Subcellular mapping of dendritic activity in optic flow processing neurons

A comprehensive neuroanatomical survey of the Drosophila Lobula Plate Tangential Neurons with predictions for their optic flow sensitivity

Flying insects exhibit remarkable navigational abilities controlled by their compact nervous systems. Optic flow, the pattern of changes in the visual scene induced by locomotion, is a crucial sensory cue for robust self-motion estimation, especially during rapid flight. Neurons that respond to specific, large-field optic flow patterns have been studied for decades, primarily in large flies, such as houseflies, blowflies, and hover flies. The best-known optic-flow sensitive neurons are the large tangential cells of the dipteran lobula plate, whose visual-motion responses, and to a lesser extent, their morphology, have been explored using single-neuron neurophysiology. Most of these studies have focused on the large, Horizontal and Vertical System neurons, yet the lobula plate houses a much larger set of 'optic-flow' sensitive neurons, many of which have been challenging to unambiguously identify or to reliably target for functional studies. Here we report the comprehensive reconstruction and identification of the Lobula Plate Tangential Neurons in an Electron Microscopy (EM) volume of a whole Drosophila brain. This catalog of 58 LPT neurons (per brain hemisphere) contains many neurons that are described here for the first time and provides a basis for systematic investigation of the circuitry linking self-motion to locomotion control. Leveraging computational anatomy methods, we estimated the visual motion receptive fields of these neurons and compared their tuning to the visual consequence of body rotations and translational movements. We also matched these neurons, in most cases on a one-for-one basis, to stochastically labeled cells in genetic driver lines, to the mirror-symmetric neurons in the same EM brain volume, and to neurons in an additional EM data set. Using cell matches across data sets, we analyzed the integration of optic flow patterns by neurons downstream of the LPTs and find that most central brain neurons establish sharper selectivity for global optic flow patterns than their input neurons. Furthermore, we found that self-motion information extracted from optic flow is processed in distinct regions of the central brain, pointing to diverse foci for the generation of visual behaviors.

Selective processing of all rotational and translational optic flow directions in the zebrafish pretectum and tectum

Background

The processing of optic flow in the pretectum/accessory optic system allows animals to stabilize retinal images by executing compensatory optokinetic and optomotor behavior. The success of this behavior depends on the integration of information from both eyes to unequivocally identify all possible translational or rotational directions of motion. However, it is still unknown whether the precise direction of ego-motion is already identified in the zebrafish pretectum or later in downstream premotor areas.

Results

Here, we show that the zebrafish pretectum and tectum each contain four populations of motion-sensitive direction-selective (DS) neurons, with each population encoding a different preferred direction upon monocular stimulation. In contrast, binocular stimulation revealed the existence of pretectal and tectal neurons that are specifically tuned to only one of the many possible combinations of monocular motion, suggesting that further downstream sensory processing might not be needed to instruct appropriate optokinetic and optomotor behavior.

Conclusion

Our results suggest that local, task-specific pretectal circuits process DS retinal inputs and carry out the binocular sensory computations necessary for optokinetic and optomotor behavior.

Electronic supplementary material

The online version of this article (10.1186/s12915-019-0648-2) contains supplementary material, which is available to authorized users.

Full reconstruction of large lobula plate tangential cells in Drosophila from a 3D EM dataset

With the advent of neurogenetic methods, the neural basis of behavior is presently being analyzed in more and more detail. This is particularly true for visually driven behavior of Drosophila melanogaster where cell-specific driver lines exist that, depending on the combination with appropriate effector genes, allow for targeted recording, silencing and optogenetic stimulation of individual cell-types. Together with detailed connectomic data of large parts of the fly optic lobe, this has recently led to much progress in our understanding of the neural circuits underlying local motion detection. However, how such local information is combined by optic flow sensitive large-field neurons is still incompletely understood. Here, we aim to fill this gap by a dense reconstruction of lobula plate tangential cells of the fly lobula plate. These neurons collect input from many hundreds of local motion-sensing T4/T5 neurons and connect them to descending neurons or central brain areas. We confirm all basic features of HS and VS cells as published previously from light microscopy. In addition, we identified the dorsal and the ventral centrifugal horizontal, dCH and vCH cell, as well as three VSlike cells, including their distinct dendritic and axonal projection area.

Glutamate Signaling in the Fly Visual System

For a proper understanding of neural circuit function, it is important to know which signals neurons relay to their downstream partners. Calcium imaging with genetically encoded calcium sensors like GCaMP has become the default approach for mapping these responses. How well such measurements represent the true neurotransmitter output of any given cell, however, remains unclear. Here, we demonstrate the viability of the glutamate sensor iGluSnFR for 2-photon in vivo imaging in Drosophila melanogaster and prove its usefulness for estimating spatiotemporal receptive fields in the visual system. We compare the results obtained with iGluSnFR with the ones obtained with GCaMP6f and find that the spatial aspects of the receptive fields are preserved between indicators. In the temporal domain, however, measurements obtained with iGluSnFR reveal the underlying response properties to be much faster than those acquired with GCaMP6f. Our approach thus offers a more accurate description of glutamatergic neurons in the fruit fly.

Sequential Nonlinear Filtering of Local Motion Cues by Global Motion Circuits

Many animals guide their movements using optic flow, the displacement of stationary objects across the retina caused by self-motion. How do animals selectively synthesize a global motion pattern from its local motion components? To what extent does this feature selectivity rely on circuit mechanisms versus dendritic processing? Here we used in vivo calcium imaging to identify pre- and postsynaptic mechanisms for processing local motion signals in global motion detection circuits in Drosophila. Lobula plate tangential cells (LPTCs) detect global motion by pooling input from local motion detectors, T4/T5 neurons. We show that T4/T5 neurons suppress responses to adjacent local motion signals whereas LPTC dendrites selectively amplify spatiotemporal sequences of local motion signals consistent with preferred global patterns. We propose that sequential nonlinear suppression and amplification operations allow optic flow circuitry to simultaneously prevent saturating responses to local signals while creating selectivity for global motion patterns critical to behavior.

Dendritic Ca2+ dynamics and multimodal processing in a cricket antennal interneuron

The integration of stimuli of different modalities is fundamental to information processing within the nervous system. A descending interneuron in the cricket brain, with prominent dendrites in the deutocerebrum, receives input from three sensory modalities: touch of the antennal flagellum, strain of the antennal base, and visual stimulation. Using calcium imaging, we demonstrate that each modality drives a Ca²⁺ increase in a different dendritic region. Moreover, touch of the flagellum is represented in a topographic map along the neuron’s dendrites. Using intracellular recording, we investigated the effects of Ca²⁺ on spike shape through the application of the Ca²⁺ channel antagonist Cd²⁺ and identified probable Ca²⁺-dependent K⁺ currents.

NEW & NOTEWORTHY Different dendritic regions of the cricket brain neuron DBNi1-2 showed localized Ca²⁺ increases when three modalities of stimulation (touch of the flagellum, strain at antennal base, and visual input) were given. Touch stimulation induces localized Ca²⁺ increases according to a topographic map of the antenna. Ca²⁺ appears to activate K⁺ currents in DBNi1-2.

Non-uniform weighting of local motion inputs underlies dendritic computation in the fly visual system

The fly visual system offers a unique opportunity to explore computations performed by single neurons. Two previous studies characterized, in vivo, the receptive field (RF) of the vertical system (VS) cells of the blowfly (calliphora vicina), both intracellularly in the axon, and, independently using Ca²⁺ imaging, in hundreds of distal dendritic branchlets. We integrated this information into detailed passive cable and compartmental models of 3D reconstructed VS cells. Within a given VS cell type, the transfer resistance (TR) from different branchlets to the axon differs substantially, suggesting that they contribute unequally to the shaping of the axonal RF. Weighting the local RFs of all dendritic branchlets by their respective TR yielded a faithful reproduction of the axonal RF. The model also predicted that the various dendritic branchlets are electrically decoupled from each other, thus acting as independent local functional subunits. The study suggests that single neurons in the fly visual system filter dendritic noise and compute the weighted average of their inputs.

Efficient encoding of motion is mediated by gap junctions in the fly visual system

Understanding the computational implications of specific synaptic connectivity patterns is a fundamental goal in neuroscience. In particular, the computational role of ubiquitous electrical synapses operating via gap junctions remains elusive. In the fly visual system, the cells in the vertical-system network, which play a key role in visual processing, primarily connect to each other via axonal gap junctions. This network therefore provides a unique opportunity to explore the functional role of gap junctions in sensory information processing. Our information theoretical analysis of a realistic VS network model shows that within 10 ms following the onset of the visual input, the presence of axonal gap junctions enables the VS system to efficiently encode the axis of rotation, θ, of the fly’s ego motion. This encoding efficiency, measured in bits, is near-optimal with respect to the physical limits of performance determined by the statistical structure of the visual input itself. The VS network is known to be connected to downstream pathways via a subset of triplets of the vertical system cells; we found that because of the axonal gap junctions, the efficiency of this subpopulation in encoding θ is superior to that of the whole vertical system network and is robust to a wide range of signal to noise ratios. We further demonstrate that this efficient encoding of motion by this subpopulation is necessary for the fly's visually guided behavior, such as banked turns in evasive maneuvers. Because gap junctions are formed among the axons of the vertical system cells, they only impact the system’s readout, while maintaining the dendritic input intact, suggesting that the computational principles implemented by neural circuitries may be much richer than previously appreciated based on point neuron models. Our study provides new insights as to how specific network connectivity leads to efficient encoding of sensory stimuli.

Understanding sensory stimuli from the environment and deciding how best to respond to it behaviorally is essential for survival. What makes organisms efficient in encoding these sensory stimuli? This study provides a novel view on this unresolved issue using the visual system of the fly. We show that a specific synaptic connectivity manifested via gap junctions (GJs) among axons in the Vertical System (VS) network leads to particularly high encoding efficiency of the axis of rotation of the fly’s ego motion. Due to these GJs, triplets of VS neurons (the VS5-6-7 triplet), which connect to a downstream motor system, encode motion stimuli at an efficiency close to the physical limit; this efficient encoding is necessary for evasive maneuvers that are critical for the fly to escape predators. We then suggest why GJs in the VS network enable such high encoding efficiency.

Visual Circuits for Direction Selectivity

Images projected onto the retina of an animal eye are rarely still. Instead, they usually contain motion signals originating either from moving objects or from retinal slip caused by self-motion. Accordingly, motion signals tell the animal in which direction a predator, prey, or the animal itself is moving. At the neural level, visual motion detection has been proposed to extract directional information by a delay-and-compare mechanism, representing a classic example of neural computation. Neurons responding selectively to motion in one but not in the other direction have been identified in many systems, most prominently in the mammalian retina and the fly optic lobe. Technological advances have now allowed researchers to characterize these neurons' upstream circuits in exquisite detail. Focusing on these upstream circuits, we review and compare recent progress in understanding the mechanisms that generate direction selectivity in the early visual system of mammals and flies.

In Vivo Imaging Reveals Composite Coding for Diagonal Motion in the Drosophila Visual System

Understanding information coding is important for resolving the functions of visual neural circuits. The motion vision system is a classic model for studying information coding as it contains a concise and complete information-processing circuit. In Drosophila, the axon terminals of motion-detection neurons (T4 and T5) project to the lobula plate, which comprises four regions that respond to the four cardinal directions of motion. The lobula plate thus represents a topographic map on a transverse plane. This enables us to study the coding of diagonal motion by investigating its response pattern. By using in vivo two-photon calcium imaging, we found that the axon terminals of T4 and T5 cells in the lobula plate were activated during diagonal motion. Further experiments showed that the response to diagonal motion is distributed over the following two regions compared to the cardinal directions of motion—a diagonal motion selective response region and a non-selective response region—which overlap with the response regions of the two vector-correlated cardinal directions of motion. Interestingly, the sizes of the non-selective response regions are linearly correlated with the angle of the diagonal motion. These results revealed that the Drosophila visual system employs a composite coding for diagonal motion that includes both independent coding and vector decomposition coding.

Fine and distributed subcellular retinotopy of excitatory inputs to the dendritic tree of a collision-detecting neuron

Individual neurons in several sensory systems receive synaptic inputs organized according to subcellular topographic maps, yet the fine structure of this topographic organization and its relation to dendritic morphology have not been studied in detail. Subcellular topography is expected to play a role in dendritic integration, particularly when dendrites are extended and active. The lobula giant movement detector (LGMD) neuron in the locust visual system is known to receive topographic excitatory inputs on part of its dendritic tree. The LGMD responds preferentially to objects approaching on a collision course and is thought to implement several interesting dendritic computations. To study the fine retinotopic mapping of visual inputs onto the excitatory dendrites of the LGMD, we designed a custom microscope allowing visual stimulation at the native sampling resolution of the locust compound eye while simultaneously performing two-photon calcium imaging on excitatory dendrites. We show that the LGMD receives a distributed, fine retinotopic projection from the eye facets and that adjacent facets activate overlapping portions of the same dendritic branches. We also demonstrate that adjacent retinal inputs most likely make independent synapses on the excitatory dendrites of the LGMD. Finally, we show that the fine topographic mapping can be studied using dynamic visual stimuli. Our results reveal the detailed structure of the dendritic input originating from individual facets on the eye and their relation to that of adjacent facets. The mapping of visual space onto the LGMD's dendrites is expected to have implications for dendritic computation.

Neural Circuit to Integrate Opposing Motions in the Visual Field

When navigating in their environment, animals use visual motion cues as feedback signals that are elicited by their own motion. Such signals are provided by wide-field neurons sampling motion directions at multiple image points as the animal maneuvers. Each one of these neurons responds selectively to a specific optic flow-field representing the spatial distribution of motion vectors on the retina. Here, we describe the discovery of a group of local, inhibitory interneurons in the fruit fly Drosophila key for filtering these cues. Using anatomy, molecular characterization, activity manipulation, and physiological recordings, we demonstrate that these interneurons convey direction-selective inhibition to wide-field neurons with opposite preferred direction and provide evidence for how their connectivity enables the computation required for integrating opposing motions. Our results indicate that, rather than sharpening directional selectivity per se, these circuit elements reduce noise by eliminating non-specific responses to complex visual information.

Seeing the whole picture: A comprehensive imaging approach to functional mapping of circuits in behaving zebrafish

In recent years, the zebrafish has emerged as an appealing model system to tackle questions relating to the neural circuit basis of behavior. This can be attributed not just to the growing use of genetically tractable model organisms, but also in large part to the rapid advances in optical techniques for neuroscience, which are ideally suited for application to the small, transparent brain of the larval fish. Many characteristic features of vertebrate brains, from gross anatomy down to particular circuit motifs and cell-types, as well as conserved behaviors, can be found in zebrafish even just a few days post fertilization, and, at this early stage, the physical size of the brain makes it possible to analyze neural activity in a comprehensive fashion. In a recent study, we used a systematic and unbiased imaging method to record the pattern of activity dynamics throughout the whole brain of larval zebrafish during a simple visual behavior, the optokinetic response (OKR). This approach revealed the broadly distributed network of neurons that were active during the behavior and provided insights into the fine-scale functional architecture in the brain, inter-individual variability, and the spatial distribution of behaviorally relevant signals. Combined with mapping anatomical and functional connectivity, targeted electrophysiological recordings, and genetic labeling of specific populations, this comprehensive approach in zebrafish provides an unparalleled opportunity to study complete circuits in a behaving vertebrate animal.

Near-optimal decoding of transient stimuli from coupled neuronal subpopulations

Coupling between sensory neurons impacts their tuning properties and correlations in their responses. How such coupling affects sensory representations and ultimately behavior remains unclear. We investigated the role of neuronal coupling during visual processing using a realistic biophysical model of the vertical system (VS) cell network in the blow fly. These neurons are thought to encode the horizontal rotation axis during rapid free-flight maneuvers. Experimental findings suggest that neurons of the VS are strongly electrically coupled, and that several downstream neurons driving motor responses to ego-rotation receive inputs primarily from a small subset of VS cells. These downstream neurons must decode information about the axis of rotation from a partial readout of the VS population response. To investigate the role of coupling, we simulated the VS response to a variety of rotating visual scenes and computed optimal Bayesian estimates from the relevant subset of VS cells. Our analysis shows that coupling leads to near-optimal estimates from a subpopulation readout. In contrast, coupling between VS cells has no impact on the quality of encoding in the response of the full population. We conclude that coupling at one level of the fly visual system allows for near-optimal decoding from partial information at the subsequent, premotor level. Thus, electrical coupling may provide a general mechanism to achieve near-optimal information transfer from neuronal subpopulations across organisms and modalities.

Motion as a source of environmental information: a fresh view on biological motion computation by insect brains

Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around ("optic flow") to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and-in many behavioral contexts-less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.

Fly visual course control: behaviour, algorithms and circuits

Understanding how the brain controls behaviour is undisputedly one of the grand goals of neuroscience research, and the pursuit of this goal has a long tradition in insect neuroscience. However, appropriate techniques were lacking for a long time. Recent advances in genetic and recording techniques now allow the participation of identified neurons in the execution of specific behaviours to be interrogated. By focusing on fly visual course control, I highlight what has been learned about the neuronal circuit modules that control visual guidance in Drosophila melanogaster through the use of these techniques.

Depth information in natural environments derived from optic flow by insect motion detection system: a model analysis

Knowing the depth structure of the environment is crucial for moving animals in many behavioral contexts, such as collision avoidance, targeting objects, or spatial navigation. An important source of depth information is motion parallax. This powerful cue is generated on the eyes during translatory self-motion with the retinal images of nearby objects moving faster than those of distant ones. To investigate how the visual motion pathway represents motion-based depth information we analyzed its responses to image sequences recorded in natural cluttered environments with a wide range of depth structures. The analysis was done on the basis of an experimentally validated model of the visual motion pathway of insects, with its core elements being correlation-type elementary motion detectors (EMDs). It is the key result of our analysis that the absolute EMD responses, i.e., the motion energy profile, represent the contrast-weighted nearness of environmental structures during translatory self-motion at a roughly constant velocity. In other words, the output of the EMD array highlights contours of nearby objects. This conclusion is largely independent of the scale over which EMDs are spatially pooled and was corroborated by scrutinizing the motion energy profile after eliminating the depth structure from the natural image sequences. Hence, the well-established dependence of correlation-type EMDs on both velocity and textural properties of motion stimuli appears to be advantageous for representing behaviorally relevant information about the environment in a computationally parsimonious way.