Two-photon calcium imaging from head-fixed Drosophila during optomotor walking behavior

Miniature linear and split-belt treadmills reveal mechanisms of adaptive motor control in walking Drosophila

To navigate complex environments, walking animals must detect and overcome unexpected perturbations. One technical challenge when investigating adaptive locomotion is measuring behavioral responses to precise perturbations during naturalistic walking; another is that manipulating neural activity in sensorimotor circuits often reduces spontaneous locomotion. To overcome these obstacles, we introduce miniature treadmill systems for coercing locomotion and tracking 3D kinematics of walking Drosophila. By systematically comparing walking in three experimental setups, we show that flies compelled to walk on the linear treadmill have similar stepping kinematics to freely walking flies, while kinematics of tethered walking flies are subtly different. Genetically silencing mechanosensory neurons altered step kinematics of flies walking on the linear treadmill across all speeds. We also discovered that flies can maintain a forward heading on a split-belt treadmill by specifically adapting the step distance of their middle legs. These findings suggest that proprioceptive feedback contributes to leg motor control irrespective of walking speed and that the fly's middle legs play a specialized role in stabilizing locomotion.

Neurofibromin deficiency alters the patterning and prioritization of motor behaviors in a state-dependent manner

Genetic disorders such as neurofibromatosis type 1 increase vulnerability to cognitive and behavioral disorders, such as autism spectrum disorder and attention-deficit/hyperactivity disorder. Neurofibromatosis type 1 results from loss-of-function mutations in the neurofibromin gene and subsequent reduction in the neurofibromin protein (Nf1). While the mechanisms have yet to be fully elucidated, loss of Nf1 may alter neuronal circuit activity leading to changes in behavior and susceptibility to cognitive and behavioral comorbidities. Here we show that mutations decreasing Nf1 expression alter motor behaviors, impacting the patterning, prioritization, and behavioral state dependence in a Drosophila model of neurofibromatosis type 1. Loss of Nf1 increases spontaneous grooming in a nonlinear spatial and temporal pattern, differentially increasing grooming of certain body parts, including the abdomen, head, and wings. This increase in grooming could be overridden by hunger in food-deprived foraging animals, demonstrating that the Nf1 effect is plastic and internal state-dependent. Stimulus-evoked grooming patterns were altered as well, with nf1 mutants exhibiting reductions in wing grooming when coated with dust, suggesting that hierarchical recruitment of grooming command circuits was altered. Yet loss of Nf1 in sensory neurons and/or grooming command neurons did not alter grooming frequency, suggesting that Nf1 affects grooming via higher-order circuit alterations. Changes in grooming coincided with alterations in walking. Flies lacking Nf1 walked with increased forward velocity on a spherical treadmill, yet there was no detectable change in leg kinematics or gait. Thus, loss of Nf1 alters motor function without affecting overall motor coordination, in contrast to other genetic disorders that impair coordination. Overall, these results demonstrate that loss of Nf1 alters the patterning and prioritization of repetitive behaviors, in a state-dependent manner, without affecting motor coordination.

A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

A leg model based on anatomical landmarks to study 3D joint kinematics of walking in Drosophila melanogaster

Walking is the most common form of how animals move on land. The model organism Drosophila melanogaster has become increasingly popular for studying how the nervous system controls behavior in general and walking in particular. Despite recent advances in tracking and modeling leg movements of walking Drosophila in 3D, there are still gaps in knowledge about the biomechanics of leg joints due to the tiny size of fruit flies. For instance, the natural alignment of joint rotational axes was largely neglected in previous kinematic analyses. In this study, we therefore present a detailed kinematic leg model in which not only the segment lengths but also the main rotational axes of the joints were derived from anatomical landmarks, namely, the joint condyles. Our model with natural oblique joint axes is able to adapt to the 3D leg postures of straight and forward walking fruit flies with high accuracy. When we compared our model to an orthogonalized version, we observed that our model showed a smaller error as well as differences in the used range of motion (ROM), highlighting the advantages of modeling natural rotational axes alignment for the study of joint kinematics. We further found that the kinematic profiles of front, middle, and hind legs differed in the number of required degrees of freedom as well as their contributions to stepping, time courses of joint angles, and ROM. Our findings provide deeper insights into the joint kinematics of walking in Drosophila, and, additionally, will help to develop dynamical, musculoskeletal, and neuromechanical simulations.

CRASH2p: Closed-loop Two Photon Imaging in Freely Moving Animals

Direct measurement of neural activity in freely moving animals is essential for understanding how the brain controls and represents behaviors. Genetically encoded calcium indicators report neural activity as changes in fluorescence intensity, but brain motion confounds quantitative measurement of fluorescence. Translation, rotation, and deformation of the brain and the movements of intervening scattering or auto-fluorescent tissue all alter the amount of fluorescent light captured by a microscope. Compared to single-photon approaches, two photon microscopy is less sensitive to scattering and off-target fluorescence, but more sensitive to motion, and two photon imaging has always required anchoring the microscope to the brain. We developed a closed-loop resonant axial-scanning high-speed two photon (CRASH2p) microscope for real-time 3D motion correction in unrestrained animals, without implantation of reference markers. We complemented CRASH2p with a novel scanning strategy and a multistage registration pipeline. We performed volumetric ratiometrically corrected functional imaging in the CNS of freely moving Drosophila larvae and discovered previously unknown neural correlates of behavior.

Long-term intravital subcellular imaging with confocal scanning light-field microscopy

Long-term observation of subcellular dynamics in living organisms is limited by background fluorescence originating from tissue scattering or dense labeling. Existing confocal approaches face an inevitable tradeoff among parallelization, resolution and phototoxicity. Here we present confocal scanning light-field microscopy (csLFM), which integrates axially elongated line-confocal illumination with the rolling shutter in scanning light-field microscopy (sLFM). csLFM enables high-fidelity, high-speed, three-dimensional (3D) imaging at near-diffraction-limit resolution with both optical sectioning and low phototoxicity. By simultaneous 3D excitation and detection, the excitation intensity can be reduced below 1 mW mm-2, with 15-fold higher signal-to-background ratio over sLFM. We imaged subcellular dynamics over 25,000 timeframes in optically challenging environments in different species, such as migrasome delivery in mouse spleen, retractosome generation in mouse liver and 3D voltage imaging in Drosophila. Moreover, csLFM facilitates high-fidelity, large-scale neural recording with reduced crosstalk, leading to high orientation selectivity to visual stimuli, similar to two-photon microscopy, which aids understanding of neural coding mechanisms.

Microfluidic Localized Hydrogel Polymerization Enables Simultaneous Recording of Neural Activity and Behavior in C. elegans

Monitoring an animal's brain activity during motion provides a means to interpret the brain activity in the context of movement. However, it is challenging to obtain information about the animal's movement during neural imaging in the popular model organism C. elegans due to its small size. Here, we present a microfluidic tool to immobilize only the head region of C. elegans for simultaneous recording of neuronal activity and tail movement. We combine hydrogel photopolymerization and microfluidics to realize controlled head immobilization in a semi-continuous fashion. To optimize the immobilization process, we characterize the hydrogel polymerization under different experimental conditions, including under the effect of fluid flow. We show that the Damköhler number specifically defined for our reactive transport phenomena can predict the success of such photopolymerized hydrogels used for sample immobilization. In addition to simultaneous recording of neural activity and behavior in C. elegans, we demonstrate our method's capability to temporarily reconfigure fluid flow and deliver chemical stimuli to the animal's nose to examine the animal's responses. We envision this approach to be useful for similar recordings for other small motile organisms, as well as scenarios where microfluidics and polymerization are used to control flow and rection.

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.

Volitional activation of remote place representations with a hippocampal brain-machine interface

The hippocampus is critical for recollecting and imagining experiences. This is believed to involve voluntarily drawing from hippocampal memory representations of people, events, and places, including maplike representations of familiar environments. However, whether representations in such "cognitive maps" can be volitionally accessed is unknown. We developed a brain-machine interface to test whether rats can do so by controlling their hippocampal activity in a flexible, goal-directed, and model-based manner. We found that rats can efficiently navigate or direct objects to arbitrary goal locations within a virtual reality arena solely by activating and sustaining appropriate hippocampal representations of remote places. This provides insight into the mechanisms underlying episodic memory recall, mental simulation and planning, and imagination and opens up possibilities for high-level neural prosthetics that use hippocampal representations.

A single photoreceptor splits perception and entrainment by cotransmission

Vision enables both image-forming perception, driven by a contrast-based pathway, and unconscious non-image-forming circadian photoentrainment, driven by an irradiance-based pathway1,2. Although two distinct photoreceptor populations are specialized for each visual task3-6, image-forming photoreceptors can additionally contribute to photoentrainment of the circadian clock in different species7-15. However, it is unknown how the image-forming photoreceptor pathway can functionally implement the segregation of irradiance signals required for circadian photoentrainment from contrast signals required for image perception. Here we report that the Drosophila R8 photoreceptor separates image-forming and irradiance signals by co-transmitting two neurotransmitters, histamine and acetylcholine. This segregation is further established postsynaptically by histamine-receptor-expressing unicolumnar retinotopic neurons and acetylcholine-receptor-expressing multicolumnar integration neurons. The acetylcholine transmission from R8 photoreceptors is sustained by an autocrine negative feedback of the cotransmitted histamine during the light phase of light-dark cycles. At the behavioural level, elimination of histamine and acetylcholine transmission impairs R8-driven motion detection and circadian photoentrainment, respectively. Thus, a single type of photoreceptor can achieve the dichotomy of visual perception and circadian photoentrainment as early as the first visual synapses, revealing a simple yet robust mechanism to segregate and translate distinct sensory features into different animal behaviours.

HI-FISH: WHOLE BRAIN IN SITU MAPPING OF NEURONAL ACTIVATION IN DROSOPHILA DURING SOCIAL BEHAVIORS AND OPTOGENETIC STIMULATION

Monitoring neuronal activity at single-cell resolution in freely moving Drosophila engaged in social behaviors is challenging because of their small size and lack of transparency. Extant methods, such as Flyception, are highly invasive. Whole-brain calcium imaging in head-fixed, walking flies is feasible but the animals cannot perform the consummatory phases of social behaviors like aggression or mating under these conditions. This has left open the fundamental question of whether neurons identified as functionally important for such behaviors using loss- or gain-of-function screens are actually active during the natural performance of such behaviors, and if so during which phase(s). Here we describe a method, called HI-FISH, for brain-wide mapping of active cells expressing the Immediate Early Gene hr38 using a high-sensitivity/low background amplification method called HCR-3.0. Using double-labeling for hr38 mRNA and for GFP, we describe the activity of several classes of aggression-promoting neurons during courtship and aggression, including P1a cells, an intensively studied population of male-specific interneurons. Using HI-FISH in combination with optogenetic activation of aggression-promoting neurons (opto-HI-FISH) we identify candidate downstream functional targets of these cells in a brain-wide, unbiased manner. Finally we compare the activity of P1a neurons during sequential performance of courtship and aggression, using intronic vs. exonic hr38 probes to differentiate newly synthesized nuclear transcripts from cytoplasmic transcripts synthesized at an earlier time. These data provide evidence suggesting that different subsets of P1a neurons may be active during courtship vs. aggression. HI-FISH and associated methods may help to fill an important lacuna in the armamentarium of tools for neural circuit analysis in Drosophila.

Long-timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied Drosophila melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such 'anti-directional turning' is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Visual feedback neurons fine-tune Drosophila male courtship via GABA-mediated inhibition

Many species of animals use vision to regulate their social behaviors. However, the molecular and circuit mechanisms underlying visually guided social interactions remain largely unknown. Here, we show that the Drosophila ortholog of the human GABAA-receptor-associated protein (GABARAP) is required in a class of visual feedback neurons, lamina tangential (Lat) cells, to fine-tune male courtship. GABARAP is a ubiquitin-like protein that maintains cell-surface levels of GABAA receptors. We demonstrate that knocking down GABARAP or GABAAreceptors in Lat neurons or hyperactivating them induces male courtship toward other males. Inhibiting Lat neurons, on the other hand, delays copulation by impairing the ability of males to follow females. Remarkably, the fly GABARAP protein and its human ortholog share a strong sequence identity, and the fly GABARAP function in Lat neurons can be rescued by its human ortholog. Using in vivo two-photon imaging and optogenetics, we reveal that Lat neurons are functionally connected to neural circuits that mediate visually guided courtship pursuits in males. Our work identifies a novel physiological function for GABARAP in regulating visually guided courtship pursuits in Drosophila males. Reduced GABAA signaling has been linked to social deficits observed in the autism spectrum and bipolar disorders. The functional similarity between the human and the fly GABARAP raises the possibility of a conserved role for this gene in regulating social behaviors across insects and mammals.

The spatial and temporal structure of neural activity across the fly brain

What are the spatial and temporal scales of brainwide neuronal activity? We used swept, confocally-aligned planar excitation (SCAPE) microscopy to image all cells in a large volume of the brain of adult Drosophila with high spatiotemporal resolution while flies engaged in a variety of spontaneous behaviors. This revealed neural representations of behavior on multiple spatial and temporal scales. The activity of most neurons correlated (or anticorrelated) with running and flailing over timescales that ranged from seconds to a minute. Grooming elicited a weaker global response. Significant residual activity not directly correlated with behavior was high dimensional and reflected the activity of small clusters of spatially organized neurons that may correspond to genetically defined cell types. These clusters participate in the global dynamics, indicating that neural activity reflects a combination of local and broadly distributed components. This suggests that microcircuits with highly specified functions are provided with knowledge of the larger context in which they operate.

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.

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.

A rapid and bidirectional reporter of neural activity reveals neural correlates of social behaviors in Drosophila

Neural activity is modulated over different timescales encompassing subseconds to hours, reflecting changes in external environment, internal state and behavior. Using Drosophila as a model, we developed a rapid and bidirectional reporter that provides a cellular readout of recent neural activity. This reporter uses nuclear versus cytoplasmic distribution of CREB-regulated transcriptional co-activator (CRTC). Subcellular distribution of GFP-tagged CRTC (CRTC::GFP) bidirectionally changes on the order of minutes and reflects both increases and decreases in neural activity. We established an automated machine-learning-based routine for efficient quantification of reporter signal. Using this reporter, we demonstrate mating-evoked activation and inactivation of modulatory neurons. We further investigated the functional role of the master courtship regulator gene fruitless (fru) and show that fru is necessary to ensure activation of male arousal neurons by female cues. Together, our results establish CRTC::GFP as a bidirectional reporter of recent neural activity suitable for examining neural correlates in behavioral contexts.

Multifaceted luminance gain control beyond photoreceptors in Drosophila

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

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Homeostatic synaptic plasticity rescues neural coding reliability

To survive, animals must recognize reoccurring stimuli. This necessitates a reliable stimulus representation by the neural code. While synaptic transmission underlies the propagation of neural codes, it is unclear how synaptic plasticity can maintain coding reliability. By studying the olfactory system of Drosophila melanogaster, we aimed to obtain a deeper mechanistic understanding of how synaptic function shapes neural coding in the live, behaving animal. We show that the properties of the active zone (AZ), the presynaptic site of neurotransmitter release, are critical for generating a reliable neural code. Reducing neurotransmitter release probability of olfactory sensory neurons disrupts both neural coding and behavioral reliability. Strikingly, a target-specific homeostatic increase of AZ numbers rescues these defects within a day. These findings demonstrate an important role for synaptic plasticity in maintaining neural coding reliability and are of pathophysiological interest by uncovering an elegant mechanism through which the neural circuitry can counterbalance perturbations.

Rabies virus-based labeling of layer 6 corticothalamic neurons for two-photon imaging in vivo

Neocortical layer 6 (L6) is less understood than other more superficial layers, largely owing to limitations of performing high-resolution investigations in vivo. Here, we show that labeling with the Challenge Virus Standard (CVS) rabies virus strain enables high-quality imaging of L6 neurons by conventional two-photon microscopes. CVS virus injection into the medial geniculate body can selectively label L6 neurons in the auditory cortex. Only three days after injection, dendrites and cell bodies of L6 neurons could be imaged across all cortical layers. Ca²⁺ imaging in awake mice showed that sound stimulation evokes neuronal responses from cell bodies with minimal contamination from neuropil signals. In addition, dendritic Ca²⁺ imaging revealed significant responses from spines and trunks across all layers. These results demonstrate a reliable method capable of rapid, high-quality labeling of L6 neurons that can be readily extended to other brain regions.

Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging

High-speed three-dimensional (3D) intravital imaging in animals is useful for studying transient subcellular interactions and functions in health and disease. Light-field microscopy (LFM) provides a computational solution for snapshot 3D imaging with low phototoxicity but is restricted by low resolution and reconstruction artifacts induced by optical aberrations, motion and noise. Here, we propose virtual-scanning LFM (VsLFM), a physics-based deep learning framework to increase the resolution of LFM up to the diffraction limit within a snapshot. By constructing a 40 GB high-resolution scanning LFM dataset across different species, we exploit physical priors between phase-correlated angular views to address the frequency aliasing problem. This enables us to bypass hardware scanning and associated motion artifacts. Here, we show that VsLFM achieves ultrafast 3D imaging of diverse processes such as the beating heart in embryonic zebrafish, voltage activity in Drosophila brains and neutrophil migration in the mouse liver at up to 500 volumes per second.

Long timescale anti-directional rotation in Drosophila optomotor behavior

Locomotor movements cause visual images to be displaced across the eye, a retinal slip that is counteracted by stabilizing reflexes in many animals. In insects, optomotor turning causes the animal to turn in the direction of rotating visual stimuli, thereby reducing retinal slip and stabilizing trajectories through the world. This behavior has formed the basis for extensive dissections of motion vision. Here, we report that under certain stimulus conditions, two Drosophila species, including the widely studied D. melanogaster, can suppress and even reverse the optomotor turning response over several seconds. Such "anti-directional turning" is most strongly evoked by long-lasting, high-contrast, slow-moving visual stimuli that are distinct from those that promote syn-directional optomotor turning. Anti-directional turning, like the syn-directional optomotor response, requires the local motion detecting neurons T4 and T5. A subset of lobula plate tangential cells, CH cells, show involvement in these responses. Imaging from a variety of direction-selective cells in the lobula plate shows no evidence of dynamics that match the behavior, suggesting that the observed inversion in turning direction emerges downstream of the lobula plate. Further, anti-directional turning declines with age and exposure to light. These results show that Drosophila optomotor turning behaviors contain rich, stimulus-dependent dynamics that are inconsistent with simple reflexive stabilization responses.

Ascending neurons convey behavioral state to integrative sensory and action selection brain regions

Knowing one's own behavioral state has long been theorized as critical for contextualizing dynamic sensory cues and identifying appropriate future behaviors. Ascending neurons (ANs) in the motor system that project to the brain are well positioned to provide such behavioral state signals. However, what ANs encode and where they convey these signals remains largely unknown. Here, through large-scale functional imaging in behaving animals and morphological quantification, we report the behavioral encoding and brain targeting of hundreds of genetically identifiable ANs in the adult fly, Drosophila melanogaster. We reveal that ANs encode behavioral states, specifically conveying self-motion to the anterior ventrolateral protocerebrum, an integrative sensory hub, as well as discrete actions to the gnathal ganglia, a locus for action selection. Additionally, AN projection patterns within the motor system are predictive of their encoding. Thus, ascending populations are well poised to inform distinct brain hubs of self-motion and ongoing behaviors and may provide an important substrate for computations that are required for adaptive behavior.

Behavioral state-dependent modulation of insulin-producing cells in Drosophila

Insulin signaling plays a pivotal role in metabolic control and aging, and insulin accordingly is a key factor in several human diseases. Despite this importance, the in vivo activity dynamics of insulin-producing cells (IPCs) are poorly understood. Here, we characterized the effects of locomotion on the activity of IPCs in Drosophila. Using in vivo electrophysiology and calcium imaging, we found that IPCs were strongly inhibited during walking and flight and that their activity rebounded and overshot after cessation of locomotion. Moreover, IPC activity changed rapidly during behavioral transitions, revealing that IPCs are modulated on fast timescales in behaving animals. Optogenetic activation of locomotor networks ex vivo, in the absence of actual locomotion or changes in hemolymph sugar levels, was sufficient to inhibit IPCs. This demonstrates that the behavioral state-dependent inhibition of IPCs is actively controlled by neuronal pathways and is independent of changes in glucose concentration. By contrast, the overshoot in IPC activity after locomotion was absent ex vivo and after starvation, indicating that it was not purely driven by feedforward signals but additionally required feedback derived from changes in hemolymph sugar concentration. We hypothesize that IPC inhibition during locomotion supports mobilization of fuel stores during metabolically demanding behaviors, while the rebound in IPC activity after locomotion contributes to replenishing muscle glycogen stores. In addition, the rapid dynamics of IPC modulation support a potential role of insulin in the state-dependent modulation of sensorimotor processing.

Real-time denoising enables high-sensitivity fluorescence time-lapse imaging beyond the shot-noise limit

A fundamental challenge in fluorescence microscopy is the photon shot noise arising from the inevitable stochasticity of photon detection. Noise increases measurement uncertainty and limits imaging resolution, speed and sensitivity. To achieve high-sensitivity fluorescence imaging beyond the shot-noise limit, we present DeepCAD-RT, a self-supervised deep learning method for real-time noise suppression. Based on our previous framework DeepCAD, we reduced the number of network parameters by 94%, memory consumption by 27-fold and processing time by a factor of 20, allowing real-time processing on a two-photon microscope. A high imaging signal-to-noise ratio can be acquired with tenfold fewer photons than in standard imaging approaches. We demonstrate the utility of DeepCAD-RT in a series of photon-limited experiments, including in vivo calcium imaging of mice, zebrafish larva and fruit flies, recording of three-dimensional (3D) migration of neutrophils after acute brain injury and imaging of 3D dynamics of cortical ATP release. DeepCAD-RT will facilitate the morphological and functional interrogation of biological dynamics with a minimal photon budget.

GABA-mediated inhibition in visual feedback neurons fine-tunes Drosophila male courtship

Vision is critical for the regulation of mating behaviors in many species. Here, we discovered that the Drosophila ortholog of human GABA A -receptor-associated protein (GABARAP) is required to fine-tune male courtship by modulating the activity of visual feedback neurons, lamina tangential cells (Lat). GABARAP is a ubiquitin-like protein that regulates cell-surface levels of GABA A receptors. Knocking down GABARAP or GABA A receptors in Lat neurons or hyperactivating them induces male courtship toward other males. Inhibiting Lat neurons, on the other hand, delays copulation by impairing the ability of males to follow females. Remarkably, the human ortholog of Drosophila GABARAP restores function in Lat neurons. Using in vivo two-photon imaging and optogenetics, we show that Lat neurons are functionally connected to neural circuits that mediate visually-guided courtship pursuits in males. Our work reveals a novel physiological role for GABARAP in fine-tuning the activity of a visual circuit that tracks a mating partner during courtship.

An optofluidic platform for interrogating chemosensory behavior and brainwide neural representation in larval zebrafish

Studying chemosensory processing desires precise chemical cue presentation, behavioral response monitoring, and large-scale neuronal activity recording. Here we present Fish-on-Chips, a set of optofluidic tools for highly-controlled chemical delivery while simultaneously imaging behavioral outputs and whole-brain neuronal activities at cellular resolution in larval zebrafish. These include a fluidics-based swimming arena and an integrated microfluidics-light sheet fluorescence microscopy (µfluidics-LSFM) system, both of which utilize laminar fluid flows to achieve spatiotemporally precise chemical cue presentation. To demonstrate the strengths of the platform, we used the navigation arena to reveal binasal input-dependent behavioral strategies that larval zebrafish adopt to evade cadaverine, a death-associated odor. The µfluidics-LSFM system enables sequential presentation of odor stimuli to individual or both nasal cavities separated by only ~100 µm. This allowed us to uncover brainwide neural representations of cadaverine sensing and binasal input summation in the vertebrate model. Fish-on-Chips is readily generalizable and will empower the investigation of neural coding in the chemical senses.

Transcriptional Genetically Encoded Calcium Indicators in Drosophila

Knowing which neurons are active during behavior is a crucial step toward understanding how nervous systems work. Neuronal activation is generally accompanied by an increase in intracellular calcium levels. Therefore, intracellular calcium levels are widely used as a proxy for neuronal activity. Many types of synthetic components and bioluminescent or fluorescent proteins that report transient and long-term changes in intracellular calcium levels have been developed over the past 60 years. Calcium indicators that enable imaging of the dynamic activity of a large ensemble of neurons in behaving animals have revolutionized the field of neuroscience. Among these, transcription-based genetically encoded calcium indicators (transcriptional GECIs) have proven easy to use and do not depend on sophisticated imaging systems, offering unique advantages over other types of calcium indicators. Here, we describe the two currently available fly transcriptional GECIs-calcium-dependent nuclear import of LexA (CaLexA) and transcriptional reporter of intracellular calcium (TRIC)-and review studies that have used them. In the accompanying protocol, we present step-by-step details for generating CaLexA- and TRIC-ready flies and for imaging CaLexA and TRIC signals in dissected brains after experimental manipulations of intact free-moving flies.

The translational genetics of ADHD and related phenotypes in model organisms

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder resulting from the interaction between genetic and environmental risk factors. It is well known that ADHD co-occurs frequently with other psychiatric disorders due, in part, to shared genetics factors. Although many studies have contributed to delineate the genetic landscape of psychiatric disorders, their specific molecular underpinnings are still not fully understood. The use of animal models can help us to understand the role of specific genes and environmental stimuli-induced epigenetic modifications in the pathogenesis of ADHD and its comorbidities. The aim of this review is to provide an overview on the functional work performed in rodents, zebrafish and fruit fly and highlight the generated insights into the biology of ADHD, with a special focus on genetics and epigenetics. We also describe the behavioral tests that are available to study ADHD-relevant phenotypes and comorbid traits in these models. Furthermore, we have searched for new models to study ADHD and its comorbidities, which can be useful to test potential pharmacological treatments.

Overcoming the Domain Gap in Neural Action Representations

Relating behavior to brain activity in animals is a fundamental goal in neuroscience, with practical applications in building robust brain-machine interfaces. However, the domain gap between individuals is a major issue that prevents the training of general models that work on unlabeled subjects. Since 3D pose data can now be reliably extracted from multi-view video sequences without manual intervention, we propose to use it to guide the encoding of neural action representations together with a set of neural and behavioral augmentations exploiting the properties of microscopy imaging. To test our method, we collect a large dataset that features flies and their neural activity. To reduce the domain gap, during training, we mix features of neural and behavioral data across flies that seem to be performing similar actions. To show our method can generalize further neural modalities and other downstream tasks, we test our method on a human neural Electrocorticography dataset, and another RGB video data of human activities from different viewpoints. We believe our work will enable more robust neural decoding algorithms to be used in future brain-machine interfaces.

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.

Naturalistic neuroscience and virtual reality

Virtual reality (VR) is one of the techniques that became particularly popular in neuroscience over the past few decades. VR experiments feature a closed-loop between sensory stimulation and behavior. Participants interact with the stimuli and not just passively perceive them. Several senses can be stimulated at once, large-scale environments can be simulated as well as social interactions. All of this makes VR experiences more natural than those in traditional lab paradigms. Compared to the situation in field research, a VR simulation is highly controllable and reproducible, as required of a laboratory technique used in the search for neural correlates of perception and behavior. VR is therefore considered a middle ground between ecological validity and experimental control. In this review, I explore the potential of VR in eliciting naturalistic perception and behavior in humans and non-human animals. In this context, I give an overview of recent virtual reality approaches used in neuroscientific research.

Review of data processing of functional optical microscopy for neuroscience

Functional optical imaging in neuroscience is rapidly growing with the development of optical systems and fluorescence indicators. To realize the potential of these massive spatiotemporal datasets for relating neuronal activity to behavior and stimuli and uncovering local circuits in the brain, accurate automated processing is increasingly essential. We cover recent computational developments in the full data processing pipeline of functional optical microscopy for neuroscience data and discuss ongoing and emerging challenges.

Microengineered devices enable long-term imaging of the ventral nerve cord in behaving adult Drosophila

The dynamics and connectivity of neural circuits continuously change on timescales ranging from milliseconds to an animal's lifetime. Therefore, to understand biological networks, minimally invasive methods are required to repeatedly record them in behaving animals. Here we describe a suite of devices that enable long-term optical recordings of the adult Drosophila melanogaster ventral nerve cord (VNC). These consist of transparent, numbered windows to replace thoracic exoskeleton, compliant implants to displace internal organs, a precision arm to assist implantation, and a hinged stage to repeatedly tether flies. To validate and illustrate our toolkit we (i) show minimal impact on animal behavior and survival, (ii) follow the degradation of chordotonal organ mechanosensory nerve terminals over weeks after leg amputation, and (iii) uncover waves of neural activity caffeine ingestion. Thus, our long-term imaging toolkit opens up the investigation of premotor and motor circuit adaptations in response to injury, drug ingestion, aging, learning, and disease.

Calcium Imaging of Neural Activity in Fly Photoreceptors

Functional imaging methodologies allow researchers to simultaneously monitor the neural activities of all single neurons in a population, and this ability has led to great advances in neuroscience research. Taking advantage of a genetically tractable model organism, functional imaging in Drosophila provides opportunities to probe scientific questions that were previously unanswerable by electrophysiological recordings. Here, we introduce comprehensive protocols for two-photon calcium imaging in fly visual neurons. We also discuss some challenges in applying optical imaging techniques to study visual systems and consider the best practices for making comparisons between different neuron groups.

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.

A place learning assay for tethered walking Drosophila

BACKGROUND

Drosophila shows a range of visually guided memory and learning behaviors, including place learning. Investigating the dynamics of neural circuits underlying such behaviors requires learning assays in tethered animals, compatible with in vivo imaging experiments.

NEW METHOD

Here, we introduce an assay for place learning for tethered walking flies. A cylindrical arena is rotated and translated in real time around the fly in concert with the rotational and translational walking activity measured with an air supported ball, resulting in a mechanical virtual reality (VR).

RESULTS

Navigation together with heat-based operant conditioning allows flies to learn the location of a cool spot with respect to a visual landmark. Flies optimize the time and distance required to find the cool spot over a similar number of trials as observed in assays with freely moving flies. Additionally, a fraction of flies remembers the location of the cool spot also after the conditioning heat is removed.

COMPARISON WITH EXISTING METHODS

Learning tasks have been implemented in tethered flying as well as walking flies. Mechanically translating and rotating an arena in concert with the fly's walking activity enables navigation in a three dimensional environment.

CONCLUSION

In the developed mechanical VR flies can learn to remember the location of a cool place within an otherwise hot environment with respect to a visual landmark. Implementing place learning in a tethered walking configuration is a precondition for investigating the underlying circuit dynamics using functional imaging.

Neural mechanisms to exploit positional geometry for collision avoidance

Visual motion provides rich geometrical cues about the three-dimensional configuration of the world. However, how brains decode the spatial information carried by motion signals remains poorly understood. Here, we study a collision-avoidance behavior in Drosophila as a simple model of motion-based spatial vision. With simulations and psychophysics, we demonstrate that walking Drosophila exhibit a pattern of slowing to avoid collisions by exploiting the geometry of positional changes of objects on near-collision courses. This behavior requires the visual neuron LPLC1, whose tuning mirrors the behavior and whose activity drives slowing. LPLC1 pools inputs from object and motion detectors, and spatially biased inhibition tunes it to the geometry of collisions. Connectomic analyses identified circuitry downstream of LPLC1 that faithfully inherits its response properties. Overall, our results reveal how a small neural circuit solves a specific spatial vision task by combining distinct visual features to exploit universal geometrical constraints of the visual world.

NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster

Animal behavior emerges from an interaction between neural network dynamics, musculoskeletal properties and the physical environment. Accessing and understanding the interplay between these elements requires the development of integrative and morphologically realistic neuromechanical simulations. Here we present NeuroMechFly, a data-driven model of the widely studied organism, Drosophila melanogaster. NeuroMechFly combines four independent computational modules: a physics-based simulation environment, a biomechanical exoskeleton, muscle models and neural network controllers. To enable use cases, we first define the minimum degrees of freedom of the leg from real three-dimensional kinematic measurements during walking and grooming. Then, we show how, by replaying these behaviors in the simulator, one can predict otherwise unmeasured torques and contact forces. Finally, we leverage NeuroMechFly's full neuromechanical capacity to discover neural networks and muscle parameters that drive locomotor gaits optimized for speed and stability. Thus, NeuroMechFly can increase our understanding of how behaviors emerge from interactions between complex neuromechanical systems and their physical surroundings.

Imaging whole-brain activity to understand behavior

The brain evolved to produce behaviors that help an animal inhabit the natural world. During natural behaviors, the brain is engaged in many levels of activity from the detection of sensory inputs to decision-making to motor planning and execution. To date, most brain studies have focused on small numbers of neurons that interact in limited circuits. This allows analyzing individual computations or steps of neural processing. During behavior, however, brain activity must integrate multiple circuits in different brain regions. The activities of different brain regions are not isolated, but may be contingent on one another. Coordinated and concurrent activity within and across brain areas is organized by (1) sensory information from the environment, (2) the animal's internal behavioral state, and (3) recurrent networks of synaptic and non-synaptic connectivity. Whole-brain recording with cellular resolution provides a new opportunity to dissect the neural basis of behavior, but whole-brain activity is also mutually contingent on behavior itself. This is especially true for natural behaviors like navigation, mating, or hunting, which require dynamic interaction between the animal, its environment, and other animals. In such behaviors, the sensory experience of an unrestrained animal is actively shaped by its movements and decisions. Many of the signaling and feedback pathways that an animal uses to guide behavior only occur in freely moving animals. Recent technological advances have enabled whole-brain recording in small behaving animals including nematodes, flies, and zebrafish. These whole-brain experiments capture neural activity with cellular resolution spanning sensory, decision-making, and motor circuits, and thereby demand new theoretical approaches that integrate brain dynamics with behavioral dynamics. Here, we review the experimental and theoretical methods that are being employed to understand animal behavior and whole-brain activity, and the opportunities for physics to contribute to this emerging field of systems neuroscience.

Axial motion estimation and correction for simultaneous multi-plane two-photon calcium imaging

Two-photon imaging in behaving animals is typically accompanied by brain motion. For functional imaging experiments, for example with genetically encoded calcium indicators, such brain motion induces changes in fluorescence intensity. These motion-related intensity changes or motion artifacts can typically not be separated from neural activity-induced signals. While lateral motion, within the focal plane, can be corrected by computationally aligning images, axial motion, out of the focal plane, cannot easily be corrected. Here, we developed an algorithm for axial motion correction for non-ratiometric calcium indicators taking advantage of simultaneous multi-plane imaging. Using temporally multiplexed beams, recording simultaneously from at least two focal planes at different z positions, and recording a z-stack for each beam as a calibration step, the algorithm separates motion-related and neural activity-induced changes in fluorescence intensity. The algorithm is based on a maximum likelihood optimisation approach; it assumes (as a first order approximation) that no distortions of the sample occurs during axial motion and that neural activity increases uniformly along the optical axis in each region of interest. The developed motion correction approach allows axial motion estimation and correction at high frame rates for isolated structures in the imaging volume in vivo, such as sparse expression patterns in the fruit fly brain.

First-order visual interneurons distribute distinct contrast and luminance information across ON and OFF pathways to achieve stable behavior

The accurate processing of contrast is the basis for all visually guided behaviors. Visual scenes with rapidly changing illumination challenge contrast computation because photoreceptor adaptation is not fast enough to compensate for such changes. Yet, human perception of contrast is stable even when the visual environment is quickly changing, suggesting rapid post receptor luminance gain control. Similarly, in the fruit fly Drosophila, such gain control leads to luminance invariant behavior for moving OFF stimuli. Here, we show that behavioral responses to moving ON stimuli also utilize a luminance gain, and that ON-motion guided behavior depends on inputs from three first-order interneurons L1, L2, and L3. Each of these neurons encodes contrast and luminance differently and distributes information asymmetrically across both ON and OFF contrast-selective pathways. Behavioral responses to both ON and OFF stimuli rely on a luminance-based correction provided by L1 and L3, wherein L1 supports contrast computation linearly, and L3 non-linearly amplifies dim stimuli. Therefore, L1, L2, and L3 are not specific inputs to ON and OFF pathways but the lamina serves as a separate processing layer that distributes distinct luminance and contrast information across ON and OFF pathways to support behavior in varying conditions.

A biophysical account of multiplication by a single neuron

Nonlinear, multiplication-like operations carried out by individual nerve cells greatly enhance the computational power of a neural system1-3, but our understanding of their biophysical implementation is scant. Here we pursue this problem in the Drosophila melanogaster ON motion vision circuit4,5, in which we record the membrane potentials of direction-selective T4 neurons and of their columnar input elements6,7 in response to visual and pharmacological stimuli in vivo. Our electrophysiological measurements and conductance-based simulations provide evidence for a passive supralinear interaction between two distinct types of synapse on T4 dendrites. We show that this multiplication-like nonlinearity arises from the coincidence of cholinergic excitation and release from glutamatergic inhibition. The latter depends on the expression of the glutamate-gated chloride channel GluClα8,9 in T4 neurons, which sharpens the directional tuning of the cells and shapes the optomotor behaviour of the animals. Interacting pairs of shunting inhibitory and excitatory synapses have long been postulated as an analogue approximation of a multiplication, which is integral to theories of motion detection10,11, sound localization12 and sensorimotor control13.

Active tactile exploration and tactually induced turning in tethered walking stick insects

Many animals use their tactile sense for active exploration and tactually guided behaviors like near-range orientation. In insects, tactile sensing is often intimately linked to locomotion, resulting in the orchestration of several concurrent active movements, including turning of the entire body, rotation of the head, and searching or sampling movements of the antennae. The present study aims at linking the sequence of tactile contact events to associated changes of all three kinds of these active movements (body, head and antennae). To do so, we chose the Indian stick insect Carausius morosus, a common organism to study sensory control of locomotion. Methodologically, we combined recordings of walking speed, heading, whole-body kinematics and antennal contact sequences during stationary, tethered walking and controlled presentation of an "artificial twig" for tactile exploration. Our results show that object presentation episodes as brief as five seconds are sufficient to allow for a systematic investigation of tactually-induced turning behavior in walking stick insects. Animals began antennating the artificial twig within 0.5 s. and altered the beating-fields of both antennae in a position-dependent manner. This change was mainly carried by a systematic shift of the head-scape joint movement and accompanied by associated changes in contact likelihood, contact location and sampling direction of the antennae. The turning tendency of the insect also depended on stimulus position, whereas the active, rhythmic head rotation remained un-affected by stimulus presentation. We conclude that the azimuth of contact location is a key parameter of active tactile exploration and tactually-induced turning in stick insects.

A pair of commissural command neurons induces Drosophila wing grooming

In many behaviors such walking and swimming, animals need to coordinate their left and right limbs. In Drosophila, wing grooming can be induced by activation of sensory organs called campaniform sensilla. Flies usually clean one wing at a time, coordinating their left and right hind legs to sweep the dorsal and ventral surfaces of the wing. Here, we identify a pair of interneurons located in the ventral nerve cord that we name wing projection neurons 1 (wPN1) whose optogenetic activation induces wing grooming. Inhibition of wPN1 activity reduces wing grooming. They receive synaptic input from ipsilateral wing campaniform sensilla and wing mechanosensory bristle neurons, and they extend axonal arbors to the hind leg neuropils. Although they project contralaterally, their activation induces ipsilateral wing grooming. Anatomical and behavioral data support a role for wPN1 as command neurons coordinating both hind legs to work together to clean the stimulated wing.

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A pair of ventral cord neurons, wPN1, is sufficient and necessary for wing grooming

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wPN1 receive contacts from two types of wing mechanosensors

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wPN1 are cholinergic and have commissural projections

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Single-side activation of wPN1 drives both hind legs to clean the ipsilateral wing

Multiphoton imaging of neural structure and activity in Drosophila through the intact cuticle

We developed a multiphoton imaging method to capture neural structure and activity in behaving flies through the intact cuticle. Our measurements showed that the fly head cuticle has surprisingly high transmission at wavelengths >900nm, and the difficulty of through-cuticle imaging is due to the air sacs and/or fat tissue underneath the head cuticle. By compressing or removing the air sacs, we performed multiphoton imaging of the fly brain through the intact cuticle. Our anatomical and functional imaging results show that 2- and 3-photon imaging are comparable in superficial regions such as the mushroom body, but 3-photon imaging is superior in deeper regions such as the central complex and beyond. We further demonstrated 2-photon through-cuticle functional imaging of odor-evoked calcium responses from the mushroom body γ-lobes in behaving flies short term and long term. The through-cuticle imaging method developed here extends the time limits of in vivo imaging in flies and opens new ways to capture neural structure and activity from the fly brain.

Excessive energy expenditure due to acute physical restraint disrupts Drosophila motivational feeding response

To study the behavior of Drosophila, it is often necessary to restrain and mount individual flies. This requires removal from food, additional handling, anesthesia, and physical restraint. We find a strong positive correlation between the length of time flies are mounted and their subsequent reflexive feeding response, where one hour of mounting is the approximate motivational equivalent to ten hours of fasting. In an attempt to explain this correlation, we rule out anesthesia side-effects, handling, additional fasting, and desiccation. We use respirometric and metabolic techniques coupled with behavioral video scoring to assess energy expenditure in mounted and free flies. We isolate a specific behavior capable of exerting large amounts of energy in mounted flies and identify it as an attempt to escape from restraint. We present a model where physical restraint leads to elevated activity and subsequent faster nutrient storage depletion among mounted flies. This ultimately further accelerates starvation and thus increases reflexive feeding response. In addition, we show that the consequences of the physical restraint profoundly alter aerobic activity, energy depletion, taste, and feeding behavior, and suggest that careful consideration is given to the time-sensitive nature of these highly significant effects when conducting behavioral, physiological or imaging experiments that require immobilization.

Automated long-term two-photon imaging in head-fixed walking Drosophila

BACKGROUND

The brain of Drosophila shows dynamics at multiple timescales, from the millisecond range of fast voltage or calcium transients to functional and structural changes occurring over multiple days. To relate such dynamics to behavior requires monitoring neural circuits across these multiple timescales in behaving animals.

NEW METHOD

Here, we develop a technique for automated long-term two-photon imaging in fruit flies, during wakefulness and extended bouts of immobility, as typically observed during sleep, navigating in virtual reality over up to seven days. The method is enabled by laser surgery, a microrobotic arm for controlling forceps for dissection assistance, an automated feeding robot, as well as volumetric, simultaneous multiplane imaging.

RESULTS

The approach is validated in the fly's head direction system and walking behavior as well a neural activity are recorded. The head direction system tracks the fly's walking direction over multiple days.

COMPARISON WITH EXISTING METHODS

In comparison with previous head-fixed preparations, the time span over which tethered behavior and neural activity can be recorded at the same time is extended from hours to days. Additionally, the reproducibility and ease of dissections are improved compared with manual approaches. Different from previous laser surgery approaches, only continuous wave lasers are required. Lastly, an automated feeding system allows continuously maintaining the fly for several days in the virtual reality setup without user intervention.

CONCLUSIONS

Imaging in behaving flies over multiple timescales will be useful for understanding circadian activity, learning and long-term memory, or sleep.

Motion cues from the background influence associative color learning of honey bees in a virtual-reality scenario

Honey bees exhibit remarkable visual learning capacities, which can be studied using virtual reality (VR) landscapes in laboratory conditions. Existing VR environments for bees are imperfect as they provide either open-loop conditions or 2D displays. Here we achieved a true 3D environment in which walking bees learned to discriminate a rewarded from a punished virtual stimulus based on color differences. We included ventral or frontal background cues, which were also subjected to 3D updating based on the bee movements. We thus studied if and how the presence of such motion cues affected visual discrimination in our VR landscape. Our results showed that the presence of frontal, and to a lesser extent, of ventral background motion cues impaired the bees' performance. Whenever these cues were suppressed, color discrimination learning became possible. We analyzed the specific contribution of foreground and background cues and discussed the role of attentional interference and differences in stimulus salience in the VR environment to account for these results. Overall, we show how background and target cues may interact at the perceptual level and influence associative learning in bees. In addition, we identify issues that may affect decision-making in VR landscapes, which require specific control by experimenters.