Converting an allocentric goal into an egocentric steering signal.

Neuronal signals that are relevant for spatial navigation have been described in many species1-10. However, a circuit-level understanding of how such signals interact to guide navigational behaviour is lacking. Here we characterize a neuronal circuit in the Drosophila central complex that compares internally generated estimates of the heading and goal angles of the fly-both of which are encoded in world-centred (allocentric) coordinates-to generate a body-centred (egocentric) steering signal. Past work has suggested that the activity of EPG neurons represents the fly's moment-to-moment angular orientation, or heading angle, during navigation2,11. An animal's moment-to-moment heading angle, however, is not always aligned with its goal angle-that is, the allocentric direction in which it wishes to progress forward. We describe FC2 cells12, a second set of neurons in the Drosophila brain with activity that correlates with the fly's goal angle. Focal optogenetic activation of FC2 neurons induces flies to orient along experimenter-defined directions as they walk forward. EPG and FC2 neurons connect monosynaptically to a third neuronal class, PFL3 cells12,13. We found that individual PFL3 cells show conjunctive, spike-rate tuning to both the heading angle and the goal angle during goal-directed navigation. Informed by the anatomy and physiology of these three cell classes, we develop a model that explains how this circuit compares allocentric heading and goal angles to build an egocentric steering signal in the PFL3 output terminals. Quantitative analyses and optogenetic manipulations of PFL3 activity support the model. Finally, using a new navigational memory task, we show that flies expressing disruptors of synaptic transmission in subsets of PFL3 cells have a reduced ability to orient along arbitrary goal directions, with an effect size in quantitative accordance with the prediction of our model. The biological circuit described here reveals how two population-level allocentric signals are compared in the brain to produce an egocentric output signal that is appropriate for motor control.

Neuronal calcium spikes enable vector inversion in the Drosophila brain.

A typical neuron signals to downstream cells when it is depolarized and firing sodium spikes. Some neurons, however, also fire calcium spikes when hyperpolarized. The function of such bidirectional signaling remains unclear in most circuits. Here we show how a neuron class that participates in vector computation in the fly central complex employs hyperpolarization-elicited calcium spikes to invert two-dimensional mathematical vectors. When cells switch from firing sodium to calcium spikes, this leads to a ~180° realignment between the vector encoded in the neuronal population and the fly's internal heading signal, thus inverting the vector. We show that the calcium spikes rely on the T-type calcium channel Ca-α1T, and argue, via analytical and experimental approaches, that these spikes enable vector computations in portions of angular space that would otherwise be inaccessible. These results reveal a seamless interaction between molecular, cellular and circuit properties for implementing vector math in the brain.

A rise-to-threshold process for a relative-value decision.

Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.

An internal expectation guides Drosophila egg-laying decisions.

To better understand how animals make ethologically relevant decisions, we studied egg-laying substrate choice in Drosophila. We found that flies dynamically increase or decrease their egg-laying rates while exploring substrates so as to target eggs to the best, recently visited option. Visiting the best option typically yielded inhibition of egg laying on other substrates for many minutes. Our data support a model in which flies compare the current substrate's value with an internally constructed expectation on the value of available options to regulate the likelihood of laying an egg. We show that dopamine neuron activity is critical for learning and/or expressing this expectation, similar to its role in certain tasks in vertebrates. Integrating sensory experiences over minutes to generate an estimate of the quality of available options allows flies to use a dynamic reference point for judging the current substrate and might be a general way in which decisions are made.

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.

Building an allocentric travelling direction signal via vector computation.

Many behavioural tasks require the manipulation of mathematical vectors, but, outside of computational models1-7, it is not known how brains perform vector operations. Here we show how the Drosophila central complex, a region implicated in goal-directed navigation7-10, performs vector arithmetic. First, we describe a neural signal in the fan-shaped body that explicitly tracks the allocentric travelling angle of a fly, that is, the travelling angle in reference to external cues. Past work has identified neurons in Drosophila8,11-13 and mammals14 that track the heading angle of an animal referenced to external cues (for example, head direction cells), but this new signal illuminates how the sense of space is properly updated when travelling and heading angles differ (for example, when walking sideways). We then characterize a neuronal circuit that performs an egocentric-to-allocentric (that is, body-centred to world-centred) coordinate transformation and vector addition to compute the allocentric travelling direction. This circuit operates by mapping two-dimensional vectors onto sinusoidal patterns of activity across distinct neuronal populations, with the amplitude of the sinusoid representing the length of the vector and its phase representing the angle of the vector. The principles of this circuit may generalize to other brains and to domains beyond navigation where vector operations or reference-frame transformations are required.

Transforming representations of movement from body- to world-centric space.

When an animal moves through the world, its brain receives a stream of information about the body's translational velocity from motor commands and sensory feedback signals. These incoming signals are referenced to the body, but ultimately, they must be transformed into world-centric coordinates for navigation1,2. Here we show that this computation occurs in the fan-shaped body in the brain of Drosophila melanogaster. We identify two cell types, PFNd and PFNv3-5, that conjunctively encode translational velocity and heading as a fly walks. In these cells, velocity signals are acquired from locomotor brain regions6 and are multiplied with heading signals from the compass system. PFNd neurons prefer forward-ipsilateral movement, whereas PFNv neurons prefer backward-contralateral movement, and perturbing PFNd neurons disrupts idiothetic path integration in walking flies7. Downstream, PFNd and PFNv neurons converge onto hΔB neurons, with a connectivity pattern that pools together heading and translation direction combinations corresponding to the same movement in world-centric space. This network motif effectively performs a rotation of the brain's representation of body-centric translational velocity according to the current heading direction. Consistent with our predictions, we observe that hΔB neurons form a representation of translational velocity in world-centric coordinates. By integrating this representation over time, it should be possible for the brain to form a working memory of the path travelled through the environment8-10.

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.

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.

A neural heading estimate is compared with an internal goal to guide oriented navigation.

Goal-directed navigation is thought to rely on the activity of head-direction cells, but how this activity guides moment-to-moment actions remains poorly understood. Here we characterize how heading neurons in the Drosophila central complex guide moment-to-moment navigational behavior. We establish an innate, heading-neuron-dependent, tethered navigational behavior where walking flies maintain a straight trajectory along a specific angular bearing for hundreds of body lengths. While flies perform this task, we use chemogenetics to transiently rotate their neural heading estimate and observe that the flies slow down and turn in a direction that aims to return the heading estimate to the angle it occupied before stimulation. These results support a working model in which the fly brain quantitatively compares an internal estimate of current heading with an internal goal heading and uses the sign and magnitude of the difference to determine which way to turn, how hard to turn and how fast to walk forward.

Building a heading signal from anatomically defined neuron types in the Drosophila central complex.

A network of a few hundred neurons in the Drosophila central complex carries an estimate of the fly's heading in the world, akin to the mammalian head-direction system. Here we describe how anatomically defined neuronal classes in this network are poised to implement specific sub-processes for building and updating this population-level heading signal. The computations we describe in the fly central complex strongly resemble those posited to exist in the mammalian brain, in computational models for building head-direction signals. By linking circuit anatomy to navigational physiology, the Drosophila central complex should provide a detailed example of how a heading signal is built.

Abolishment of Spontaneous Flight Turns in Visually Responsive Drosophila.

Animals react rapidly to external stimuli, such as an approaching predator, but in other circumstances, they seem to act spontaneously, without any obvious external trigger. How do the neural processes mediating the execution of reflexive and spontaneous actions differ? We studied this question in tethered, flying Drosophila. We found that silencing a large but genetically defined set of non-motor neurons virtually eliminates spontaneous flight turns while preserving the tethered flies' ability to perform two types of visually evoked turns, demonstrating that, at least in flies, these two modes of action are almost completely dissociable.

A neural circuit architecture for angular integration in Drosophila.

Many animals keep track of their angular heading over time while navigating through their environment. However, a neural-circuit architecture for computing heading has not been experimentally defined in any species. Here we describe a set of clockwise- and anticlockwise-shifting neurons in the Drosophila central complex whose wiring and physiology provide a means to rotate an angular heading estimate based on the fly's angular velocity. We show that each class of shifting neurons exists in two subtypes, with spatiotemporal activity profiles that suggest different roles for each subtype at the start and end of tethered-walking turns. Shifting neurons are required for the heading system to properly track the fly's heading in the dark, and stimulation of these neurons induces predictable shifts in the heading signal. The central features of this biological circuit are analogous to those of computational models proposed for head-direction cells in rodents and may shed light on how neural systems, in general, perform integration.

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.

Cellular evidence for efference copy in Drosophila visuomotor processing.

Each time a locomoting fly turns, the visual image sweeps over the retina and generates a motion stimulus. Classic behavioral experiments suggested that flies use active neural-circuit mechanisms to suppress the perception of self-generated visual motion during intended turns. Direct electrophysiological evidence, however, has been lacking. We found that visual neurons in Drosophila receive motor-related inputs during rapid flight turns. These inputs arrived with a sign and latency appropriate for suppressing each targeted cell's visual response to the turn. Precise measurements of behavioral and neuronal response latencies supported the idea that motor-related inputs to optic flow-processing cells represent internal predictions of the expected visual drive induced by voluntary turns. Motor-related inputs to small object-selective visual neurons could reflect either proprioceptive feedback from the turn or internally generated signals. Our results in Drosophila echo the suppression of visual perception during rapid eye movements in primates, demonstrating common functional principles of sensorimotor processing across phyla.

Modulation of visual physiology by behavioral state in monkeys, mice, and flies.

When a monkey attends to a visual stimulus, neurons in visual cortex respond differently to that stimulus than when the monkey attends elsewhere. In the 25 years since the initial discovery, the study of attention in primates has been central to understanding flexible visual processing. Recent experiments demonstrate that visual neurons in mice and fruit flies are modulated by locomotor behaviors, like running and flying, in a manner that resembles attention-based modulations in primates. The similar findings across species argue for a more generalized view of state-dependent sensory processing and for a renewed dialogue among vertebrate and invertebrate research communities.

Olfactory modulation of flight in Drosophila is sensitive, selective and rapid.

Freely flying Drosophila melanogaster respond to odors by increasing their flight speed and turning upwind. Both these flight behaviors can be recapitulated in a tethered fly, which permits the odor stimulus to be precisely controlled. In this study, we investigated the relationship between these behaviors and odor-evoked activity in primary sensory neurons. First, we verified that these behaviors are abolished by mutations that silence olfactory receptor neurons (ORNs). We also found that antennal mechanosensors in Johnston's organ are required to guide upwind turns. Flight responses to an odor depend on the identity of the ORNs that are active, meaning that these behaviors involve odor discrimination and not just odor detection. Flight modulation can begin rapidly (within about 85 ms) after the onset of olfactory transduction. Moreover, just a handful of spikes in a single ORN type is sufficient to trigger these behaviors. Finally, we found that the upwind turn is triggered independently from the increase in wingbeat frequency, implying that ORN signals diverge to activate two independent and parallel motor commands. Together, our results show that odor-evoked flight modulations are rapid and sensitive responses to specific patterns of sensory neuron activity. This makes these behaviors a useful paradigm for studying the relationship between sensory neuron activity and behavioral decision-making in a simple and genetically tractable organism.

Active flight increases the gain of visual motion processing in Drosophila.

We developed a technique for performing whole-cell patch-clamp recordings from genetically identified neurons in behaving Drosophila. We focused on the properties of visual interneurons during tethered flight, but this technique generalizes to different cell types and behaviors. We found that the peak-to-peak responses of a class of visual motion-processing interneurons, the vertical-system visual neurons (VS cells), doubled when flies were flying compared with when they were at rest. Thus, the gain of the VS cells is not fixed, but is instead behaviorally flexible and changes with locomotor state. Using voltage clamp, we found that the passive membrane resistance of VS cells was reduced during flight, suggesting that the elevated gain was a result of increased synaptic drive from upstream motion-sensitive inputs. The ability to perform patch-clamp recordings in behaving Drosophila promises to help unify the understanding of behavior at the gene, cell and circuit levels.

Beyond Poisson: increased spike-time regularity across primate parietal cortex.

Cortical areas differ in their patterns of connectivity, cellular composition, and functional architecture. Spike trains, on the other hand, are commonly assumed to follow similarly irregular dynamics across neocortex. We examined spike-time statistics in four parietal areas using a method that accounts for nonstationarities in firing rate. We found that, whereas neurons in visual areas fire irregularly, many cells in association and motor-like parietal regions show increasingly regular spike trains by comparison. Regularity was evident both in the shape of interspike interval distributions and in spike-count variability across trials. Thus, Poisson-like randomness is not a universal feature of neocortex. Rather, many parietal cells have reduced trial-to-trial variability in spike counts that could provide for more reliable firing-rate signals. These results suggest that spiking dynamics may play different roles in different cortical areas and should not be assumed to arise from fundamentally irreducible noise sources.

A simple vision-based algorithm for decision making in flying Drosophila.

Animals must quickly recognize objects in their environment and act accordingly. Previous studies indicate that looming visual objects trigger avoidance reflexes in many species [1-5]; however, such reflexes operate over a close range and might not detect a threatening stimulus at a safe distance. We analyzed how fruit flies (Drosophila melanogaster) respond to simple visual stimuli both in free flight and in a tethered-flight simulator. Whereas Drosophila, like many other insects, are attracted toward long vertical objects [6-10], we found that smaller visual stimuli elicit not weak attraction but rather strong repulsion. Because aversion to small spots depends on the vertical size of a moving object, and not on looming, it can function at a much greater distance than expansion-dependent reflexes. The opposing responses to long stripes and small spots reflect a simple but effective object classification system. Attraction toward long stripes would lead flies toward vegetative perches or feeding sites, whereas repulsion from small spots would help them avoid aerial predators or collisions with other insects. The motion of flying Drosophila depends on a balance of these two systems, providing a foundation for studying the neural basis of behavioral choice in a genetic model organism.