Emerging biological insights enabled by high-resolution 3D motion data: promises, perspectives and pitfalls

Through the looking glass: attempting to predict future opportunities and challenges in experimental biology

To celebrate its centenary year, Journal of Experimental Biology (JEB) commissioned a collection of articles examining the past, present and future of experimental biology. This Commentary closes the collection by considering the important research opportunities and challenges that await us in the future. We expect that researchers will harness the power of technological advances, such as '-omics' and gene editing, to probe resistance and resilience to environmental change as well as other organismal responses. The capacity to handle large data sets will allow high-resolution data to be collected for individual animals and to understand population, species and community responses. The availability of large data sets will also place greater emphasis on approaches such as modeling and simulations. Finally, the increasing sophistication of biologgers will allow more comprehensive data to be collected for individual animals in the wild. Collectively, these approaches will provide an unprecedented understanding of 'how animals work' as well as keys to safeguarding animals at a time when anthropogenic activities are degrading the natural environment.

Characterizing tongue deformations during mastication using changes in planar components of three-dimensional angles

Understanding of tongue deformations during mammalian mastication is limited, but has benefited from recent developments in multiplanar imaging technology. Here, we demonstrate how a standardized radiopaque marker implant configuration and biplanar fluoroscopy can quantify three-dimensional shape changes during chewing in pigs. Transverse and sagittal components of the three-dimensional angle between markers enable characterizing deformations in anatomically relevant directions. The transverse component illustrates bending to the left or to the right, which can occur symmetrically or asymmetrically, the latter sometimes indicating regional widening. The sagittal component reflects 'arching' or convex deformations in the dorsoventral dimension symmetrically or asymmetrically, the latter characteristic of twisting. Trends are detected in both the transverse and sagittal planes, and combinations thereof, to modify tongue shape in complex deformations. Both the transverse and sagittal components were also measured at key jaw and tongue positions, demonstrating variability particularly with respect to maximum and minimum gape. This highlights the fact that unlike tongue position, tongue deformations are more independent of jaw position, likely in response to the ever-changing bolus shape and position. From a methodological perspective, our study showcases advantages of a repeatable three-marker implant configuration suitable for animals of different sizes and highlights considerations for different implant patterns. This article is part of the theme issue 'Food processing and nutritional assimilation in animals'.

A hull reconstruction-reprojection method for pose estimation of free-flying fruit flies

Understanding the mechanisms of insect flight requires high-quality data of free-flight kinematics, e.g. for comparative studies or genetic screens. Although recent improvements in high-speed videography allow us to acquire large amounts of free-flight data, a significant bottleneck is automatically extracting accurate body and wing kinematics. Here, we present an experimental system and a hull reconstruction-reprojection algorithm for measuring the flight kinematics of fruit flies. The experimental system can automatically record hundreds of flight events per day. Our algorithm resolves a significant portion of the occlusions in this system by a reconstruction-reprojection scheme that integrates information from all cameras. Wing and body kinematics, including wing deformation, are then extracted from the hulls of the wing boundaries and body. This model-free method is fully automatic, accurate and open source, and can be readily adjusted for different camera configurations or insect species.

Recovery of dynamical similarity from lossy representations of collective behavior of midge swarms

Understanding emergent collective phenomena in biological systems is a complex challenge due to the high dimensionality of state variables and the inability to directly probe agent-based interaction rules. Therefore, if one wants to model a system for which the underpinnings of the collective process are unknown, common approaches such as using mathematical models to validate experimental data may be misguided. Even more so, if one lacks the ability to experimentally measure all the salient state variables that drive the collective phenomena, a modeling approach may not correctly capture the behavior. This problem motivates the need for model-free methods to characterize or classify observed behavior to glean biological insights for meaningful models. Furthermore, such methods must be robust to low dimensional or lossy data, which are often the only feasible measurements for large collectives. In this paper, we show that a model-free and unsupervised clustering of high dimensional swarming behavior in midges (Chironomus riparius), based on dynamical similarity, can be performed using only two-dimensional video data where the animals are not individually tracked. Moreover, the results of the classification are physically meaningful. This work demonstrates that low dimensional video data of collective motion experiments can be equivalently characterized, which has the potential for wide applications to data describing animal group motion acquired in both the laboratory and the field.