Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: II mechanisms

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.

Optoelectronic graded neurons for bioinspired in-sensor motion perception

Motion processing has proven to be a computational challenge and demands considerable computational resources. Contrast this with the fact that flying insects can agilely perceive real-world motion with their tiny vision system. Here we show that phototransistor arrays can directly perceive different types of motion at sensory terminals, emulating the non-spiking graded neurons of insect vision systems. The charge dynamics of the shallow trapping centres in MoS2 phototransistors mimic the characteristics of graded neurons, showing an information transmission rate of 1,200 bit s-1 and effectively encoding temporal light information. We used a 20 × 20 photosensor array to detect trajectories in the visual field, allowing the efficient perception of the direction and vision saliency of moving objects and achieving 99.2% recognition accuracy with a four-layer neural network. By modulating the charge dynamics of the shallow trapping centres of MoS2, the sensor array can recognize motion with a temporal resolution ranging from 101 to 106 ms.

Multifaceted luminance gain control beyond photoreceptors in Drosophila

Animals navigating in natural environments must handle vast changes in their sensory input. Visual systems, for example, handle changes in luminance at many timescales, from slow changes across the day to rapid changes during active behavior. To maintain luminance-invariant perception, visual systems must adapt their sensitivity to changing luminance at different timescales. We demonstrate that luminance gain control in photoreceptors alone is insufficient to explain luminance invariance at both fast and slow timescales and reveal the algorithms that adjust gain past photoreceptors in the fly eye. We combined imaging and behavioral experiments with computational modeling to show that downstream of photoreceptors, circuitry taking input from the single luminance-sensitive neuron type L3 implements gain control at fast and slow timescales. This computation is bidirectional in that it prevents the underestimation of contrasts in low luminance and overestimation in high luminance. An algorithmic model disentangles these multifaceted contributions and shows that the bidirectional gain control occurs at both timescales. The model implements a nonlinear interaction of luminance and contrast to achieve gain correction at fast timescales and a dark-sensitive channel to improve the detection of dim stimuli at slow timescales. Together, our work demonstrates how a single neuronal channel performs diverse computations to implement gain control at multiple timescales that are together important for navigation in natural environments.

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.

Sustained deep-tissue voltage recording using a fast indicator evolved for two-photon microscopy

Genetically encoded voltage indicators are emerging tools for monitoring voltage dynamics with cell-type specificity. However, current indicators enable a narrow range of applications due to poor performance under two-photon microscopy, a method of choice for deep-tissue recording. To improve indicators, we developed a multiparameter high-throughput platform to optimize voltage indicators for two-photon microscopy. Using this system, we identified JEDI-2P, an indicator that is faster, brighter, and more sensitive and photostable than its predecessors. We demonstrate that JEDI-2P can report light-evoked responses in axonal termini of Drosophila interneurons and the dendrites and somata of amacrine cells of isolated mouse retina. JEDI-2P can also optically record the voltage dynamics of individual cortical neurons in awake behaving mice for more than 30 min using both resonant-scanning and ULoVE random-access microscopy. Finally, ULoVE recording of JEDI-2P can robustly detect spikes at depths exceeding 400 μm and report voltage correlations in pairs of neurons.

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.

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.

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.

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.

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.

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.

Subcellular Imaging of Voltage and Calcium Signals Reveals Neural Processing In Vivo

A mechanistic understanding of neural computation requires determining how information is processed as it passes through neurons and across synapses. However, it has been challenging to measure membrane potential changes in axons and dendrites in vivo. We use in vivo, two-photon imaging of novel genetically encoded voltage indicators, as well as calcium imaging, to measure sensory stimulus-evoked signals in the Drosophila visual system with subcellular resolution. Across synapses, we find major transformations in the kinetics, amplitude, and sign of voltage responses to light. We also describe distinct relationships between voltage and calcium signals in different neuronal compartments, a substrate for local computation. Finally, we demonstrate that ON and OFF selectivity, a key feature of visual processing across species, emerges through the transformation of membrane potential into intracellular calcium concentration. By imaging voltage and calcium signals to map information flow with subcellular resolution, we illuminate where and how critical computations arise.

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.

Naturalistic stimulation changes the dynamic response of action potential encoding in a mechanoreceptor

Naturalistic signals were created from vibrations made by locusts walking on a Sansevieria plant. Both naturalistic and Gaussian noise signals were used to mechanically stimulate VS-3 slit-sense mechanoreceptor neurons of the spider, Cupiennius salei, with stimulus amplitudes adjusted to give similar firing rates for either stimulus. Intracellular microelectrodes recorded action potentials, receptor potential, and receptor current, using current clamp and voltage clamp. Frequency response analysis showed that naturalistic stimulation contained relatively more power at low frequencies, and caused increased neuronal sensitivity to higher frequencies. In contrast, varying the amplitude of Gaussian stimulation did not change neuronal dynamics. Naturalistic stimulation contained less entropy than Gaussian, but signal entropy was higher than stimulus in the resultant receptor current, indicating addition of uncorrelated noise during transduction. The presence of added noise was supported by measuring linear information capacity in the receptor current. Total entropy and information capacity in action potentials produced by either stimulus were much lower than in earlier stages, and limited to the maximum entropy of binary signals. We conclude that the dynamics of action potential encoding in VS-3 neurons are sensitive to the form of stimulation, but entropy and information capacity of action potentials are limited by firing rate.

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.

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.

Design principles of insect and vertebrate visual systems

A century ago, Cajal noted striking similarities between the neural circuits that underlie vision in vertebrates and flies. Over the past few decades, structural and functional studies have provided strong support for Cajal's view. In parallel, genetic studies have revealed some common molecular mechanisms controlling development of vertebrate and fly visual systems and suggested that they share a common evolutionary origin. Here, we review these shared features, focusing on the first several layers-retina, optic tectum (superior colliculus), and lateral geniculate nucleus in vertebrates; and retina, lamina, and medulla in fly. We argue that vertebrate and fly visual circuits utilize common design principles and that taking advantage of this phylogenetic conservation will speed progress in elucidating both functional strategies and developmental mechanisms, as has already occurred in other areas of neurobiology ranging from electrical signaling and synaptic plasticity to neurogenesis and axon guidance.

The functional organisation of glia in the adult brain of Drosophila and other insects

This review annotates and categorises the glia of adult Drosophila and other model insects and analyses the developmental origins of these in the Drosophila optic lobe. The functions of glia in the adult vary depending upon their sub-type and location in the brain. The task of annotating glia is essentially complete only for the glia of the fly's lamina, which comprise: two types of surface glia-the pseudocartridge and fenestrated glia; two types of cortex glia-the distal and proximal satellite glia; and two types of neuropile glia-the epithelial and marginal glia. We advocate that the term subretinal glia, as used to refer to both pseudocartridge and fenestrated glia, be abandoned. Other neuropiles contain similar glial subtypes, but other than the antennal lobes these have not been described in detail. Surface glia form the blood brain barrier, regulating the flow of substances into and out of the nervous system, both for the brain as a whole and the optic neuropiles in particular. Cortex glia provide a second level of barrier, wrapping axon fascicles and isolating neuronal cell bodies both from neighbouring brain regions and from their underlying neuropiles. Neuropile glia can be generated in the adult and a subtype, ensheathing glia, are responsible for cleaning up cellular debris during Wallerian degeneration. Both the neuropile ensheathing and astrocyte-like glia may be involved in clearing neurotransmitters from the extracellular space, thus modifying the levels of histamine, glutamate and possibly dopamine at the synapse to ultimately affect behaviour.

Overexpressing temperature-sensitive dynamin decelerates phototransduction and bundles microtubules in Drosophila photoreceptors

shibire(ts1), a temperature-sensitive mutation of the Drosophila gene encoding a Dynamin orthologue, blocks vesicle endocytosis and thus synaptic transmission, at elevated, or restrictive temperatures. By targeted Gal4 expression, UAS-shibire(ts1) has been used to dissect neuronal circuits. We investigated the effects of UAS-shibire(ts1) overexpression in Drosophila photoreceptors at permissive (19 degrees C) and restrictive (31 degrees C) temperatures. At 19 degrees C, overexpression of UAS-shi(ts1) causes decelerated phototransduction and reduced neurotransmitter release. This phenotype is exacerbated with dark adaptation, age and in white mutants. Photoreceptors overexpressing UAS-shibire(ts1) contain terminals with widespread vacuolated mitochondria, reduced numbers of vesicles and bundled microtubules. Immuno-electron microscopy reveals that the latter are dynamin coated. Further, the microtubule phenotype is not restricted to photoreceptors, as UAS-shibire(ts1) overexpression in lamina cells also bundles microtubules. We conclude that dynamin has multiple functions that are interrupted by UAS-shibire(ts1) overexpression in Drosophila photoreceptors, destabilizing their neural communication irreversibly at previously reported permissive temperatures.

Network adaptation improves temporal representation of naturalistic stimuli in Drosophila eye: I dynamics

Because of the limited processing capacity of eyes, retinal networks must adapt constantly to best present the ever changing visual world to the brain. However, we still know little about how adaptation in retinal networks shapes neural encoding of changing information. To study this question, we recorded voltage responses from photoreceptors (R1–R6) and their output neurons (LMCs) in the Drosophila eye to repeated patterns of contrast values, collected from natural scenes. By analyzing the continuous photoreceptor-to-LMC transformations of these graded-potential neurons, we show that the efficiency of coding is dynamically improved by adaptation. In particular, adaptation enhances both the frequency and amplitude distribution of LMC output by improving sensitivity to under-represented signals within seconds. Moreover, the signal-to-noise ratio of LMC output increases in the same time scale. We suggest that these coding properties can be used to study network adaptation using the genetic tools in Drosophila, as shown in a companion paper (Part II).