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Tracking mosquitoes in real time, as opposed to recording video files and performing the tracking step later, is useful for two reasons. The first is efficiency. Real-time tracking requires less storage because video images do not need to be saved and followed by a tracking step. The second is that tracking data can be used to interact with the animal in some way, such as triggering the approach of a looming object. In this protocol, we discuss the use of Braid, free software for performing real-time, multicamera, multianimal tracking. We describe a setup with four cameras capable of tracking the three-dimensional (3D) position of mosquitoes at 100 frames per second in a volume of 30 cm × 30 cm × 60 cm with millimeter accuracy. The specific hardware configuration is flexible and can be substituted using different or additional components to adjust the tracking parameters as needed.

Flying insects have evolved the ability to evade looming objects, such as predators and swatting hands. This is particularly relevant for blood-feeding insects, such as mosquitoes that routinely need to evade the defensive actions of their blood hosts. To minimize the chance of being swatted, a mosquito can use two distinct strategies—continuously exhibiting an unpredictable flight path or maximizing its escape maneuverability. We studied how baseline flight unpredictability and escape maneuverability affect the escape performance of day-active and night-active mosquitoes (Aedes aegypti and Anopheles coluzzii, respectively). We used a multi-camera high-speed videography system to track how freely flying mosquitoes respond to an event-triggered rapidly approaching mechanical swatter, in four different light conditions ranging from pitch darkness to overcast daylight. Results show that both species exhibit enhanced escape performance in their natural blood-feeding light condition (daylight for Aedes and dark for Anopheles). To achieve this, they show strikingly different behaviors. The enhanced escape performance of Anopheles at night is explained by their increased baseline unpredictable erratic flight behavior, whereas the increased escape performance of Aedes in overcast daylight is due to their enhanced escape maneuvers. This shows that both day and night-active mosquitoes modify their flight behavior in response to light intensity such that their escape performance is maximum in their natural blood-feeding light conditions, when these defensive actions by their blood hosts occur most. Because Aedes and Anopheles mosquitoes are major vectors of several deadly human diseases, this knowledge can be used to optimize vector control methods for these specific species.

RT-qPCR-based diagnostic tests play important roles in combating virus-caused pandemics such as Covid-19. However, their dependence on sophisticated equipment and the associated costs often limits their widespread use. Loop-mediated isothermal amplification after reverse transcription (RT-LAMP) is an alternative nucleic acid detection method that overcomes these limitations. Here, we present a rapid, robust, and sensitive RT-LAMP-based SARS-CoV-2 detection assay. Our 40-min procedure bypasses the RNA isolation step, is insensitive to carryover contamination, and uses a colorimetric readout that enables robust SARS-CoV-2 detection from various sample types. Based on this assay, we have increased sensitivity and scalability by adding a nucleic acid enrichment step (Bead-LAMP), developed a version for home testing (HomeDip-LAMP), and identified open-source RT-LAMP enzymes that can be produced in any molecular biology laboratory. On a dedicated website, rtlamp.org (DOI: 10.5281/zenodo.6033689), we provide detailed protocols and videos. Our optimized, general-purpose RT-LAMP assay is an important step toward population-scale SARS-CoV-2 testing.

We consider the problem of purely visual pose stabilization (also known as servoing) of a second-order rigid-body system with six degrees of freedom: how to choose forces and torques, based on the current view and a memorized goal image, to steer the pose towards a desired one. Emphasis has been given to the bio-plausibility of the computation, in the sense that the control laws could be in principle implemented on the neural substrate of simple insects. We show that stabilizing laws can be realized by bilinear/quadratic operations on the visual input. This particular computational structure has several numerically favorable characteristics (sparse, local, and parallel), and thus permits an efficient engineering implementation. We show results of the control law tested on an indoor helicopter platform.

The paper describes an indoor helicopter testbed that allows implementing and testing of bio-inspired control algorithms developed from scientific studies on insects. The helicopter receives and is controlled by simulated sensory inputs (e.g. visual stimuli) generated in a virtual 3D environment, where the connection between the physical world and the virtual world is provided by a video camera tracking system. The virtual environment is specified by a 3D computer model and is relatively simple to modify compared to realistic scenes. This enables rapid examinations of whether a certain control law is robust under various environments, an important feature of insect behavior. As a first attempt, flight stabilization and yaw rate control near hover are demonstrated, utilizing biologically realistic visual stimuli as in the fruit fly Drosophila melanogaster.

How do animals regulate self-movement despite large variation in the luminance contrast of the environment? Insects are capable of regulating flight speed based on the velocity of image motion, but the mechanisms for this are unclear. The Hassenstein–Reichardt correlator model and elaborations can accurately predict responses of motion detecting neurons under many conditions but fail to explain the apparent lack of spatial pattern and contrast dependence observed in freely flying bees and flies. To investigate this apparent discrepancy, we recorded intracellularly from horizontal-sensitive (HS) motion detecting neurons in the hoverfly while displaying moving images of natural environments. Contrary to results obtained with grating patterns, we show these neurons encode the velocity of natural images largely independently of the particular image used despite a threefold range of contrast. This invariance in response to natural images is observed in both strongly and minimally motion-adapted neurons but is sensitive to artificial manipulations in contrast. Current models of these cells account for some, but not all, of the observed insensitivity to image contrast. We conclude that fly visual processing may be matched to commonalities between natural scenes, enabling accurate estimates of velocity largely independent of the particular scene.

We use a biologically motivated model of the Drosophila's flight mechanics and sensor processing to design a feedback control scheme to regulate forward flight. The model used for insect flight is the grand unified fly (GUF) [3] simulation consisting of rigid body kinematics, aerodynamic forces and moments, sensory systems, and a 3D environment model. We seek to design a control algorithm that will convert the sensory signals into proper wing beat commands to regulate forward flight. Modulating the wing beat frequency and mean stroke angle produces changes in the flight envelope. The sensory signals consist of estimates of rotational velocity from the haltere organs and translational velocity estimates from visual elementary motion detectors (EMD's) and matched retinal velocity filters. The controller is designed based on a longitudinal model of the flight dynamics. Feedforward commands are generated based on a desired forward velocity. The dynamics are linearized around this operating point and a feedback controller designed to correct deviations from the operating point. The control algorithm is implemented in the GUF simulator and achieves the desired tracking of the forward reference velocities and exhibits biologically realistic responses.

Eyes of the hoverfly Eristalis tenax are sexually dimorphic such that males have a fronto-dorsal region of large facets. In contrast to other large flies in which large facets are associated with a decreased interommatidial angle to form a dorsal `acute zone' of increased spatial resolution, we show that a dorsal region of large facets in males appears to form a `bright zone' of increased light capture without substantially increased spatial resolution. Theoretically, more light allows for increased performance in tasks such as motion detection. To determine the effect of the bright zone on motion detection, local properties of wide field motion detecting neurons were investigated using localized sinusoidal gratings. The pattern of local preferred directions of one class of these cells, the HS cells, in Eristalis is similar to that reported for the blowfly Calliphora. The bright zone seems to contribute to local contrast sensitivity; high contrast sensitivity exists in portions of the receptive field served by large diameter facet lenses of males and is not observed in females. Finally, temporal frequency tuning is also significantly faster in this frontal portion of the world, particularly in males, where it overcompensates for the higher spatial-frequency tuning and shifts the predicted local velocity optimum to higher speeds. These results indicate that increased retinal illuminance due to the bright zone of males is used to enhance contrast sensitivity and speed motion detector responses. Additionally, local neural properties vary across the visual world in a way not expected if HS cells serve purely as matched filters to measure yaw-induced visual motion.