Biology subjects

Bueschges, A.

Publications and source records attributed to Bueschges, A..

7 recordsLinked to original sources

bioRxiv2026

Breaking Symmetry in Walking: Drosophila Recruits Task- and Leg-Specific Motor Modules for Curve Walking

Walking animals must continuously reorient to navigate their environment, yet how leg kinematics are reconfigured to produce directional changes of varying magnitude remains poorly understood. Here, we used high-resolution leg tracking to characterize steering behavior in freely walking Drosophila. We focus our analysis on two major strategies, arcs and turns. Although arc and turn trajectories are statistically separable, several parameters suggest an underlying spatial continuum spanning both behavioral categories, involving a change in the steering mechanism rather than a discontinuity in the kinematic space. Arcs, representing shallow curves, and were generated primarily through: (1) graded shifts in the posterior extreme position (PEPs) of the front and inside middle legs, and bilateral asymmetries in stance amplitude, lengthening on the outside (2) and shortening on the inside (3) while step timing and ipsilateral coordination remained at straight-walking baseline. Turns, in contrast, were associated with higher steering demands and relied on: (4) progressive displacement of the anterior extreme positions (AEPs) in front and middle legs, (5) extreme reduction of inside middle and hind leg amplitudes to anchor the turning pivot, (6) skipped steps of inside middle and hind legs, (7) lateral steps of inside middle legs, and (8) spontaneous appearance of synchronized backward-stepping in particular legs beyond a critical turning threshold. Finally, a common kinematic configuration emerges at maximal turning demand. These results suggest a hierarchical, bipartite organization of steering: PEP- and AEP-driven mechanisms operating across moderate and severe trajectory curvatures, and a shared saturated motor state at the behavioral extreme that links descending steering commands to segment-specific leg kinematics in a freely walking insect

animal behavior and cognition↗

bioRxiv2026

Role of leg campaniform sensilla sensory feedback in Drosophila melanogaster adaptive walking

With the newly uncovered access to a genetic line labeling all campaniform sensilla in Drosophila melanogaster and the many insights gathered from larger insects, we analyzed the distribution and patterning of this class of proprioceptors throughout the fly nervous system and studied CS function in motor control. We demonstrate via two-photon calcium imaging microscopy that campaniform sensilla activation induces activity in many leg muscles, showing that these proprioceptive stimuli can influence motor neuron activity. We then dissected how the lack of these proprioceptive stimuli influence walking behavior, leg kinematics, and interleg coordination in freely-walking flies using transient optogenetic inhibition and video tracking with high spatiotemporal resolution. We show that CS inhibition robustly affects Drosophila melanogasters ability to reach their typical walking speeds. Detailed analysis of leg kinematic suggests that shorter stance amplitudes characterized by their long-lasting duration were behind the speed deficits. Dissecting this phenotype also revealed the inability to maintain coordinated interleg stepping patterns as well as postural control in absence of proprioceptive force and load feedback.

neuroscience↗

bioRxiv2025

Task-specificity of local load feedback depends on intersegmental information in an insect walking system

Load proprioceptive feedback measured by campaniform sensilla (CS) substantially contributes to the generation of leg stepping during walking. In stick insects, the effect of load feedback on the antagonistic protractor and retractor motor neurons (MNs) reverses depending on the walking direction to support the functional stance MN pool in both stepping directions. However, this was shown in highly reduced preparations in which the stimulated leg did not perform actual stepping movements, but the effect was inferred from MN activity profiles. It is still largely unknown whether the load feedback similarly shows a direction dependent reversal in its effects on protractor and retractor activity during actual stepping of the stimulated leg. Here, we implemented load stimulation in a single-middle leg preparation and recorded protractor and retractor MN activity extracellularly during fictive forward and backward stepping. We show that CS stimulation during the stance phase prolonged stance (retractor) activity for the duration of the stimulation and induced stance (retractor) activity when applied during the swing phase in forward stepping. During backward stepping, when protractor and retractor switch phases, the same stimulation again prolonged stance (protractor) activity for the duration of the stimulation. However, it rarely induced stance (protractor) activity when applied during the swing phase. We provide evidence that this is due to the absence of signals about the stepping direction of the neighboring legs, thus highlighting the importance of intersegmental signals for task-specific processing of load proprioceptive feedback. New and NoteworthyProprioceptive feedback needs to be processed in a task-dependent manner to serve its function, even when the leg kinematics change to generate different behaviors. We show for forward and backward stepping that load signals initiate and maintain the activity of the functional stance phase motor neuron pool and that intersegmental signals about stepping of the neighboring legs are relevant for the task-specific processing of load feedback.

neuroscience↗

bioRxiv2024

AutoGaitA - Automated Gait Analysis in Python

Individual behaviours require the nervous system to execute specialised motor programs, each characterised by unique patterns of coordinated movements across body parts. Deep learning approaches for body-posture tracking have facilitated the analysis of such motor programs. However, translating the resulting time-stamped coordinate datasets into meaningful kinematic representations of motor programs remains a long-standing challenge. We developed the versatile quantitative framework AutoGaitA (Automated Gait Analysis), a Python toolbox that enables comparisons of motor programs at multiple levels of granularity and across tracking methods, species and behaviours. AutoGaitA allowed us to demonstrate that flies, mice, and humans, despite divergent biomechanics, converge on the age-dependent loss of propulsive strength, and that, in mice, locomotor programs adapt as an integrated function of both age and task difficulty. AutoGaitA represents a truly universal framework for robust analyses of motor programs and changes thereof in health and disease, and across species and behaviours.

animal behavior and cognition↗

bioRxiv2024

A biomimetic fruit fly robot for studying the neuromechanics of legged locomotion

For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, "biomimetic" robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. In this work, we report the development and validation of the robot Drosophibot II, a meso-scale robotic model of an adult fruit fly, Drosophila melanogaster. This robot is novel for its close attention to the kinematics and dynamics of Drosophila, an increasingly important model of legged locomotion. Each legs proportions and degrees of freedom have been modeled after Drosophila 3D pose estimation data. We developed a program to automatically solve the inverse kinematics necessary for walking and solve the inverse dynamics necessary for mechatronic design. By applying this solver to a fly-scale body structure, we demonstrate that the robots dynamics fits those modeled for the fly. We validate the robots ability to walk forward and backward via open-loop straight line walking with biologically inspired foot trajectories. This robot will be used to test biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which will increase our understanding of how the nervous system controls legged locomotion.

bioengineering↗

bioRxiv2023

A parametric finite element model of leg campaniform sensilla in Drosophila to study CS location and arrangement.

Campaniform sensilla (CS) are mechanosensors embedded within the cuticle of many insects at key locations such as nearby leg segment joints or halters. CS located at leg segments were found to respond to cuticle bending which can be induced by walking or jumping movements or by the underlying tensile forces of the muscles. For Drosophila it is unclear how CS location and material property variation influence stress levels within and around CS but this information is crucial to understand how flies might use CS input to adjust walking behaviour. Here, we designed a parametric model of the femoral CS field for Drosophila to allow for a systematic testing of the influence of CS location, orientation and material property variation on stress levels. The model consists of 7 changeable parameters per CS and 12 which can be changed for the CS field. Simulations of leg bending are in line with general beam bending theory: At the specific proximal CS field location nearby the trochantero-femoral leg joint, displacements are smaller than distal, while stresses are higher. When changing CS location towards more distal leg parts the situation changes towards more displacement and less stress. Changes in material property values for CS substructures or whole CS fields have a very low influence on stress or displacement magnitudes (regarding curve shape and amplitude) at the CS caps to which the nerve cells attach. Taken together, our simulation results indicate that for CS fields located at proximal leg parts, the displacements induced by other sources such as muscle tensile forces might be more relevant stimuli than the overall leg bending induced by typical locomotion scenarios. Future parametric finite element models should contain experimentally validated information on the anisotropic and viscoelastic properties of materials contained in this sensory system to further our understanding of CS activation patterns.

zoology↗

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↗