Biology subjects

Haustein, M.

Publications and source records attributed to Haustein, M..

4 recordsLinked to original sources

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 leg model based on anatomical landmarks to study 3D joint kinematics of walking in Drosophila melanogaster

Walking is the most common form of how animals move on land. The model organism Drosophila melanogaster has become increasingly popular for studying how the nervous system controls behavior in general and walking in particular. Despite recent advances in tracking and modeling leg movements of walking Drosophila in 3D, there are still gaps in knowledge about the biomechanics of leg joints due to the tiny size of fruit flies. For instance, the natural alignment of joint rotational axes was largely neglected in previous kinematic analyses. In this study we therefore present a detailed kinematic leg model in which not only the segment lengths but also the main rotational axes of the joints were derived from anatomical landmarks, namely the joint condyles. Our model with natural oblique joint axes is able to adapt to the 3D leg postures of straight and forward walking fruit flies with high accuracy. When we compared our model to an orthogonalized version, we observed that our model showed a smaller error as well as differences in the used range of motion (ROM), highlighting the advantages of modeling natural rotational axes alignment for the study of joint kinematics. We further found that the kinematic profiles of front, middle, and hind legs differed in the number of required degrees of freedom as well as their contributions to stepping, time courses of joint angles, and ROM. Our findings provide deeper insights into the joint kinematics of walking in Drosophila, and, additionally, help to develop dynamical, musculoskeletal, and neuromechanical simulations.

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↗