The Interactive Fly
Genes regulating behavior
Visual systems process the information from the environment in parallel neuronal subsystems. In higher vertebrates, for instance, the visual modalities of color, form, and motion are segregated at the level of the retina into separate channels. Similarly, insects have distinct sets of photoreceptors for motion and color. Investigating the motion channel in the fly Drosophila, this study shows that at the next level below the eye, the lamina, the motion channel is again split into several functionally distinct parallel pathways (Rister, 2007).
Directional responses to visual motion have been intensely studied, predominantly in dipteran flies. They are provided by arrays of elementary movement detectors (EMDs), the smallest motion-sensitive units that temporally compare the intensity fluctuations in neighboring visual elements (sampling units). Their neuronal implementation in flies is still unknown. In the rabbit retina, a candidate interneuron computing directional motion has recently been identified. The present study is confined to the input side of the movement-detection circuitry (Rister, 2007).
The compound eye of Drosophila is composed of about 750 ommatidia. Each of these contains eight photoreceptors (R1-8) that can be structurally and functionally grouped into two subsystems: six large photoreceptors (R1-6) mediate the detection of motion , whereas two small ones (R7, R8), together forming one rhabdomere in the center of the ommatidium, are required for color vision (Rister, 2007).
The lamina consists of corresponding units called neuro-ommatidia, or cartridges. These are the sampling units of the motion channel, whereas the color channel (R7, R8) bypasses the lamina cartridge to terminate in the second neuropil, the medulla. The lamina is anatomically and ultrastructurally known in exquisite detail. Its functional significance, however, is little understood (Rister, 2007).
In the lamina, the motion channel is split into four parallel pathways. In each cartridge, the photoreceptor terminals are connected by tetradic synapses to four neurons, L1, L2, L3, and the amacrine cell α (amc; connecting to the medulla via the basket cell T1). The most prominent of these are the large monopolar cells L1 and L2. Their position in the center and their radially distributed dendrites throughout the depth of the cartridge suggest a key role in peripheral processing. This can be visualized by 3H-deoxyglucose activity labeling. Single-unit recordings of L1 and L2 in large flies so far have revealed only subtle differences between them. Their specific functional contribution to behavior is largely unknown (Rister, 2007).
Several hypotheses have been advanced over the last 40 years. The loss of L1 and L2 and concomitantly of optomotor responses in the mutant Vacuolar medullaKS74 had prompted a proposal that these cells were involved in motion detection. If indeed L1 and L2 mediate motion vision, are they functionally specialized or redundant? The latter is unlikely to be the whole answer, considering the differing synaptic relationships of the two neurons. For one, they have their terminals in separate layers of the medulla. Second, L2, but not L1, has feedback synapses onto R1-6. These might play a role in neuronal adaptation and could exert a modulatory influence on the photoreceptor output (Rister, 2007).
In Drosophila, L2 innervates and reciprocally receives input from a second-order interneuron, L4, that has two conspicuous backward oriented collaterals connecting its own cartridge to the neighboring ones along the x and y axes of the hexagonal array. In this network, the L2 neurons are connected to the L4 neurons of two adjacent cartridges, and the L4 neurons are directly connected to all six neighboring L4s. The significance of this circuitry is not yet understood (Rister, 2007).
Using the two-component UAS/GAL4 system for targeted transgene expression, single interneurons or combinations of them were manipulated, in all lamina cartridges. To study whether a particular pathway was necessary for a given behavioral task, their synaptic output was blocked using the temperature-sensitive allele of shibire, shits1. In addition, the inverse strategy was adopted, studying whether single lamina pathways were sufficient for mediating the behavior in the same experimental context. Using a mutant of the histamine receptor gene outer rhabdomeres transientless (ort) that has all lamina pathways impaired, the wild-type ort-cDNA was expressed in chosen types of lamina interneurons known to receive histaminergic input from R1-6. Testing necessity and sufficiency it is not possible to relate the structural organization of the lamina to visually guided behavior (Rister, 2007).
Animals must quickly recognize objects in their environment and act accordingly. Previous studies indicate that looming visual objects trigger avoidance reflexes in many species; however, such reflexes operate over a close range and might not detect a threatening stimulus at a safe distance. This study analyzed how fruit flies 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, 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 (Maimon, 2008).
Observations on free-flying flies together with experiments on tethered flies in closed and open loop demonstrate that Drosophila possess two opposing visuomotor reflexes that explain salient features of the animal's flight behavior. Animals are attracted to long vertical objects, whereas they are repulsed by small objects. The visually guided behaviors detailed in this paper are most probably mediated by motion-sensitive neurons downstream of photoreceptors R1-R6. Specifically, in the lobula plate of blowflies, 'feature-detecting' cells respond vigorously to elongated vertical contours. The homologs of these neurons might mediate fixation of long stripes in Drosophila. In houseflies and hoverflies, other neurons in the lobula plate and lobula respond best to small stimuli, and the homologs of these cells might underlie small-object aversion in Drosophila. Because the chromaticity of the stimuli was not varied, the contribution of color as an additional cue that flies use in triggering attractive and aversive flight responses cannot be excluded (Maimon, 2008).
Males of many fly species, including houseflies (Musca domestica, Fania cunnicularis), flesh flies (Sarcophaga bullata), and hoverflies (Syritta pipiens), chase females as part of courtship. Long-legged flies (Dolichopodidae) and robber flies (Asilidae) prey upon small insects on the wing. Thus, at least in certain behavioral contexts, some flying dipterans are attracted toward small spots, not repelled. Drosophila, however, do not prey on other insects, and courtship does not involve flight. From an ethological point of view, Drosophila would do well to avoid any small object in midair, even static objects, because these could only signify a hazard. In contrast, dipterans that chase conspecifics, or hunt while flying, require a more sophisticated algorithm that may, for example, rely on more complex features of object motion or color to differentiate repulsive predators from attractive mates and prey (Maimon, 2008).
The results indicate that flying flies use a rather simple vision-based algorithm to avoid potentially harmful objects. Might walking flies use a similar strategy? The visual-motor behaviors of walking Drosophila are likely to be more complicated because these flies exhibit social behaviors such as courtship and aggression while on the ground. For example, male flies could not chase and orient toward female flies if small objects were aversive to them. It has been suggested that walking Drosophila might exhibit a similar behavior as the one reported here for flying Drosophila, i.e., attraction to tall stripes and aversion to small spots. However, this behavior is not consistent with studies using 'Buridan's paradigm,' which show that walking flies respond equivalently to long and short visual objects, or another study that did not report either clear attraction to or repulsion by small objects. Collectively, these studies do not present a simple picture of comparable reflexes in walking Drosophila, as might be expected from the more complicated suite of behaviors that occur on the ground (Maimon, 2008).
This study describes a new visuomotor reflex: small-object repulsion, which has a measurable influence on free-flight behavior. Whereas the neural mechanisms of this reflex remain unknown, the differing responses to long and short objects suggest that the two behaviors may be, at least partly, mediated by different neural circuits (although it is likely that many of the same cells are activated in both behaviors, especially near the sensory and motor periphery). An intriguing possibility is that the visual control of flight in Drosophila arises from a handful of partly nonoverlapping sensorimotor neural pathways, including long-object fixation, small-object repulsion, expansion avoidance, optomotor equilibrium, and landing responses. These innate behaviors, and potentially others yet to be discovered, could additionally be modified by learning. The molecular tools available in Drosophila should allow for a rich, mechanistic description of each individual pathway. More significantly, however, elementary rules governing the interaction of these putative sensorimotor modules may come into sharper focus, thereby allowing for the formulation of a bottom-up, biologically driven theory of behavior (Maimon, 2008).
Ants can navigate over long distances between their nest and food sites using visual cues. Can ants use their visual memories of the terrestrial cues when going backward? The results suggest that ants do not adjust their direction of travel based on the perceived scene while going backward. Instead, they maintain a straight direction using their celestial compass. This direction can be dictated by their path integrator but can also be set using terrestrial visual cues after a forward peek. If the food item is too heavy to enable body rotations, ants moving backward drop their food on occasion, rotate and walk a few steps forward, return to the food, and drag it backward in a now-corrected direction defined by terrestrial cues. Furthermore, it was shown that ants can maintain their direction of travel independently of their body orientation. It thus appears that egocentric retinal alignment is required for visual scene recognition, but ants can translate this acquired directional information into a holonomic frame of reference, which enables them to decouple their travel direction from their body orientation and hence navigate backward. This reveals substantial flexibility and communication between different types of navigational information: from terrestrial to celestial cues and from egocentric to holonomic directional memories (Schwarz, 2017).
Flies generate robust and high-performance olfactory and visual behaviors. Adult fruit flies can distinguish small differences in odor concentration across antennae separated by less than 1 mm, and a single olfactory sensory neuron is sufficient for near-normal gradient tracking in larvae. During flight a male housefly chasing a female executes a corrective turn within 40 ms after a course deviation by its target. The challenges imposed by flying apparently benefit from the tight integration of unimodal sensory cues. Crossmodal interactions reduce the discrimination threshold for unimodal memory retrieval by enhancing stimulus salience, and dynamic crossmodal processing is required for odor search during free flight because animals fail to locate an odor source in the absence of rich visual feedback. The visual requirements for odor localization are unknown. In this study, a hungry fly was tethered in a magnetic field, allowing it to yaw freely, odor plumes were presented, and how visual cues influence odor tracking was examined. Flies were found to be unable to use a small-field object or landmark to assist plume tracking, whereas odor activates wide-field optomotor course control to enable accurate orientation toward an attractive food odor (Duistermars, 2008).
This study investigated the motor control of active plume tracking by adapting a magnetic tether system into a 'virtual plume simulator' in which a fly is free to steer into and out of a spatially discrete plume of vinegar odor while simultaneously receiving visual feedback from a stationary wraparound electronic display. Flight behavior on the magnetic tether, like in free flight, is characterized by segments of straight flight interspersed with transient 'spikes' in angular velocity called 'body saccades' for their functional analogy with human gaze-stabilizing eye movements. Within a visual arena composed of equally spaced, high-contrast vertical stripes, a pattern that generates strong, spatially homogeneous optic-flow signals when the animal rotates on its pivot, the vinegar plume was periodically switched between 0° and 180° positions in the circular arena and the fly's heading was tracked. Under these conditions, the animal periodically encounters the plume by steering into it. Upon plume contact, identified by the animal's heading with respect to the odor port, the interval between saccades increases, whereas subsequently deviating from the plume results in a return of the typical saccadic rhythm. Thus by presenting only the water vapor control, flies iterate saccades with little apparent preferred orientation, resulting in an even distribution of heading within the arena. By contrast, encountering an odor plume results in stabilized flight heading directed toward the plume at either side of the arena. These results confirm that the two odor plumes were the most attractive features of the arena, that both locations could reliably and reversibly elicit stable odor tracking, and that the plume itself is narrow, as reflected by the 18° width of the heading histograms at half-maximum (Duistermars, 2008).
When compared to the high-contrast panorama in the absence of an odor plume, the visually uniform arena itself elicits smaller angle saccades, with shorter intervals between them. In an odor plume, these two responses would work against one another for stable tracking; smaller amplitude saccades would keep the animal close to the plume, but shorter saccade intervals (increased rate) would not. Upon encountering the odor plume within the high-contrast visual panorama, flies show decreased saccade amplitude and increased intersaccade interval (ISI) in comparison to the same flight trajectories oriented outside the plume. These two responses combine to facilitate plume tracking because saccades that would move the fly out of the plume are fewer and smaller. Under uniform featureless visual conditions, there are no such changes in saccade frequency or amplitude upon plume contact, indicating a crossmodal influence on saccade motor commands. Furthermore, only within the high-contrast visual treatment are saccade amplitude and ISI outside the attractive odor plume lower than during the no-odor experiment. It would appear, therefore, that like the casting dynamics of free flight, saccade amplitude and ISI are influenced both by plume acquisition and subsequent plume loss but in a visual-context-dependent manner. It seems reasonable to postulate that visual feedback provides a directional cue that enables a fly to correct a deviation from the plume during a saccade (Duistermars, 2008).
Once initiated, saccade dynamics are coordinated entirely by mechanosensory feedback, whereas flying straight and avoiding collisions require well-studied optomotor equilibrium reflexes. Saccades in the odor plume are fewer and smaller, but not altogether absent. Is the visually dependent quantitative reduction in saccade rate and amplitude fully sufficient to enable stable plume tracking, or do odor cues activate optomotor responses in order to stabilize flight heading between saccades? There is no a priori reason to suspect the latter, particularly because a walking fruit fly is capable of orienting toward a static concentration gradient delivered across the antennae in the absence of visual cues. Yet, for accurate odor tracking during free flight, Drosophila require visual feedback from the lateral panorama (Duistermars, 2008).
To address this issue, the accuracy of plume tracking was measured for animals exposed to a sequence of different visual conditions. Taking advantage of a well-known and powerful object-orientation reflex in which flies actively fixate a high-contrast, vertical stripe within their forward field of view, a narrow stripe was slowly oscillated to visually 'drag' flies into the odor plume at the 180° arena position before instantly replacing the stripe with a stationary visual panorama. Therefore, for each experimental treatment, animals started from the same heading within either the water or vinegar plume and were subsequently exposed to either a high-contrast pattern of evenly spaced stripes or a featureless grayscale panorama of identical mean luminance, which provides light levels necessary to sustain active flight but provides minimal visual motion cues. To quantify the accuracy of plume tracking for each flight trajectory, the cumulative deviation from the odor plume was derived by subtracting 180 from the heading values, taking the absolute value and integrating it over time. The resultant cumulative time series has units of degree seconds and represents the flies' ability to stabilize the plume such that low values represent accurate plume tracking, and high values correspond to orientation 'error'(turning away from the plume into other regions of the arena). Note that cumulative deviation generally cannot remain at zero because flies continuously make fine-scale, back-and-forth adjustments to their heading, which results in an ever increasing cumulative deviation from the 180° arena position. Therefore, by design, mean cumulative plume deviation is a conservative estimate of a fly's ability to actively track a plume (Duistermars, 2008).
For the water vapor plume set against the uniform grayscale visual panorama, flies executed the usual rhythm of saccades and thus deviated from the plume within a few seconds after the start of the trial. Switching the visual panorama to high-contrast stripes did not significantly change flies' cumulative plume deviation. Predictably, for the water vapor plume and both visual treatments, flies oriented randomly throughout the arena. However, upon activating the odor plume against the high-contrast stripe background, the same animals remained tightly centered within the plume for the duration of the trial, resulting in 75% reduction in cumulative plume deviation. Remarkably, replacing the high-contrast visual scene with the featureless uniform panorama resulted in decreased tracking accuracy because animals quickly deviated from the odor plume in a manner similar to the no-odor control. The cumulative plume deviation was not significantly different between the uniform visual arena with odor and the striped arena without odor, indicating that in the absence of rich visual feedback the flies essentially behave as if there were no odor, highlighting the crossmodal requirements for odor tracking (Duistermars, 2008).
The visual influence on odor-tracking accuracy was further examined by activating the odor plume continuously while presenting a sequence of three visual treatments including high-contrast stripes, uniform grayscale, and a second high-contrast treatment. Each fly therefore started within the vinegar plume and was exposed to the three visual stimuli at 20 second intervals. When the striped panorama appeared at the start of the trial, flies maintained their heading into the plume. But once the stripes disappeared, the flies steered out of the plume and began generating saccades. Whereas occasionally they reencounter the plume within the uniform visual panorama, they generally are unable to remain there until the high-contrast pattern reappears, at which point accurate plume tracking resumes. Mean cumulative plume deviation increased significantly between the first high-contrast treatment and the uniform arena and then recovered to the initial value for the second high-contrast treatment (Duistermars, 2008).
For the visual manipulation experiments, the order of experimental treatments followed a predetermined sequence and each fly was presented with the sequence once and only once. To examine whether treatment order influenced the results, the entire experiment was repeated with a random block design in which the set of visual and olfactory treatments were randomly shuffled for each individual fly. The randomized experiment disclosed the same results as the ordered experiment; the high-contrast visual panorama significantly reduces the cumulative deviation from the odor plume by comparison to a uniform grayscale panorama (Duistermars, 2008).
Anatomical, physiological, and behavioral analyses suggest that the fly optomotor system is segregated into two parallel channels: one processes wide-field visual motion and the other processes small-field visual and object motion. It is thought that these two separate systems contribute to figure-ground discrimination and enable animals to see and track moving objects against a cluttered visual background. Additionally, active stripe fixation during flight may represent the fly's attempt to approach a suitable landing site, such as a plant stalk. Another remarkable use of small-field vision is demonstrated by home-base foragers, such as ants, that use objects located some distance from food resources or nests as landmarks to navigate return paths to those sites. This study shows that crossmodal feedback generated by the fly's movement within a homogeneous wide-field visual landscape enables active plume tracking. Is the synergistic crossmodal influence on odor tracking specific to wide-field visual signals, or can flies also use small-field visual cues, such as spatial landmarks, to maintain their heading in an odor plume? To examine this idea, flies were subjected to a stationary vertical stripe offset 90° from the odor plume. Flies starting within a control water plume veered out of the plume within several seconds and instead fixated the visual object, thus resulting in a rapidly increasing mean cumulative plume deviation. Starting a new trial with the vinegar-odor stimulus, the same flies showed a stronger tendency to stay in or near the plume, resulting in a roughly 50% reduction in cumulative plume deviation. At first glance, it might appear that the small-field stripe enhances odor tracking by comparison to the no-odor control. However, the critical question is whether a laterally displaced small-field object reduces the cumulative plume deviation by comparison to a uniform panorama, and it does not. The mean cumulative plume deviation for the small-field stripe is equivalent to the measurement for the uniform grayscale panorama. Accurate plume tracking requires wide-field visual input (Duistermars, 2008).
Unlike the propagation of visual or acoustic stimuli, an olfactory signal contains no intrinsic directional information. Therefore, animals often rely on ambient wind cues to determine the route to an odor source. Odor tracking by upwind flight requires visual feedback generated by background motion because an animal cannot easily distinguish ambient wind direction from self-induced airflow during flight. As such, in the absence of wind cues, tethered Drosophila provided with a visual stimulus analogous to being carried downwind steer so as to maintain an upwind heading. This response persists whether the animal views the moving ground below or the visual landscape laterally. In addition to directional control, when faced with headwinds, insects such as flies, beetles, bees, and moths regulate their airspeed and altitude by the use of visual cues, the combination of which enables accurate navigation of a female pheromone plume by a male moth. In previous free-flight experiments, it has not been possible to determine whether optomotor stabilization is triggered directly by odor cues or indirectly by wind-driven ground motion. This study shows that rotational stabilization reflexes are directly activated by odor cues independent of ambient wind cues (Duistermars, 2008).
The crossmodal influence of visual feedback on odor tracking in flies provides insight into how complex behaviors are controlled within environments containing nondirectional, weak, noisy, or subthreshold sensory stimuli. Fruit flies have 700 times lower visual spatial resolution than humans, and they have five times fewer olfactory receptor types. Yet their ability to find smelly things in visual landscapes as diverse as forests, deserts, and backyard patios would suggest behavioral performance greater than might be predicted by the sum of the salient sensory inputs. The results presented in this study show that odor signals activate powerful visual stabilization reflexes to accurately track an appetitive odor plume. The requisite visual feedback cues emerge from the wide-field visual-processing centers of the brain, not the small-field object-tracking centers, thus hinting at possible neuroanatomical substrates. Furthermore, the functional interaction of crossmodal integration for plume tracking in flies is reminiscent of multisensory enhancement (MSE) exhibited by single neurons within the cat superior colliculus. Here, neurons with overlapping receptive fields generally obey a principle known as 'inverse effectiveness,' whereby smaller, modality-specific responses are associated with larger, multisensory responses. As such, MSE results in cell excitability that is greater than the mathematical sum of the individual inputs, especially when unimodal input is weak. The superior colliculus forms a tissue map registering spatial information from two sensory modalities. It seems unlikely that visual-olfactory integration in the fly brain occurs with a structurally analogous system but, rather, a functionally analogous one. In gypsy moths, spiking responses within visually selective premotor interneurons are enhanced by sex pheromones. Similarly, the rattlesnake optic tectum contains individual neurons that exhibit nonlinear crossmodal enhancement of visual and thermal responses, presumably to guide prey capture in near darkness. It would appear that crossmodal integration at the behavioral and cellular level represents a functional adaptation for distinguishing and responding to critically important features of a complex sensory environment (Duistermars, 2008).
The evolution of powered flight in insects had major consequences for global biodiversity and involved the acquisition of adaptive processes allowing individuals to disperse to new ecological niches. Flies use both vision and olfactory input from their antennae to guide their flight; chemosensors on fly wings have been described, but their function remains mysterious. This study examineed Drosophila flight in a wind tunnel. By genetically manipulating wing chemosensors, it was shown that these structures play an essential role in flight performance with a sex-specific effect. Pheromonal systems are also involved in Drosophila flight guidance: transgenic expression of the pheromone production and detection gene, desat1, produced low, rapid flight that was absent in control flies. This study suggests that the sex-specific modulation of free-flight odor tracking depends on gene expression in various fly tissues including wings and pheromonal-related tissues (Houot, 2017).
Climbing over chasms larger than step size is vital to fruit flies, since foraging and mating are achieved while walking. Flies avoid futile climbing attempts by processing parallax-motion vision to estimate gap width. To identify neuronal substrates of climbing control, a large collection of fly lines with temporarily inactivated neuronal populations were screened in a novel high-throughput assay. The observed climbing phenotypes were classified; lines in each group are reported. Selected lines were further analysed by high-resolution video cinematography. One striking class of flies attempts to climb chasms of unsurmountable width; expression analysis led to C2 optic-lobe interneurons. C2 columnar feedback neurons project from the second visual neuropil, the medulla, to the most peripheral optic-lobe region, the lamina. Inactivation of C2 or the closely related C3 neurons with highly specific intersectional driver lines consistently reproduced hyperactive climbing whereas strong or weak artificial depolarization of C2/C3 neurons strongly or mildly decreased climbing frequency. Contrast-manipulation experiments support conclusion that C2/C3 neurons are part of the distance-evaluation system (Triphan, 2016).
Animals must use external cues to maintain a straight course over long distances. This study investigated how the fruit fly, Drosophila melanogaster, selects and maintains a flight heading relative to the axis of linearly polarized light, a visual cue produced by the atmospheric scattering of sunlight. To track flies' headings over extended periods, a flight simulator was used that coupled the angular velocity of dorsally presented polarized light to the stroke amplitude difference of the animal's wings. In the simulator, most flies actively maintained a stable heading relative to the axis of polarized light for the duration of 15 minute flights. Individuals selected arbitrary, unpredictable headings relative to the polarization axis, which demonstrates that Drosophila can perform proportional navigation using a polarized light pattern. When flies flew in two consecutive bouts separated by a 5 minute gap, the two flight headings were correlated, suggesting individuals retain a memory of their chosen heading. Adding a polarized light pattern to a light intensity gradient was found to enhance flies' orientation ability, suggesting Drosophila use a combination of cues to navigate. For both polarized light and intensity cues, flies' capacity to maintain a stable heading gradually increased over several minutes from the onset of flight. These findings are consistent with a model in which each individual initially orients haphazardly but then settles on a heading which is maintained via a self-reinforcing process. This may be a general dispersal strategy for animals with no target destination (Warren, 2081).
It is widely accepted for humans and higher animals that vision is an active process in which the organism interprets the stimulus. To find out whether this also holds for lower animals, an ambiguous motion stimulus was designed that serves as something like a multi-stable perception paradigm in Drosophila behavior. Confronted with a uniform panoramic texture in a closed-loop situation in stationary flight, the flies adjust their yaw torque to stabilize their virtual self-rotation. To make the visual input ambiguous, a second texture was examined. Both textures got a rotatory bias to move into opposite directions at a constant relative angular velocity. The results indicate that the fly now had three possible frames of reference for self-rotation: either of the two motion components as well as the integrated motion vector of the two. In this ambiguous stimulus situation, the flies generated a continuous sequence of behaviors, each one adjusted to one or another of the three references (Toepfer, 2018).
Climbing over chasms larger than step size is vital to fruit flies, since foraging and mating are achieved while walking. Flies avoid futile climbing attempts by processing parallax-motion vision to estimate gap width. To identify neuronal substrates of climbing control, a large collection of fly lines with temporarily inactivated neuronal populations were screened in a novel high-throughput assay. The observed climbing phenotypes were classified; lines in each group are reported. Selected lines were further analysed by high-resolution video cinematography. One striking class of flies attempts to climb chasms of unsurmountable width; expression analysis led to C2 optic-lobe interneurons. C2 columnar feedback neurons project from the second visual neuropil, the medulla, to the most peripheral optic-lobe region, the lamina. Inactivation of C2 or the closely related C3 neurons with highly specific intersectional driver lines consistently reproduced hyperactive climbing whereas strong or weak artificial depolarization of C2/C3 neurons strongly or mildly decreased climbing frequency. Contrast-manipulation experiments support conclusion that C2/C3 neurons are part of the distance-evaluation system (Triphan, 2016).
For a fruit fly, locating fermenting fruit where it can feed, find mates, and lay eggs is an essential and difficult task requiring the integration of olfactory and visual cues. An approach has been developed to correlate flies' free-flight behavior with their olfactory experience under different wind and visual conditions, yielding new insight into plume tracking based on over 70 hr of data. To localize an odor source, flies exhibit three iterative, independent, reflex-driven behaviors, which remain constant through repeated encounters of the same stimulus: (1) 190 +/- 75 ms after encountering a plume, flies increase their flight speed and turn upwind, using visual cues to determine wind direction. Due to this substantial response delay, flies pass through the plume shortly after entering it. (2) 450 +/- 165 ms after losing the plume, flies initiate a series of vertical and horizontal casts, using visual cues to maintain a crosswind heading. (3) After sensing an attractive odor, flies exhibit an enhanced attraction to small visual features, which increases their probability of finding the plume's source. Due to plume structure and sensory-motor delays, a fly's olfactory experience during foraging flights consists of short bursts of odor stimulation. As a consequence, delays in the onset of crosswind casting and the increased attraction to visual features are necessary behavioral components for efficiently locating an odor source. These results provide a quantitative behavioral background for elucidating the neural basis of plume tracking using genetic and physiological approaches (van Breugel, 2014).
To better understand how organisms make decisions on the basis of temporally varying multi-sensory input, this study identified computations made by Drosophila larvae responding to visual and optogenetically induced fictive olfactory stimuli. The larva's navigational decision was modeled to initiate turns as the output of a Linear-Nonlinear-Poisson cascade. Reverse-correlation was used to fit parameters to this model; the parameterized model predicted larvae's responses to novel stimulus patterns. For multi-modal inputs, it was found that larvae linearly combine olfactory and visual signals upstream of the decision to turn. This prediction was verified by measuring larvae's responses to coordinated changes in odor and light. Other navigational decisions were studied, and larvae were found to integrate odor and light according to the same rule in all cases. These results suggest that photo-taxis and odor-taxis are mediated by a shared computational pathway (Gepner, 2015).
A key step in 'cracking' neural circuits is defining the computations carried out by those circuits. Recent work has refined the measurements of circuits' behavioral outputs, for example, from simply counting animals accumulating near an odor source to specifying the sequence of motor outputs that allow odor gradient ascent. This study carried on this refinement, quantifying the transformation from sensory activity to motor decision with sub-second temporal resolution. Reverse-correlation analysis captured the essential features of the larva's navigational decision making, including the time scales and stimulus features associated with various decisions (Gepner, 2015).
The results are consistent with the understanding of how larvae navigate natural environments previously developed by observing behavior in structured environments of light or gaseous odors. For instance, when placed in environments with spatially varying Ethyl Butyrate or Ethyl Acetate oncentrations, larvae initiate turns more frequently when headed in directions of decreasing concentrations of these attractive odors. The current study has shown that larvae initiate turns in response to a decrease in activity in Or42a or Or42b receptor neurons, the primary receptors for Ethyl Acetate and Ethyl Butyrate. Additionally, this study showed that larvae mainly use only the previous two seconds of receptor activity to decide whether to turn. This detail cannot be resolved from experiments in natural odor gradients, nor can the fact that larvae integrate changes in odor receptor activity over a much longer time period to decide the size of their turns (Gepner, 2015).
When larvae move their heads through a spatially heterogeneous environment, they generate changes in sensory input that could be used to decode local spatial gradients. It has been directly shown that warming a cold larva during a head-sweep causes the larva to accept that head-sweep, beginning a new run. For light and odor, a strong circumstantial case has been made that larvae use information gathered during head-sweeps to bias turn direction: the first head-sweep of a turn is unbiased but larvae are more likely to begin a run following a sweep in a direction of higher concentration of attractive odor, lower concentration of carbon dioxide, or lower luminosity and larvae with only a single functional odor receptor can still bias turn direction via head-sweeping. This work has directly shown that larvae do in fact use changes in odor receptor activity and light level measured during head-sweeps to determine whether to begin a new run or initiate a second head-sweep (Gepner, 2015).
The experiments with a single stimulus also found a previously unknown difference in how larvae use CO2 receptor activity to modulate turn size and head-sweep acceptance compared to visual stimuli and to attractive olfactory receptor activity. This could be related to a difference in how larvae modulate their forward motion in response to changes in CO2 concentration compared to changes in light intensity or EtAc concentration. Previous studies have measured larvae's responses to linear temporal ramps of light intensity, and EtAc and CO2 concentrations (Gershow, 2012). For light and EtAc, larvae changed their rate of turning and the size of their turns in response to changing environmental conditions, but when they were actually engaged in forward movement, their speed of progress was the same whether conditions were improving or declining. In contrast, larvae dramatically decreased their forward run speed in response to increases in the concentration of CO2. Larvae with non-functional CO2 receptors did not change their speed at all in response to CO2, so this modulation was due to a sensory-motor transformation and not to metabolic effects (Gepner, 2015).
Larvae move forward through a series of tail to head peristaltic waves of muscle contraction and modulate their forward speed by changing the frequency with which they initiate these waves. The observed CO2 dependent speed modulation might therefore reflect the presence of a pathway by which Gr21a receptor neuron activity can down-regulate the probability of initiating forward peristaltic waves. In order to accept a head-sweep, that is, transition from head-sweeping to forward movement, larvae must initiate a new peristaltic wave (Lahiri, 2011). If an increase in Gr21a activity decreases the probability of initiating such a wave, this would explain why an increase in Gr21a activity prior to head-sweep initiation results in an increased probability of head-sweep rejection. Similarly, an increase in Gr21a activity might bias the larva towards larger reorientations by decreasing the probability of quick, small course corrections (Gepner, 2015).
In addition to defining the computations by which larvae navigate environments of varying light or varying odor, a quantitative model of odor-light integration was developed for this study. Previously, it has proven difficult to establish even a qualitative understanding of odor and light integration using static combinations of the two cues. Consider a simple experiment where a petri dish is divided into light and dark halves and a droplet of attractive odor is placed on the lighted half. If a larva moves towards the odor at the expense of moving out of darkness, is this because the larva naturally places more importance on odor than light regardless of intensity, because the particular concentrations of odor and intensities of light in the experiment favor a move towards odor, or because behavior is variable and larvae often make idiosyncratic choices? In the reverse-correlation experiments, hundreds of larvae were presented with thousands of combinations of light and odor variation and it was thus possible to resolve these ambiguities. The study determined not just how larvae balance an overall attraction to odor and aversion to light, but how they combine transient odor and light signals to make individual navigational decisions (Gepner, 2015).
This study has demonstrated the power of reverse-correlation analysis of larvae's behavioral responses to white-noise visual and fictive olfactory stimuli to decode the computations underlying the Drosophila larva's navigation of natural environments. This analysis could be used to decode the rules by which the larva integrates signals from distinct sensory organs. Larvae appear to use a single linear combination of odor and light inputs to make all navigational decisions, suggesting these signals are combined at early stages of the navigational circuitry (Gepner, 2015).
This work used optogenetics to explore how perturbations in the activities of identified neurons are interpreted behaviorally. CsChrimson was expressed in specific neurons to relate patterns of activity in these neurons to decisions regulating the frequency, size, and direction of turns. Using model parameters extracted from reverse-correlation experiments, it was possible to predict how larvae would respond to novel perturbations of these neurons' activities. How activity in one particular neuron type modulated the larva's responses to a natural light stimulus was explored and predictions were made of how the larva's natural response to blue light stepsv would be altered by simultaneous perturbation of this neuron. This study addressed sensory neurons, but the approach can be used generally to identify computations carried out on activities of interneurons, to determine whether activity in a neuron is interpreted as attractive or aversive, to measure how that activity combines with other sources of information to produce decisions, and to find neurons most responsible for making navigational decisions (Gepner, 2015).
The means by which brains transform sensory information into coherent motor actions is poorly understood. In flies, a relatively small set of descending interneurons are responsible for conveying sensory information and higher-order commands from the brain to motor circuits in the ventral nerve cord. This study describes three pairs of genetically identified descending interneurons that integrate information from wide-field visual interneurons and project directly to motor centers controlling flight behavior. The physiological responses of these three cells were measured during flight, and they were found to respond maximally to visual movement corresponding to rotation around three distinct body axes. After characterizing the tuning properties of an array of nine putative upstream visual interneurons, it was shown that simple linear combinations of their outputs can predict the responses of the three descending cells. Last, a machine vision-tracking system was developed that allows monitoring of multiple motor systems simultaneously, and each visual descending interneuron class was found to correlate with a discrete set of motor programs (Suver, 2016).
This study has identified three pairs of descending neurons that integrate input from an array of visual interneurons in Drosophila. DNOVS1 and DNOVS2 are likely the homologs of neurons in larger flies, whereas DNHS1 is a previously undescribed cell. The tuning properties of these neurons during flight were measured, and they were found to encode three distinct axes of rotation, which are predicted by a linear summation of the responses of presynaptic vertical system (VS) and horizontal system (HS) cells (lobula plate tangential cells). The descending neurons project to nonoverlapping regions of dorsal neuropil within the ventral nerve cord (VNC), suggesting that they control different motor programs associated with flight. Indeed, it was found that the neurons were most strongly correlated with various body movements in response to visual motion, although this by no means indicates a causal relationship (Suver, 2016).
The large axonal diameter and abrupt terminals of DNOVS1 in the neck neuropil suggest that this cell is specialized for regulating rapid movements of the head. Neck motor neurons innervate 21 pairs of neck muscles and their activation elicits rotations of the head about specific axes. The neck motor neurons respond strongly to visual motion. In Calliphora, the haltere nerve innervates the neck motor neuropil and contralateral haltere interneurons are electrically coupled with both neck motor neurons and DNOVS1. This convergence of visual and mechanosensory feedback could enable precise compensatory movements of the head to reduce motion blur. Although the halteres provide self-motion information more rapidly than the visual system, DNOVS1 likely represents the fastest pathway by which visual information influences the fly's motor responses (Suver, 2016).
DNOVS2 and DNHS1 also have terminals in the neck motor region, although they do not appear to be electrically coupled to any motor neurons. Unlike DNOVS1, however, these cells also project to the wing and haltere neuropils. Visual input to the haltere motor system has been documented physiologically in blowflies and behaviorally in Drosophila, a phenomenon that might be mediated by DNHS1. The tuning curves for both head yaw and abdominal ruddering were quite similar to that of DNHS1, a correlation that should be explored in future studies (Suver, 2016).
Drosophila exhibit flight patterns in which straight sequences are interspersed with rapid stereotyped turns called body saccades. Flies execute saccades by generating a rapid banked turn in which they first roll to reorient their flight force and then counter roll to regain an upright pose. In Drosophila hydei, these roll and counter-roll axes are oriented at ~36° and 8°, respectively, relative to the longitudinal axis of the fly. The orientation of the initial roll axis is remarkably similar to the axis that elicits a peak response in the DNOVS2 cell (~35.7°), suggesting a possible role for this neuron during body saccades (Suver, 2016).
The representation of self-motion appears to be similar between Drosophila and blowflies despite the fact that fruit flies possess approximately half the number of VS cells. Theoretically, two cells would be sufficient to encode any arbitrary rotation in the azimuthal plane. However, the receptive fields of the VS cells cover different sectors of the visual world and no two cells extend over the entire field of view. Therefore, more than two cells are required to accurately encode rotation in a sparse visual scene. In addition, the large number of VS cells likely increases the speed and accuracy of self-motion estimation. The reduction in the number of VS cells in Drosophila may reflect a much lower number of ommatidia covering the azimuth compared with larger flies. It is not known, however, if the reduced number of VS cells translates into a smaller number of downstream interneurons. This study identified two descending neurons downstream of the VS cells, whereas four have been described in blowflies. However, it is premature to draw conclusions until more comprehensive maps of the descending neurons have been compiled for both species (Suver, 2016).
This study found that the visually evoked responses of LPTCs during flight were, on average, a few millivolts higher than during quiescence, consistent with prior studies. In contrast, this study observed much more substantial increases in the spike rate response of DNOVS2 and DNHS1 to visual motion during flight, suggesting that the relatively small flight-dependent increases observed in LPTCs are amplified in the descending neurons. With the exception of VS2, none of the descending interneurons or LPTCs displayed a statistically significant shift in their orientation tuning during flight compared with quiescence (Suver, 2016).
Collectively, the three cells that are described in this study encode body rotation around three approximately orthogonal axes (two in the azimuthal plane and one in the sagittal plane). Therefore, the projections of the three cells in the VNC might constitute a map from which any arbitrary rotation could be reconstructed. For example, all three descending neurons that were characterized in this study project to the neck neuropil, where local circuits could use the map to compute any arbitrary rotation. In general, this representation scheme would be analogous to the vestibulocerebellum system in rabbits, in which distinct classes of visually sensitive neurons respond to three axes of rotation and translation oriented at 45° and 135° on the azimuth and the vertical axis. Pigeons possess a similar system, with neurons in the accessory optic system and vestibulocerebellum encoding translation and rotation. The orientation of the three axes encoded in the vestibulocerebellum is quite similar to those encoded by the descending neurons in Drosophila; two cells are tuned to rotation on either side of the midline and one is tuned to yaw. The three axes identified in this study may not be the only ones encoded by descending neurons, but the similarities between mammals and flies suggest that animals may use a simple encoding scheme that avoids redundancy (Suver, 2016).
An alternate interpretation of these descending neurons is that they do not constitute a general map of body rotation, but rather are simply elements in parallel pathways that control distinct sensory motor reflexes. In this view, the outputs of the three cells may never be combined by downstream circuits to calculate an arbitrary angle of body rotation, but each cell may drive motor reflexes that rely solely on estimates of rotation about the individual axes of rotation. The fact that the projection patterns of the three cells are somewhat distinct (e.g., DNOVS1 only projects to the first thoracic neuropil and DNHS1 skips the second thoracic neuropil) supports this view. However, it is possible that the information conveyed by the three cells is functionally combined via their synergistic effects on distinct motor reflexes. For example, a reflex mediated by DNHS1 on the haltere motor system might combine with the effects of a reflex mediated by DNOVS2 on the wing motor system that would be behaviorally appropriate for a compensatory reflex regulating body motion about an axis not encoded directly by the two cells. In addition, a combination of these two encoding schemes might be implemented in which some systems (e.g., the neck motor system) compute arbitrary rotation angles from the three neurons and others (e.g., the wing motor system) rely on the direct influence of only one rotation axis and possibly indirect action from others (Suver, 2016).
This study reveals the neural circuitry responsible for encoding rotation along three body axes during flight in Drosophila. The descending interneurons that were characterized are involved in the transformation from visual to motor output and this takes place in as few as six synapses, making it a relatively tractable circuit. In this system, behaviorally relevant visual information is delivered to multiple motor systems and provides a basis for further investigations of cellular mechanisms of sensorimotor processing in a behaving animal (Suver, 2016).
Neuropeptide signaling influences animal behavior by modulating neuronal activity and thus altering circuit dynamics. Insect flight is a key innate behavior that very likely requires robust neuromodulation. Cellular and molecular components that help modulate flight behavior are therefore of interest and require investigation. In a genetic RNAi screen for G-protein coupled receptors that regulate flight bout durations, several receptors have been identified, including the receptor for the neuropeptide FMRFa (FMRFaR). To further investigate modulation of insect flight by FMRFa CRISPR-Cas9 mutants were generated in the gene encoding the Drosophila FMRFaR. The mutants exhibit significant flight deficits with a focus in dopaminergic cells. Expression of a receptor specific RNAi in adult central dopaminergic neurons resulted in progressive loss of sustained flight. Further, genetic and cellular assays demonstrated that FMRFaR stimulates intracellular calcium signaling through the IP3R and helps maintain neuronal excitability in a subset of dopaminergic neurons for positive modulation of flight bout durations (Ravi, 2018).
The ability to track odor plumes to their source (food, mate, etc.) is key to the survival of many insects. During this odor-guided navigation, flapping wings could actively draw odorants to the antennae to enhance olfactory sensitivity, but it is unclear if improving olfactory function comes at a cost to aerodynamic performance. This study computationally quantified the odor plume features around a fruit fly in forward flight and confirmed that the antenna is well positioned to receive a significant increase of odor mass flux (peak 1.8 times), induced by wing flapping, vertically from below the body but not horizontally. This anisotropic odor spatial sampling may have important implications for behavior and the algorithm during plume tracking. Further analysis also suggests that, because both aerodynamic and olfactory functions are indispensable during odor-guided navigation, the wing shape and size may be a balance between the two functions (Li, 2018).
Insect flight is a complex behavior that requires the integration of multiple sensory inputs with flight motor output. Although previous genetic studies identified central brain monoaminergic neurons that modulate Drosophila flight, neuro-modulatory circuits underlying sustained flight bouts remain unexplored. Certain classes of dopaminergic and octopaminergic neurons that project to the mushroom body, a higher integrating center in the insect brain, are known to modify neuronal output based on contextual cues and thereby organismal behavior. This study focuses on how monoaminergic modulation of mushroom body GABAergic output neurons (MBONs) regulates the duration of flight bouts. Octopaminergic neurons in the sub-esophageal zone stimulate central dopaminergic neurons (protocerebral anterior medial, PAM) that project to GABAergic MBONs. Either inhibition of octopaminergic and dopaminergic neurons or activation of GABAergic MBONs reduces the duration of flight bouts. Moreover, activity in the PAM neurons inhibits the GABAergic MBONs. These data suggest that disinhibition of the identified neural circuit very likely occurs after flight initiation and is required to maintain the "flight state" when searching for distant sites, possibly related to food sources, mating partners, or a suitable egg-laying site (Manjila, 2018).
Thermal flight performance curves (TFPCs) may be a useful proxy for determining dispersal on daily timescales in winged insect species. To better understand how flight performance may be correlated with geographic range extent and potential latitudinal climate variability, the thermal performance curves of flight ability was estimated in 11 Drosophilidae species (in 4 degrees C increments across 16-28 degrees C) after standard laboratory rearing for two generations. Whether key morphological, evolutionary or ecological factors (e.g. species identity, sex, body mass, wing loading, geographic range size) predicted traits of TFPCs (including optimum temperature, maximum performance, thermal breadth of performance) or flight ability (success/failure to fly) was tested. Although several parameters of TFPCs varied among species, these were typically not statistically significant probably owing to the relatively small pool of species assessed and the limited trait variation detected. The best explanatory model of these flight responses across species included significant positive effects of test temperature and wing area. However, the rank of geographic distribution breadth and phylogeny failed to explain significant variation in most of the traits, except for thermal performance breadth, of thermal flight performance curves among these 11 species. Future studies that employ a wider range of Drosophilidae species, especially if coupled with fine-scale estimates of species' environmental niches, would be useful (De Araujo, 2019).
Flies execute their remarkable aerial maneuvers using a set of wing steering muscles, which are activated at specific phases of the stroke cycle. The activation phase of these muscles-which determines their biomechanical output - arises via feedback from mechanoreceptors at the base of the wings and structures unique to flies called halteres. Evolved from the hindwings, the tiny halteres oscillate at the same frequency as the wings, although they serve no aerodynamic function and are thought to act as gyroscopes. Like the wings, halteres possess minute control muscles whose activity is modified by descending visual input, raising the possibility that flies control wing motion by adjusting the motor output of their halteres, although this hypothesis has never been directly tested. Using genetic techniques possible in Drosophila melanogaster, this study tested the hypothesis that visual input during flight modulates haltere muscle activity and that this, in turn, alters the mechanosensory feedback that regulates the wing steering muscles. The results suggest that rather than acting solely as a gyroscope to detect body rotation, halteres also function as an adjustable clock to set the spike timing of wing motor neurons, a specialized capability that evolved from the generic flight circuitry of their four-winged ancestors. In addition to demonstrating how the efferent control loop of a sensory structure regulates wing motion, these results provide insight into the selective scenario that gave rise to the evolution of halteres (Dickerson, 2019).
Many navigating insects include the celestial polarization pattern as an additional visual cue to orient their travels. Spontaneous orientation responses of both walking and flying fruit flies (Drosophila melanogaster) to linearly polarized light have previously been demonstrated. Using newly designed modular flight arenas consisting entirely of off-the-shelf parts and 3D-printed components this study presented individual flying flies with a slow and continuous rotational change in the incident angle of linear polarization. Under such open-loop conditions, single flies choose arbitrary headings with respect to the angle of polarized light and show a clear tendency to maintain those chosen headings for several minutes, thereby adjusting their course to the slow rotation of the incident stimulus. Importantly, flies show the tendency to maintain a chosen heading even when two individual test periods under a linearly polarized stimulus are interrupted by an epoch of unpolarized light lasting several minutes. Finally, it was shown that these behavioral responses are wavelength-specific, existing under polarized UV stimulus while being absent under polarized green light. Taken together, these findings provide further evidence supporting Drosophila's abilities to use celestial cues for visually guided navigation and course correction (Mathejczyk, 2019).
An internal sense of heading direction is computed from various cues, including steering maneuvers of the animal. Although neurons encoding heading and steering have been found in multiple brain regions, it is unclear whether and how they are organized into neural circuits. This study shows that, in flying Drosophila, heading and turning behaviors are encoded by population dynamics of specific cell types connecting the subregions of the central complex (CX), a brain structure implicated in navigation. Columnar neurons in the fan-shaped body (FB) of the CX exhibit circular dynamics that multiplex information about turning behavior and heading. These dynamics are coordinated with those in the ellipsoid body, another CX subregion containing a heading representation, although only FB neurons flip turn preference depending on the visual environment. Thus, the navigational system spans multiple subregions of the CX, where specific cell types show coordinated but distinct context-dependent dynamics (Shiozaki, 2020).
Fruit flies, Drosophila melanogaster, are active over a range of light intensities in the wild, but lab-reared flies are often tested only in bright light. Similarly, scarce feeding during larval stages-common in nature-generates smaller adults, and a wide range of eye sizes not found in well-fed lab colonies. Both dimmer light and smaller eyes limit light capture and have undetermined effects on visual behaviors such as flight. This study used moving sinusoidal gratings to test spatial acuity, temporal acuity, and contrast threshold of female flies of varying eye sizes at different light intensities. Vision was also tested in the smaller and often neglected male fruit flies. As light intensity drops from 50.1 lx to 0.3 lx, flies have a reduced spatial acuity (females: from 0.1 to 0.06 cycles per degree, CPD, males: 0.1 to 0.04 CPD) and temporal acuity (females: from 50 Hz to 10 Hz, males: 25 Hz to 10 Hz), and an increased contrast detection threshold (females: from 10% to 29%, males: 19% to 48%). No major sex-specific differences were found after accounting for eye size. Visual abilities in both small (eye area of 0.1-0.17 mm(2)) and large flies (0.17-0.23 mm(2)) suffer at 0.3 lx compared to 50.1 lx, but small flies suffer more (spatial acuity: 0.03 vs 0.06 CPD, contrast threshold: 76% vs 57%, temporal acuity: 5 Hz vs 10 Hz). These results suggest visual abilities of small flies suffer more than large flies at low light levels, possibly leading to size- and light intensity-dependent effects on foraging, navigation, and flight (Palavalli-Nettimi, 2020).
Glycogen is a critical store for locomotion. Depleted glycogen stores are associated with increased fatigue during exercise. The reduced effectiveness of low-carbohydrate diets for weight loss over longer time periods may arise because such diets reduce glycogen stores and thereby physical activity energy expenditure. To explore the effect of a low-carbohydrate diet on activity and glycogen utilisation, adult Drosophila melanogaster were fed a standard or low-carbohydrate diet for nine days, and patterns of flight activity and rates of glycogen depletion were measured. It was hypothesised that flight activity and rates of glycogen depletion would be reduced on a low-carbohydrate diet. Flight activity was elevated in the low-carbohydrate group but glycogen depletion rates were unchanged. It is concluded that increased activity is likely a foraging response to carbohydrate deficiency and it is speculated that the previously demonstrated metabolic depression that occurs on a low-carbohydrate diet in this species may allow for increased flight activity without increased glycogen depletion (Winwood-Smith, 2020).
The Drosophila ventral nerve cord (VNC) is composed of thousands of neurons born from a set of individually identifiable stem cells. The VNC harbors neuronal circuits required to execute key behaviors, such as flying and walking. Leveraging the lineage-based functional organization of the VNC, this study investigated the developmental and molecular basis of behavior by focusing on lineage-specific functions of the homeodomain transcription factor, Unc-4. Unc-4 was found to function in lineage 11A to promote cholinergic neurotransmitter identity and suppress the GABA fate. In lineage 7B, Unc-4 promotes proper neuronal projections to the leg neuropil and a specific flight-related take-off behavior. It was also uncovered that Unc-4 acts peripherally to promote proprioceptive sensory organ development and the execution of specific leg-related behaviors. Through time-dependent conditional knock-out of Unc-4, it was found that its function is required during development, but not in the adult, to regulate the above events (Lacin, 2020).hn of integral feedback and feed-forward regulation of olfactory transduction. In olfactory virtual reality experiments, this study reports that high activity levels of the OSN suppress turning, whereas low activity levels facilitate turning. Using a generalized linear model, how peripheral encoding of olfactory stimuli modulates the probability of switching from a run to a turn is explained. This work clarifies the link between computations carried out at the sensory periphery and action selection underlying navigation in odor gradients (Schultz, 2015).
Most primary sensory neurons operate differently from proportional counters. Individual OSNs of C. elegans and cockroaches function as bipolar detectors that selectively respond to either increases or decreases in stimulus intensity. A similar specialization into ON-OFF detection pathways has been observed for thermotaxis in C. elegans and motion perception in adult flies. In contrast with these binary sensory responses, this study discovered that a single larval OSN is sensitive to both the stimulus intensity and its first derivative. The enhanced information-processing capacity of primary olfactory neurons in the larva is consistent with the response characteristics of OSNs in adult flies, which encode complex dynamical features of airborne odorant stimuli (Schultz, 2015).
To describe the input-output response properties of single larval OSNs, the study set out to build a biophysical model of the olfactory transduction pathway. IFB motifs constitute the core mechanism of chemoreception in bacteria, olfactory transduction, and phototransduction. In adult flies, wheather the potential involvement of negative feedback on the olfactory transduction cascade could account for dynamical and adaptive features of OSN response was invsestigated. On the other hand, IFF motifs are implicated in the regulation of numerous cellular and developmental processes, and their contribution to sensory processing has been documented in recent work. These results led this study to conjecture that two regulatory motifs might be involved in larval olfactory transduction: an IFB and an IFF featuring direct excitation and indirect inhibition. Using a parameter optimization approach, it was found that a pure IFF motif is sufficient to approximate the response properties of the OSN. Combining the IFF and IFB motifs was nonetheless necessary to recapitulate the richness of OSN dynamics elicited by naturalistic olfactory stimuli. Consistent with the model proposed by Nagel (2011), the numerical simulations indicate that the integral feedback applies to the signaling pathway specific to the odorant receptor (OR). Nagel suggested that a diffusible effector-potentially intracellular calcium-inhibits the activity of the OR, thereby affecting the onset and offset kinetics of the OSN response. By contrast, the IFF motif would describe a regulatory mechanism acting on components of the transduction pathway downstream from the OR. It is plausible that the IFF regulation is also mediated by intracellular calcium (Schultz, 2015).
What features of the olfactory stimulus are encoded in the spiking dynamics of single larval OSNs? The biophysical model of the olfactory transduction cascade shows that the spiking activity of the OSN follows a standard hyperbolic dose-response when stimulated by prolonged pulses of odor. In this regime, the maximum OSN firing rate observed for IAA is modest. Changes in odor concentration occurring on a timescale relevant to the behavior-a second or shorter-can produce significantly higher (or lower) firing rates. This sensitivity to positive and negative changes in stimulus intensity can be explained by the mathematical solution that was derived for the OSN dynamics. Upon changes in odor concentration, the dose-response function describing the OSN spiking activity is transiently rescaled (or 'normalized') by the short-term history of the stimulus derivative ('memory' on characteristic time scale of 1 s). As a result, positive derivatives in stimulus intensity excite the OSN. Negative derivatives can inhibit the OSN firing rate in a manner consistent with the stimulus-offset inhibitions observed in adult-fly OSNs. This model indicates that a single Or42a OSN combines the function of a slope (ON) detector in response to positive gradients and an OFF detector in response to negative gradients. When larvae ascend Gaussian odor gradients originating from single odor sources, high OSN firing rates were expected. Robust inhibition of OSN spiking activity would result from motion that takes larvae down the odor gradient (Schultz, 2015).
How relevant are the features encoded by the spiking activity of the Or42a OSN to the behavioral dynamics directing chemotaxis? To address this question, the odor stimulation was substituted with optogenetics-based light stimulation and unprecedented control was gained over the spiking activity evoked in a genetically targeted OSN. Under the conditions of open-loop light stimulation, it was found that OFF responses (offset inhibition of the OSN firing) promote turning, whereas ON responses (sustained high firing) suppress turning. A Generalized Linear Model (GLM) was applied to describe the link between the OSN spiking dynamics and the probability of switching from a run to a turn. The accuracy of the model's output showed a striking dependence on the nonlinear transformation achieved by the olfactory transduction cascade. Ultimately, the biophysical model for the OSN spiking dynamics was combined with the GLM to make robust predictions about closed-loop behavior in virtual and in real odor gradients (Schultz, 2015).
The integrated stimulus-to-behavior GLM clarifies how features encoded in the activity pattern of individual primary olfactory neurons influence behavioral dynamics. The information transmitted by a single larval OSN is sufficient to represent positive and negative odor gradients through the excitation and inhibition of spiking activity. Unlike for chemotaxis and thermotaxis in C. elegans where the ON and OFF pathways are associated with different cellular substrates, the same larval OSN is capable of controlling up-gradient and down-gradient sensorimotor programs. This observation echoes findings recently made for thermotaxis in the Drosophila larva. Furthermore, it corroborates the idea that sensory representations are rapidly transformed into motor representations in the circuit controlling chemotaxis (Schultz, 2015).
In the future, it will be important to define whether the sensorimotor principles proposed for the Or42a OSN can be generalized to OSNs expressing other odorant receptors. In addition, the network of interneurons located in the larval antennal lobe is expected to participate in the processing of olfactory information arising from the OSNs. Although this work suggests that the computations achieved by the antennal lobe are not strictly necessary to guide robust chemotaxis, the function of the transformation carried out by the synapse between the Or42a OSN and its cognate projection neuron (PN) remains to be elucidated in the larva. As adult-fly PNs encode the second derivative of olfactory stimuli (Kim, 2015) including circuit elements downstream of the OSNs in the present multilevel model are expected to improve the accuracy of the behavioral predictions of the model (Schultz, 2015).
The aim of this study was to clarify the relationships between the peripheral encoding of naturalistic olfactory stimuli and gradient ascent toward an odor source. By exploiting the sufficiency of a single OSN to direct larval chemotaxis, a mathematical model was developed accounting for the transformation of time-varying stimuli into the firing rate of an OSN and the conversion of dynamical patterns of OSN activity into the selection between two basic types of action-running and turning. It will be interesting to examine the validity of the present model for the sensorimotor control of other aspects of larval chemotaxis such as turn orientation through lateral head casts (casting-to-turn transitions). In adult flies, turn orientation is determined by the crossing of the boundaries of odor plumes: upon encountering of an odor plume, flies veer upwind whereas exiting the plume initiates lateral and vertical casting-an orientation strategy related to the surge-and-cast response of moths. To orient in a rapidly changing olfactory landscape, the OSNs of various flying insects are capable of tracking rapid odor pulses on sub-second timescales and differentiating these signals. Whether the processing of turbulent olfactory inputs involves more temporal integration than that described by the sensorimotor model proposed in this study remains to be elucidated. Finally, the Drosophila larva offers a unique opportunity to delineate the neural circuit basis of behavior. Interdisciplinary approaches combining behavioral screens, functional imaging, and circuit reconstruction on the one hand, and computational modeling and robotics on the other hand, should improve understanding of how brains with reduced numerical complexity exploit streams of sensory information to direct action selection (Schultz, 2015).
Spatial maps in the brain are most accurate when they are linked to external sensory cues. This study shows that the compass in the Drosophila brain is linked to the direction of the wind. Shifting the wind rightward rotates the compass as if the fly were turning leftward, and vice versa. The mechanisms are described of several computations that integrate wind information into the compass. First, an intensity-invariant representation of wind direction is computed by comparing left-right mechanosensory signals. Then, signals are reformatted to reduce the coding biases inherent in peripheral mechanics, and wind cues are brought into the same circular coordinate system that represents visual cues and self-motion signals. Because the compass incorporates both mechanosensory and visual cues, it should enable navigation under conditions where no single cue is consistently reliable. These results show how local sensory signals can be transformed into a global, multimodal, abstract representation of space (Okubo, 2020).
Animals use active sensing to respond to sensory inputs and guide future motor decisions. In flight, flies generate a pattern of head and body movements to stabilize gaze. How the brain relays visual information to control head and body movements and how active head movements influence downstream motor control remains elusive. Using a control theoretic framework, the optomotor gaze stabilization reflex was studied in tethered flight and quantified how head movements stabilize visual motion and shape wing steering efforts in fruit flies (Drosophila). By shaping visual inputs, head movements increased the gain of wing steering responses and coordination between stimulus and wings, pointing to a tight coupling between head and wing movements. Head movements followed the visual stimulus in as little as 10 ms-a delay similar to the human vestibulo-ocular reflex-whereas wing steering responses lagged by more than 40 ms. This timing difference suggests a temporal order in the flow of visual information such that the head filters visual information eliciting downstream wing steering responses. Head fixation significantly decreased the mechanical power generated by the flight motor by reducing wingbeat frequency and overall thrust. By simulating an elementary motion detector array, this study showd that head movements shift the effective visual input dynamic range onto the sensitivity optimum of the motion vision pathway. Taken together, these results reveal a transformative influence of active vision on flight motor responses in flies. This work provides a framework for understanding how to coordinate moving sensors on a moving body (Cellini, 2020).
Detailed observations of larval Drosophila chemotaxis have characterised the relationship between the odour gradient and the runs, head casts and turns made by the animal. This study used a computational model to test whether hypothesised sensorimotor control mechanisms are sufficient to account for larval behaviour. The model combines three mechanisms based on simple transformations of the recent history of odour intensity at the head location. The first is an increased probability of terminating runs in response to gradually decreasing concentration, the second an increased probability of terminating head casts in response to rapidly increasing concentration, and the third a biasing of run directions up concentration gradients through modulation of small head casts. This model can be tuned to produce behavioural statistics comparable to those reported for the larva, and this tuning results in similar chemotaxis performance to the larva. Each mechanism can be demonstrated to enable odour approach, but the combination of mechanisms is most effective. How these low-level control mechanisms relate to behavioural measures such as the preference indices was used to investigate larval learning behaviour in group assays (Davies, 2015).
Unlike creatures that walk, flying animals need to control their horizontal motion as well as their height above the ground. Research on insects, the first animals to evolve flight, has revealed several visual reflexes that are used to govern horizontal course. For example, insects orient toward prominent vertical features in their environment and generate compensatory reactions to both rotations and translations of the visual world. Insects also avoid impending collisions by veering away from visual expansion. In contrast to this extensive understanding of the visual reflexes that regulate horizontal course, the sensory-motor mechanisms that animals use to control altitude are poorly understood. Using a 3D virtual reality environment, this study found that Drosophila utilize three reflexes -- edge tracking, wide-field stabilization, and expansion avoidance -- to control altitude. By implementing a dynamic visual clamp, it was found that flies do not regulate altitude by maintaining a fixed value of optic flow beneath them, as suggested by a recent model (Franceschini, 2007). The results identify a means by which insects determine their absolute height above the ground and uncover a remarkable correspondence between the sensory-motor algorithms used to regulate motion in the horizontal and vertical domains (Straw, 2010).
This study shows that Drosophila flies establish an altitude set point on the basis of nearby horizontal edges and tend to fly at the same height as such features. This reflex is invariant to contrast sign, such that a light-to-dark edge is roughly as attractive as a dark-to-light edge. Flies respond to wide-field motion with syndirectional velocity changes such that vertical, forward, and lateral visual motions elicit movement in the same direction. Finally, flies also avoid strong ventral expansion, flying upward away from the stimulus in what may be interpreted as a collision avoidance reflex. Thus, flies use a combination of at least three sensory-motor reflexes to control their vertical motion during flight. For each of these components, a similar response is involved in the azimuthal control of steering, suggesting close parallels for the reflexes used to control altitude and those used to control horizontal steering. The steering reflexes used in walking and flying are similar (e.g., the stripe fixation and wide-field stabilization behaviors of walking Drosophila are similar to those described in flight), and presumably they evolved prior to those required to regulate altitude. The similarity of the sensory-motor algorithms in the horizontal and vertical domains suggests that the neural substrates for altitude control either converged upon or were co-opted from those that underlie steering (Straw, 2010).
What is the relevance of these reflexes for animals flying in natural environments? On the basis of experiments with extended horizontal edges, it is speculated that flies approach and fly level with nearby objects, such as vegetation, using the visual edge created by the top of such objects with the background. This reflex might simply provide a convenient local set point for altitude, but it might also increase the probability of landing near the top of such objects. Indeed, when small solid cylinders were placed in the middle of the flight tunnel, it was observed that flies landed almost exclusively near the top. Recent experiments have demonstrated that when walking flies explore a 3D landscape, they also show a strong preference for the tops of objects, suggesting that there may be some ethological advantage to elevated perches. In many situations, numerous horizontal edges of various sizes, contrasts, and distances will be visible to a flying fly, and these experiments do not offer insight into how flies choose among them, although comparison with object fixation by walking flies would suggest that animals may attend to the closest, fastest-moving edge. Furthermore, the edge-tracking behavior is only one of the altitude responses described in this study, and it is unclear how it would interact with the other visual-motor altitude control pathways that presumably operate in parallel (Straw, 2010).
Given the complex evolutionary history of insects and their diverse natural histories, it is expected that other species may employ different algorithms for flight control. For example, although no evidence was found for ventral optic flow regulation of altitude in flies, honeybees do descend when presented with ventral regressive optic flow and thus may employ such an algorithm. Furthermore, many species of insects appear to fly at a level altitude without use of any obvious nearby horizontal edges or to travel hundreds of meters above ground during migration, suggesting mechanisms beyond those described in this study. It will be interesting to discover how the rules used for altitude control vary with the particular life history of different species. Nevertheless, the identification of a large suite of algorithms in Drosophila will make possible their study at the cellular and behavioral levels using convenient genetic tools (Straw, 2010).
To navigate through the world, animals must stabilize their path against disturbances and change direction to avoid obstacles and to search for resources. Locomotion is thus guided by sensory cues but also depends on intrinsic processes, such as motivation and physiological state. Flies, for example, turn with the direction of large-field rotatory motion, an optomotor reflex that is thought to help them fly straight. Occasionally, however, they execute fast turns, called body saccades, either spontaneously or in response to patterns of visual motion such as expansion. These turns can be measured in tethered flying Drosophila, which facilitates the study of underlying neural mechanisms. Whereas there is evidence for an efference copy input to visual interneurons during saccades, the circuits that control spontaneous and visually elicited saccades are not well known. Using two-photon calcium imaging and electrophysiological recordings in tethered flying Drosophila, this study identified a descending neuron whose activity is correlated with both spontaneous and visually elicited turns during tethered flight. The cell's activity in open- and closed-loop experiments suggests that it does not underlie slower compensatory responses to horizontal motion but rather controls rapid changes in flight path. The activity of this neuron can explain some of the behavioral variability observed in response to visual motion and appears sufficient for eliciting turns when artificially activated. This work provides an entry point into studying the circuits underlying the control of rapid steering maneuvers in the fly brain (Schnell, 2017).
Insects maintain a constant bearing across a wide range of
spatial scales. Monarch butterflies and locusts traverse
continents, and foraging bees and ants travel hundreds
of meters to return to their nests, whereas many other
insects fly straight for only a few centimeters before
changing direction. Despite this variation in spatial scale,
the brain region thought to underlie long-distance navigation
is remarkably conserved, suggesting that the use
of a celestial compass is a general and perhaps ancient
capability of insects. Laboratory studies of Drosophila
have identified a local search mode in which short, straight
segments are interspersed with rapid turns. However,
this flight mode is inconsistent with measured gene flow
between geographically separated populations, and
individual Drosophila can travel 10 km across desert terrain
in a single night - a feat that would be impossible
without prolonged periods of straight flight. To directly
examine orientation behavior under outdoor conditions,
a portable flight arena was build in which a fly viewed the
natural sky through a liquid crystal device that could experimentally
rotate the polarization angle. The findings indicate
that Drosophila actively orient using the sky's natural polarization
pattern (Weir, 2012).
Collectively, these results indicate that Drosophila possess the
optic and neural machinery to navigate, if in a rudimentary
fashion, using the pattern of skylight polarization. They can
hold a straighter course when provided with a natural polarization
pattern than they can when this signal is scrambled by
a circular polarizer. When an artificial pattern of linear
polarization (but naturalistic in terms of color and intensity) was
shifted instantaneously by 90, flies changed course accordingly. When the unaltered polarization pattern of
skylight was shifted by 90 without changing its other features,
flies also responded with course adjustments (Weir, 2012).
Central place foragers such as bees and desert ants have
been the subject of intensive investigation into the role of
a celestial compass in insect navigation. Among other topics,
the important concepts of time compensation, path integration, and multisensory integration have been examined in detail in these organisms. A small specialized
region of the eye called the dorsal rim area is thought to be
critical for these behaviors in many species, although
the evidence in flies is somewhat contradictory. Flies possess
a dorsal rim area, which has been implicated in polarization
responses, but prior experiments using a tethered
flight arena suggest that the rest of the eye may play a role
in responses to polarized light. The current results do not bear
directly on this discrepancy, because the sky stimulus was
visible to ommatidia both within and outside the dorsal rim
area. Within the dorsal rim area, photoreceptors R7 and R8,
which have been proposed to underlie polarization vision,
both express an opsin with a peak sensitivity in the ultraviolet.
Thus, the observation of polarization dependent responses
to wavelengths longer than 400 nm provides further indirect
evidence for the role of other photoreceptors besides R7 and
R8 within the dorsal rim. Their involvement cannot however be ruled out because it is possible that they exhibit some small but functional sensitivity to the wavelengths used in these experiments. The possible existence of alternate, spectrally
distinct pathways for detecting polarized light may
have contributed to the variability that was measured in experiments
in which UV light was attenuated by filters (Weir, 2012).
Through studies of migratory insects such as monarch
butterflies and locusts, the neural circuitry that underlies
polarization vision and its influence on motor behavior has
begun to be elucidated. Researchers have traced the polarization
vision pathway from the eye to the central brain to
neurons arborizing in the thoracic ganglion. This electrophysiological
evidence suggests that the central complex, a series of unpaired neuropils of the central brain, plays a key role in processing polarized light. The ubiquity of this brain
region along with the relevance of polarization vision to the life
history of a variety of species suggests that orientation
responses using polarized light may represent a rather ancient
component of insect behavior. At first glance, the fruit fly,
which is neither a central place forager nor known as a seasonal migrant, seems to be a strange choice of species in which to study polarization vision. Because long-distance
directed flights, either for migration or homing, have not
been directly observed in flies, one cannot rely on innate
motivation to navigate to a specific location when designing
experiments. Nonetheless, a fly (or any insect for that matter)
that finds itself in a resource-poor area, without observable
attractive cues, faces a critical challenge. Maintaining a
straight path ensures that it does not waste limited resources
repeatedly traversing the same ground. Indeed, evidence
suggests that several species of fruit flies, including
Drosophila melanogaster, could fly over 10 km across a desert
without access to food or water. Given the energy resources of even a well-fed fly, this feat would only be possible by maintaining a straight heading. Because the
sun is often obscured by clouds, masked by local features,
or below the horizon, an alternative source of compass information - such as that available from sky light polarization - would be extremely useful for animals attempting to maintain a heading relative to global coordinates. An intrinsic compass
preference would not be necessary, simply the ability to
choose a heading and maintain it. The current experiments were designed
to mimic this situation, and it was observed that flies did
indeed use skylight polarization to help maintain a steady
course. The fruit fly, too often thought of without reference to
its evolutionary history, thus displays another of the almost
implausibly complex behaviors found in the insect world.
The wealth of behavioral, physiological, and genetic tools
available in Drosophila make it an ideal system in which to
examine the open questions surrounding this behavior. Observation of flies using celestial polarization to hold a course is a step in this direction (Weir, 2012).
An important role of visual systems is to detect nearby predators, prey, and potential mates, which may be distinguished in part by their motion. When an animal is at rest, an object moving in any direction may easily be detected by motion-sensitive visual circuits. During locomotion, however, this strategy is compromised because the observer must detect a moving object within the pattern of optic flow created by its own motion through the stationary background. However, objects that move creating back-to-front (regressive) motion may be unambiguously distinguished from stationary objects because forward locomotion creates only front-to-back (progressive) optic flow. Thus, moving animals should exhibit an enhanced sensitivity to regressively moving objects. This study explicitly tested this hypothesis by constructing a simple fly-sized robot that was programmed to interact with a real fly. The measurements indicate that whereas walking female flies freeze in response to a regressively moving object, they ignore a progressively moving one. Regressive motion salience also explains observations of behaviors exhibited by pairs of walking flies. Because the assumptions underlying the regressive motion salience hypothesis are general, it is suspected that the behavior observed in Drosophila may be widespread among eyed, motile organisms (Zabala, 2012).
Experiments using a computer-controlled robot indicate that walking female flies respond to a regressively moving fly-sized object with much greater probability than to a progressively moving target. Under the assumption that the freezing behavior of the fly is a proxy for its ability to detect the small target, the results provide strong support for the regressive motion saliency hypothesis and confirm anecdotal observations of interactions between pairs of flies. These experiments provide further evidence for the utility of behavioral robotics as a method for analyzing the sensory basis of social interactions. The results might alternatively be taken as evidence for progressive motion blindness, but either way, the experiments suggest that the ability of flies to detect small moving objects during locomotion is strongly constrained by the optic flow patterns created by self-motion and that they can use regressive motion as a simple rule of thumb that does not require sophisticated compensation for self-motion. This is the first time that this hypothesis has been proposed or tested. However, the phenomenon may be related to the principle of motion camouflage, a mechanism for crypsis that has been proposed for flying insect. To implement motion camouflage, an animal must move in a way so that it appears stationary (to another moving animal) relative to a distant background. The current results would suggest that such camouflage might not require perfect compensation, but might be effective as long as an animal's own motion did not create regressive motion on another's retina (Zabala, 2012).
This analysis depends critically on the interpretation that walking females reflexively freeze when detecting a nearby moving object. This is believed to be justified since many animals freeze upon detecting a nearby animal, a simple behavioral reflex that has several advantages. By stopping an animal's visual performance is no longer compromised by the optic flow created by self-motion, a stationary animal is harder to detect, and once stopped, an animal can better prepare for an action such as an escape. An alternative interpretation of the data is that progressively moving objects are as detectable, but female flies simply 'decide' not to stop. According to this view, the reflex might serve some useful function such as to establish rights of way when animals are on a collision course, similar to rules used by boat captains. However, it is not easy to imagine a selective scenario by which such etiquette would evolve, and given the distance at which these reflexes operates, the interpretation is favored that the difference in behavioral responses to progressive and regressive motion indicates a limitation of visual processing rather than a behavioral choice. Another interesting question is whether this reflex evolved in flies specifically for mediating interactions between conspecifics, or alternatively, represents a general reaction to nearby organisms (Zabala, 2012).
Sensitivity to regressive motion is not a general feature of visual reflexes in flies. Indeed, studies of object orientation behavior in tethered flying animals indicate that flies are more sensitive to progressively moving objects than to regressively moving ones, and this asymmetry has been proposed to explain the stable fixation of vertical stripes. In contrast, studies of object orientation and optomotor equilibriumin walking flies suggests that the sensitivity to regressive and progressive motion is comparable. However, these prior studies focus on a fly's ability to orient toward visual landmarks and walk straight using large-field optomotor cues and may not be relevant to the behavior describe in this study, which are interpreted as a reflex used to detect the presence of a nearby organism. In particular, the female flies responded to the robot's motion by freezing, not by steering toward the stimulus as would be expected in an object orientation behavior. The neurons responsible for the behavior are not known, and the evidence precludes the involvement of looming detector neurons that have recently been described in this species (de Vries, 2012; Fotowat, 2009). Large-field neurons might be capable of detecting small targets provided the contrast was sufficient. However, the results indicating that the response to regressive motion may be triggered by targets smaller than an ommatidial acceptance angle implicate the classes of cells in insects termed figure detectors (FDs) and small target movement detectors (STMDs). The fact that the behavior degrades if the animal is rotating at the onset of stimulus motion suggests that the underlying circuits cannot detect a regressively moving object when superimposed on the reafferent large field rotatory optic flow generated by self-motion. Nevertheless, the detection threshold of approximately one-third an ommatidial acceptance angle is impressive for an animal (Drosophila) that is not behaviorally specialized for detecting small prey as are dragonflies or detecting mates and territorial interlopers as are hoverflies and houseflies. Further exploration of these hypotheses will require identification of the underlying visual interneurons and recordings of their visual responses during locomotion, an approach that may be possible in Drosophila due to recent methodological advances (Zabala, 2012).
Unsignaled stress can have profound effects on animal behavior. While most investigation of stress-effects on behavior follows chronic exposures, less is understood about acute exposures and potential after-effects. This study examined walking activity in Drosophila following acute exposure to high temperature or electric shock. Compared to initial walking activity, flies first increase walking with exposure to high temperatures then have a strong reduction in activity. These effects are related to the intensity of the high temperature and number of exposures. The reduction in walking activity following high temperature and electric shock exposures survives context changes and lasts at least five hours. Reduction in the function of the biogenic amines octopamine / tyramine and serotonin both strongly blunt the increase in locomotor activity with high temperature exposure. However, neither set of biogenic amines alter the long lasting depression in walking activity after exposure (Ostrowski, 2018).
Rhythmic animal behaviors are regulated in part by neural circuits called the central pattern generators (CPGs). Classifying neural population activities correlated with body movements and identifying the associated component neurons are critical steps in understanding CPGs. Previous methods that classify neural dynamics obtained by dimension reduction algorithms often require manual optimization which could be laborious and preparation-specific. This study presents a simpler and more flexible method that is based on the pre-trained convolutional neural network model VGG-16 and unsupervised learning, and successfully classifies the fictive motor patterns in Drosophila larvae under various imaging conditions. Voxel-wise correlation mapping was also used to identify neurons associated with motor patterns. By applying these methods to neurons targeted by 5-HT2A-GAL4, which was generated by the CRISPR/Cas9-system, two classes of interneurons were identified, termed Seta and Leta, which are specifically active during backward but not forward fictive locomotion. Optogenetic activation of Seta and Leta neurons increased backward locomotion. Conversely, thermogenetic inhibition of 5-HT2A-GAL4 neurons or application of a 5-HT2 antagonist decreased backward locomotion induced by noxious light stimuli. This study establishes an accelerated pipeline for activity profiling and cell identification in larval Drosophila and implicates the serotonergic system in the modulation of backward locomotion (Park, 2018).
During walking, insects must coordinate the movements of their six legs for efficient locomotion. This interleg coordination is speed-dependent; fast walking in insects is associated with tripod coordination patterns, while slow walking is associated with more variable, tetrapod-like patterns. To date, however, there has been no comprehensive explanation as to why these speed-dependent shifts in interleg coordination should occur in insects. Tripod coordination would be sufficient at low walking speeds. The fact that insects use a different interleg coordination pattern at lower speeds suggests that it is more optimal or advantageous at these speeds. Furthermore, previous studies focused on discrete tripod and tetrapod coordination patterns. Experimental data, however, suggest that changes observed in interleg coordination are part of a speed-dependent spectrum. This study explored these issues in relation to static stability as an important aspect for interleg coordination in Drosophila. A model was created that uses basic experimentally measured parameters in fruit flies to find the interleg phase relationships that maximize stability for a given walking speed. The model predicted a continuum of interleg coordination patterns spanning the complete range of walking speeds as well as an anteriorly directed swing phase progression. Furthermore, for low walking speeds the model predicted tetrapod-like patterns to be most stable, while at high walking speeds tripod coordination emerged as most optimal. Finally, the basic assumption of a continuum of interleg coordination patterns was validated in a large set of experimental data from walking fruit flies and these data were compared with the model-based predictions (Szczecinski, 2018).
The most fundamental choice an animal has to make when it detects a threat is whether to freeze, reducing its chances of being noticed, or to flee to safety. This study shows that Drosophila melanogaster exposed to looming stimuli in a confined arena either freeze or flee. The probability of freezing versus fleeing is modulated by the fly's walking speed at the time of threat, demonstrating that freeze/flee decisions depend on behavioral state. A pair of descending neurons crucially implicated in freezing is described. Genetic silencing of DNp09 descending neurons disrupts freezing yet does not prevent fleeing. Optogenetic activation of both DNp09 neurons induces running and freezing in a state-dependent manner. These findings establish walking speed as a key factor in defensive response choices and reveal a pair of descending neurons as a critical component in the circuitry mediating selection and execution of freezing or fleeing behaviors (Zacarias, 2018).
Animals rely on an internal sense of body position and movement to effectively control motor behavior. This sense of proprioception is mediated by diverse populations of mechanosensory neurons distributed throughout the body. This study investigated neural coding of leg proprioception in Drosophila, using in vivo two-photon calcium imaging of proprioceptive sensory neurons during controlled movements of the fly tibia. The axons of leg proprioceptors are organized into distinct functional projections that contain topographic representations of specific kinematic features. Using subclass-specific genetic driver lines, this study shows that one group of axons encodes tibia position (flexion/extension), another encodes movement direction, and a third encodes bidirectional movement and vibration frequency. Overall, these findings reveal how proprioceptive stimuli from a single leg joint are encoded by a diverse population of sensory neurons, and provide a framework for understanding how proprioceptive feedback signals are used by motor circuits to coordinate the body (Mamiya, 2018).
Animals' behaviors vary in response to their environment, both biotic and abiotic. These behavioral responses have significant impacts on animal survival and fitness, and thus, many behavioral responses are at least partially under genetic control. In Drosophila for example, genes impacting aggression, courtship behavior, circadian rhythms, and sleep have been identified. Animal activity also is influenced strongly by genetics. Previous work used the Drosophila melanogaster Genetics Reference Panel (DGRP) to investigate activity levels and identified over 100 genes linked to activity. This study re-examine these data to determine if Drosophila strains differ in their response to rotational exercise stimulation, not simply in the amount of activity, but in activity patterns and timing of activity. Specifically, it was asked if there are fly strains exhibiting either a "marathoner" pattern of activity, i.e. remaining active throughout the two-hour exercise period, or a "sprinter" pattern, i.e. carrying out most of the activity early in the exercise period. The DGRP strains examined differ significantly in how much activity is carried out at the beginning of the exercise period, and this pattern is influenced by both sex and genotype. Interestingly, there is no clear link between the activity response pattern and lifespan of the animals. Using GWASs, ten high confidence candidate genes were identified that control to which degree Drosophila exercise behaviors fit a marathoner or sprinter activity pattern. This finding suggests that, similar to other aspects of locomotor behavior, timing of activity patterns in response to exercise stimulation is under genetic control (Riddle, 2020).
A special class of random walks, so-called Lévy walks, has been observed in a variety of organisms ranging from cells, insects, fishes, and birds to mammals, including humans. Although their prevalence is considered to be a consequence of natural selection for higher search efficiency, some findings suggest that Lévy walks might also be epiphenomena that arise from interactions with the environment. Therefore, why they are common in biological movements remains an open question. Based on some evidence that Lévy walks are spontaneously generated in the brain and the fact that power-law distributions in Lévy walks can emerge at a critical point, it was hypothesized that the advantages of Lévy walks might be enhanced by criticality. However, the functional advantages of Lévy walks are poorly understood. Here, we modeled nonlinear systems for the generation of locomotion and showed that Lévy walks emerging near a critical point had optimal dynamic ranges for coding information. This discovery suggested that Lévy walks could change movement trajectories based on the magnitude of environmental stimuli. This study then showed that the high flexibility of Lévy walks enabled switching exploitation/exploration based on the nature of external cues. Finally, this study analyzed the movement trajectories of freely moving Drosophila larvae and showed empirically that the Lévy walks may emerge near a critical point and have large dynamic range and high flexibility. The results suggest that the commonly observed Lévy walks emerge near a critical point and could be explained on the basis of these functional advantages (Abe, 2020).
An animal at rest or engaged in stationary behaviors can instantaneously initiate goal-directed walking. How descending brain inputs trigger rapid transitions from a non-walking state to an appropriate walking state is unclear. This study identify two neuronal types, P9 and BPN, in the Drosophila brain that, upon activation, initiate and maintain two distinct coordinated walking patterns. P9 drives forward walking with ipsilateral turning, receives inputs from central courtship-promoting neurons and visual projection neurons, and is necessary for a male to pursue a female during courtship. In contrast, BPN drives straight, forward walking and is not required during courtship. BPN is instead recruited during and required for fast, straight, forward walking bouts. Thus, this study reveals separate brain pathways for object-directed walking and fast, straight, forward walking, providing insight into how the brain initiates context-appropriate walking programs (Bidaye, 2020).
In insects, the small number of ~300-500 descending neurons (DNs) that project to the ventral nerve cord (VNC) provides the opportunity to finely probe how locomotor control is encoded in descending pathways. Although specific DNs have been associated with specific aspects of walking, including walking initiation, in different insect species, lack of reproducible access to these neurons makes it difficult to examine their function. In addition, little is known about how higher brain neurons control context-specific walking initiation in insects. The sophisticated genetic tools in Drosophila melanogaster allow reproducible access to specific neurons, including DNs, and greatly facilitate functional characterization. Recent work revealed that many DNs can modify an ongoing walking program. In addition, the activity of a few DNs has been shown to correlate with locomotor patterns. However, it is still unclear if specific brain inputs, at the level of both DNs and higher brain areas, can initiate a coordinated walking pattern and how distinct walking initiations are manifested in different behavioral contexts (Bidaye, 2020).
This study leveraged recently developed genetic tools and coupled them with novel behavioral assays and functional imaging to examine walking initiation neurons in Drosophila. From a targeted optogenetic screen for walking initiation neurons, this study identified two neuronal types that initiate two distinct modes of forward walking: P9 DN induces forward walking with an ipsilateral turning component, whereas novel higher brain neurons, which this study names Bolt protocerebral neurons (BPNs), induce straight forward walking. Functional connectivity and neural silencing studies revealed that the ipsilateral turning walking program driven by P9 contributes to object-directed walking in the context of courtship. In contrast, BPNs were dispensable for courtship. Instead, in vivo imaging and behavioral experiments showed that BPNs are specifically necessary for fast, long-duration, straight forward walking. These studies show that the activity of specific brain neurons is sufficient to switch downstream motor control circuits from a non-walking state into a walking state and provide evidence for distinct descending pathways for walking initiations in different contexts (Bidaye, 2020).
P9 receives inputs from courtship-promoting neurons and visual projection neurons and drives forward walking with an ipsilateral turning component. Moreover, P9 is required during object-directed walking in the context of courtship, whereas BPN is not required for object-directed walking in this context. Instead, BPN activity is correlated with straight, long, fast walking bouts, and manipulating activity of these neurons modifies walking speed and duration without affecting turning. Thus, the characterization of these neurons reveals two distinct pathways that initiate two different forward walking programs in different behavioral contexts (Bidaye, 2020).
P9 and BPN uncover separate brain pathways for object-directed forward steering and fast, straight, forward walking, respectively. The existence of these independent walking initiation pathways suggests that specific brain inputs can drive distinct and complete walking programs in a context-specific manner. This may be achieved by driving a common downstream walking circuit that is modulated to generate specific walking modes, as suggested by neuromechanical models for directional control of walking. Alternatively, these pathways may recruit distinct downstream premotor circuits, each generating a distinct motor pattern. Examining the downstream circuits of these walking initiation pathways will help unravel the mechanisms of these distinct walking initiations (Bidaye, 2020).
Complex motor patterns observed in natural behaviors likely result from combined activity of populations of descending commands from the brain. Interactions among DNs may bring about a concerted change in the functional state of nerve cord circuits, as seen in crawling circuits in C. elegans and Drosophila larvae (Carreira-Rosario, 2018). Therefore, in natural behaviors, P9 and BPN pathways may be active in parallel with other descending signals. An interesting question is whether a population of descending commands generates a motor output more complex than the sum of its constituents. Genetic access to characterized walking initiation neurons (P9 and BPN) will now enable examination of this question and will guide future experiments aimed at elucidating how brain neurons influence walking contro (Bidaye, 2020).
From an activation screen of approximately half of all DNs in the fly (Namiki, 2018), the P9 DNs were the only DNs to initiate walking. These results suggest that very few single DNs encode forward walking initiation. Similarly, a previous unbiased behavioral screen revealed MDN as the only DN sufficient to drive backward walking (Bidaye, 2014). Although DN combinations likely elicit and modulate walking, these studies suggest that P9 neurons have a privileged role as a DN class triggering a complete forward walking program (Bidaye, 2020).
Previous studies have shown the strong importance of vision in pursuing a potential mate during courtship. Male flies initiate walking toward any object with visual characteristics that grossly match those of a potential mate, indicating that visual information may directly influence walking control neurons. This study has shown that P9 receives direct inputs from LC9 that serve as feature detectors, suggesting that P9 participates in a shallow pathway from visual detection to motor command. Direct connections between visual projection neurons and DNs are also seen in the giant fiber escape pathway and in visually guided flight control, suggesting a common circuit motif to minimize response times when rapid action is required (Bidaye, 2020).
In addition to visual inputs, P9 is also activated by pC1 neurons (Koganezawa, 2016), master regulators of courtship behavior that integrate olfactory, pheromonal, and auditory cues and drive a complex courtship sequence. pC1-activated flies show enhanced object pursuit behavior that persists for several minutes, suggesting strong potentiation of the downstream locomotor control circuit. The findings of this study reveal a circuit configuration in which pC1 may gate/potentiate the LC-P9 sensorimotor loop, leading to context-specific object-directed walking. Consistent with this, recent studies demonstrated that LC10 neurons participate in object tracking during courtship and proposed that LC10 and pC1 converge on downstream targets to drive object-directed walking (Ribeiro, 2018). Although LC10 did not activate P9, it is possible that its effect on P9 is gated by pC1 activity. Similar to the P9 pathway, state-dependent gating of sensorimotor loops in Drosophila was recently demonstrated for a visually evoked landing circuit (Ache, 2019), suggesting a general circuit architecture for context-dependent, modular regulation of sensory-driven responses (Bidaye, 2020).
Although this study defined a role for P9 in object pursuit during courtship behavior, it is unlikely that P9 neurons are the only DNs involved in walking control during courtship, as males with P9 transmission blocked are able to track females for short periods. In addition, this study has not explored the role of P9 in other steering behaviors. Indeed, cricket DNs implicated in walking control have been shown to be responsive to multiple sensory stimuli in a state-dependent fashion (Bidaye, 2020).
The ability of BPNs to drive high-speed, straight forward walks (or 'sprints') inspired the name 'Bolt' neurons, given Usain Bolt's unmatched sprinting records. Unilateral BPN activation induced straight forward walking, in contrast to turning phenotypes elicited by unilateral activation of other walking initiation neurons (P9, MDN, and cricket DNs). BPNs also likely function in speed control, as increasing activity increased walking speed. The activation, silencing, and neural activity recording studies suggest BPNs are important when animals execute long, straight, fast walking (i.e., when the fly needs to cover a large distance in a short time). This suggests a potential role in exploratory or escape-like behaviors. However, their widespread dendritic fibers in the higher brain suggest that they might integrate multiple sensory inputs and may represent higher order regulators of walking, akin to pC1 neurons for courtship control. This anatomy makes BPNs unlikely to be involved in reflexive escape behaviors (e.g., like the jumping response encoded by the giant fiber neurons). Instead, the hypothesis is favored that BPN is involved in sustained walking during certain types of exploratory behaviors (e.g., exploring new environments) or other forms of escape that require moving out of an unpleasant environment. As not all BPNs showed detectable responses during spontaneous walking (Figure S6; STAR Methods), there may be functional subclasses within the BPN population (Bidaye, 2020).
The BPN pathway shows remarkable similarity to a recently described mouse MLR-caudal brainstem circuit that promotes high-speed walking: in both cases, unilateral activation induces walking initiation without a turning bias, activation strength correlates with walking speed, and reduced activity causes specific defects in high-speed walking. Moreover, this study demonstrate that BPN is active during high-speed straight forward walks, when the animal is spontaneously walking. Taken together, these studies suggest that high-speed walking is executed by specialized walking circuits that serve an essential function across different organisms (Bidaye, 2020).
Although BPNs are necessary for fast walking, the ability of BPNs to drive different walking speeds at different stimulation frequencies provides an opportunity to examine downstream mechanisms for speed control. Recent studies in zebrafish showed a gradient of recruitment of distinct premotor circuits at increasing swimming speeds. In Drosophila, recent work (Azevedo, 2020) has characterized distinct motor neurons recruited in a similar manner as leg movements accelerate. Examining how BPNs recruit these motor programs in an intensity-dependent manner will help illuminate the mechanism of walking speed control in Drosophila (Bidaye, 2020).
Unlike the mammalian locomotor system, which has been explored at multiple hierarchical levels such as the cortex, basal ganglia, cerebellum, brain stem, and spinal cord, the invertebrate walking control has been investigated mainly at the level of the nerve cord circuits and DNs. The only higher brain structure analyzed in the context of locomotion is the central complex (CC), which has been implicated as the site for generation of an internal heading signal. These heading signals are thought to directly influence CC output neurons involved in turning and speed control. It is unclear how CC or other higher brain areas control downstream locomotor circuits (Bidaye, 2020).
The P9 and BPN pathways elucidate genetically defined, specific brain neurons that drive coordinated walking behaviors. These neurons are upstream of nerve cord circuits and likely downstream or independent of CC navigation circuits. As BPNs are higher brain neurons located outside the CC and are not involved in turning behaviors, BPNs could constitute a CC-independent pathway involved in non-directed high-speed forward walking, providing an important landmark in examining higher brain regions for walking control. In addition, the LC9-P9-pC1 neural circuit motif provides a model of how context impinges on locomotor decisions directly at the level of DNs. Furthermore, because BPN and P9 activation elicits complete, distinct walking programs, they are critical nodes that will enable evaluation of how downstream locomotor circuits in the VNC execute different walking patterns. Thus, P9 and BPN pathways reveal organization of the invertebrate walking control circuits across different hierarchical levels and provide an important advance in understanding of how brain pathways switch on downstream walking control circuits (Bidaye, 2020).
How insects navigate complex odor plumes, where the location and timing of odor packets are uncertain, remains unclear. This study imaged complex odor plumes simultaneously with freely-walking flies, quantifying how behavior is shaped by encounters with individual odor packets. Navigation was stochastic and did not rely on the continuous modulation of speed or orientation. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Further, flies used the timing of odor encounters to modulate the transition rates between walks and stops. In more regular environments, flies continuously modulate speed and orientation, even though encounters can still occur randomly due to animal motion. In less predictable environments, where encounters are random in both space and time, walking flies navigate with random walks biased by encounter timing (Demir, 2020).
Animals typically avoid unwanted situations with stereotyped escape behavior. For instance, Drosophila larvae often escape from aversive stimuli to the head, such as mechanical stimuli and blue light irradiation, by backward locomotion. Responses to these aversive stimuli are mediated by a variety of sensory neurons including mechanosensory class III da (C3da) sensory neurons and blue-light responsive class IV da (C4da) sensory neurons and Bolwig's organ (BO). How these distinct sensory pathways evoke backward locomotion at the circuit level is still incompletely understood. This study shows that a pair of cholinergic neurons in the subesophageal zone, designated AMBs, evoke robust backward locomotion upon optogenetic activation. Anatomical and functional analysis shows that AMBs act upstream of MDNs, the command-like neurons for backward locomotion. Further functional analysis indicates that AMBs preferentially convey aversive blue light information from C4da neurons to MDNs to elicit backward locomotion, whereas aversive information from BO converges on MDNs through AMB-independent pathways. This study also found that, unlike in adult flies, MDNs are dispensable for the dead end-evoked backward locomotion in larvae. These findings thus reveal the neural circuits by which two distinct blue light-sensing pathways converge on the command-like neurons to evoke robust backward locomotion, and suggest that distinct but partially redundant neural circuits including the command-like neurons might be utilized to drive backward locomotion in response to different sensory stimuli as well as in adults and larvae (Omamiuda-Ishikawa, 2020).
How do descending inputs from the brain control leg motor circuits to change how an animal walks? Conceptually, descending neurons are thought to function either as command-type neurons, in which a single type of descending neuron exerts a high-level control to elicit a coordinated change in motor output, or through a population coding mechanism, whereby a group of neurons, each with local effects, act in combination to elicit a global motor response. The Drosophila Moonwalker Descending Neurons (MDNs), which alter leg motor circuit dynamics so that the fly walks backwards, exemplify the command-type mechanism. This study identified several dozen MDN target neurons within the leg motor circuits showed that two of them mediate distinct and highly-specific changes in leg muscle activity during backward walking: LBL40 neurons provide the hindleg power stroke during stance phase; LUL130 neurons lift the legs at the end of stance to initiate swing. Through these two effector neurons, MDN directly controls both the stance and swing phases of the backward stepping cycle. These findings suggest that command-type descending neurons can also operate through the distributed control of local motor circuits (Feng, 2020).
Whole-brain recordings give a global perspective of the brain in action. This study describes a method using light field microscopy to record near-whole brain calcium and voltage activity at high speed in behaving adult flies. Global activity maps were first obtained for various stimuli and behaviors. Notably, brain activity was found to increase on a global scale when the fly walked but not when it groomed. This global increase with walking was particularly strong in dopamine neurons, which showed little activity otherwise. Second, maps were extracted of spatially distinct sources of activity as well as their time series using principal component analysis and independent component analysis. The characteristic shapes in the maps matched the anatomy of subneuropil regions and, in some cases, a specific neuron type. Brain structures that responded to light and odor were consistent with previous reports, confirming the new technique's validity. Previously uncharacterized behavior-related activity wee also observed as well as patterns of spontaneous voltage activity (Aimon, 2019).
Terrestrial locomotion requires animals to coordinate their limb movements to efficiently traverse their environment. While previous studies in hexapods have reported that limb coordination patterns can vary substantially, the structure of this variability is not yet well understood. This study characterized the symmetric and asymmetric components of variation in walking kinematics in the genetic model organism Drosophila. Drosophila were found to use a single continuum of coordination patterns without evidence for preferred configurations. Spontaneous symmetric variability was associated with modulation of a single control parameter-stance duration-while asymmetric variability consisted of small, limb-specific modulations along multiple dimensions of the underlying symmetric pattern. Commands that modulated walking speed, originating from artificial neural activation or from the visual system, evoked modulations consistent with spontaneous behavior. These findings suggest that Drosophila employ a low-dimensional control architecture, which provides a framework for understanding the neural circuits that regulate hexapod legged locomotion (DeAngelis, 2019).
Mechanisms that control movements range from navigational mechanisms, in which the animal employs directional cues to reach a specific destination, to search movements during which there are little or no environmental cues. Even though most real-world movements result from an interplay between these mechanisms, an experimental system and theoretical framework for the study of interplay of these mechanisms is not available. This study rectifies this deficit. A new method is created to stimulate the olfactory system in Drosophila. As flies explore a circular arena, their olfactory receptor neurons (ORNs) are optogenetically activated within a central region making this region attractive to the flies without emitting any clear directional signals outside this central region. In the absence of ORN activation, the fly's locomotion can be described by a random walk model where a fly's movement is described by its speed and turn-rate (or kinematics). Upon optogenetic stimulation, the fly's behavior changes dramatically in two respects. First, there are large kinematic changes. Second, there are more turns at the border between light-zone and no-light-zone and these turns have an inward bias. Surprisingly, there is no increase in turn-rate, rather a large decrease in speed that makes it appear that the flies are turning at the border. Similarly, the inward bias of the turns is a result of the increase in turn angle. These two mechanisms entirely account for the change in a fly's locomotion. No complex mechanisms such as path-integration or a careful evaluation of gradients are necessary (Tao, 2020).
To move the body, the brain must precisely coordinate patterns of activity among diverse populations of motor neurons. This study used in vivo calcium imaging, electrophysiology, and behavior to understand how genetically-identified motor neurons control flexion of the fruit fly tibia. Leg motor neurons exhibit a coordinated gradient of anatomical, physiological, and functional properties. Large, fast motor neurons control high force, ballistic movements while small, slow motor neurons control low force, postural movements. Intermediate neurons fall between these two extremes. This hierarchical organization resembles the size principle, first proposed as a mechanism for establishing recruitment order among vertebrate motor neurons. Recordings in behaving flies confirmed that motor neurons are typically recruited in order from slow to fast. However, this study also found that fast, intermediate, and slow motor neurons receive distinct proprioceptive feedback signals, suggesting that the size principle is not the only mechanism that dictates motor neuron recruitment. Overall, this work reveals the functional organization of the fly leg motor system and establishes Drosophila as a tractable system for investigating neural mechanisms of limb motor control (Azevedo, 2020).
Animals rely on an internal sense of body position and movement to effectively control motor behavior. This sense of proprioception is mediated by diverse populations of mechanosensory neurons distributed throughout the body. This study investigated neural coding of leg proprioception in Drosophila, using in vivo two-photon calcium imaging of proprioceptive sensory neurons during controlled movements of the fly tibia. The axons of leg proprioceptors are organized into distinct functional projections that contain topographic representations of specific kinematic features. Using subclass-specific genetic driver lines, this study shows that one group of axons encodes tibia position (flexion/extension), another encodes movement direction, and a third encodes bidirectional movement and vibration frequency. Overall, these findings reveal how proprioceptive stimuli from a single leg joint are encoded by a diverse population of sensory neurons, and provide a framework for understanding how proprioceptive feedback signals are used by motor circuits to coordinate the body (Mamiya, 2018).
This study used in vivo calcium imaging to investigate the population coding of leg proprioception in the femoral chordotonal organ (FeCO) of Drosophila. The results reveal a basic logic for proprioceptive sensory coding: genetically distinct proprioceptor subclasses detect and encode distinct kinematic features, including tibia position, directional movement, and vibration. The cell bodies of each proprioceptor subclass reside in separate parts of the FeCO in the leg, and their axons project to distinct regions of the fly VNC. This organization suggests that different kinematic features may be processed by separate downstream circuits, and function as parallel feedback channels for the neural control of leg movement and behavior (Mamiya, 2018).
Claw neurons encode the position of the tibia relative to the femur, club neurons encode bidirectional tibia movement, and hook neurons encode birectional tibia movement. Specifically, each branch of a claw neuron consists of two sub-branches, whose calcium signals increase when the tibia is flexed or extended. Imaging from single claw neurons revealed that individual cells can be narrowly tuned to even more specific tibia angles. These data are consistent with previous reports of angular range fractionation in the locust FeCO. Interestingly, minimal activity in claw axons was observed when the tibia was close to 90°, and no single claw neuron was found tuned to this range in a limited sample. Similar tuning distributions have been observed in multiunit recordings from the FeCO of locusts and stick insects. However, single-unit recordings from these species also revealed the existence of a small number of position-tuned cells with peak activity in this middle range. It is possible that the driver lines that were used did not label the FeCO neurons tuned to this range. It is also possible that this represents a real difference between Drosophila and other insects. The fly FeCO has about half as many neurons as that of the stick insect and locust, and the biomechanics of the organ may also differ between species (Mamiya, 2018).
How does the position tuning of claw neurons relate to natural leg kinematics? When a fly is standing still, the tibia of the front leg rests ~90° relative to the femur; during straight walking, the tibia flexes to ~40° and extends to 120°. Thus, it is predicted that claw neurons are largely silent in a stationary fly, while extension- and flexion-tuned neurons are rhythmically active during walking. Encoding deviations from the natural resting position may reflect an adaptive strategy to minimize metabolic cost (Mamiya, 2018).
Position-encoding claw neurons exhibit response hysteresis (a lag between input and output): both flexion- and extension-tuned sub-branches of the claw showed larger steady-state activity when the tibia is moved in a direction that increases their activity. This response asymmetry is notable because it presents a problem for downstream circuits and computations that rely on a stable readout of tibia angle. Proprioceptive hysteresis has also been described in vertebrate muscle spindles and FeCO neurons of other insects. One possible solution for solving the ambiguities created by hysteresis would be to combine the tonic activity of claw neurons with signals from directionally selective hook neurons. This could allow a neuron to decode tibia position based on past history of tibia movement. However, it is also possible that tibia angle hysteresis is a useful feature of the proprioceptive system, rather than a bug. For example, it has been proposed that hysteresis could compensate for the nonlinear properties of muscle activation in short sensorimotor loops (Mamiya, 2018).
This study identified two functional subclasses of FeCO neurons that respond phasically to tibia movement. Club neurons respond to both flexion and the extension of the tibia, while hook neurons respond only to flexion. In both population and single neuron imaging experiments, directionally selective responses to tibia extension were observe, although it was not possible to identify a specific Gal4 line for this response subclass. The movement sensitivity of the club and hook neurons resembles that of other phasic proprioceptors, including primary muscle spindle afferents, and movement-tuned FeCO neurons recorded in the locust and stick insect. Although the slow temporal dynamics of GCaMP6f did not permit a detailed analysis of velocity tuning, the results indicate that FeCO neurons respond to the natural range of leg speeds encountered during walking. In the future, it will be interesting to investigate how FeCO neurons encode leg movements during walking, and how active movements may be encoded differently from passive movements, for example through presynaptic inhibition of FeCO axon terminals (Mamiya, 2018).
In addition to their directional tuning, this sudy found that club and hook neurons differ in their sensitivity to fast (100-2,000 Hz), low-amplitude (0.9-0.054 μm) tibia vibration. Club neurons are strongly activated by vibration stimuli, but hook neurons are not. This difference in vibration sensitivity is not likely to be caused by a difference in velocity tuning because these differences are relatively small at the range of the speeds experienced during tibia vibration. Rather, it seems that the club neurons have a lower mechanical threshold and/or may be more sensitive to the constant acceleration produced by vibration (Mamiya, 2018).
The functional role of vibration-sensitive FeCO neurons is not entirely clear. Previous studies in stick insects and locusts have found that vibration-tuned FeCO neurons do not contribute to postural reflexes in the same manner as FeCO neurons tuned to joint position and directional movement. This raises the possibility that vibration-tuned chordotonal neurons sense external mechanosensory stimuli. For example, club neurons could monitor substrate vibrations in the environment, which serve as an important communication signal for many insect species. Abdominal vibrations produced during courtship by male Drosophila coincide with pausing behavior in females, and hence increased receptivity to copulation. These vibrations occur at frequencies that match the sensitivity of club neurons (200-2,000 Hz). Therefore, club neurons are well-positioned to mediate intraspecific vibratory communication during courtship or other behaviors (Mamiya, 2018).
Using genetic driver lines for specific FeCO neuron subclasses, this study provides the first detailed anatomical characterization of Drosophila leg proprioceptors. The anatomy and imaging experiments revealed a systematic relationship between the functional tuning of proprioceptor subclasses and their anatomical structure. The cell bodies of the three proprioceptor subclasses are clustered in different regions of the femur, an organization that may reflect biomechanical specialization for detecting position, movement, and vibration. Proprioceptor axons then converge within the leg nerve, before branching within the VNC to form subclass-specific projections that are called the club, claw, and hook. This organization was found to be highly stereotyped across flies (Mamiya, 2018).
The axons of claw neurons split into three symmetric branches, resembling a claw. This unique arborization pattern is suggestive of a Cartesian coordinate system; for example, each branch could represent a different spatial axis. However, this study found that each claw neuron innervates all three branches, and that the X, Y, and Z branches all encode the same stimuli. Specifically, calcium imaging experiments revealed that each claw branch is divided into two sub-branches that are specialized for encoding flexion or extension of the tibia. If each claw branch is functionally similar, what is the purpose of this tri-partite structure? Each branch may target different downstream neurons, or could be independently modulated by presynaptic inhibition. Interestingly, the axons of directionally tuned hook neurons arborized alongside the claw but did not innervate all three of the claw branches. Thus, the X, Y, and Z branches may facilitate integration of positional information with directionally tuned movement signals (Mamiya, 2018).
It was surprising to discover a topographic map of leg vibration frequency within the axon terminals of club neurons. This structure has not previously been described in flies, but resembles the tonotopic map of sensory afferents in the cricket auditory system or the cochlear nucleus in vertebrates. Interestingly, the spatial layout of the frequency map in club axons was consistent across different vibration amplitudes, despite a shift in the peak frequency tuning curve. Recordings from single club neurons suggest that this frequency map is comprised of individual axons that are each tuned to a narrow frequency band. An orderly map of vibration frequency could facilitate feature identification in downstream circuits, for example through lateral inhibition between neighboring axons with shared tuning (Mamiya, 2018).
Neurons in the FeCO population can be generally classified as either tonic (position-encoding) or phasic (movement-encoding). This division has been observed among proprioceptors of many animals, including other insects, crustaceans, and mammals. For example, mammalian muscle spindles are innervated by both phasic (Group 1a) and tonic (Group II) afferents. The same has been found in other primary mechanosensory neurons, including touch, hearing, and vestibular afferents. The ubiquity of tonic and phasic neurons suggests that these two parallel information channels are essential building blocks of sensory circuits. Now that this study has identified genetic tools that delineate tonic and phasic neurons in the proprioceptive system of Drosophila, these circuits have the potential to provide general insights into the utility of this sensory coding strategy (Mamiya, 2018).
Flies possess other chordotonal organs: the most well-studied is the Johnston's organ (JO), which detects antennal movements produced by near-field sound, wind, gravity, and touch. Unlike the FeCO, the JO monitors rotation of a body segment that is not actively controlled by muscles or coupled to the substrate. The JO is also much larger (~500 versus ~135 neurons). Despite these differences, the coding schemes of the two mechanosensory organs share some key similarities. JO neurons can be classified into tonic and phasic classes, some exhibit direction selectivity, and their axon terminals form a rough tonotopic map of frequency. The FeCO and JO share genetic and developmental homology, which suggests that mechanosensory specialization in these organs could arise through similar molecular or biomechanical mechanisms (Mamiya, 2018).
With the advent of new methods for simultaneously monitoring the activity of hundreds or thousands of neurons, a critical challenge has been to link the activity of large neuronal populations to the underlying diversity of specific cell types. Previous efforts have used statistical methods to compare the responses of single neurons to simultaneous optical or electrophysiological population recordings. This study took a different approach, which took advantage of the fact that neurons in the fly can be reliably identified across individuals. Two-photon imaging was first used to monitor activity across a population of proprioceptive sensory neurons during controlled leg movements. From this population data, spatially distinct axon branches were identified that encode specific proprioceptive stimulus features.Genetic driver lines were sought that specifically labeled each axon branch and further characterized their functional tuning with targeted calcium imaging. With this approach, it was possible to identify and characterize the major neuronal subclasses in a key proprioceptive organ (Mamiya, 2018).
With a genetic handle on position, movement, and direction pathways, it should now be possible to trace the flow of proprioceptive signals into downstream circuits and to identify the functional role of specific proprioceptor subclasses within the broader context of motor control and behavior. It is anticipated that Drosophila will provide a useful complement to other model organisms in dissecting fundamental mechanisms of proprioception and deepening understanding of this mysterious 'sixth sense' (Mamiya, 2018).
Walking trajectory is frequently measured to assess animal behavior. Air-supported spherical treadmills have been developed for real-time monitoring of animal walking trajectories. However, current systems for mice mainly employ computer mouse microcameras (chip-on-board sensors) to monitor ball motion, and these detectors exhibit technical issues with focus and rotation scale. In addition, computational methods to analyze and quantify the "random walk" of organisms are under-developed. This work has overcome the hurdle of frame-to-signal translation to develop a treadmill system with camera-based detection. Moreover, a package of mathematical methods were generated to quantify distinct aspects of Drosophila walking trajectories. By extracting and quantifying certain features of walking dynamics with high temporal resolution, it was found that depending on their internal state, flies employ different walking strategies to approach environmental cues. This camera-based treadmill system and method package may also be applicable to monitor the walking trajectories of other diverse animal species (Tsai, 2019).
External cues, including touch, enable walking animals to flexibly maneuver around obstacles and extricate themselves from dead-ends. In a screen for neurons that enable Drosophila melanogaster to retreat when it encounters a dead-end, this study identified a pair of ascending neurons, the TwoLumps Ascending (TLA) neurons. Silencing TLA activity impairs backward locomotion, whereas optogenetic activation triggers backward walking. TLA-induced reversal is mediated in part by the Moonwalker Descending Neurons (MDNs), which receive excitatory input from the TLAs. Silencing the TLAs decreases the extent to which freely walking flies back up upon encountering a physical barrier in the dark, and TLAs show calcium responses to optogenetic activation of neurons expressing the mechanosensory channel NOMPC. It is infered that TLAs convey feedforward mechanosensory stimuli to transiently activate MDNs in response to anterior body touch (Sen, 2019)
To navigate complex environments, animals must generate highly robust, yet flexible, locomotor behaviors. For example, walking speed must be tailored to the needs of a particular environment. Not only must animals choose the correct speed and gait, they must also adapt to changing conditions and quickly respond to sudden and surprising new stimuli. Neuromodulators, particularly the small biogenic amine neurotransmitters, have the ability to rapidly alter the functional outputs of motor circuits. This study shows that the serotonergic system in the vinegar fly, Drosophila melanogaster, can modulate walking speed in a variety of contexts and also change how flies respond to sudden changes in the environment. These multifaceted roles of serotonin in locomotion are differentially mediated by a family of serotonergic receptors with distinct activities and expression patterns (Howard, 2019).
The CORL family of CNS-specific proteins share a Smad-binding region with mammalian SnoN and c-Ski protooncogenes. In this family Drosophila CORL has two mouse and two human relatives. Roles for the mouse and human CORL proteins are largely unknown. Based on genome-wide association studies linking the human CORL proteins Fussel15 and Fussel18 with ataxia, this study tested the hypothesis that dCORL mutations will cause adult movement disorders. For initial tests, side by side studies were conducted of adults with the small deletion Df(4)dCORL and eight control strains. Deletion mutants exhibit three types of behavioral plasticity. First, significant climbing defects attributable to loss of dCORL are eliminated by age. Second, significant phototaxis defects due to loss of dCORL are partially ameliorated by age and are not due to faulty photoreceptors. Third, Df(4)dCORL males raised in groups have a lower courtship index than males raised as singles though this defect is not due to loss of dCORL Subsequent tests showed that the climbing and phototaxis defects were phenocpied by dCORL(21B) and dCORL(23C) two CRISPR generated mutations. Overall, the finding that adult movement defects due to loss of dCORL are subject to age-dependent plasticity suggests new hypotheses for CORL functions in flies and mammals (Dimitriadou, 2020).
Previous work has characterized how walking Drosophila coordinate the movements of individual limbs. To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior. However, it has remained difficult to manipulate neural activity in individual limbs of freely moving animals. This study demonstrates a simple method for optogenetic stimulation with body side-, body segment-, and limb-specificity that does not require real-time tracking. Instead, precise locations were activated at random in time and space and use post hoc analysis to determine behavioral responses to specific activations. Using this method, this study has characterized limb coordination and walking behavior in response to transient activation of mechanosensitive bristle neurons and sweet-sensing chemoreceptor neurons. these findings reveal that activating these neurons has opposite effects on turning, and that activations in different limbs and body regions produce distinct behaviors (DeAngelis, 2020).
Avoiding predators is an essential behavior in which animals must quickly transform sensory cues into evasive actions. Sensory reflexes are particularly fast in flying insects such as flies, but the means by which they evade aerial predators is not known. Using high-speed videography and automated tracking of flies in combination with aerodynamic measurements on flapping robots, this study showed that flying flies react to looming stimuli with directed banked turns. The maneuver consists of a rapid body rotation followed immediately by an active counter-rotation and is enacted by remarkably subtle changes in wing motion. These evasive maneuvers of flies are substantially faster than steering maneuvers measured previously and indicate the existence of sensory-motor circuitry that can reorient the fly's flight path within a few wingbeats (Muijres, 2014).
Previous studies on free-flying flies suggested that yaw torque is generated by a regulation of wing rotation, effectively changing the relative aerodynamic angle of attack during the upstroke and downstroke. In this study of banked turns, it was also found that wing rotation was an important control parameter, although its contribution was relatively minor. In addition, the primary changes this study measured in wing rotation were associated with shifts in timing, possibly modulating rotational lift rather than angle of attack during upstroke and downstroke. This discrepancy with previous studies might reflect an interesting difference in the control of pitch and roll compared with yaw. It is also noteworthy that stroke angle exerts a stronger influence over forces and moments than either wing rotation or stroke deviation. This finding is consistent with many previous studies in tethered flight which show that flies robustly modulate stroke amplitude in response to sensory signals that elicit changes in flight force, as well as roll, pitch, and yaw (Muijres, 2014).
These results indicate that flies escape from looming objects by exhibiting a rapid banked turn. The motor basis of these rapid maneuvers are quite distinct from those previously described in that the change in direction is generated by a combination of pitch and roll, requiring active torque and countertorque generated by a fine-scaled, coordinated change in all aspects of wing motion. The changes in heading during these maneuvers are roughly 5 times as fast (5300o s-1) as those measured during voluntary saccadic turns (1000o s-1), suggesting that this strategy provides the animals with the fastest possible means for altering direction. Using the genetic and physiological approaches available in the closely related species D. melanogaster, it should be possible to elucidate the neural circuitry and muscle physiology that underlies these rapid behaviors (Muijres, 2014).
While the wing kinematics of many flapping insects have been well characterized, understanding the underlying sensory, neural, and physiological mechanisms that determine these kinematics is still a challenge. Two main difficulties in understanding the physiological mechanisms arise from the complexity of the interaction between a flapping wing and its own unsteady flow, as well as the intricate mechanics of the insect wing hinge, which is among the most complicated joints in the animal kingdom. These difficulties call for the application of reduced-order approaches. This strategy was used to model the torques exerted by the wing hinge along the wing-pitch axis of maneuvering fruit flies as a damped torsional spring with elastic and damping coefficients as well as a rest angle. Furthermore, the air flows were modeled using simplified quasistatic aerodynamics. The findings suggest that flies take advantage of the passive coupling between aerodynamics and the damped torsional spring to indirectly control their wing-pitch kinematics by modulating the spring parameters. The damped torsional-spring model explains the changes measured in wing-pitch kinematics during roll correction maneuvers through modulation of the spring damping and elastic coefficients. These results, in conjunction with the previous literature, indicate that flies can accurately control their wing-pitch kinematics on a sub-wing-beat time scale by modulating all three effective spring parameters on longer time scales (Beatus, 2015).