Microsaccadic sampling of moving image information provides Drosophila hyperacute vision

A recurrent neural circuit in Drosophila deblurs visual inputs

A critical goal of vision is to detect changes in light intensity, even when these changes are blurred by the spatial resolution of the eye and the motion of the animal. Here we describe a recurrent neural circuit in Drosophila that compensates for blur and thereby selectively enhances the perceived contrast of moving edges. Using in vivo , two-photon voltage imaging, we measured the temporal response properties of L1 and L2, two cell types that receive direct synaptic input from photoreceptors. These neurons have biphasic responses to brief flashes of light, a hallmark of cells that encode changes in stimulus intensity. However, the second phase was often much larger than the first, creating an unusual temporal filter. Genetic dissection revealed that recurrent neural circuitry strongly shapes the second phase of the response, informing the structure of a dynamical model. By applying this model to moving natural images, we demonstrate that rather than veridically representing stimulus changes, this temporal processing strategy systematically enhances them, amplifying and sharpening responses. Comparing the measured responses of L2 to model predictions across both artificial and natural stimuli revealed that L2 tunes its properties as the model predicts in order to deblur images. Since this strategy is tunable to behavioral context, generalizable to any time-varying sensory input, and implementable with a common circuit motif, we propose that it could be broadly used to selectively enhance sharp and salient changes.

Contiguity in perception: origins in cellular associative computations

Our brains are good at detecting and learning associative structures; according to some linguistic theories, this capacity even constitutes a prerequisite for the development of syntax and compositionality in language and verbalized thought. I will argue that the search for associative motifs in input patterns is an evolutionary old brain function that enables contiguity in sensory perception and orientation in time and space. It has its origins in an elementary material property of cells that is particularly evident at chemical synapses: input-assigned calcium influx that activates calcium sensor proteins involved in memory storage. This machinery for the detection and learning of associative motifs generates knowledge about input relationships and integrates this knowledge into existing networks through updates in connectivity patterns.

Direct comparison reveals algorithmic similarities in fly and mouse visual motion detection

Evolution has equipped vertebrates and invertebrates with neural circuits that selectively encode visual motion. While similarities in the computations performed by these circuits in mouse and fruit fly have been noted, direct experimental comparisons have been lacking. Because molecular mechanisms and neuronal morphology in the two species are distinct, we directly compared motion encoding in these two species at the algorithmic level, using matched stimuli and focusing on a pair of analogous neurons, the mouse ON starburst amacrine cell (ON SAC) and Drosophila T4 neurons. We find that the cells share similar spatiotemporal receptive field structures, sensitivity to spatiotemporal correlations, and tuning to sinusoidal drifting gratings, but differ in their responses to apparent motion stimuli. Both neuron types showed a response to summed sinusoids that deviates from models for motion processing in these cells, underscoring the similarities in their processing and identifying response features that remain to be explained.

Long-timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Long timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied D. melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such "anti-directional turning" is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Measuring compound eye optics with microscope and microCT images

With a great variety of shapes and sizes, compound eye morphologies give insight into visual ecology, development, and evolution, and inspire novel engineering. In contrast to our own camera-type eyes, compound eyes reveal their resolution, sensitivity, and field of view externally, provided they have spherical curvature and orthogonal ommatidia. Non-spherical compound eyes with skewed ommatidia require measuring internal structures, such as with MicroCT (µCT). Thus far, there is no efficient tool to characterize compound eye optics, from either 2D or 3D data, automatically. Here we present two open-source programs: (1) the ommatidia detecting algorithm (ODA), which measures ommatidia count and diameter in 2D images, and (2) a µCT pipeline (ODA-3D), which calculates anatomical acuity, sensitivity, and field of view across the eye by applying the ODA to 3D data. We validate these algorithms on images, images of replicas, and µCT eye scans from ants, fruit flies, moths, and a bee.

Muscles that move the retina augment compound eye vision in Drosophila

Most animals have compound eyes, with tens to thousands of lenses attached rigidly to the exoskeleton. A natural assumption is that all of these species must resort to moving either their head or their body to actively change their visual input. However, classic anatomy has revealed that flies have muscles poised to move their retinas under the stable lenses of each compound eye1-3. Here we show that Drosophila use their retinal muscles to smoothly track visual motion, which helps to stabilize the retinal image, and also to perform small saccades when viewing a stationary scene. We show that when the retina moves, visual receptive fields shift accordingly, and that even the smallest retinal saccades activate visual neurons. Using a head-fixed behavioural paradigm, we find that Drosophila perform binocular, vergence movements of their retinas-which could enhance depth perception-when crossing gaps, and impairing the physiology of retinal motor neurons alters gap-crossing trajectories during free behaviour. That flies evolved an ability to actuate their retinas suggests that moving the eye independently of the head is broadly paramount for animals. The similarities of smooth and saccadic movements of the Drosophila retina and the vertebrate eye highlight a notable example of convergent evolution.

Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila

Natural vision is dynamic: as an animal moves, its visual input changes dramatically. How can the visual system reliably extract local features from an input dominated by self-generated signals? In Drosophila, diverse local visual features are represented by a group of projection neurons with distinct tuning properties. Here, we describe a connectome-based volumetric imaging strategy to measure visually evoked neural activity across this population. We show that local visual features are jointly represented across the population, and a shared gain factor improves trial-to-trial coding fidelity. A subset of these neurons, tuned to small objects, is modulated by two independent signals associated with self-movement, a motor-related signal, and a visual motion signal associated with rotation of the animal. These two inputs adjust the sensitivity of these feature detectors across the locomotor cycle, selectively reducing their gain during saccades and restoring it during intersaccadic intervals. This work reveals a strategy for reliable feature detection during locomotion.

Insect-inspired AI for autonomous robots

Autonomous robots are expected to perform a wide range of sophisticated tasks in complex, unknown environments. However, available onboard computing capabilities and algorithms represent a considerable obstacle to reaching higher levels of autonomy, especially as robots get smaller and the end of Moore's law approaches. Here, we argue that inspiration from insect intelligence is a promising alternative to classic methods in robotics for the artificial intelligence (AI) needed for the autonomy of small, mobile robots. The advantage of insect intelligence stems from its resource efficiency (or parsimony) especially in terms of power and mass. First, we discuss the main aspects of insect intelligence underlying this parsimony: embodiment, sensory-motor coordination, and swarming. Then, we take stock of where insect-inspired AI stands as an alternative to other approaches to important robotic tasks such as navigation and identify open challenges on the road to its more widespread adoption. Last, we reflect on the types of processors that are suitable for implementing insect-inspired AI, from more traditional ones such as microcontrollers and field-programmable gate arrays to unconventional neuromorphic processors. We argue that even for neuromorphic processors, one should not simply apply existing AI algorithms but exploit insights from natural insect intelligence to get maximally efficient AI for robot autonomy.

Binocular mirror-symmetric microsaccadic sampling enables Drosophila hyperacute 3D vision

To move efficiently, animals must continuously work out their x,y,z positions with respect to real-world objects, and many animals have a pair of eyes to achieve this. How photoreceptors actively sample the eyes’ optical image disparity is not understood because this fundamental information-limiting step has not been investigated in vivo over the eyes’ whole sampling matrix. This integrative multiscale study will advance our current understanding of stereopsis from static image disparity comparison to a morphodynamic active sampling theory. It shows how photomechanical photoreceptor microsaccades enable Drosophila superresolution three-dimensional vision and proposes neural computations for accurately predicting these flies’ depth-perception dynamics, limits, and visual behaviors.

Neural mechanisms behind stereopsis, which requires simultaneous disparity inputs from two eyes, have remained mysterious. Here we show how ultrafast mirror-symmetric photomechanical contractions in the frontal forward-facing left and right eye photoreceptors give Drosophila superresolution three-dimensional (3D) vision. By interlinking multiscale in vivo assays with multiscale simulations, we reveal how these photoreceptor microsaccades—by verging, diverging, and narrowing the eyes’ overlapping receptive fields—channel depth information, as phasic binocular image motion disparity signals in time. We further show how peripherally, outside stereopsis, microsaccadic sampling tracks a flying fly’s optic flow field to better resolve the world in motion. These results change our understanding of how insect compound eyes work and suggest a general dynamic stereo-information sampling strategy for animals, robots, and sensors.

High-speed imaging of light-induced photoreceptor microsaccades in compound eyes

Inside compound eyes, photoreceptors contract to light changes, sharpening retinal images of the moving world in time. Current methods to measure these so-called photoreceptor microsaccades in living insects are spatially limited and technically challenging. Here, we present goniometric high-speed deep pseudopupil (GHS-DPP) microscopy to assess how the rhabdomeric insect photoreceptors and their microsaccades are organised across the compound eyes. This method enables non-invasive rhabdomere orientation mapping, whilst their microsaccades can be locally light-activated, revealing the eyes' underlying active sampling motifs. By comparing the microsaccades in wild-type Drosophila's open rhabdom eyes to spam-mutant eyes, reverted to an ancestral fused rhabdom state, and honeybee's fused rhabdom eyes, we show how different eye types sample light information. These results show different ways compound eyes initiate the conversion of spatial light patterns in the environment into temporal neural signals and highlight how this active sampling can evolve with insects' visual needs.

Multiscale 'whole-cell' models to study neural information processing - New insights from fly photoreceptor studies

Understanding a neuron's input-output relationship is a longstanding challenge. Arguably, these signalling dynamics can be better understood if studied at three levels of analysis: computational, algorithmic and implementational (Marr, 1982). But it is difficult to integrate such analyses into a single platform that can realistically simulate neural information processing. Multiscale dynamical "whole-cell" modelling, a recent systems biology approach, makes this possible. Dynamical "whole-cell" models are computational models that aim to account for the integrated function of numerous genes or molecules to behave like virtual cells in silico. However, because constructing such models is laborious, only a couple of examples have emerged since the first one, built for Mycoplasma genitalium bacterium, was reported in 2012. Here, we review dynamic "whole-cell" neuron models for fly photoreceptors and how these have been used to study neural information processing. Specifically, we review how the models have helped uncover the mechanisms and evolutionary rules of quantal light information sampling and integration, which underlie light adaptation and further improve our understanding of insect vision.

Stark trade-offs and elegant solutions in arthropod visual systems

Vision is one of the most important senses for humans and animals alike. Diverse elegant specializations have evolved among insects and other arthropods in response to specific visual challenges and ecological needs. These specializations are the subject of this Review, and they are best understood in light of the physical limitations of vision. For example, to achieve high spatial resolution, fine sampling in different directions is necessary, as demonstrated by the well-studied large eyes of dragonflies. However, it has recently been shown that a comparatively tiny robber fly (Holcocephala) has similarly high visual resolution in the frontal visual field, despite their eyes being a fraction of the size of those of dragonflies. Other visual specializations in arthropods include the ability to discern colors, which relies on parallel inputs that are tuned to spectral content. Color vision is important for detection of objects such as mates, flowers and oviposition sites, and is particularly well developed in butterflies, stomatopods and jumping spiders. Analogous to color vision, the visual systems of many arthropods are specialized for the detection of polarized light, which in addition to communication with conspecifics, can be used for orientation and navigation. For vision in low light, optical superposition compound eyes perform particularly well. Other modifications to maximize photon capture involve large lenses, stout photoreceptors and, as has been suggested for nocturnal bees, the neural pooling of information. Extreme adaptations even allow insects to see colors at very low light levels or to navigate using the Milky Way.

Hybrid visual control in fly flight: insights into gaze shift via saccades

Flies fly by alternating between periods of fixation and body saccades, analogous to how our own eyes move. Gaze fixation via smooth movement in fly flight has been studied extensively, but comparatively less is known about the mechanism by which flies trigger and control body saccades to shift their gaze. Why do flies implement a hybrid fixate-and-saccade locomotion strategy? Here we review recent developments that provide new insights into this question. We focus on the interplay between smooth movement and saccades, the trigger classes of saccades, and the timeline of saccade execution. We emphasize recent mechanistic advances in Drosophila, where genetic tools have enabled cellular circuit analysis at an unprecedented level in a flying insect. In addition, we review trade-offs in behavioral paradigms used to study saccades. Throughout we highlight exciting avenues for future research in the control of fly flight.

Fractal Web Design of a Hemispherical Photodetector Array with Organic-Dye-Sensitized Graphene Hybrid Composites

The vision system of arthropods consists of a dense array of individual photodetecting elements across a curvilinear surface. This compound-eye architecture could be a useful model for optoelectronic sensing devices that require a large field of view and high sensitivity to motion. Strategies that aim to mimic the compound-eye architecture involve integrating photodetector pixels with a curved microlens, but their fabrication on a curvilinear surface is challenged by the use of standard microfabrication processes that are traditionally designed for planar, rigid substrates (e.g., Si wafers). Here, a fractal web design of a hemispherical photodetector array that contains an organic-dye-sensitized graphene hybrid composite is reported to serve as an effective photoactive component with enhanced light-absorbing capabilities. The device is first fabricated on a planar Si wafer at the microscale and then transferred to transparent hemispherical domes with different curvatures in a deterministic manner. The unique structural property of the fractal web design provides protection of the device from damage by effectively tolerating various external loads. Comprehensive experimental and computational studies reveal the essential design features and optoelectronic properties of the device, followed by the evaluation of its utility in the measurement of both the direction and intensity of incident light.

Mechanosensitivity is an essential component of phototransduction in vertebrate rods

Photoreceptors are specialized cells devoted to the transduction of the incoming visual signals. Rods are able also to shed from their tip old disks and to synthesize at the base of the outer segment (OS) new disks. By combining electrophysiology, optical tweezers (OTs), and biochemistry, we investigate mechanosensitivity in the rods of Xenopus laevis, and we show that 1) mechanosensitive channels (MSCs), transient receptor potential canonical 1 (TRPC1), and Piezo1 are present in rod inner segments (ISs); 2) mechanical stimulation—of the order of 10 pN—applied briefly to either the OS or IS evokes calcium transients; 3) inhibition of MSCs decreases the duration of photoresponses to bright flashes; 4) bright flashes of light induce a rapid shortening of the OS; and 5) the genes encoding the TRPC family have an ancient association with the genes encoding families of protein involved in phototransduction. These results suggest that MSCs play an integral role in rods’ phototransduction.

It is widely thought that sensory neurons are specialized to transduce just a single sensory modality. A combination of electrophysiology, optical tweezers, and histochemistry reveals that rod photoreceptors not only express mechanosensitive channels but display mechanosensitivity, which is crucial for phototransduction.

Retinal Drug Delivery: Rethinking Outcomes for the Efficient Replication of Retinal Behavior

The retina is a highly organized structure that is considered to be "an approachable part of the brain." It is attracting the interest of development scientists, as it provides a model neurovascular system. Over the last few years, we have been witnessing significant development in the knowledge of the mechanisms that induce the shape of the retinal vascular system, as well as knowledge of disease processes that lead to retina degeneration. Knowledge and understanding of how our vision works are crucial to creating a hardware-adaptive computational model that can replicate retinal behavior. The neuronal system is nonlinear and very intricate. It is thus instrumental to have a clear view of the neurophysiological and neuroanatomic processes and to take into account the underlying principles that govern the process of hardware transformation to produce an appropriate model that can be mapped to a physical device. The mechanistic and integrated computational models have enormous potential toward helping to understand disease mechanisms and to explain the associations identified in large model-free data sets. The approach used is modulated and based on different models of drug administration, including the geometry of the eye. This work aimed to review the recently used mathematical models to map a directed retinal network.

The neuroplasticity of division of labor: worker polymorphism, compound eye structure and brain organization in the leafcutter ant Atta cephalotes

Our understanding of how sensory structure design is coupled with neural processing capacity to adaptively support division of labor is limited. Workers of the remarkably polymorphic fungus-growing ant Atta cephalotes are behaviorally specialized by size: the smallest workers (minims) tend fungi in dark subterranean chambers while larger workers perform tasks outside the nest. Strong differences in worksite light conditions are predicted to influence sensory and processing requirements for vision. Analyzing confocal scans of worker eyes and brains, we found that eye structure and visual neuropils appear to have been selected to maximize task performance according to light availability. Minim eyes had few ommatidia, large interommatidial angles and eye parameter values, suggesting selection for visual sensitivity over acuity. Large workers had larger eyes with disproportionally more and larger ommatidia, and smaller interommatidial angles and eye parameter values, indicating peripheral sensory adaptation to ambient rainforest light. Optic lobes and mushroom body collars were disproportionately small in minims. Within the optic lobe, lamina and lobula relative volumes increased with worker size whereas medulla volume decreased. Visual system phenotypes thus correspond to task specializations in dark or light environments and illustrate a functional neuroplasticity underpinning division of labor in this socially complex agricultural ant.

Fly eyes are not still: a motion illusion in Drosophila flight supports parallel visual processing

Most animals shift gaze by a 'fixate and saccade' strategy, where the fixation phase stabilizes background motion. A logical prerequisite for robust detection and tracking of moving foreground objects, therefore, is to suppress the perception of background motion. In a virtual reality magnetic tether system enabling free yaw movement, Drosophila implemented a fixate and saccade strategy in the presence of a static panorama. When the spatial wavelength of a vertical grating was below the Nyquist wavelength of the compound eyes, flies drifted continuously and gaze could not be maintained at a single location. Because the drift occurs from a motionless stimulus - thus any perceived motion stimuli are generated by the fly itself - it is illusory, driven by perceptual aliasing. Notably, the drift speed was significantly faster than under a uniform panorama, suggesting perceptual enhancement as a result of aliasing. Under the same visual conditions in a rigid-tether paradigm, wing steering responses to the unresolvable static panorama were not distinguishable from those to a resolvable static pattern, suggesting visual aliasing is induced by ego motion. We hypothesized that obstructing the control of gaze fixation also disrupts detection and tracking of objects. Using the illusory motion stimulus, we show that magnetically tethered Drosophila track objects robustly in flight even when gaze is not fixated as flies continuously drift. Taken together, our study provides further support for parallel visual motion processing and reveals the critical influence of body motion on visuomotor processing. Motion illusions can reveal important shared principles of information processing across taxa.

Von Uexküll Revisited: Addressing Human Biases in the Study of Animal Perception

More than 100 years ago, the biologist Jakob von Uexküll suggested that, because sensory systems are diverse, animals likely inhabit different sensory worlds (umwelten) than we do. Since von Uexküll, work across sensory modalities has confirmed that animals sometimes perceive sensory information that humans cannot, and it is now well-established that one must account for this fact when studying an animal's behavior. We are less adept, however, at recognizing cases in which non-human animals may not detect or perceive stimuli the same way we do, which is our focus here. In particular, we discuss three ways in which our own perception can result in misinformed hypotheses about the function of various stimuli. In particular, we may (1) make untested assumptions about how sensory information is perceived, based on how we perceive or measure it, (2) attribute undue significance to stimuli that we perceive as complex or striking, and (3) assume that animals divide the sensory world in the same way that we as scientists do. We discuss each of these biases and provide examples of cases where animals cannot perceive or are not attending to stimuli in the same way that we do, and how this may lead us to mistaken assumptions. Because what an animal perceives affects its behavior, we argue that these biases are especially important for researchers in sensory ecology, cognition, and animal behavior and communication to consider. We suggest that studying animal umwelten requires integrative approaches that combine knowledge of sensory physiology with behavioral assays.

Rapid Release of Ca2+ from Endoplasmic Reticulum Mediated by Na+/Ca2+ Exchange

Phototransduction in Drosophila is mediated by phospholipase C (PLC) and Ca²⁺-permeable TRP channels, but the function of endoplasmic reticulum (ER) Ca²⁺ stores in this important model for Ca²⁺ signaling remains obscure. We therefore expressed a low affinity Ca²⁺ indicator (ER-GCaMP6-150) in the ER, and measured its fluorescence both in dissociated ommatidia and in vivo from intact flies of both sexes. Blue excitation light induced a rapid (tau ∼0.8 s), PLC-dependent decrease in fluorescence, representing depletion of ER Ca²⁺ stores, followed by a slower decay, typically reaching ∼50% of initial dark-adapted levels, with significant depletion occurring under natural levels of illumination. The ER stores refilled in the dark within 100-200 s. Both rapid and slow store depletion were largely unaffected in InsP₃ receptor mutants, but were much reduced in trp mutants. Strikingly, rapid (but not slow) depletion of ER stores was blocked by removing external Na⁺ and in mutants of the Na⁺/Ca²⁺ exchanger, CalX, which we immuno-localized to ER membranes in addition to its established localization in the plasma membrane. Conversely, overexpression of calx greatly enhanced rapid depletion. These results indicate that rapid store depletion is mediated by Na⁺/Ca²⁺ exchange across the ER membrane induced by Na⁺ influx via the light-sensitive channels. Although too slow to be involved in channel activation, this Na⁺/Ca²⁺ exchange-dependent release explains the decades-old observation of a light-induced rise in cytosolic Ca²⁺ in photoreceptors exposed to Ca²⁺-free solutions.SIGNIFICANCE STATEMENT Phototransduction in Drosophila is mediated by phospholipase C, which activates TRP cation channels by an unknown mechanism. Despite much speculation, it is unknown whether endoplasmic reticulum (ER) Ca²⁺ stores play any role. We therefore engineered flies expressing a genetically encoded Ca²⁺ indicator in the photoreceptor ER. Although NCX Na⁺/Ca²⁺ exchangers are classically believed to operate only at the plasma membrane, we demonstrate a rapid light-induced depletion of ER Ca²⁺ stores mediated by Na⁺/Ca²⁺ exchange across the ER membrane. This NCX-dependent release was too slow to be involved in channel activation, but explains the decades-old observation of a light-induced rise in cytosolic Ca²⁺ in photoreceptors bathed in Ca²⁺-free solutions.

Bioinspired Zoom Compound Eyes Enable Variable-Focus Imaging

Natural compound eyes provide the inspiration for developing artificial optical devices that feature a large field of view (FOV). However, the imaging ability of artificial compound eyes is generally based on the large number of ommatidia. The lack of a tunable imaging mechanism significantly limits the practical applications of artificial compound eyes, for instance, distinguishing targets at different distances. Herein, we reported zoom compound eyes that enable variable-focus imaging by integrating a deformable poly(dimethylsiloxane) (PDMS) microlens array (MLA) with a microfluidic chamber. The thin and soft PDMS MLA was fabricated by soft lithography using a hard template prepared by a combined technology of femtosecond laser processing and wet etching. As compared with other mechanical machining strategies, our combined technology features high flexibility, efficiency, and uniformity, as well as designable processing capability, since the size, distribution, and arrangement of the ommatidia can be well controlled during femtosecond laser processing. By tuning the volume of water injected into the chamber, the PDMS MLA can deform from a planar structure to a hemispherical shape, evolving into a tunable compound eye of variable FOV up to 180°. More importantly, the tunable chamber can functionalize as the main zoom lens for tunable imaging, which endows the compound eye with the additional capability of distinguishing targets at different distances. Its focal length can be turned from 3.03 mm to infinity with an angular resolution of 3.86 × 10^-4 rad. This zoom compound eye combines the advantages of monocular eyes and compound eyes together, holding great promise for developing advanced micro-optical devices that enable large FOV and variable-focus imaging.

Ca2+-Activated K+ Channels Reduce Network Excitability, Improving Adaptability and Energetics for Transmitting and Perceiving Sensory Information

Ca2+-activated K+ channels (BK and SK) are ubiquitous in synaptic circuits, but their role in network adaptation and sensory perception remains largely unknown. Using electrophysiological and behavioral assays and biophysical modeling, we discover how visual information transfer in mutants lacking the BK channel (dSlo- ), SK channel (dSK- ), or both (dSK- ;; dSlo- ) is shaped in the female fruit fly (Drosophila melanogaster) R1-R6 photoreceptor-LMC circuits (R-LMC-R system) through synaptic feedforward-feedback interactions and reduced R1-R6 Shaker and Shab K+ conductances. This homeostatic compensation is specific for each mutant, leading to distinctive adaptive dynamics. We show how these dynamics inescapably increase the energy cost of information and promote the mutants' distorted motion perception, determining the true price and limits of chronic homeostatic compensation in an in vivo genetic animal model. These results reveal why Ca2+-activated K+ channels reduce network excitability (energetics), improving neural adaptability for transmitting and perceiving sensory information.SIGNIFICANCE STATEMENT In this study, we directly link in vivo and ex vivo experiments with detailed stochastically operating biophysical models to extract new mechanistic knowledge of how Drosophila photoreceptor-interneuron-photoreceptor (R-LMC-R) circuitry homeostatically retains its information sampling and transmission capacity against chronic perturbations in its ion-channel composition, and what is the cost of this compensation and its impact on optomotor behavior. We anticipate that this novel approach will provide a useful template to other model organisms and computational neuroscience, in general, in dissecting fundamental mechanisms of homeostatic compensation and deepening our understanding of how biological neural networks work.

A low-cost hyperspectral scanner for natural imaging and the study of animal colour vision above and under water

Hyperspectral imaging is a widely used technology for industrial and scientific purposes, but the high cost and large size of commercial setups have made them impractical for most basic research. Here, we designed and implemented a fully open source and low-cost hyperspectral scanner based on a commercial spectrometer coupled to custom optical, mechanical and electronic components. We demonstrate our scanner's utility for natural imaging in both terrestrial and underwater environments. Our design provides sub-nm spectral resolution between 350-950 nm, including the UV part of the light spectrum which has been mostly absent from commercial solutions and previous natural imaging studies. By comparing the full light spectra from natural scenes to the spectral sensitivity of animals, we show how our system can be used to identify subtle variations in chromatic details detectable by different species. In addition, we have created an open access database for hyperspectral datasets collected from natural scenes in the UK and India. Together with comprehensive online build- and use-instructions, our setup provides an inexpensive and customisable solution to gather and share hyperspectral imaging data.

Contrast sensitivity reveals an oculomotor strategy for temporally encoding space

The contrast sensitivity function (CSF), how sensitivity varies with the frequency of the stimulus, is a fundamental assessment of visual performance. The CSF is generally assumed to be determined by low-level sensory processes. However, the spatial sensitivities of neurons in the early visual pathways, as measured in experiments with immobilized eyes, diverge from psychophysical CSF measurements in primates. Under natural viewing conditions, as in typical psychophysical measurements, humans continually move their eyes even when looking at a fixed point. Here, we show that the resulting transformation of the spatial scene into temporal modulations on the retina constitutes a processing stage that reconciles human CSF and the response characteristics of retinal ganglion cells under a broad range of conditions. Our findings suggest a fundamental integration between perception and action: eye movements work synergistically with the spatio-temporal sensitivities of retinal neurons to encode spatial information.

Can Drosophila melanogaster tell who's who?

Drosophila melanogaster are known to live in a social but cryptic world of touch and odours, but the extent to which they can perceive and integrate static visual information is a hotly debated topic. Some researchers fixate on the limited resolution of D. melanogaster's optics, others on their seemingly identical appearance; yet there is evidence of individual recognition and surprising visual learning in flies. Here, we apply machine learning and show that individual D. melanogaster are visually distinct. We also use the striking similarity of Drosophila's visual system to current convolutional neural networks to theoretically investigate D. melanogaster's capacity for visual understanding. We find that, despite their limited optical resolution, D. melanogaster's neuronal architecture has the capability to extract and encode a rich feature set that allows flies to re-identify individual conspecifics with surprising accuracy. These experiments provide a proof of principle that Drosophila inhabit a much more complex visual world than previously appreciated.

Opportunities and Challenges of Whole-Cell and -Tissue Simulations of the Outer Retina in Health and Disease

Visual processing starts in the outer retina, where photoreceptor cells sense photons that trigger electrical responses. Retinal pigment epithelial cells are located external to the photoreceptor layer and have critical functions in supporting cell and tissue homeostasis and thus sustaining a healthy retina. The high level of specialization makes the retina vulnerable to alterations that promote retinal degeneration. In this review, we discuss opportunities and challenges in proposing whole-cell and -tissue simulations of the human outer retina. An implicit position taken throughout this review is that mapping diverse data sets onto integrative computational models is likely to be a pivotal approach to understanding complex disease and developing novel interventions.

Visual approach computation in feeding hoverflies

On warm sunny days, female hoverflies are often observed feeding from a wide range of wild and cultivated flowers. In doing so, hoverflies serve a vital role as alternative pollinators, and are suggested to be the most important pollinators after bees and bumblebees. Unless the flower hoverflies are feeding from is large, they do not readily share the space with other insects, but instead opt to leave if another insect approaches. We used high-speed videography followed by 3D reconstruction of flight trajectories to quantify how female Eristalis hoverflies respond to approaching bees, wasps and two different hoverfly species. We found that, in 94% of the interactions, the occupant female left the flower when approached by another insect. We found that compared with spontaneous take-offs, the occupant hoverfly's escape response was performed at ∼3 times higher speed (spontaneous take-off at 0.2±0.05 m s⁻¹ compared with 0.55±0.08 m s⁻¹ when approached by another Eristalis). The hoverflies tended to take off upward and forward, while taking the incomer's approach angle into account. Intriguingly, we found that, when approached by wasps, the occupant Eristalis took off at a higher speed and when the wasp was further away. This suggests that feeding hoverflies may be able to distinguish these predators, demanding impressive visual capabilities. Our results, including quantification of the visual information available before occupant take-off, provide important insight into how freely behaving hoverflies perform escape responses from competitors and predators (e.g. wasps) in the wild.

Highlighted Article: Reconstruction of the take-off and flight of feeding female hoverflies when approached by other insects, and quantification of visual parameters, reveals how freely behaving hoverflies perform escape responses from competitors and predators in the wild.

Modeling elucidates how refractory period can provide profound nonlinear gain control to graded potential neurons

Refractory period (RP) plays a central role in neural signaling. Because it limits an excitable membrane's recovery time from a previous excitation, it can restrict information transmission. Classically, RP means the recovery time from an action potential (spike), and its impact to encoding has been mostly studied in spiking neurons. However, many sensory neurons do not communicate with spikes but convey information by graded potential changes. In these systems, RP can arise as an intrinsic property of their quantal micro/nanodomain sampling events, as recently revealed for quantum bumps (single photon responses) in microvillar photoreceptors. Whilst RP is directly unobservable and hard to measure, masked by the graded macroscopic response that integrates numerous quantal events, modeling can uncover its role in encoding. Here, we investigate computationally how RP can affect encoding of graded neural responses. Simulations in a simple stochastic process model for a fly photoreceptor elucidate how RP can profoundly contribute to nonlinear gain control to achieve a large dynamic range.

A biomimetic fly photoreceptor model elucidates how stochastic adaptive quantal sampling provides a large dynamic range

Light intensities (photons s^-1  μm^-2 ) in a natural scene vary over several orders of magnitude from shady woods to direct sunlight. A major challenge facing the visual system is how to map such a large dynamic input range into its limited output range, so that a signal is neither buried in noise in darkness nor saturated in brightness. A fly photoreceptor has achieved such a large dynamic range; it can encode intensity changes from single to billions of photons, outperforming man-made light sensors. This performance requires powerful light adaptation, the neural implementation of which has only become clear recently. A computational fly photoreceptor model, which mimics the real phototransduction processes, has elucidated how light adaptation happens dynamically through stochastic adaptive quantal information sampling. A Drosophila R1-R6 photoreceptor's light sensor, the rhabdomere, has 30,000 microvilli, each of which stochastically samples incoming photons. Each microvillus employs a full G-protein-coupled receptor signalling pathway to adaptively transduce photons into quantum bumps (QBs, or samples). QBs then sum the macroscopic photoreceptor responses, governed by four quantal sampling factors (limitations): (i) the number of photon sampling units in the cell structure (microvilli), (ii) sample size (QB waveform), (iii) latency distribution (time delay between photon arrival and emergence of a QB), and (iv) refractory period distribution (time for a microvillus to recover after a QB). Here, we review how these factors jointly orchestrate light adaptation over a large dynamic range.

How a fly photoreceptor samples light information in time

A photoreceptor's information capture is constrained by the structure and function of its light‐sensitive parts. Specifically, in a fly photoreceptor, this limit is set by the number of its photon sampling units (microvilli), constituting its light sensor (the rhabdomere), and the speed and recoverability of their phototransduction reactions. In this review, using an insightful constructionist viewpoint of a fly photoreceptor being an ‘imperfect’ photon counting machine, we explain how these constraints give rise to adaptive quantal information sampling in time, which maximises information in responses to salient light changes while antialiasing visual signals. Interestingly, such sampling innately determines also why photoreceptors extract more information, and more economically, from naturalistic light contrast changes than Gaussian white‐noise stimuli, and we explicate why this is so. Our main message is that stochasticity in quantal information sampling is less noise and more processing, representing an ‘evolutionary adaptation’ to generate a reliable neural estimate of the variable world.

Object-Detecting Neurons in Drosophila

Many animals rely on vision to detect objects such as conspecifics, predators, and prey. Hypercomplex cells found in feline cortex and small target motion detectors found in dragonfly and hoverfly optic lobes demonstrate robust tuning for small objects, with weak or no response to larger objects or movement of the visual panorama [1-3]. However, the relationship among anatomical, molecular, and functional properties of object detection circuitry is not understood. Here we characterize a specialized object detector in Drosophila, the lobula columnar neuron LC11 [4]. By imaging calcium dynamics with two-photon excitation microscopy, we show that LC11 responds to the omni-directional movement of a small object darker than the background, with little or no responses to static flicker, vertically elongated bars, or panoramic gratings. LC11 dendrites innervate multiple layers of the lobula, and each dendrite spans enough columns to sample 75° of visual space, yet the area that evokes calcium responses is only 20° wide and shows robust responses to a 2.2° object spanning less than half of one facet of the compound eye. The dendrites of neighboring LC11s encode object motion retinotopically, but the axon terminals fuse into a glomerular structure in the central brain where retinotopy is lost. Blocking inhibitory ionic currents abolishes small object sensitivity and facilitates responses to elongated bars and gratings. Our results reveal high-acuity object motion detection in the Drosophila optic lobe.