Machine learning reveals the control mechanics of an insect wing hinge.

Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolution of active flight. Unlike pterosaurs, birds and bats, the wings of insects did not evolve from legs1, but are novel structures that are attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings2. The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the three-dimensional motion of the wings with high-speed cameras. Using machine learning, we created a convolutional neural network3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation incorporating our hinge model generates flight manoeuvres that are remarkably similar to those of free-flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Machine learning reveals the control mechanics of an insect wing hinge.

Insects constitute the most species-rich radiation of metazoa, a success due to the evolution of active flight. Unlike pterosaurs, birds, and bats, the wings of insects did not evolve from legs 1 , but are novel structures attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings 2 . The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here, we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the 3D motion of the wings with high-speed cameras. Using machine learning approaches, we created a convolutional neural network 3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder 4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation that incorporates our model of the hinge generates flight maneuvers that are remarkably similar to those of free flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Nonlinear ultrasound imaging of nanoscale acoustic biomolecules.

Ultrasound imaging is widely used to probe the mechanical structure of tissues and visualize blood flow. However, the ability of ultrasound to observe specific molecular and cellular signals is limited. Recently, a unique class of gas-filled protein nanostructures called gas vesicles (GVs) was introduced as nanoscale (∼250 nm) contrast agents for ultrasound, accompanied by the possibilities of genetic engineering, imaging of targets outside the vasculature and monitoring of cellular signals such as gene expression. These possibilities would be aided by methods to discriminate GV-generated ultrasound signals from anatomical background. Here, we show that the nonlinear response of engineered GVs to acoustic pressure enables selective imaging of these nanostructures using a tailored amplitude modulation strategy. Finite element modeling predicted a strongly nonlinear mechanical deformation and acoustic response to ultrasound in engineered GVs. This response was confirmed with ultrasound measurements in the range of 10 to 25 MHz. An amplitude modulation pulse sequence based on this nonlinear response allows engineered GVs to be distinguished from linear scatterers and other GV types with a contrast ratio greater than 11.5 dB. We demonstrate the effectiveness of this nonlinear imaging strategy in vitro, in cellulo, and in vivo.

Acoustic Behavior of Halobacterium salinarum Gas Vesicles in the High-Frequency Range: Experiments and Modeling.

Gas vesicles (GVs) are a new and unique class of biologically derived ultrasound contrast agents with sub-micron size whose acoustic properties have not been fully elucidated. In this study, we investigated the acoustic collapse pressure and behavior of Halobacterium salinarum gas vesicles at transmit center frequencies ranging from 12.5 to 27.5 MHz. The acoustic collapse pressure was found to be above 550 kPa at all frequencies, nine-fold higher than the critical pressure observed under hydrostatic conditions. We illustrate that gas vesicles behave non-linearly when exposed to ultrasound at incident pressure ranging from 160 kPa to the collapse pressure and generate second harmonic amplitudes of -2 to -6 dB below the fundamental in media with viscosities ranging from 0.89 to 8 mPa·s. Simulations performed using a Rayleigh-Plesset-type model accounting for buckling and a dynamic finite-element analysis suggest that buckling is the mechanism behind the generation of harmonics. We found good agreement between the level of second harmonic relative to the fundamental measured at 20 MHz and the Rayleigh-Plesset model predictions. Finite-element simulations extended these findings to a non-spherical geometry, confirmed that the acoustic buckling pressure corresponds to the critical pressure under hydrostatic conditions and support the hypothesis of limited gas flow across the GV shell during the compression phase in the frequency range investigated. From simulations, estimates of GV bandwidth-limited scattering indicate that a single GV has a scattering cross section comparable to that of a red blood cell. These findings will inform the development of GV-based contrast agents and pulse sequences to optimize their detection with ultrasound.

Flies compensate for unilateral wing damage through modular adjustments of wing and body kinematics.

Using high-speed videography, we investigated how fruit flies compensate for unilateral wing damage, in which loss of area on one wing compromises both weight support and roll torque equilibrium. Our results show that flies control for unilateral damage by rolling their body towards the damaged wing and by adjusting the kinematics of both the intact and damaged wings. To compensate for the reduction in vertical lift force due to damage, flies elevate wingbeat frequency. Because this rise in frequency increases the flapping velocity of both wings, it has the undesired consequence of further increasing roll torque. To compensate for this effect, flies increase the stroke amplitude and advance the timing of pronation and supination of the damaged wing, while making the opposite adjustments on the intact wing. The resulting increase in force on the damaged wing and decrease in force on the intact wing function to maintain zero net roll torque. However, the bilaterally asymmetrical pattern of wing motion generates a finite lateral force, which flies balance by maintaining a constant body roll angle. Based on these results and additional experiments using a dynamically scaled robotic fly, we propose a simple bioinspired control algorithm for asymmetric wing damage.

Flies evade looming targets by executing rapid visually directed banked turns.

Avoiding predators is an essential behavior in which animals must quickly transform sensory cues into evasive actions. Sensory reflexes are particularly fast in flying insects such as flies, but the means by which they evade aerial predators is not known. Using high-speed videography and automated tracking of flies in combination with aerodynamic measurements on flapping robots, we show that flying flies react to looming stimuli with directed banked turns. The maneuver consists of a rapid body rotation followed immediately by an active counter-rotation and is enacted by remarkably subtle changes in wing motion. These evasive maneuvers of flies are substantially faster than steering maneuvers measured previously and indicate the existence of sensory-motor circuitry that can reorient the fly's flight path within a few wingbeats.