their home ganglion’s activity state and send it to their anterior or posterior target ganglia, respectively. ComInt 1, which is electrically coupled to the CPG, receives the coordinating information. The isolated abdominal ganglia chain reliably produces fictive swimming. Motor burst strength is encoded by the number of spikes per ASCE and DSC burst. If motor burst strength varies spontaneously, the coordinating neurons track these changes linearly. The neurons are hypothesized to adapt their spiking range to the occurring motor burst strengths. One aim of this study was to investigate the putative adaptive encoding of the coordinating neurons in electrophysiological experiments. This revealed that the system’s excitation level influenced both the whole system and the individual coordinating neurons. These mechanisms allowed the coordinating neurons to adapt to the range of burst strengths at any given excitation level by encoding relative burst strengths. The second aim was to identify the transmitters of the coordinating neurons at the synapse to ComInt 1. Immunohistochemical experiments demonstrated that coordinating neurons were not co-localized with serotonin-immunoreactive positive neurons. MALDI-TOF mass spectrometry suggested acetylcholine as presumable transmitter