Processing of horizontal optic flow in three visual interneurons of the Drosophila brain

Dendrite architecture determines mitochondrial distribution patterns in vivo

Neuronal morphology influences synaptic connectivity and neuronal signal processing. However, it remains unclear how neuronal shape affects steady-state distributions of organelles like mitochondria. In this work, we investigated the link between mitochondrial transport and dendrite branching patterns by combining mathematical modeling with in vivo measurements of dendrite architecture, mitochondrial motility, and mitochondrial localization patterns in Drosophila HS (horizontal system) neurons. In our model, different forms of morphological and transport scaling rules-which set the relative thicknesses of parent and daughter branches at each junction in the dendritic arbor and link mitochondrial motility to branch thickness-predict dramatically different global mitochondrial localization patterns. We show that HS dendrites obey the specific subset of scaling rules that, in our model, lead to realistic mitochondrial distributions. Moreover, we demonstrate that neuronal activity does not affect mitochondrial transport or localization, indicating that steady-state mitochondrial distributions are hard-wired by the architecture of the neuron.

Neural mechanisms to incorporate visual counterevidence in self-movement estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can be spuriously triggered by visual motion created by objects moving in the world. Here, we show that stationary patterns on the retina, which constitute evidence against observer rotation, suppress inappropriate stabilizing rotational behavior in the fruit fly Drosophila. In silico experiments show that artificial neural networks (ANNs) that are optimized to distinguish observer movement from external object motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's local motion and optic-flow detectors. Our results show how the fly brain incorporates negative evidence to improve heading stability, exemplifying how a compact brain exploits geometrical constraints of the visual world.

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.

Circuits for self-motion estimation and walking control in Drosophila

The brain's evolution and operation are inextricably linked to animal movement, and critical functions, such as motor control, spatial perception, and navigation, rely on precise knowledge of body movement. Such internal estimates of self-motion emerge from the integration of mechanosensory and visual feedback with motor-related signals. Thus, this internal representation likely depends on the activity of circuits distributed across the central nervous system. However, the circuits responsible for self-motion estimation, and the exact mechanisms by which motor-sensory coordination occurs within these circuits remain poorly understood. Recent technological advances have positioned Drosophila melanogaster as an advantageous model for investigating the emergence, maintenance, and utilization of self-motion representations during naturalistic walking behaviors. In this review, I will illustrate how the adult fly is providing insights into the fundamental problems of self-motion computations and walking control, which have relevance for all animals.

Neural mechanisms to incorporate visual counterevidence in self motion estimation

In selecting appropriate behaviors, animals should weigh sensory evidence both for and against specific beliefs about the world. For instance, animals measure optic flow to estimate and control their own rotation. However, existing models of flow detection can confuse the movement of external objects with genuine self motion. Here, we show that stationary patterns on the retina, which constitute negative evidence against self rotation, are used by the fruit fly Drosophila to suppress inappropriate stabilizing rotational behavior. In silico experiments show that artificial neural networks optimized to distinguish self and world motion similarly detect stationarity and incorporate negative evidence. Employing neural measurements and genetic manipulations, we identified components of the circuitry for stationary pattern detection, which runs parallel to the fly's motion- and optic flow-detectors. Our results exemplify how the compact brain of the fly incorporates negative evidence to improve heading stability, exploiting geometrical constraints of the visual world.

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.

Parallel motion vision pathways in the brain of a tropical bee

Spatial orientation is a prerequisite for most behaviors. In insects, the underlying neural computations take place in the central complex (CX), the brain's navigational center. In this region different streams of sensory information converge to enable context-dependent navigational decisions. Accordingly, a variety of CX input neurons deliver information about different navigation-relevant cues. In bees, direction encoding polarized light signals converge with translational optic flow signals that are suited to encode the flight speed of the animals. The continuous integration of speed and directions in the CX can be used to generate a vector memory of the bee's current position in space in relation to its nest, i.e., perform path integration. This process depends on specific, complex features of the optic flow encoding CX input neurons, but it is unknown how this information is derived from the visual periphery. Here, we thus aimed at gaining insight into how simple motion signals are reshaped upstream of the speed encoding CX input neurons to generate their complex features. Using electrophysiology and anatomical analyses of the halictic bees Megalopta genalis and Megalopta centralis, we identified a wide range of motion-sensitive neurons connecting the optic lobes with the central brain. While most neurons formed pathways with characteristics incompatible with CX speed neurons, we showed that one group of lobula projection neurons possess some physiological and anatomical features required to generate the visual responses of CX optic-flow encoding neurons. However, as these neurons cannot explain all features of CX speed cells, local interneurons of the central brain or alternative input cells from the optic lobe are additionally required to construct inputs with sufficient complexity to deliver speed signals suited for path integration in bees.

Muscles that move the retina augment compound eye vision in Drosophila

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

Motion vision: Drosophila neural pathways that go with the visual flow

Processing visual motion cues to interpret self-motion, the movement of others, and the environment's structure is vital to all animals, whether prey or predator. A new study in Drosophila identifies multiple pathways likely contributing to visual motion-dependent computations and behaviors.

Neuronal circuits integrating visual motion information in Drosophila melanogaster

The detection of visual motion enables sophisticated animal navigation, and studies on flies have provided profound insights into the cellular and circuit bases of this neural computation. The fly's directionally selective T4 and T5 neurons encode ON and OFF motion, respectively. Their axons terminate in one of the four retinotopic layers in the lobula plate, where each layer encodes one of the four directions of motion. Although the input circuitry of the directionally selective neurons has been studied in detail, the synaptic connectivity of circuits integrating T4/T5 motion signals is largely unknown. Here, we report a 3D electron microscopy reconstruction, wherein we comprehensively identified T4/T5's synaptic partners in the lobula plate, revealing a diverse set of new cell types and attributing new connectivity patterns to the known cell types. Our reconstruction explains how the ON- and OFF-motion pathways converge. T4 and T5 cells that project to the same layer connect to common synaptic partners and comprise a core motif together with bilayer interneurons, detailing the circuit basis for computing motion opponency. We discovered pathways that likely encode new directions of motion by integrating vertical and horizontal motion signals from upstream T4/T5 neurons. Finally, we identify substantial projections into the lobula, extending the known motion pathways and suggesting that directionally selective signals shape feature detection there. The circuits we describe enrich the anatomical basis for experimental and computations analyses of motion vision and bring us closer to understanding complete sensory-motor pathways.

Walking strides direct rapid and flexible recruitment of visual circuits for course control in Drosophila

Flexible mapping between activity in sensory systems and movement parameters is a hallmark of motor control. This flexibility depends on the continuous comparison of short-term postural dynamics and the longer-term goals of an animal, thereby necessitating neural mechanisms that can operate across multiple timescales. To understand how such body-brain interactions emerge across timescales to control movement, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We show that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical for stride-by-stride steering adjustments driven by the visual circuit, and, at longer timescales, it provides information about the moving body’s state to flexibly recruit the visual circuit for course control. Thus, our findings demonstrate the presence of an elegant stride-based mechanism operating at multiple timescales for context-dependent course control. We propose that this mechanism functions as a general basis for the adaptive control of locomotion.

•

HS cells receive stride-coupled signals via ascending neurons

•

The stride-coupled signals reflect an internal motor context

•

Motor context modulates HS cells at multiple timescales

•

HS cells drive rapid steering depending on motor context

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

Planning, Designing, and Managing Green Roofs and Green Walls for Public Health – An Ecosystem Services Approach

Installing green roofs and green walls in urban areas is suggested to supply multiple ecosystem services of benefit to human health and well-being. In a three-step literature review, we examined current knowledge on the link between public health and green roofs and green walls. A systematic search identified 69 scientific articles on green roofs/walls with a public health discourse. These articles were categorized according to type of health path covered (reduction of temperature, air pollution, noise or environmental appraisal) and coverage of issues of relevance for strategies on planning, design/construction, and maintenance of green roofs and green walls. Articles identified through the structured search were complemented with reviews (with no explicit public health rationale) covering reduction of noise, temperature, or air pollution and environmental appraisal. Other relevant studies were identified through snowballing. Several of the articles provided guidelines for optimizing the effect of green roofs/walls in supporting ecosystem services and maximizing well-being benefits to support health pathways identified. These included specifications about planning issues, with recommended spatial allocation (locations where people live, sun-exposed for maximum ambient temperature reduction) and with physical access needed for environmental appraisal. Recommendations regarding design parameters covered substrate depth (deeper generally being better), plant choices (more diverse roofs providing more services), and maintenance issues (moist substrate positively correlated with heat reduction).

Populations of local direction-selective cells encode global motion patterns generated by self-motion

Self-motion generates visual patterns on the eye that are important for navigation. These optic flow patterns are encoded by the population of local direction–selective cells in the mouse retina, whereas in flies, local direction–selective T4/T5 cells are thought to be uniformly tuned. How complex global motion patterns can be computed downstream is unclear. We show that the population of T4/T5 cells in Drosophila encodes global motion patterns. Whereas the mouse retina encodes four types of optic flow, the fly visual system encodes six. This matches the larger number of degrees of freedom and the increased complexity of translational and rotational motion patterns during flight. The four uniformly tuned T4/T5 subtypes described previously represent a local subset of the population. Thus, a population code for global motion patterns appears to be a general coding principle of visual systems that matches local motion responses to modes of the animal’s movement.

Suppression of motion vision during course-changing, but not course-stabilizing, navigational turns

From mammals to insects, locomotion has been shown to strongly modulate visual-system physiology. Does the manner in which a locomotor act is initiated change the modulation observed? We performed patch-clamp recordings from motion-sensitive visual neurons in tethered, flying Drosophila. We observed motor-related signals in flies performing flight turns in rapid response to looming discs and also during spontaneous turns, but motor-related signals were weak or non-existent in the context of turns made in response to brief pulses of unidirectional visual motion (i.e., optomotor responses). Thus, the act of a locomotor turn is variably associated with modulation of visual processing. These results can be understood via the following principle: suppress visual responses during course-changing, but not course-stabilizing, navigational turns. This principle is likely to apply broadly-even to mammals-whenever visual cells whose activity helps to stabilize a locomotor trajectory or the visual gaze angle are targeted for motor modulation.

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.

Insect inspired vision-based velocity estimation through spatial pooling of optic flow during linear motion

Insects rely on the perception of image motion, or optic flow, to estimate their velocity relative to nearby objects. This information provides important sensory input for avoiding obstacles. However, certain behaviors, such as estimating the absolute distance to a landing target, accurately measuring absolute distance traveled, and estimating the ambient wind speed require decoupling optic flow into its component parts: absolute ground velocity and distance to nearby objects. Behavioral experiments suggest that insects perform these calculations, but their mechanism for doing so remains unknown. Here we present a novel algorithm that combines the geometry of dynamic forward motion with known features of insect visual processing to provide a hypothesis for how insects mightdirectlyestimate absolute ground velocity from a combination of optic flow and acceleration information. Our robotics-inspired-biology approach reveals three critical requirements. First, absolute ground velocity can only be directly estimated from optic flow during times of active acceleration and deceleration. Second, spatial pooling of optic flow across a receptive field helps to alleviate the effects of noise and/or low resolution visual systems. Third, averaging velocity estimates from multiple receptive fields further helps to reject noise. Our algorithm provides a hypothesis for how insects might estimate absolute velocity from vision during active maneuvers, and also provides a theoretical framework for designing fast analog circuitry for efficient state estimation that can be applied to insect-sized robots.

Stabilizing responses to sideslip disturbances in Drosophila melanogaster are modulated by the density of moving elements on the ground

Stabilizing responses to sideslip disturbances are a critical part of the flight control system in flies. While strongly mediated by mechanoreception, much of the final response results from the wide-field motion detection system associated with vision. In order to be effective, these responses must match the disturbance they are aimed to correct. To do this, flies must estimate the velocity of the disturbance, although it is not known how they accomplish this task when presented with natural images or dot fields. The recent finding, that motion parallax in dot fields can modulate stabilizing responses only if perceived below the fly, raises the question of whether other image statistics are also processed differently between eye regions. One such parameter is the density of elements moving in translational optic flow. Depending on the habitat, there might be strong differences in the density of elements providing information about self-motion above and below the fly, which in turn could act as selective pressures tuning the visual system to process this parameter on a regional basis. By presenting laterally moving dot fields of different densities we found that, in Drosophila melanogaster, the amplitude of the stabilizing response is significantly affected by the number of elements in the field of view. Flies countersteer strongly within a relatively low and narrow range of element densities. But this effect is exclusive to the ventral region of the eye, and dorsal stimuli elicit an unaltered and stereotypical response regardless of the density of elements in the flow. This highlights local specialization of the eye and suggests the lower region may play a more critical role in translational flight stabilization.

Parallel Visual Pathways with Topographic versus Nontopographic Organization Connect the Drosophila Eyes to the Central Brain

One hallmark of the visual system is a strict retinotopic organization from the periphery toward the central brain, where functional imaging in Drosophila revealed a spatially accurate representation of visual cues in the central complex. This raised the question how, on a circuit level, the topographic features are implemented, as the majority of visual neurons enter the central brain converge in optic glomeruli. We discovered a spatial segregation of topographic versus nontopographic projections of distinct classes of medullo-tubercular (MeTu) neurons into a specific visual glomerulus, the anterior optic tubercle (AOTU). These parallel channels synapse onto different tubercular-bulbar (TuBu) neurons, which in turn relay visual information onto specific central complex ring neurons in the bulb neuropil. Hence, our results provide the circuit basis for spatially accurate representation of visual information and highlight the AOTU's role as a prominent relay station for spatial information from the retina to the central brain.

•

A Drosophila visual circuit conveys input from the periphery to the central brain

•

Several synaptic pathways form parallel channels using the anterior optic tubercle

•

Some pathways maintain topographic relationships across several synaptic steps

•

Different target neurons in the central brain are identified

Active vision shapes and coordinates flight motor responses in flies

Animals use active sensing to respond to sensory inputs and guide future motor decisions. In flight, flies generate a pattern of head and body movements to stabilize gaze. How the brain relays visual information to control head and body movements and how active head movements influence downstream motor control remains elusive. Using a control theoretic framework, we studied the optomotor gaze stabilization reflex in tethered flight and quantified how head movements stabilize visual motion and shape wing steering efforts in fruit flies (Drosophila). By shaping visual inputs, head movements increased the gain of wing steering responses and coordination between stimulus and wings, pointing to a tight coupling between head and wing movements. Head movements followed the visual stimulus in as little as 10 ms-a delay similar to the human vestibulo-ocular reflex-whereas wing steering responses lagged by more than 40 ms. This timing difference suggests a temporal order in the flow of visual information such that the head filters visual information eliciting downstream wing steering responses. Head fixation significantly decreased the mechanical power generated by the flight motor by reducing wingbeat frequency and overall thrust. By simulating an elementary motion detector array, we show that head movements shift the effective visual input dynamic range onto the sensitivity optimum of the motion vision pathway. Taken together, our results reveal a transformative influence of active vision on flight motor responses in flies. Our work provides a framework for understanding how to coordinate moving sensors on a moving body.

SPARC enables genetic manipulation of precise proportions of cells

Many experimental approaches rely on controlling gene expression in select subsets of cells within an individual animal. However, reproducibly targeting transgene expression to specific fractions of a genetically defined cell type is challenging. We developed Sparse Predictive Activity through Recombinase Competition (SPARC), a generalizable toolkit that can express any effector in precise proportions of post-mitotic cells in Drosophila. Using this approach, we demonstrate targeted expression of many effectors in several cell types and apply these tools to calcium imaging of individual neurons and optogenetic manipulation of sparse cell populations in vivo.

Object-Displacement-Sensitive Visual Neurons Drive Freezing in Drosophila

Visual systems are often equipped with neurons that detect small moving objects, which may represent prey, predators, or conspecifics. Although the processing properties of those neurons have been studied in diverse organisms, links between the proposed algorithms and animal behaviors or circuit mechanisms remain elusive. Here, we have investigated behavioral function, computational algorithm, and neurochemical mechanisms of an object-selective neuron, LC11, in Drosophila. With genetic silencing and optogenetic activation, we show that LC11 is necessary for a visual object-induced stopping behavior in walking flies, a form of short-term freezing, and its activity can promote stopping. We propose a new quantitative model for small object selectivity based on the physiology and anatomy of LC11 and its inputs. The model accurately reproduces LC11 responses by pooling fast-adapting, tightly size-tuned inputs. Direct visualization of neurotransmitter inputs to LC11 confirmed the model conjectures about upstream processing. Our results demonstrate how adaptation can enhance selectivity for behaviorally relevant, dynamic visual features.

Ventral motion parallax enhances fruit fly steering to visual sideslip

Flies and other insects use incoherent motion (parallax) to the front and sides to measure distances and identify obstacles during translation. Although additional depth information could be drawn from below, there is no experimental proof that they use it. The finding that blowflies encode motion disparities in their ventral visual fields suggests this may be an important region for depth information. We used a virtual flight arena to measure fruit fly responses to optic flow. The stimuli appeared below (n = 51) or above the fly (n = 44), at different speeds, with or without parallax cues. Dorsal parallax does not affect responses, and similar motion disparities in rotation have no effect anywhere in the visual field. But responses to strong ventral sideslip (206° s⁻¹) change drastically depending on the presence or absence of parallax. Ventral parallax could help resolve ambiguities in cluttered motion fields, and enhance corrective responses to nearby objects.

The diversity of lobula plate tangential cells (LPTCs) in the Drosophila motion vision system

To navigate through the environment, animals rely on visual feedback to control their movements relative to their surroundings. In dipteran flies, visual feedback is provided by the wide-field motion-sensitive neurons in the visual system called lobula plate tangential cells (LPTCs). Understanding the role of LPTCs in fly behaviors can address many fundamental questions on how sensory circuits guide behaviors. The blowfly was estimated to have ~ 60 LPTCs, but only a few have been identified in Drosophila. We conducted a Gal4 driver screen and identified five LPTC subtypes in Drosophila, based on their morphological characteristics: LPTCs have large arborizations in the lobula plate and project to the central brain. We compared their morphologies to the blowfly LPTCs and named them after the most similar blowfly cells: CH, H1, H2, FD1 and FD3, and V1. We further characterized their pre- and post-synaptic organizations, as well as their neurotransmitter profiles. These anatomical features largely agree with the anatomy and function of their likely blowfly counterparts. Nevertheless, several anatomical details indicate the Drosophila LPTCs may have more complex functions. Our characterization of these five LPTCs in Drosophila will facilitate further functional studies to understand their roles in the visual circuits that instruct fly behaviors.

Visual experience drives sleep need in Drosophila

Sleep optimizes waking behavior, however, waking experience may also influence sleep. We used the fruit fly Drosophila melanogaster to investigate the relationship between visual experience and sleep in wild-type and mutant flies. We found that the classical visual mutant, optomotor-blind (omb), which has undeveloped horizontal system/vertical system (HS/VS) motion-processing cells and are defective in motion and visual salience perception, showed dramatically reduced and less consolidated sleep compared to wild-type flies. In contrast, optogenetic activation of the HS/VS motion-processing neurons in wild-type flies led to an increase in sleep following the activation, suggesting an increase in sleep pressure. Surprisingly, exposing wild-type flies to repetitive motion stimuli for extended periods did not increase sleep pressure. However, we observed that exposing flies to more complex image sequences from a movie led to more consolidated sleep, particularly when images were randomly shuffled through time. Our results suggest that specific forms of visual experience that involve motion circuits and complex, nonrepetitive imagery, drive sleep need in Drosophila.

Extreme Compartmentalization in a Drosophila Amacrine Cell

A neuron is conventionally regarded as a single processing unit. It receives input from one or several presynaptic cells, transforms these signals, and transmits one output signal to its postsynaptic partners. Exceptions exist: amacrine cells in the mammalian retina [1-3] or interneurons in the locust mesothoracic ganglion [4] are thought to represent many electrically isolated microcircuits within one neuron. An extreme case of such an amacrine cell has recently been described in the Drosophila visual system. This cell, called CT1, reaches into two neuropils of the optic lobe, where it visits each of 700 repetitive columns, thereby covering the whole visual field [5, 6]. Due to its unusual morphology, CT1 has been suspected to perform local computations [6, 7], but this has never been proven. Using 2-photon calcium imaging and visual stimulation, we find highly compartmentalized retinotopic response properties in neighboring terminals of CT1, with each terminal acting as an independent functional unit. Model simulations demonstrate that this extreme case of compartmentalization is at the biophysical limit of neural computation.

Transcriptional control of morphological properties of direction-selective T4/T5 neurons in Drosophila

In the Drosophila visual system, T4/T5 neurons represent the first stage of computation of the direction of visual motion. T4 and T5 neurons exist in four subtypes, each responding to motion in one of the four cardinal directions and projecting axons into one of the four lobula plate layers. However, all T4/T5 neurons share properties essential for sensing motion. How T4/T5 neurons acquire their properties during development is poorly understood. We reveal that the transcription factors SoxN and Sox102F control the acquisition of properties common to all T4/T5 neuron subtypes, i.e. the layer specificity of dendrites and axons. Accordingly, adult flies are motion blind after disruption of SoxN or Sox102F in maturing T4/T5 neurons. We further find that the transcription factors Ato and Dac are redundantly required in T4/T5 neuron progenitors for SoxN and Sox102F expression in T4/T5 neurons, linking the transcriptional programmes specifying progenitor identity to those regulating the acquisition of morphological properties in neurons. Our work will help to link structure, function and development in a neuronal type performing a computation that is conserved across vertebrate and invertebrate visual systems.

Bi-directional Control of Walking Behavior by Horizontal Optic Flow Sensors

Moving animals experience constant sensory feedback, such as panoramic image shifts on the retina, termed optic flow. Underlying neuronal signals are thought to be important for exploratory behavior by signaling unintended course deviations and by providing spatial information about the environment [1, 2]. Particularly in insects, the encoding of self-motion-related optic flow is well understood [1-5]. However, a gap remains in understanding how the associated neuronal activity controls locomotor trajectories. In flies, visual projection neurons belonging to two groups encode panoramic horizontal motion: horizontal system (HS) cells respond with depolarization to front-to-back motion and hyperpolarization to the opposite direction [6, 7], and other neurons have the mirror-symmetrical response profile [6, 8, 9]. With primarily monocular sensitivity, the neurons' responses are ambiguous for different rotational and translational self-movement components. Such ambiguities can be greatly reduced by combining signals from both eyes [10-12] to determine turning and movement speed [13-16]. Here, we explore the underlying functional logic by optogenetic HS cell manipulation in tethered walking Drosophila. We show that de- and hyperpolarization evoke opposite turning behavior, indicating that both direction-selective signals are transmitted to descending pathways for course control. Further experiments reveal a negative effect of bilaterally symmetric de- and hyperpolarization on walking velocity. Our results are therefore consistent with a functional architecture in which the HS cells' membrane potential influences walking behavior bi-directionally via two decelerating pathways.

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.

Visual Control of Walking Speed in Drosophila

An animal's self-motion generates optic flow across its retina, and it can use this visual signal to regulate its orientation and speed through the world. While orientation control has been studied extensively in Drosophila and other insects, much less is known about the visual cues and circuits that regulate translational speed. Here, we show that flies regulate walking speed with an algorithm that is tuned to the speed of visual motion, causing them to slow when visual objects are nearby. This regulation does not depend strongly on the spatial structure or the direction of visual stimuli, making it algorithmically distinct from the classic computation that controls orientation. Despite the different algorithms, the visual circuits that regulate walking speed overlap with those that regulate orientation. Taken together, our findings suggest that walking speed is controlled by a hierarchical computation that combines multiple motion detectors with distinct tunings. VIDEO ABSTRACT.

Multisensory Control of Orientation in Tethered Flying Drosophila

A longstanding goal of systems neuroscience is to quantitatively describe how the brain integrates sensory cues over time. Here, we develop a closed-loop orienting paradigm in Drosophila to study the algorithms by which cues from two modalities are integrated during ongoing behavior. We find that flies exhibit two behaviors when presented simultaneously with an attractive visual stripe and aversive wind cue. First, flies perform a turn sequence where they initially turn away from the wind but later turn back toward the stripe, suggesting dynamic sensory processing. Second, turns toward the stripe are slowed by the presence of competing wind, suggesting summation of turning drives. We develop a model in which signals from each modality are filtered in space and time to generate turn commands and then summed to produce ongoing orienting behavior. This computational framework correctly predicts behavioral dynamics for a range of stimulus intensities and spatial arrangements.

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.

Apparent Motion Perception in the Praying Mantis: Psychophysics and Modelling

Simple Summary

Computer monitors, smart phone screens, and other forms of digital displays present a series of still images (frames) in which objects are displaced in small steps, tricking us into perceiving smooth motion. This illusion is referred to as “apparent motion”. For motion to be perceived, the magnitude of each displacement step must be smaller than a certain limit, referred to as Dmax. Previous studies have investigated the relationship between this limit and object size in humans and found that the maximum displacement is larger for larger objects than for smaller ones. In this work, we investigated the same relationship in the praying mantis Sphodromantis lineola by presenting them with moving random chequerboard patterns on a computer monitor. Even though motion perception in humans and insects are believed to be explained equally well by the same underlying model, we found that Dmax scales differently with object size in mantids. These results suggest that there may be qualitative differences in how mantids perceive apparent motion compared to humans.

Abstract

Apparent motion is the perception of motion created by rapidly presenting still frames in which objects are displaced in space. Observers can reliably discriminate the direction of apparent motion when inter-frame object displacement is below a certain limit, Dmax. Earlier studies of motion perception in humans found that Dmax is lower-bounded at around 15 arcmin, and thereafter scales with the size of the spatial elements in the images. Here, we run corresponding experiments in the praying mantis Sphodromantis lineola to investigate how Dmax scales with the element size. We use random moving chequerboard patterns of varying element and displacement step sizes to elicit the optomotor response, a postural stabilization mechanism that causes mantids to lean in the direction of large-field motion. Subsequently, we calculate Dmax as the displacement step size corresponding to a 50% probability of detecting an optomotor response in the same direction as the stimulus. Our main findings are that the mantis Dmax scales roughly as a square-root of element size and that, in contrast to humans, it is not lower-bounded. We present two models to explain these observations: a simple high-level model based on motion energy in the Fourier domain and a more-detailed one based on the Reichardt Detector. The models present complementary intuitive and physiologically-realistic accounts of how Dmax scales with the element size in insects. We conclude that insect motion perception is limited by only a single stage of spatial filtering, reflecting the optics of the compound eye. In contrast, human motion perception reflects a second stage of spatial filtering, at coarser scales than imposed by human optics, likely corresponding to the magnocellular pathway. After this spatial filtering, mantis and human motion perception and Dmax are qualitatively very similar.

A biophysical mechanism for preferred direction enhancement in fly motion vision

Seeing the direction of motion is essential for survival of all sighted animals. Consequently, nerve cells that respond to visual stimuli moving in one but not in the opposite direction, so-called 'direction-selective' neurons, are found abundantly. In general, direction selectivity can arise by either signal amplification for stimuli moving in the cell's preferred direction ('preferred direction enhancement'), signal suppression for stimuli moving along the opposite direction ('null direction suppression'), or a combination of both. While signal suppression can be readily implemented in biophysical terms by a hyperpolarization followed by a rectification corresponding to the nonlinear voltage-dependence of the Calcium channel, the biophysical mechanism for signal amplification has remained unclear so far. Taking inspiration from the fly, I analyze a neural circuit where a direction-selective ON-cell receives inhibitory input from an OFF cell on the preferred side of the dendrite, while excitatory ON-cells contact the dendrite centrally. This way, an ON edge moving along the cell's preferred direction suppresses the inhibitory input, leading to a release from inhibition in the postsynaptic cell. The benefit of such a two-fold signal inversion lies in the resulting increase of the postsynaptic cell's input resistance, amplifying its response to a subsequent excitatory input signal even with a passive dendrite, i.e. without voltage-gated ion channels. A motion detector implementing this mechanism together with null direction suppression shows a high degree of direction selectivity over a large range of temporal frequency, narrow directional tuning, and a large signal-to-noise ratio.

Neural mechanisms underlying sensitivity to reverse-phi motion in the fly

Optical illusions provide powerful tools for mapping the algorithms and circuits that underlie visual processing, revealing structure through atypical function. Of particular note in the study of motion detection has been the reverse-phi illusion. When contrast reversals accompany discrete movement, detected direction tends to invert. This occurs across a wide range of organisms, spanning humans and invertebrates. Here, we map an algorithmic account of the phenomenon onto neural circuitry in the fruit fly Drosophila melanogaster. Through targeted silencing experiments in tethered walking flies as well as electrophysiology and calcium imaging, we demonstrate that ON- or OFF-selective local motion detector cells T4 and T5 are sensitive to certain interactions between ON and OFF. A biologically plausible detector model accounts for subtle features of this particular form of illusory motion reversal, like the re-inversion of turning responses occurring at extreme stimulus velocities. In light of comparable circuit architecture in the mammalian retina, we suggest that similar mechanisms may apply even to human psychophysics.

Sensation during Active Behaviors

A substantial portion of our sensory experience happens during active behaviors such as walking around or paying attention. How do sensory systems work during such behaviors? Neural processing in sensory systems can be shaped by behavior in multiple ways ranging from a modulation of responsiveness or sharpening of tuning to a dynamic change of response properties or functional connectivity. Here, we review recent findings on the modulation of sensory processing during active behaviors in different systems: insect vision, rodent thalamus, and rodent sensory cortices. We discuss the circuit-level mechanisms that might lead to these modulations and their potential role in sensory function. Finally, we highlight the open questions and future perspectives of this exciting new field.

A common directional tuning mechanism of Drosophila motion-sensing neurons in the ON and in the OFF pathway

In the fruit fly optic lobe, T4 and T5 cells represent the first direction-selective neurons, with T4 cells responding selectively to moving brightness increments (ON) and T5 cells to brightness decrements (OFF). Both T4 and T5 cells comprise four subtypes with directional tuning to one of the four cardinal directions. We had previously found that upward-sensitive T4 cells implement both preferred direction enhancement and null direction suppression (Haag et al., 2016). Here, we asked whether this mechanism generalizes to OFF-selective T5 cells and to all four subtypes of both cell classes. We found that all four subtypes of both T4 and T5 cells implement both mechanisms, that is preferred direction enhancement and null direction inhibition, on opposing sides of their receptive fields. This gives rise to the high degree of direction selectivity observed in both T4 and T5 cells within each subpopulation.

An Array of Descending Visual Interneurons Encoding Self-Motion in Drosophila

The means by which brains transform sensory information into coherent motor actions is poorly understood. In flies, a relatively small set of descending interneurons are responsible for conveying sensory information and higher-order commands from the brain to motor circuits in the ventral nerve cord. Here, we describe three pairs of genetically identified descending interneurons that integrate information from wide-field visual interneurons and project directly to motor centers controlling flight behavior. We measured the physiological responses of these three cells during flight and found that they respond maximally to visual movement corresponding to rotation around three distinct body axes. After characterizing the tuning properties of an array of nine putative upstream visual interneurons, we show that simple linear combinations of their outputs can predict the responses of the three descending cells. Last, we developed a machine vision-tracking system that allows us to monitor multiple motor systems simultaneously and found that each visual descending interneuron class is correlated with a discrete set of motor programs.

SIGNIFICANCE STATEMENT

Most animals possess specialized sensory systems for encoding body rotation, which they use for stabilizing posture and regulating motor actions. In flies and other insects, the visual system contains an array of specialized neurons that integrate local optic flow to estimate body rotation during locomotion. However, the manner in which the output of these cells is transformed by the downstream neurons that innervate motor centers is poorly understood. We have identified a set of three visual descending neurons that integrate the output of nine large-field visual interneurons and project directly to flight motor centers. Our results provide new insight into how the sensory information that encodes body motion is transformed into a code that is appropriate for motor actions.

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.

Object-Detecting Neurons in Drosophila

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

Quantitative Predictions Orchestrate Visual Signaling in Drosophila

Vision influences behavior, but ongoing behavior also modulates vision in animals ranging from insects to primates. The function and biophysical mechanisms of most such modulations remain unresolved. Here, we combine behavioral genetics, electrophysiology, and high-speed videography to advance a function for behavioral modulations of visual processing in Drosophila. We argue that a set of motion-sensitive visual neurons regulate gaze-stabilizing head movements. We describe how, during flight turns, Drosophila perform a set of head movements that require silencing their gaze-stability reflexes along the primary rotation axis of the turn. Consistent with this behavioral requirement, we find pervasive motor-related inputs to the visual neurons, which quantitatively silence their predicted visual responses to rotations around the relevant axis while preserving sensitivity around other axes. This work proposes a function for a behavioral modulation of visual processing and illustrates how the brain can remove one sensory signal from a circuit carrying multiple related signals.

A faithful internal representation of walking movements in the Drosophila visual system

The integration of sensorimotor signals to internally estimate self-movement is critical for spatial perception and motor control. However, which neural circuits accurately track body motion and how these circuits control movement remain unknown. We found that a population of Drosophila neurons that were sensitive to visual flow patterns typically generated during locomotion, the horizontal system (HS) cells, encoded unambiguous quantitative information about the fly's walking behavior independently of vision. Angular and translational velocity signals were integrated with a behavioral-state signal and generated direction-selective and speed-sensitive graded changes in the membrane potential of these non-spiking cells. The nonvisual direction selectivity of HS cells cooperated with their visual selectivity only when the visual input matched that expected from the fly's movements, thereby revealing a circuit for internally monitoring voluntary walking. Furthermore, given that HS cells promoted leg-based turning, the activity of these cells could be used to control forward walking.

The aerodynamics and control of free flight manoeuvres in Drosophila

A firm understanding of how fruit flies hover has emerged over the past two decades, and recent work has focused on the aerodynamic, biomechanical and neurobiological mechanisms that enable them to manoeuvre and resist perturbations. In this review, we describe how flies manipulate wing movement to control their body motion during active manoeuvres, and how these actions are regulated by sensory feedback. We also discuss how the application of control theory is providing new insight into the logic and structure of the circuitry that underlies flight stability.This article is part of the themed issue 'Moving in a moving medium: new perspectives on flight'.

Comprehensive Characterization of the Major Presynaptic Elements to the Drosophila OFF Motion Detector

Estimating motion is a fundamental task for the visual system of sighted animals. In Drosophila, direction-selective T4 and T5 cells respond to moving brightness increments (ON) and decrements (OFF), respectively. Current algorithmic models of the circuit are based on the interaction of two differentially filtered signals. However, electron microscopy studies have shown that T5 cells receive their major input from four classes of neurons: Tm1, Tm2, Tm4, and Tm9. Using two-photon calcium imaging, we demonstrate that T5 is the first direction-selective stage within the OFF pathway. The four cells provide an array of spatiotemporal filters to T5. Silencing their synaptic output in various combinations, we find that all input elements are involved in OFF motion detection to varying degrees. Our comprehensive survey challenges the simplified view of how neural systems compute the direction of motion and suggests that an intricate interplay of many signals results in direction selectivity.