@article {69484, title = {Mechanosensory representation of wing deformations}, journal = {bioRxiv}, year = {2024}, month = {2024 Jun 02}, abstract = {

Efficient representation of structural deformations is crucial for monitoring the instantaneous state of biological structures. Insects{\textquoteright} ability to encode wing deformations during flight demonstrates a general morphological computing principle applicable across sensory systems in nature as well as engineered systems. To characterize how relevant features are encoded, we measured and modelled displacement and strain across dragonfly wing surfaces in tethered and free flight. Functional interpretations were supported by neuroanatomical maps, and ablation and perturbation experiments. We find that signal redundancy is reduced by non-random sensor distributions and that morphology limits the stimulus space such that sensory systems can monitor natural states with few sensors. Deviations from the natural states are detected by a flexible population of additional sensors with many distinguishable activation patterns.

}, doi = {10.1101/2024.06.02.596338}, url = {https://www.biorxiv.org/content/early/2024/06/02/2024.06.02.596338}, author = {Yarger, Alexandra M and Maeda, Masateru and Siwanowicz, Igor and Kajiyama, Haruhiro and Walker, Simon M and Bomphrey, Richard J and Lin, Huai-Ti} } @article {69667, title = {Wireless recordings from dragonfly target detecting neurons during prey interception flight}, journal = {bioRxiv}, year = {2024}, month = {2024 Nov 13}, abstract = {

Target interception is a complex sensorimotor behavior which requires fine tuning of the sensory system and its strategic coordination with the motor system. Despite various theories about how interception is achieved, its neural implementation remains unknown. We have previously shown that hunting dragonflies employ a balance of reactive and predictive control to intercept prey, using sophisticated model driven predictions to account for expected prey and self-motion. Here we explore the neural substrate of this interception system by investigating a well-known class of target-selective descending neurons (TSDNs). These cells have long been speculated to underlie interception steering but have never been studied in a behaving dragonfly. We combined detailed neuroanatomy, high-precision kinematics data and state-of-the-art neural telemetry to measure TSDN activity during flight. We found that TSDNs are exquisitely tuned to prey angular size and speed at ethological distances, and that they synapse directly onto neck and wing motoneurons in an unusual manner. However, we found that TSDNs were only weakly active during flight and are thus unlikely to provide the primary steering signal. Instead, they appear to drive the foveating head movements that stabilize prey on the eye before and likely throughout the interception flight. We suggest the TSDN population implements the reactive portion of the interception steering control system, coordinating head and wing movements to compensate for unexpected prey motion.

}, doi = {10.1101/2024.11.12.622977}, url = {https://doi.org/10.1101/2024.11.12.622977}, author = {Lin, Huai-Ti and Siwanowicz, Igor and Leonardo, Anthony} } @article {68022, title = {Systematic characterization of wing mechanosensors that monitor airflow and wing deformations.}, journal = {iScience}, volume = {25}, year = {2022}, month = {2022 Apr 15}, pages = {104150}, abstract = {

Animal wings deform during flight in ways that can enhance lift, facilitate flight control, and mitigate damage. Monitoring the structural and aerodynamic state of the wing is challenging because deformations are passive, and the flow fields are unsteady; it requires distributed mechanosensors that respond to local airflow and strain on the wing. Without a complete map of the sensor arrays, it is impossible to model control strategies underpinned by them. Here, we present the first systematic characterization of mechanosensors on the dragonfly{\textquoteright}s wings: morphology, distribution, and wiring. By combining a cross-species survey of sensor distribution with quantitative neuroanatomy and a high-fidelity finite element analysis, we show that the mechanosensors are well placed to perceive features of the wing dynamics relevant to flight. This work describes the wing sensory apparatus in its entirety and advances our understanding of the sensorimotor loop that facilitates exquisite flight control in animals with highly deformable wings.

}, issn = {2589-0042}, doi = {10.1016/j.isci.2022.104150}, author = {Fabian, Joseph and Siwanowicz, Igor and Uhrhan, Myriam and Maeda, Masateru and Bomphrey, Richard J and Lin, Huai-Ti} } @article {48374, title = {Heuristic rules underlying dragonfly prey selection and interception.}, journal = {Current Biology : CB}, volume = {27}, year = {2017}, month = {2017 Mar 28}, pages = {1124-37}, abstract = {

Animals use rules to initiate behaviors. Such rules are\ often described as triggers that determine when behavior begins. However, although less explored, these selection rules are also an opportunity to establish sensorimotor constraints that influence how the behavior ends. These constraints may be particularly significant in influencing success in prey capture. Here we explore this in dragonfly prey interception. We found that in the moments leading up to takeoff, perched dragonflies employ a series of sensorimotor rules that determine the time of takeoff and increase the probability of successful capture. First, the dragonfly makes a head saccade followed by smooth pursuit movements to orient its\ direction-of-gaze at potential prey. Second, the dragonfly assesses whether the prey{\textquoteright}s angular size and speed co-vary within a privileged range. Finally, the dragonfly times the moment of its takeoff to a prediction of when the prey will cross the zenith. Each of these processes serves a purpose. The angular size-speed criteria biases interception flights to catchable prey, while the head movements and the predictive takeoff ensure flights begin with the prey visually fixated and directly overhead-the key parameters that underlie interception steering. Prey that do not elicit takeoff generally fail at least one of the criterion, and the loss of prey fixation or overhead positioning during flight is strongly correlated with terminated flights. Thus from an abundance of potential targets, the dragonfly selects a stereotyped set of takeoff conditions based on the prey and body states most likely to end in successful capture.

}, issn = {1879-0445}, doi = {10.1016/j.cub.2017.03.010}, author = {Lin, Huai-Ti and Leonardo, Anthony} } @article {47768, title = {Flight of the dragonflies and damselflies.}, journal = {Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences}, volume = {371}, year = {2016}, month = {2016 Sep 26}, abstract = {

This work is a synthesis of our current understanding of the mechanics, aerodynamics and visually mediated control of dragonfly and damselfly flight, with the addition of new experimental and computational data in several key areas. These are: the diversity of dragonfly wing morphologies, the aerodynamics of gliding flight, force generation in flapping flight, aerodynamic efficiency, comparative flight performance and pursuit strategies during predatory and territorial flights. New data are set in context by brief reviews covering anatomy at several scales, insect aerodynamics, neuromechanics and behaviour. We achieve a new perspective by means of a diverse range of techniques, including laser-line mapping of wing topographies, computational fluid dynamics simulations of finely detailed wing geometries, quantitative imaging using particle image velocimetry of on-wing and wake flow patterns, classical aerodynamic theory, photography in the field, infrared motion capture and multi-camera optical tracking of free flight trajectories in laboratory environments. Our comprehensive approach enables a novel synthesis of datasets and subfields that integrates many aspects of flight from the neurobiology of the compound eye, through the aeromechanical interface with the surrounding fluid, to flight performance under cruising and higher-energy behavioural modes.This article is part of the themed issue {\textquoteright}Moving in a moving medium: new perspectives on flight{\textquoteright}.

}, issn = {1471-2970}, doi = {10.1098/rstb.2015.0389}, author = {Bomphrey, Richard J and Nakata, Toshiyuki and Henningsson, Per and Lin, Huai-Ti} } @article {45700, title = {Bone-free: soft mechanics for adaptive locomotion.}, journal = {Integrative and Comparative Biology}, volume = {54}, year = {2014}, month = {2014 Dec}, pages = {1122-35}, abstract = {

Muscular hydrostats (such as mollusks), and fluid-filled animals (such as annelids), can exploit their constant-volume tissues to transfer forces and displacements in predictable ways, much as articulated animals use hinges and levers. Although larval insects contain pressurized fluids, they also have internal air tubes that are compressible and, as a result, they have more uncontrolled degrees of freedom. Therefore, the mechanisms by which larval insects control their movements are expected to reveal useful strategies for designing soft biomimetic robots. Using caterpillars as a tractable model system, it is now possible to identify the biomechanical and neural strategies for controlling movements in such highly deformable animals. For example, the tobacco hornworm, Manduca sexta, can stiffen its body by increasing muscular tension (and therefore body pressure) but the internal cavity (hemocoel) is not iso-barometric, nor is pressure used to directly control the movements of its limbs. Instead, fluid and tissues flow within the hemocoel and the body is soft and flexible to conform to the substrate. Even the gut contributes to the biomechanics of locomotion; it is decoupled from the movements of the body wall and slides forward within the body cavity at the start of each step. During crawling the body is kept in tension for part of the stride and compressive forces are exerted on the substrate along the axis of the caterpillar, thereby using the environment as a skeleton. The timing of muscular activity suggests that crawling is coordinated by proleg-retractor motoneurons and that the large segmental muscles produce anterograde waves of lifting that do not require precise timing. This strategy produces a robust form of locomotion in which the kinematics changes little with orientation. In different species of caterpillar, the presence of prolegs on particular body segments is related to alternative kinematics such as "inching." This suggests a mechanism for the evolution of different gaits through changes in the usage of prolegs, rather than, through extensive alterations in the motor program controlling the body wall. Some of these findings are being used to design and test novel control-strategies for highly deformable robots. These "softworm" devices are providing new insights into the challenges faced by any soft animal navigating in a terrestrial environment.

}, issn = {1557-7023}, doi = {10.1093/icb/icu076}, author = {Trimmer, B A and Lin, Huai-Ti} } @article {45720, title = {Internal models direct dragonfly interception steering.}, journal = {Nature}, year = {2014}, month = {2014 Dec 10}, abstract = {

Sensorimotor control in vertebrates relies on internal models. When extending an arm to reach for an object, the brain uses predictive models of both limb dynamics and target properties. Whether invertebrates use such models remains unclear. Here we examine to what extent prey interception by dragonflies (Plathemis lydia), a behaviour analogous to targeted reaching, requires internal models. By simultaneously tracking the position and orientation of a dragonfly{\textquoteright}s head and body during flight, we provide evidence that interception steering is driven by forward and inverse models of dragonfly body dynamics and by models of prey motion. Predictive rotations of the dragonfly{\textquoteright}s head continuously track the prey{\textquoteright}s angular position. The head-body angles established by prey tracking appear to guide systematic rotations of the dragonfly{\textquoteright}s body to align it with the prey{\textquoteright}s flight path. Model-driven control thus underlies the bulk of interception steering manoeuvres, while vision is used for reactions to unexpected prey movements. These findings illuminate the computational sophistication with which insects construct behaviour.

}, issn = {1476-4687}, doi = {10.1038/nature14045}, author = {Mischiati, Matteo and Lin, Huai-Ti and Herold, Paul and Imler, Elliot and Olberg, Robert and Leonardo, Anthony} }