Feedback network controls photoreceptor output at the layer of first visual synapses in Drosophila

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.

A look into feedback neural computation upon collision selectivity

Physiological studies have shown that a group of locust's lobula giant movement detectors (LGMDs) has a diversity of collision selectivity to approaching objects, relatively darker or brighter than their backgrounds in cluttered environments. Such diversity of collision selectivity can serve locusts to escape from attack by natural enemies, and migrate in swarm free of collision. For computational studies, endeavours have been made to realize the diverse selectivity which, however, is still one of the most challenging tasks especially in complex and dynamic real world scenarios. The existing models are mainly formulated as multi-layered neural networks with merely feed-forward information processing, and do not take into account the effect of re-entrant signals in feedback loop, which is an essential regulatory loop for motion perception, yet never been explored in looming perception. In this paper, we inaugurate feedback neural computation for constructing a new LGMD-based model, named F-LGMD to look into the efficacy upon implementing different collision selectivity. Accordingly, the proposed neural network model features both feed-forward processing and feedback loop. The feedback control propagates output signals of parallel ON/OFF channels back into their starting neurons, thus makes part of the feed-forward neural network, i.e. the ON/OFF channels and the feedback loop form an iterative cycle system. Moreover, the feedback control is instantaneous, which leads to the existence of a fixed point whereby the fixed point theorem is applied to rigorously derive valid range of feedback coefficients. To verify the effectiveness of the proposed method, we conduct systematic experiments covering synthetic and natural collision datasets, and also online robotic tests. The experimental results show that the F-LGMD, with a unified network, can fulfil the diverse collision selectivity revealed in physiology, which not only reduces considerably the handcrafted parameters compared to previous studies, but also offers a both efficient and robust scheme for collision perception through feedback neural computation.

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.

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.

Predicting individual neuron responses with anatomically constrained task optimization

Artificial neural networks trained to solve sensory tasks can develop statistical representations that match those in biological circuits. However, it remains unclear whether they can reproduce properties of individual neurons. Here, we investigated how artificial networks predict individual neuron properties in the visual motion circuits of the fruit fly Drosophila. We trained anatomically constrained networks to predict movement in natural scenes, solving the same inference problem as fly motion detectors. Units in the artificial networks adopted many properties of analogous individual neurons, even though they were not explicitly trained to match these properties. Among these properties was the split into ON and OFF motion detectors, which is not predicted by classical motion detection models. The match between model and neurons was closest when models were trained to be robust to noise. These results demonstrate how anatomical, task, and noise constraints can explain properties of individual neurons in a small neural network.

Acute Application of Imidacloprid Alters the Sensitivity of Direction Selective Motion Detecting Neurons in an Insect Pollinator

Cholinergic pesticides, such as the neonicotinoid imidacloprid, are the most important insecticides used for plant protection worldwide. In recent decades, concerns have been raised about side effects on non-target insect species, including altered foraging behavior and navigation. Although pollinators rely on visual cues to forage and navigate their environment, the effects of neonicotinoids on visual processing have been largely overlooked. To test the effect of acute treatment with imidacloprid at known concentrations in the brain, we developed a modified electrophysiological setup that allows recordings of visually evoked responses while perfusing the brain in vivo. We obtained long-lasting recordings from direction selective wide-field, motion sensitive neurons of the hoverfly pollinator, Eristalis tenax. Neurons were treated with imidacloprid (3.9 μM, 0.39 μM or a sham control treatment using the solvent (dimethylsulfoxide) only. Exposure to a high, yet sub-lethal concentration of imidacloprid significantly alters their physiological response to motion stimuli. We observed a general effect of imidacloprid (3.9 μM) increasing spontaneous activity, reducing contrast sensitivity and giving weaker directional tuning to wide-field moving stimuli, with likely implications for errors in flight control, hovering and routing. Our electrophysiological approach reveals the robustness of the fly visual pathway against cholinergic perturbance (i.e., at 0.39 μM) but also potential threatening effects of cholinergic pesticides (i.e., evident at 3.9 μM) for the visual motion detecting system of an important pollinator.

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.

Parallel Synaptic Acetylcholine Signals Facilitate Large Monopolar Cell Repolarization and Modulate Visual Behavior in Drosophila

Appropriate termination of the photoresponse in image-forming photoreceptors and downstream neurons is critical for an animal to achieve high temporal resolution. Although the cellular and molecular mechanisms of termination in image-forming photoreceptors have been extensively studied in Drosophila, the underlying mechanism of termination in their downstream large monopolar cells remains less explored. Here, we show that synaptic ACh signaling, from both amacrine cells (ACs) and L4 neurons, facilitates the rapid repolarization of L1 and L2 neurons. Intracellular recordings in female flies show that blocking synaptic ACh output from either ACs or L4 neurons leads to slow repolarization of L1 and L2 neurons. Genetic and electrophysiological studies in both male and female flies determine that L2 neurons express ACh receptors and directly receive ACh signaling. Moreover, our results demonstrate that synaptic ACh signaling from both ACs and L4 neurons simultaneously facilitates ERG termination. Finally, visual behavior studies in both male and female flies show that synaptic ACh signaling, from either ACs or L4 neurons to L2 neurons, is essential for the optomotor response of the flies in high-frequency light stimulation. Our study identifies parallel synaptic ACh signaling for repolarization of L1 and L2 neurons and demonstrates that synaptic ACh signaling facilitates L1 and L2 neuron repolarization to maintain the optomotor response of the fly on high-frequency light stimulation.SIGNIFICANCE STATEMENT The image-forming photoreceptor downstream neurons receive multiple synaptic inputs from image-forming photoreceptors and various types of interneurons. It remains largely unknown how these synaptic inputs modulate the neural activity and function of image-forming photoreceptor downstream neurons. We show that parallel synaptic ACh signaling from both amacrine cells and L4 neurons facilitates rapid repolarization of large monopolar cells in Drosophila and maintains the optomotor response of the fly on high-frequency light stimulation. This work is one of the first reports showing how parallel synaptic signaling modulates the activity of large monopolar cells and motion vision simultaneously.

The spectral sensitivity of Drosophila photoreceptors

Drosophila melanogaster has long been a popular model insect species, due in large part to the availability of genetic tools and is fast becoming the model for insect colour vision. Key to understanding colour reception in Drosophila is in-depth knowledge of spectral inputs and downstream neural processing. While recent studies have sparked renewed interest in colour processing in Drosophila, photoreceptor spectral sensitivity measurements have yet to be carried out in vivo. We have fully characterised the spectral input to the motion and colour vision pathways, and directly measured the effects of spectral modulating factors, screening pigment density and carotenoid-based ocular pigments. All receptor sensitivities had significant shifts in spectral sensitivity compared to previous measurements. Notably, the spectral range of the Rh6 visual pigment is substantially broadened and its peak sensitivity is shifted by 92 nm from 508 to 600 nm. We show that this deviation can be explained by transmission of long wavelengths through the red screening pigment and by the presence of the blue-absorbing filter in the R7y receptors. Further, we tested direct interactions between inner and outer photoreceptors using selective recovery of activity in photoreceptor pairs.

Better Sleep at Night: How Light Influences Sleep in Drosophila

Sleep-like states have been described in Drosophila and the mechanisms and factors that generate and define sleep-wake profiles in this model organism are being thoroughly investigated. Sleep is controlled by both circadian and homeostatic mechanisms, and environmental factors such as light, temperature, and social stimuli are fundamental in shaping and confining sleep episodes into the correct time of the day. Among environmental cues, light seems to have a prominent function in modulating the timing of sleep during the 24 h and, in this review, we will discuss the role of light inputs in modulating the distribution of the fly sleep-wake cycles. This phenomenon is of growing interest in the modern society, where artificial light exposure during the night is a common trait, opening the possibility to study Drosophila as a model organism for investigating shift-work disorders.

A minimal synaptic model for direction selective neurons in Drosophila

Visual motion estimation is a canonical neural computation. In Drosophila, recent advances have identified anatomic and functional circuitry underlying direction-selective computations. Models with varying levels of abstraction have been proposed to explain specific experimental results but have rarely been compared across experiments. Here we use the wealth of available anatomical and physiological data to construct a minimal, biophysically inspired synaptic model for Drosophila’s first-order direction-selective T4 cells. We show how this model relates mathematically to classical models of motion detection, including the Hassenstein-Reichardt correlator model. We used numerical simulation to test how well this synaptic model could reproduce measurements of T4 cells across many datasets and stimulus modalities. These comparisons include responses to sinusoid gratings, to apparent motion stimuli, to stochastic stimuli, and to natural scenes. Without fine-tuning this model, it sufficed to reproduce many, but not all, response properties of T4 cells. Since this model is flexible and based on straightforward biophysical properties, it provides an extensible framework for developing a mechanistic understanding of T4 neural response properties. Moreover, it can be used to assess the sufficiency of simple biophysical mechanisms to describe features of the direction-selective computation and identify where our understanding must be improved.

Serotonergic modulation of visual neurons in Drosophila melanogaster

Sensory systems rely on neuromodulators, such as serotonin, to provide flexibility for information processing as stimuli vary, such as light intensity throughout the day. Serotonergic neurons broadly innervate the optic ganglia of Drosophila melanogaster, a widely used model for studying vision. It remains unclear whether serotonin modulates the physiology of interneurons in the optic ganglia. To address this question, we first mapped the expression patterns of serotonin receptors in the visual system, focusing on a subset of cells with processes in the first optic ganglion, the lamina. Serotonin receptor expression was found in several types of columnar cells in the lamina including 5-HT2B in lamina monopolar cell L2, required for spatiotemporal luminance contrast, and both 5-HT1A and 5-HT1B in T1 cells, whose function is unknown. Subcellular mapping with GFP-tagged 5-HT2B and 5-HT1A constructs indicated that these receptors localize to layer M2 of the medulla, proximal to serotonergic boutons, suggesting that the medulla neuropil is the primary site of serotonergic regulation for these neurons. Exogenous serotonin increased basal intracellular calcium in L2 terminals in layer M2 and modestly decreased the duration of visually induced calcium transients in L2 neurons following repeated dark flashes, but otherwise did not alter the calcium transients. Flies without functional 5-HT2B failed to show an increase in basal calcium in response to serotonin. 5-HT2B mutants also failed to show a change in amplitude in their response to repeated light flashes but other calcium transient parameters were relatively unaffected. While we did not detect serotonin receptor expression in L1 neurons, they, like L2, underwent serotonin-induced changes in basal calcium, presumably via interactions with other cells. These data demonstrate that serotonin modulates the physiology of interneurons involved in early visual processing in Drosophila.

Serotonergic neurons innervate the Drosophila melanogaster eye, but it was not known whether serotonin signaling could induce acute physiological responses in visual interneurons. We found serotonin receptors expressed in all neuropils of the optic lobe and identified specific neurons involved in visual information processing that express serotonin receptors. Activation of these receptors increased intracellular calcium in first order interneurons L1 and L2 and may enhance visually induced calcium transients in L2 neurons. These data support a role for the serotonergic neuromodulation of interneurons in the Drosophila visual system.

Communication Among Photoreceptors and the Central Clock Affects Sleep Profile

Light is one of the most important factors regulating rhythmical behavior of Drosophila melanogaster. It is received by different photoreceptors and entrains the circadian clock, which controls sleep. The retina is known to be essential for light perception, as it is composed of specialized light-sensitive cells which transmit signal to deeper parts of the brain. In this study we examined the role of specific photoreceptor types and peripheral oscillators located in these cells in the regulation of sleep pattern. We showed that sleep is controlled by the visual system in a very complex way. Photoreceptors expressing Rh1, Rh3 are involved in night-time sleep regulation, while cells expressing Rh5 and Rh6 affect sleep both during the day and night. Moreover, Hofbauer-Buchner (HB) eyelets which can directly contact with s-LN v s and l-LN v s play a wake-promoting function during the day. In addition, we showed that L2 interneurons, which receive signal from R1-6, form direct synaptic contacts with l-LN v s, which provides new light input to the clock network.

A Directionally Selective Small Target Motion Detecting Visual Neural Network in Cluttered Backgrounds

Discriminating targets moving against a cluttered background is a huge challenge, let alone detecting a target as small as one or a few pixels and tracking it in flight. In the insect's visual system, a class of specific neurons, called small target motion detectors (STMDs), have been identified as showing exquisite selectivity for small target motion. Some of the STMDs have also demonstrated direction selectivity which means these STMDs respond strongly only to their preferred motion direction. Direction selectivity is an important property of these STMD neurons which could contribute to tracking small targets such as mates in flight. However, little has been done on systematically modeling these directionally selective STMD neurons. In this paper, we propose a directionally selective STMD-based neural network for small target detection in a cluttered background. In the proposed neural network, a new correlation mechanism is introduced for direction selectivity via correlating signals relayed from two pixels. Then, a lateral inhibition mechanism is implemented on the spatial field for size selectivity of the STMD neurons. Finally, a population vector algorithm is used to encode motion direction of small targets. Extensive experiments showed that the proposed neural network not only is in accord with current biological findings, i.e., showing directional preferences but also worked reliably in detecting the small targets against cluttered backgrounds.

Sparse identification of contrast gain control in the fruit fly photoreceptor and amacrine cell layer

The fruit fly's natural visual environment is often characterized by light intensities ranging across several orders of magnitude and by rapidly varying contrast across space and time. Fruit fly photoreceptors robustly transduce and, in conjunction with amacrine cells, process visual scenes and provide the resulting signal to downstream targets. Here, we model the first step of visual processing in the photoreceptor-amacrine cell layer. We propose a novel divisive normalization processor (DNP) for modeling the computation taking place in the photoreceptor-amacrine cell layer. The DNP explicitly models the photoreceptor feedforward and temporal feedback processing paths and the spatio-temporal feedback path of the amacrine cells. We then formally characterize the contrast gain control of the DNP and provide sparse identification algorithms that can efficiently identify each the feedforward and feedback DNP components. The algorithms presented here are the first demonstration of tractable and robust identification of the components of a divisive normalization processor. The sparse identification algorithms can be readily employed in experimental settings, and their effectiveness is demonstrated with several examples.

Luminance Information Is Required for the Accurate Estimation of Contrast in Rapidly Changing Visual Contexts

Visual perception scales with changes in the visual stimulus, or contrast, irrespective of background illumination. However, visual perception is challenged when adaptation is not fast enough to deal with sudden declines in overall illumination, for example, when gaze follows a moving object from bright sunlight into a shaded area. Here, we show that the visual system of the fly employs a solution by propagating a corrective luminance-sensitive signal. We use in vivo 2-photon imaging and behavioral analyses to demonstrate that distinct OFF-pathway inputs encode contrast and luminance. Predictions of contrast-sensitive neuronal responses show that contrast information alone cannot explain behavioral responses in sudden dim light. The luminance-sensitive pathway via the L3 neuron is required for visual processing in such rapidly changing light conditions, ensuring contrast constancy when pure contrast sensitivity underestimates a stimulus. Thus, retaining a peripheral feature, luminance, in visual processing is required for robust behavioral responses.

Distinct expression of potassium channels regulates visual response properties of lamina neurons in Drosophila melanogaster

The computational organization of sensory systems depends on the diversification of individual cell types with distinct signal-processing capabilities. The Drosophila visual system, for instance, splits information into channels with different temporal properties directly downstream of photoreceptors in the first-order interneurons of the OFF pathway, L2 and L3. However, the biophysical mechanisms that determine this specialization are largely unknown. Here, we show that the voltage-gated K_a channels Shaker and Shal contribute to the response properties of the major OFF pathway input L2. L3 calcium response kinetics postsynaptic to photoreceptors resemble the sustained calcium signals of photoreceptors, whereas L2 neurons decay transiently. Based on a cell-type-specific RNA-seq data set and endogenous protein tagging, we identified Shaker and Shal as the primary candidates to shape L2 responses. Using in vivo two-photon imaging of L2 calcium signals in combination with pharmacological and genetic perturbations of these K_a channels, we show that the wild-type Shaker and Shal function is to enhance L2 responses and cell-autonomously sharpen L2 kinetics. Our results reveal a role for K_a channels in determining the signal-processing characteristics of a specific cell type in the visual system.

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.

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging, and so forth. A good number of motion detectors have been identified in the insects' visual pathways. Computational modeling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research on insects' visual systems in the literature. These motion perception models or neural networks consist of the looming-sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation-sensitive neural systems of direction-selective neurons (DSNs) in fruit flies, bees, and locusts, and the small-target motion detectors (STMDs) in dragonflies and hoverflies. We also review the applications of these models to robots and vehicles. Through these modeling studies, we summarize the methodologies that generate different direction and size selectivity in motion perception. Finally, we discuss multiple systems integration and hardware realization of these bio-inspired motion perception models.

Two novel forms of ERG oscillation in Drosophila: age and activity dependence

Over an animal's lifespan, neuronal circuits and systems often decline in an inherently heterogeneous fashion. To compare the age-dependent progression of changes in visual behavior with alterations in retinal physiology, we examined phototaxis and electroretinograms (ERGs) in a wild-type D. melanogaster strain (Canton-S) across their lifespan. In aged flies (beyond 50% median lifespan), we found a marked decline in phototaxis, while motor coordination was less disrupted, as indicated by relatively stronger negative geotaxis. These aged flies displayed substantially reduced ERG transient amplitudes while the receptor potentials (RP) remained largely intact. Using a repetitive light flash protocol, we serendipitously discovered two forms of activity-dependent oscillation in the ERG waveforms of young flies: 'light-off' and 'light-on' oscillations. After repeated 500 ms light flashes, light-off oscillations appeared during the ERG off-transients (frequency: 50-120 Hz, amplitude: ∼1 mV). Light-on oscillations (100-200 Hz, ∼0.3 mV) were induced by a series of 50 ms flashes, and were evident during the ERG on-transients. Both forms of oscillation were observed in other strains of D. melanogaster (Oregon-R, Berlin), additional Drosophila species (D. funerbris, D. euronotus, D. hydei, D. americana), and were evoked by a variety of light sources. Both light-off and light-on oscillations were distinct from previously described ERG oscillations in the visual mutant rosA in terms of location within the waveform and frequency. However, within rosA mutants, light-off oscillations, but not light-on oscillations could be recruited by the repetitive light flash protocol. Importantly though, we found that both forms of oscillation were rarely observed in aged flies. Although the physiological bases of these oscillations remain to be elucidated, they may provide important clues to age-related changes in neuronal excitability and synaptic transmission.

Point process analysis of noise in early invertebrate vision

Noise is a prevalent and sometimes even dominant aspect of many biological processes. While many natural systems have adapted to attenuate or even usefully integrate noise, the variability it introduces often still delimits the achievable precision across biological functions. This is particularly so for visual phototransduction, the process responsible for converting photons of light into usable electrical signals (quantum bumps). Here, randomness of both the photon inputs (regarded as extrinsic noise) and the conversion process (intrinsic noise) are seen as two distinct, independent and significant limitations on visual reliability. Past research has attempted to quantify the relative effects of these noise sources by using approximate methods that do not fully account for the discrete, point process and time ordered nature of the problem. As a result the conclusions drawn from these different approaches have led to inconsistent expositions of phototransduction noise performance.

This paper provides a fresh and complete analysis of the relative impact of intrinsic and extrinsic noise in invertebrate phototransduction using minimum mean squared error reconstruction techniques based on Bayesian point process (Snyder) filters. An integrate-fire based algorithm is developed to reliably estimate photon times from quantum bumps and Snyder filters are then used to causally estimate random light intensities both at the front and back end of the phototransduction cascade. Comparison of these estimates reveals that the dominant noise source transitions from extrinsic to intrinsic as light intensity increases. By extending the filtering techniques to account for delays, it is further found that among the intrinsic noise components, which include bump latency (mean delay and jitter) and shape (amplitude and width) variance, it is the mean delay that is critical to noise performance. As the timeliness of visual information is important for real-time action, this delay could potentially limit the speed at which invertebrates can respond to stimuli. Consequently, if one wants to increase visual fidelity, reducing the photoconversion lag is much more important than improving the regularity of the electrical signal.

The invertebrate phototransduction system captures and converts environmental light inputs into electrical signals for use in later visual processing. Consequently, one would expect it to be optimised in some way to ensure that only a minimal amount of environmental information is lost during conversion. Confirming this requires an understanding and quantification of the performance limiting noise sources. Photons, which are inherently random and discrete, introduce extrinsic noise. The phototransduction cascade, which converts photons into electrical bumps possessing non-deterministic shapes and latencies, contributes intrinsic noise. Previous work on characterising the relative impact of all these sources did not account for the discrete, causal, point process nature of the problem and thus results were often inconclusive. Here we use non-linear Poisson process filtering to show that photon noise is dominant at low light intensity and cascade noise limiting at high intensity. Further, our analysis reveals that mean bump delay is the most deleterious aspect of the intrinsic noise. Our work emphasises a new approach to assessing sensory noise and provides the first complete description and evaluation of the relative impact of noise in phototransduction that does not rely on continuity, linearity or Gaussian approximations.

Microsaccadic sampling of moving image information provides Drosophila hyperacute vision

Small fly eyes should not see fine image details. Because flies exhibit saccadic visual behaviors and their compound eyes have relatively few ommatidia (sampling points), their photoreceptors would be expected to generate blurry and coarse retinal images of the world. Here we demonstrate that Drosophila see the world far better than predicted from the classic theories. By using electrophysiological, optical and behavioral assays, we found that R1-R6 photoreceptors’ encoding capacity in time is maximized to fast high-contrast bursts, which resemble their light input during saccadic behaviors. Whilst over space, R1-R6s resolve moving objects at saccadic speeds beyond the predicted motion-blur-limit. Our results show how refractory phototransduction and rapid photomechanical photoreceptor contractions jointly sharpen retinal images of moving objects in space-time, enabling hyperacute vision, and explain how such microsaccadic information sampling exceeds the compound eyes’ optical limits. These discoveries elucidate how acuity depends upon photoreceptor function and eye movements.

Fruit flies have five eyes: two large compound eyes which support vision, plus three smaller single lens eyes which are used for navigation. Each compound eye monitors 180° of space and consists of roughly 750 units, each containing eight light-sensitive cells called photoreceptors. This relatively wide spacing of photoreceptors is thought to limit the sharpness, or acuity, of vision in fruit flies. The area of the human retina (the light-sensitive surface at back of our eyes) that generates our sharpest vision contains photoreceptors that are 500 times more densely packed.

Despite their differing designs, human and fruit fly eyes work via the same general principles. If we, or a fruit fly, were to hold our gaze completely steady, the world would gradually fade from view as the eye adapted to the unchanging visual stimulus. To ensure this does not happen, animals continuously make rapid, automatic eye movements called microsaccades. These refresh the image on the retina and prevent it from fading. Yet it is not known why do they not also cause blurred vision.

Standard accounts of vision assume that the retina and the brain perform most of the information processing required, with photoreceptors simply detecting how much light enters the eye. However, Juusola, Dau, Song et al. now challenge this idea by showing that photoreceptors are specially adapted to detect the fluctuating patterns of light that enter the eye as a result of microsaccades. Moreover, fruit fly eyes resolve small moving objects far better than would be predicted based on the spacing of their photoreceptors.

The discovery that photoreceptors are well adapted to deal with eye movements changes our understanding of insect vision. The findings also disprove the 100-year-old dogma that the spacing of photoreceptors limits the sharpness of vision in compound eyes. Further studies are required to determine whether photoreceptors in the retinas of other animals, including humans, have similar properties.

Neural organization of afferent pathways from the stomatopod compound eye

Crustaceans and insects share many similarities of brain organization suggesting that their common ancestor possessed some components of those shared features. Stomatopods (mantis shrimps) are basal eumalacostracan crustaceans famous for their elaborate visual system, the most complex of which possesses 12 types of color photoreceptors and the ability to detect both linearly and circularly polarized light. Here, using a palette of histological methods we describe neurons and their neuropils most immediately associated with the stomatopod retina. We first provide a general overview of the major neuropil structures in the eyestalks lateral protocerebrum, with respect to the optical pathways originating from the six rows of specialized ommatidia in the stomatopod's eye, termed the midband. We then focus on the structure and neuronal types of the lamina, the first optic neuropil in the stomatopod visual system. Using Golgi impregnations to resolve single neurons we identify cells in different parts of the lamina corresponding to the three different regions of the stomatopod eye (midband and the upper and lower eye halves). While the optic cartridges relating to the spectral and polarization sensitive midband ommatidia show some specializations not found in the lamina serving the upper and lower eye halves, the general morphology of the midband lamina reflects cell types elsewhere in the lamina and cell types described for other species of Eumalacostraca.

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.

Electrophysiological Method for Recording Intracellular Voltage Responses of Drosophila Photoreceptors and Interneurons to Light Stimuli In Vivo

Voltage responses of insect photoreceptors and visual interneurons can be accurately recorded with conventional sharp microelectrodes. The method described here enables the investigator to measure long-lasting (from minutes to hours) high-quality intracellular responses from single Drosophila R1-R6 photoreceptors and Large Monopolar Cells (LMCs) to light stimuli. Because the recording system has low noise, it can be used to study variability among individual cells in the fly eye, and how their outputs reflect the physical properties of the visual environment. We outline all key steps in performing this technique. The basic steps in constructing an appropriate electrophysiology set-up for recording, such as design and selection of the experimental equipment are described. We also explain how to prepare for recording by making appropriate (sharp) recording and (blunt) reference electrodes. Details are given on how to fix an intact fly in a bespoke fly-holder, prepare a small window in its eye and insert a recording electrode through this hole with minimal damage. We explain how to localize the center of a cell's receptive field, dark- or light-adapt the studied cell, and to record its voltage responses to dynamic light stimuli. Finally, we describe the criteria for stable normal recordings, show characteristic high-quality voltage responses of individual cells to different light stimuli, and briefly define how to quantify their signaling performance. Many aspects of the method are technically challenging and require practice and patience to master. But once learned and optimized for the investigator's experimental objectives, it grants outstanding in vivo neurophysiological data.

Frequency-selective transmission of graded signals in large monopolar neurons of blowfly Calliphora vicina compound eye

The functional roles of voltage-gated K(+)(Kv) channels in visual system interneurons remain poorly studied. We have addressed this problem in the large monopolar cells (LMCs) of the blowfly Calliphora vicina, using intracellular recordings and mathematical modeling methods. Intracellular recordings were performed in two cellular compartments: the synaptic zone, which receives input from photoreceptors, and the axon, which provides graded potential output to the third-order visual neurons. Biophysical properties of Kv conductances in the physiological voltage range were examined in the dark with injections of current in the discontinuous current-clamp mode. Putative LMC types 1/2 and 3 (L1/2 and L3, respectively) had dissimilar Kv channelomes: L1/2 displayed a prominent inactivating Kv conductance in the axon, while L3 cells were characterized by a sustained delayed-rectifier Kv conductance. To study the propagation of voltage signals, the data were incorporated into the previously developed mathematical model. We demonstrate that the complex interaction between the passive membrane properties, Kv conductances, and the neuronal geometry leads to a resonance-like filtering of signals with peak frequencies of transmission near 15 and 40 Hz for L3 and L1/2, respectively. These results point to distinct physiological roles of different types of LMCs.

Evidence for Dynamic Network Regulation of Drosophila Photoreceptor Function from Mutants Lacking the Neurotransmitter Histamine

Synaptic feedback from interneurons to photoreceptors can help to optimize visual information flow by balancing its allocation on retinal pathways under changing light conditions. But little is known about how this critical network operation is regulated dynamically. Here, we investigate this question by comparing signaling properties and performance of wild-type Drosophila R1-R6 photoreceptors to those of the hdc (JK910) mutant, which lacks the neurotransmitter histamine and therefore cannot transmit information to interneurons. Recordings show that hdc (JK910) photoreceptors sample similar amounts of information from naturalistic stimulation to wild-type photoreceptors, but this information is packaged in smaller responses, especially under bright illumination. Analyses reveal how these altered dynamics primarily resulted from network overload that affected hdc (JK910) photoreceptors in two ways. First, the missing inhibitory histamine input to interneurons almost certainly depolarized them irrevocably, which in turn increased their excitatory feedback to hdc (JK910) R1-R6s. This tonic excitation depolarized the photoreceptors to artificially high potentials, reducing their operational range. Second, rescuing histamine input to interneurons in hdc (JK910) mutant also restored their normal phasic feedback modulation to R1-R6s, causing photoreceptor output to accentuate dynamic intensity differences at bright illumination, similar to the wild-type. These results provide mechanistic explanations of how synaptic feedback connections optimize information packaging in photoreceptor output and novel insight into the operation and design of dynamic network regulation of sensory neurons.

Ih channels control feedback regulation from amacrine cells to photoreceptors

In both vertebrates and invertebrates, photoreceptors’ output is regulated by feedback signals from interneurons that contribute to several important visual functions. Although synaptic feedback regulation of photoreceptors is known to occur in Drosophila, many questions about the underlying molecular mechanisms and physiological implementation remain unclear. Here, we systematically investigated these questions using a broad range of experimental methods. We isolated two I_h mutant fly lines that exhibit rhythmic photoreceptor depolarization without light stimulation. We discovered that I_h channels regulate glutamate release from amacrine cells by modulating calcium channel activity. Moreover, we showed that the eye-enriched kainate receptor (EKAR) is expressed in photoreceptors and receives the glutamate signal released from amacrine cells. Finally, we presented evidence that amacrine cell feedback regulation helps maintain light sensitivity in ambient light. Our findings suggest plausible molecular underpinnings and physiological effects of feedback regulation from amacrine cells to photoreceptors. These results provide new mechanistic insight into how synaptic feedback regulation can participate in network processing by modulating neural information transfer and circuit excitability.

A systematic study of the Drosophila visual system clarifies the molecular mechanisms and physiological effects of feedback regulation of photoreceptors by amacrine cells, essential for maintaining light sensitivity.

Feedback regulation is a common feature of neural circuits during the process of acquiring information. Therefore, it is important to understand how this phenomenon occurs. Using the primary visual system of the fruit fly Drosophila melanogaster as a model, we systematically investigated the molecular mechanisms and the physiological implementation of feedback regulation from amacrine cells (second order neurons that are present in the lamina) to photoreceptors. We isolated two fly lines with mutations in the gene that encodes for the ion channel known as I_h, whose photoreceptors exhibited rhythmic depolarizations in the absence of light stimulation. We demonstrated that I_h channels function in amacrine cells to regulate the release of the neurotransmitter glutamate by modulating the activity of the voltage-gated calcium channel, Cac. We further found that the glutamate signal released by amacrine cells is sensed and transduced by glutamate receptors expressed by the photoreceptors. Finally, we showed that this feedback regulation is critical for maintaining light sensitivity in the presence of ambient light. Our results suggest that regulation of synaptic feedback in a neuronal network modulates information transfer and circuit excitability.

Synaptic connections of first-stage visual neurons in the locust Schistocerca gregaria extend evolution of tetrad synapses back 200 million years

The small size of some insects, and the crystalline regularity of their eyes, have made them ideal for large-scale reconstructions of visual circuits. In phylogenetically recent muscomorph flies, like Drosophila, precisely coordinated output to different motion-processing pathways is delivered by photoreceptors (R cells), targeting four different postsynaptic cells at each synapse (tetrad). Tetrads were linked to the evolution of aerial agility. To reconstruct circuits for vision in the larger brain of a locust, a phylogenetically old, flying insect, we adapted serial block-face scanning electron microscopy (SBEM). Locust lamina monopolar cells, L1 and L2, were the main targets of the R cell pathway, L1 and L2 each fed a different circuit, only L1 providing feedback onto R cells. Unexpectedly, 40% of all locust R cell synapses onto both L1 and L2 were tetrads, revealing the emergence of tetrads in an arthropod group present 200 million years before muscomorph flies appeared, coinciding with the early evolution of flight.

Refractory sampling links efficiency and costs of sensory encoding to stimulus statistics

Sensory neurons integrate information about the world, adapting their sampling to its changes. However, little is understood mechanistically how this primary encoding process, which ultimately limits perception, depends upon stimulus statistics. Here, we analyze this open question systematically by using intracellular recordings from fly (Drosophila melanogaster and Coenosia attenuata) photoreceptors and corresponding stochastic simulations from biophysically realistic photoreceptor models. Recordings show that photoreceptors can sample more information from naturalistic light intensity time series (NS) than from Gaussian white-noise (GWN), shuffled-NS or Gaussian-1/f stimuli; integrating larger responses with higher signal-to-noise ratio and encoding efficiency to large bursty contrast changes. Simulations reveal how a photoreceptor's information capture depends critically upon the stochastic refractoriness of its 30,000 sampling units (microvilli). In daylight, refractoriness sacrifices sensitivity to enhance intensity changes in neural image representations, with more and faster microvilli improving encoding. But for GWN and other stimuli, which lack longer dark contrasts of real-world intensity changes that reduce microvilli refractoriness, these performance gains are submaximal and energetically costly. These results provide mechanistic reasons why information sampling is more efficient for natural/naturalistic stimulation and novel insight into the operation, design, and evolution of signaling and code in sensory neurons.

Cognitive components of color vision in honey bees: how conditioning variables modulate color learning and discrimination

Since the demonstration of color vision in honey bees 100 years ago by Karl von Frisch, appetitive conditioning to color targets has been used as the principal way to access behavioral aspects of bee color vision. Yet, analyses on how conditioning parameters affect color perception remained scarce. Conclusions on bee color vision have often been made without referring them to the experimental context in which they were obtained, and thus presented as absolute facts instead of realizing that subtle variations in conditioning procedures might yield different results. Here, we review evidence showing that color learning and discrimination in bees are not governed by immutable properties of their visual system, but depend on how the insects are trained and thus learn a task. The use of absolute or differential conditioning protocols, the presence of aversive reinforcement in differential conditioning and the degrees of freedom of motor components determine dramatic variations in color discrimination. We, thus, suggest top-down attentional modulation of color vision to explain the changes in color learning and discrimination reviewed here. We discuss the possible neural mechanisms of this modulation and conclude that color vision experiments require a careful consideration of how training parameters shape behavioral responses.

Abnormal visual gain control in a Parkinson's disease model

Our understanding of Parkinson's disease (PD) has been revolutionized by the discovery of disease-causing genetic mutations. The most common of these is the G2019S mutation in the LRRK2 kinase gene, which leads to increased kinase activity. However, the link between increased kinase activity and PD is unclear. Previously, we showed that dopaminergic expression of the human LRRK2-G2019S transgene in flies led to an activity-dependent loss of vision in older animals and we hypothesized that this may have been preceded by a failure to regulate neuronal activity correctly in younger animals. To test this hypothesis, we used a sensitive measure of visual function based on frequency-tagged steady-state visually evoked potentials. Spectral analysis allowed us to identify signals from multiple levels of the fly visual system and wild-type visual response curves were qualitatively similar to those from human cortex. Dopaminergic expression of hLRRK2-G2019S increased contrast sensitivity throughout the retinal network. To test whether this was due to increased kinase activity, we fed Drosophila with kinase inhibitors targeted at LRRK2. Contrast sensitivity in both day 1 and day 14 flies was normalized by a novel LRRK2 kinase inhibitor ‘BMPPB-32’. Biochemical and cellular assays suggested that BMPPB-32 would be a more specific kinase inhibitor than LRRK2-IN-1. We confirmed this in vivo, finding that dLRRK⁻ null flies show large off-target effects with LRRK2-IN-1 but not BMPPB-32. Our data link the increased Kinase activity of the G2019S-LRRK2 mutation to neuronal dysfunction and demonstrate the power of the Drosophila visual system in assaying the neurological effects of genetic diseases and therapies.

Contributions of the 12 neuron classes in the fly lamina to motion vision

Motion detection is a fundamental neural computation performed by many sensory systems. In the fly, local motion computation is thought to occur within the first two layers of the visual system, the lamina and medulla. We constructed specific genetic driver lines for each of the 12 neuron classes in the lamina. We then depolarized and hyperpolarized each neuron type and quantified fly behavioral responses to a diverse set of motion stimuli. We found that only a small number of lamina output neurons are essential for motion detection, while most neurons serve to sculpt and enhance these feedforward pathways. Two classes of feedback neurons (C2 and C3), and lamina output neurons (L2 and L4), are required for normal detection of directional motion stimuli. Our results reveal a prominent role for feedback and lateral interactions in motion processing and demonstrate that motion-dependent behaviors rely on contributions from nearly all lamina neuron classes.

Glia-related circadian plasticity in the visual system of Diptera

The circadian changes in morphology of the first visual neuropil or lamina of Diptera represent an example of the neuronal plasticity controlled by the circadian clock (circadian plasticity). It is observed in terminals of the compound eye photoreceptor cells, the peripheral oscillators expressing the clock genes. However, it has been found also in their postsynaptic partners, the L1 and L2 monopolar cells, in which the activity of the clock genes have not yet been detected. The circadian input that the L1 and L2 receive seems to originate not only from the retina photoreceptors and from the circadian pacemaker neurons located in the brain, but also from the glial cells that express the clock genes and thus contain circadian oscillators. This paper summarizes the morphological and biochemical rhythms in glia of the optic lobe, shows how they contribute to circadian plasticity, and discusses how glial clocks may modulate circadian rhythms in the lamina.

Impact and sources of neuronal variability in the fly's motion vision pathway

Nervous systems encode information about dynamically changing sensory input by changes in neuronal activity. Neuronal activity changes, however, also arise from noise sources within and outside the nervous system or from changes of the animal's behavioral state. The resulting variability of neuronal responses in representing sensory stimuli limits the reliability with which animals can respond to stimuli and may thus even affect the chances for survival in certain situations. Relevant sources of noise arising at different stages along the motion vision pathway have been investigated from the sensory input to the initiation of behavioral reactions. Here, we concentrate on the reliability of processing visual motion information in flies. Flies rely on visual motion information to guide their locomotion. They are among the best established model systems for the processing of visual motion information allowing us to bridge the gap between behavioral performance and underlying neuronal computations. It has been possible to directly assess the consequences of noise at major stages of the fly's visual motion processing system on the reliability of neuronal signals. Responses of motion sensitive neurons and their variability have been related to optomotor movements as indicators for the overall performance of visual motion computation. We address whether and how noise already inherent in the stimulus, e.g. photon noise for the visual system, influences later processing stages and to what extent variability at the output level of the sensory system limits behavioral performance. Recent advances in circuit analysis and the progress in monitoring neuronal activity in behaving animals should now be applied to understand how the animal meets the requirements of fast and reliable manoeuvres in naturalistic situations.

Participation of the histamine receptor encoded by the gene hclB (HCLB) in visual sensitivity control: an electroretinographic study in Drosophila melanogaster

PURPOSE

Histaminergic transmission in the first synapse of the visual system in Drosophila melanogaster is mediated by two types of histamine receptors: 1) encoded by the gene hclA (HCLA), which is expressed in the second-order neurons-the large monopolar cells of the lamina, and is absolutely required for forward signal transmission; and 2) encoded by the gene hclB (HCLB), which is expressed in epithelial glia, and is involved in modulation of synaptic transmission from photoreceptors to large monopolar cells. The aim of our study was to establish whether the HCLB receptor-mediated modulation of synaptic transmission 1) contributes to the process of light adaptation, and 2) is involved in the control of the dynamics of sensitivity recovery after short-term light adaptation.

METHODS

The effects of mutations in the gene hclB, encoding the subunits of the histamine receptor HCLB, were studied on 1) the intensity-response (V/logI) function of electroretinographic (ERG) responses under dark adaptation, as well as under three levels of background illumination; and 2) the dynamics of the dark sensitivity recovery after short-term light adaptation.

RESULTS

The amplitude of the photoreceptor component in the electroretinogram (ERG) was not significantly different between the hclB mutants and the wild-type flies, while the amplitude of the ERG ON and OFF transients, representing the activity of the second-order visual cells, was increased in the hclB mutants under both dark and light adaptation. The ON responses were affected to a greater degree. Under a given background, the ON response V/logI function was steeper and the response dynamic range was narrowed. The absolute sensitivity of the two transients was increased, as revealed by the decrease of their thresholds. The relative sensitivity of the transients, assessed by the semisaturation points of their V/logI functions, was decreased in ON responses to long (2 s) stimuli under dark and moderate light adaptation, being unchanged under bright backgrounds. Thus, the shift of the ON response V/logI function along the stimulus intensity axis during light adaptation occurred within a narrower range. The peak latencies of the ERG transients were delayed. The slower kinetics of the ERG transients was also indicated by their lower sensitivity to low-pass filtering, the effect being more pronounced under light adaptation. In wild-type flies, an instant dark sensitivity recovery or postadaptational potentiation of the ERG transients was usually observed after short-term light adaptation. In the hclB mutants the dark sensitivity recovery in similar conditions was significantly delayed.

CONCLUSIONS

The glial histamine receptor HCLB participates in visual sensitivity control at the level of the first synapse of the Drosophila visual system under a wide range of ambient illumination conditions and contributes to the process of light adaptation. The HCLB receptor-mediated modulation of synaptic gain helps avoid response saturation and increases the range of stimulus intensities within which dynamic responses can be generated. The HCLB receptors also speed up the sensitivity recovery after short-term light adaptation and contribute to the mechanism of postadaptational potentiation. They modulate the temporal characteristics of visual responses in a way that improves the temporal resolution of the visual system and reduces redundant (low-frequency) information.

Stochastic, adaptive sampling of information by microvilli in fly photoreceptors

Background

In fly photoreceptors, light is focused onto a photosensitive waveguide, the rhabdomere, consisting of tens of thousands of microvilli. Each microvillus is capable of generating elementary responses, quantum bumps, in response to single photons using a stochastically operating phototransduction cascade. Whereas much is known about the cascade reactions, less is known about how the concerted action of the microvilli population encodes light changes into neural information and how the ultrastructure and biochemical machinery of photoreceptors of flies and other insects evolved in relation to the information sampling and processing they perform.

Results

We generated biophysically realistic fly photoreceptor models, which accurately simulate the encoding of visual information. By comparing stochastic simulations with single cell recordings from Drosophila photoreceptors, we show how adaptive sampling by 30,000 microvilli captures the temporal structure of natural contrast changes. Following each bump, individual microvilli are rendered briefly (∼100–200 ms) refractory, thereby reducing quantum efficiency with increasing intensity. The refractory period opposes saturation, dynamically and stochastically adjusting availability of microvilli (bump production rate: sample rate), whereas intracellular calcium and voltage adapt bump amplitude and waveform (sample size). These adapting sampling principles result in robust encoding of natural light changes, which both approximates perceptual contrast constancy and enhances novel events under different light conditions, and predict information processing across a range of species with different visual ecologies.

Conclusions

These results clarify why fly photoreceptors are structured the way they are and function as they do, linking sensory information to sensory evolution and revealing benefits of stochasticity for neural information processing.

Multiple spectral inputs improve motion discrimination in the Drosophila visual system

Color and motion information are thought to be channeled through separate neural pathways, but it remains unclear whether and how these pathways interact to improve motion perception. In insects, such as Drosophila, it has long been believed that motion information is fed exclusively by one spectral class of photoreceptor, so-called R1 to R6 cells; whereas R7 and R8 photoreceptors, which exist in multiple spectral classes, subserve color vision. Here, we report that R7 and R8 also contribute to the motion pathway. By using electrophysiological, optical, and behavioral assays, we found that R7/R8 information converge with and shape the motion pathway output, explaining flies' broadly tuned optomotor behavior by its composite responses. Our results demonstrate that inputs from photoreceptors of different spectral sensitivities improve motion discrimination, increasing robustness of perception.

Bimodal optomotor response to plaids in blowflies: mechanisms of component selectivity and evidence for pattern selectivity

Many animals estimate their self-motion and the movement of external objects by exploiting panoramic patterns of visual motion. To probe how visual systems process compound motion patterns, superimposed visual gratings moving in different directions, plaid stimuli, have been successfully used in vertebrates. Surprisingly, nothing is known about how visually guided insects process plaids. Here, we explored in the blowfly how the well characterized yaw optomotor reflex and the activity of identified visual interneurons depend on plaid stimuli. We show that contrary to previous expectations, the yaw optomotor reflex shows a bimodal directional tuning for certain plaid stimuli. To understand the neural correlates of this behavior, we recorded the responses of a visual interneuron supporting the reflex, the H1 cell, which was also bimodally tuned to the plaid direction. Using a computational model, we identified the essential neural processing steps required to capture the observed response properties. These processing steps have functional parallels with mechanisms found in the primate visual system, despite different biophysical implementations. By characterizing other visual neurons supporting visually guided behaviors, we found responses that ranged from being bimodally tuned to the stimulus direction (component-selective), to responses that appear to be tuned to the direction of the global pattern (pattern-selective). Our results extend the current understanding of neural mechanisms of motion processing in insects, and indicate that the fly employs a wider range of behavioral responses to multiple motion cues than previously reported.

Large-scale automated histology in the pursuit of connectomes

How does the brain compute? Answering this question necessitates neuronal connectomes, annotated graphs of all synaptic connections within defined brain areas. Further, understanding the energetics of the brain's computations requires vascular graphs. The assembly of a connectome requires sensitive hardware tools to measure neuronal and neurovascular features in all three dimensions, as well as software and machine learning for data analysis and visualization. We present the state of the art on the reconstruction of circuits and vasculature that link brain anatomy and function. Analysis at the scale of tens of nanometers yields connections between identified neurons, while analysis at the micrometer scale yields probabilistic rules of connection between neurons and exact vascular connectivity.

Wiring economy and volume exclusion determine neuronal placement in the Drosophila brain

Wiring economy has successfully explained the individual placement of neurons in simple nervous systems like that of Caenorhabditis elegans [1-3] and the locations of coarser structures like cortical areas in complex vertebrate brains [4]. However, it remains unclear whether wiring economy can explain the placement of individual neurons in brains larger than that of C. elegans. Indeed, given the greater number of neuronal interconnections in larger brains, simply minimizing the length of connections results in unrealistic configurations, with multiple neurons occupying the same position in space. Avoiding such configurations, or volume exclusion, repels neurons from each other, thus counteracting wiring economy. Here we test whether wiring economy together with volume exclusion can explain the placement of neurons in a module of the Drosophila melanogaster brain known as lamina cartridge [5-13]. We used newly developed techniques for semiautomated reconstruction from serial electron microscopy (EM) [14] to obtain the shapes of neurons, the location of synapses, and the resultant synaptic connectivity. We show that wiring length minimization and volume exclusion together can explain the structure of the lamina microcircuit. Therefore, even in brains larger than that of C. elegans, at least for some circuits, optimization can play an important role in individual neuron placement.

The Drosophila SK channel (dSK) contributes to photoreceptor performance by mediating sensitivity control at the first visual network

The contribution of the SK (small-conductance calcium-activated potassium) channel to neuronal functions in complex circuits underlying sensory processing and behavior is largely unknown in the absence of suitable animal models. Here, we generated a Drosophila line that lacks the single highly conserved SK gene in its genome (dSK). In R1-R6 photoreceptors, dSK encodes a slow Ca²⁺-activated K(+) current similar to its mammalian counterparts. Compared with wild-type, dSK(-) photoreceptors and interneurons showed accelerated oscillatory responses and adaptation. These enhanced kinetics were accompanied with more depolarized dSK(-) photoreceptors axons, assigning a role for dSK in network gain control during light-to-dark transitions. However, compensatory network adaptation, through increasing activity between synaptic neighbors, overcame many detriments of missing dSK current enabling dSK(-) photoreceptors to maintain normal information transfer rates to naturalistic stimuli. While demonstrating important functional roles for dSK channel in the visual circuitry, these results also clarify how homeostatically balanced network functions can compensate missing or faulty ion channels.

Compound eyes and retinal information processing in miniature dipteran species match their specific ecological demands

The compound eye of insects imposes a tradeoff between resolution and sensitivity, which should exacerbate with diminishing eye size. Tiny lenses are thought to deliver poor acuity because of diffraction; nevertheless, miniature insects have visual systems that allow a myriad of lifestyles. Here, we investigate whether size constraints result in an archetypal eye design shared between miniature dipterans by comparing the visual performance of the fruit fly Drosophila and the killer fly Coenosia. These closely related species have neural superposition eyes and similar body lengths (3 to 4 mm), but Coenosia is a diurnal aerial predator, whereas slow-flying Drosophila is most active at dawn and dusk. Using in vivo intracellular recordings and EM, we report unique adaptations in the form and function of their photoreceptors that are reflective of their distinct lifestyles. We find that although these species have similar lenses and optical properties, Coenosia photoreceptors have three- to fourfold higher spatial resolution and rate of information transfer than Drosophila. The higher performance in Coenosia mostly results from dramatically diminished light sensors, or rhabdomeres, which reduce pixel size and optical cross-talk between photoreceptors and incorporate accelerated phototransduction reactions. Furthermore, we identify local specializations in the Coenosia eye, consistent with an acute zone and its predatory lifestyle. These results demonstrate how the flexible architecture of miniature compound eyes can evolve to match information processing with ecological demands.

Intrinsic activity in the fly brain gates visual information during behavioral choices

The small insect brain is often described as an input/output system that executes reflex-like behaviors. It can also initiate neural activity and behaviors intrinsically, seen as spontaneous behaviors, different arousal states and sleep. However, less is known about how intrinsic activity in neural circuits affects sensory information processing in the insect brain and variability in behavior. Here, by simultaneously monitoring Drosophila's behavioral choices and brain activity in a flight simulator system, we identify intrinsic activity that is associated with the act of selecting between visual stimuli. We recorded neural output (multiunit action potentials and local field potentials) in the left and right optic lobes of a tethered flying Drosophila, while its attempts to follow visual motion (yaw torque) were measured by a torque meter. We show that when facing competing motion stimuli on its left and right, Drosophila typically generate large torque responses that flip from side to side. The delayed onset (0.1–1 s) and spontaneous switch-like dynamics of these responses, and the fact that the flies sometimes oppose the stimuli by flying straight, make this behavior different from the classic steering reflexes. Drosophila, thus, seem to choose one stimulus at a time and attempt to rotate toward its direction. With this behavior, the neural output of the optic lobes alternates; being augmented on the side chosen for body rotation and suppressed on the opposite side, even though the visual input to the fly eyes stays the same. Thus, the flow of information from the fly eyes is gated intrinsically. Such modulation can be noise-induced or intentional; with one possibility being that the fly brain highlights chosen information while ignoring the irrelevant, similar to what we know to occur in higher animals.