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Abstract To understand how behaviors arise in animals, it is necessary to investigate both the neural circuits and the biomechanics of the periphery. A tractable model system for studying multifunctional control is the feeding apparatus of the marine molluskAplysia californica. Previousin silicoandin robotomodels have investigated how the nervous and muscular systems interact in this system. However, these models are still limited in their ability to matchin vivodata both qualitatively and quantitatively. We introduce a new neuromechanical model ofAplysiafeeding that combines a modified version of a previously developed neural model with a novel biomechanical model that better reflects the anatomy and kinematics ofAplysiafeeding. The model was calibrated using a combination of previously measured biomechanical parameters and hand-tuning to behavioral data. Using this model, simulated feeding experiments were conducted, and the resulting behavioral metrics were compared to animal data. The model successfully produces three key behaviors seen inAplysiaand demonstrates a good quantitative agreement with biting and swallowing behaviors. Additional work is needed to match rejection behavior quantitatively and to reflect qualitative observations related to the relative contributions of two key muscles, the hinge and I3. Future improvements will focus on incorporating the effects of deformable 3D structures in the simulated buccal mass. 

Summary Animals need to fine-control the speed and direction of locomotion to navigate complex and dynamic environments. To achieve this, they integrate multimodal sensory inputs with their internal drive to constantly adjust their motor output. This integration involves the interplay of neuronal populations across different hierarchical levels along the sensorimotor axis – from sensory, central, and modulatory neurons in the brain to descending neurons and motor networks in the nerve cord. Here, we characterize two populations of neurons that control distinct aspects of walking on different hierarchical levels inDrosophila. First, we usein-vivoelectrophysiological recordings to demonstrate that moonwalker descending neurons (MDN) integrate antennal touch to drive changes in walking direction from forward to backward. Second, we establish DopaMeander as an important component in the control of forward walking through a combination of optogenetic activation, silencing, connectomics, andin-vivorecordings. These dopaminergic modulatory neurons drive forward walking with increased turning, and the activity of individual neurons is correlated with ipsiversive turning. Hence, MDN and DopaMeander control opposite regimes of walking on different hierarchical levels. Computational models reveal that their activity predicts key parameters of spontaneous walking. Moreover, we find that both MDN and DopaMeander are gated out during flight. This suggests that neuronal populations across levels of control are modulated by the behavioral state to minimize cross-talk between motor programs. 

Abstract Insulin is a peptide hormone that is secreted in Golgi-derived dense-core vesicles from mammalian pancreatic beta-cells in response to nutrients. InDrosophila melanogaster, three insulin-like peptides are secreted as neuropeptides from the insulin-producing cells in the brain. Peroxisomes are lipid-metabolizing organelles that engage into various membrane contact sites with other organelles. Impaired peroxisomal metabolism has been associated with beta-cell apoptosis and impaired insulin secretion. How peroxisomes contribute to insulin and neuropeptide secretion is unknown. Here we demonstrate that peroxisomes interact with the Golgi apparatus inDrosophilainsulin-producing cells. Secretion of insulin-like peptide 2 is cell-intrinsically impaired in mutants lacking the peroxisome assembly factor Pex19. Loss of peroxisomes shifts the profile of sphingolipids towards longer sphingoid bases and leads to accumulation of sphingolipids in the Golgi. We show that peroxisomes dynamically interact with the Golgi in insulin-producing cells and that Pex19 directly contributes to peroxisome-Golgi interaction via the fatty acyl-CoA reductase FAR2/waterproof in the peroxisomal membrane. We propose that this peroxisome-Pex19-Golgi axis is required to adjust Golgi membranes upon starvation by withdrawing lipids with longer side chains, thereby optimizing Golgi membrane flexibility for dense-core vesicle secretion upon refeeding. 

ABSTRACT Insects use walking behavior in a large number of contexts, such as exploration, foraging, escape and pursuit, or migration. A lot is known about how nervous systems produce this behavior in general and also how certain parameters vary with regard to walking direction or speed, for instance. An aspect that has not received much attention is whether and how walking behavior varies across individuals of a particular species. To address this, we created a large corpus of kinematic walking data of many individuals of the fruit fly Drosophila. We only selected instances of straight walking in a narrow range of walking speeds to minimize the influence of high-level parameters, such as turning and walking speed, aiming to uncover more subtle aspects of variability. Using high-speed videography and automated annotation, we captured the positions of the six leg tips for thousands of steps and used principal components analysis to characterize the postural space individuals used during walking. Our analysis shows that the largest part of walking kinematics can be described by five principal components (PCs). Separation of these five PCs into a 2D and a 3D subspace divided the description of walking behavior into invariant features shared across individuals and features that relate to the specifics of individuals; the latter features can be regarded as idiosyncrasies. We also demonstrate that this approach can detect the effects of experimental interventions in an unbiased manner and that general aspects of individuality, such as the individual walking posture, can be described. 

Abstract When locomoting bipedally at higher speeds, macaques preferred unilateral skipping (galloping). The same skipping pattern was maintained while hurdling across two low obstacles at the distance of a stride within our experimental track. The present study investigated leg and trunk joint rotations and leg joint moments, with the aim of clarifying the differential leg and trunk operation during skipping in bipedal macaques. Especially at the hip, the range of joint rotation and extension at lift off was larger in the leading than in the trailing leg. The flexing knee absorbed energy and the extending ankle generated work during each step. The trunk showed only minor deviations from symmetry. Hurdling amplified the differences and notably resulted in a quasi‐elastic use of the leading knee and in an asymmetric operation of the trunk. 

Abstract 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 leg’s 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 robot’s dynamics fit those modeled for the fly. We validate the robot’s 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. 

Abstract Studying the nervous system underlying animal motor control can shed light on how animals can adapt flexibly to a changing environment. We focus on the neural basis of feeding control inAplysia californica. Using the Synthetic Nervous System framework, we developed a model ofAplysiafeeding neural circuitry that balances neurophysiological plausibility and computational complexity. The circuitry includes neurons, synapses, and feedback pathways identified in existing literature. We organized the neurons into three layers and five subnetworks according to their functional roles. Simulation results demonstrate that the circuitry model can capture the intrinsic dynamics at neuronal and network levels. When combined with a simplified peripheral biomechanical model, it is sufficient to mediate three animal-like feeding behaviors (biting, swallowing, and rejection). The kinematic, dynamic, and neural responses of the model also share similar features with animal data. These results emphasize the functional roles of sensory feedback during feeding. 

Abstract The coordination of complex behavior requires knowledge of both neural dynamics and the mechanics of the periphery. The feeding system ofAplysia californicais an excellent model for investigating questions in soft body systems’ neuromechanics because of its experimental tractability. Prior work has attempted to elucidate the mechanical properties of the periphery by using a Hill-type muscle model to characterize the force generation capabilities of the key protractor muscle responsible for movingAplysia’s grasper anteriorly, the I2 muscle. However, the I1/I3 muscle, which is the main driver of retractions ofAplysia’s grasper, has not been characterized. Because of the importance of the musculature’s properties in generating functional behavior, understanding the properties of muscles like the I1/I3 complex may help to create more realistic simulations of the feeding behavior ofAplysia, which can aid in greater understanding of the neuromechanics of soft-bodied systems. To bridge this gap, in this work, the I1/I3 muscle complex was characterized using force-frequency, length-tension, and force-velocity experiments and showed that a Hill-type model can accurately predict its force-generation properties. Furthermore, the muscle’s peak isometric force and stiffness were found to exceed those of the I2 muscle, and these results were analyzed in the context of prior studies on the I1/I3 complex’s kinematics in vivo. 

Abstract During walking, sensory information is measured and monitored by sensory organs that can be found on and within various limb segments. Strain can be monitored by insect load sensors, campaniform sensilla (CS), which have components embedded within the exoskeleton. CS vary in eccentricity, size, and orientation, which can affect their sensitivity to specific strains. Directly investigating the mechanical interfaces that these sensors utilize to encode changes in load bears various obstacles, such as modeling of viscoelastic properties. To circumvent the difficulties of modeling and performing biological experiments in small insects, we developed 3-dimensional printed resin models based on high-resolution imaging of CS. Through the utilization of strain gauges and a motorized tensile tester, physiologically plausible strain can be mimicked while investigating the compression and tension forces that CS experience; here, this was performed for a field of femoral CS inDrosophila melanogaster. Different loading scenarios differentially affected CS compression and the likely neuronal activity of these sensors and elucidate population coding of stresses acting on the cuticle. 

ABSTRACT Macaques trained to perform bipedally used running gaits across a wide range of speeds. At higher speeds they preferred unilateral skipping (galloping). The same asymmetric stepping pattern was used while hurdling across two low obstacles placed at the distance of a stride within our experimental track. In bipedal macaques during skipping, we expected a differential use of the trailing and leading legs. The present study investigated global properties of the effective and virtual leg, the location of the virtual pivot point (VPP), and the energetics of the center of mass (CoM), with the aim of clarifying the differential leg operation during skipping in bipedal macaques. When skipping, macaques displayed minor double support and aerial phases during one stride. Asymmetric leg use was indicated by differences in leg kinematics. Axial damping and tangential leg work did not influence the indifferent peak ground reaction forces and impulses, but resulted in a lift of the CoM during contact of the leading leg. The aerial phase was largely due to the use of the double support. Hurdling amplified the differential leg operation. Here, higher ground reaction forces combined with increased double support provided the vertical impulse to overcome the hurdles. Following CoM dynamics during a stride, skipping and hurdling represented bouncing gaits. The elevation of the VPP of bipedal macaques resembled that of human walking and running in the trailing and leading phases, respectively. Because of anatomical restrictions, macaque unilateral skipping differs from that of humans, and may represent an intermediate gait between grounded and aerial running.