Influence of electrotonic structure and synaptic mapping on the receptive field properties of a collision-detecting neuron

Recent advances in insect vision in a 3D world: looming stimuli and escape behaviour

Detecting looming motion directly towards the insect is vital to its survival. Looming detection in two insects, flies and locusts, is described and contrasted. Pathways using looming detectors to trigger action and their topographical layout in the brain is explored in relation to facilitating behavioural selection. Similar visual stimuli, such as looming motion, are processed by nearby glomeruli in the brain. Insect-inspired looming motion detectors are combined to detect and avoid collision in different scenarios by robots, vehicles and unmanned aerial vehicle (UAV)s.

Contrast polarity-specific mapping improves efficiency of neuronal computation for collision detection

Neurons receive information through their synaptic inputs, but the functional significance of how those inputs are mapped on to a cell's dendrites remains unclear. We studied this question in a grasshopper visual neuron that tracks approaching objects and triggers escape behavior before an impending collision. In response to black approaching objects, the neuron receives OFF excitatory inputs that form a retinotopic map of the visual field onto compartmentalized, distal dendrites. Subsequent processing of these OFF inputs by active membrane conductances allows the neuron to discriminate the spatial coherence of such stimuli. In contrast, we show that ON excitatory synaptic inputs activated by white approaching objects map in a random manner onto a more proximal dendritic field of the same neuron. The lack of retinotopic synaptic arrangement results in the neuron's inability to discriminate the coherence of white approaching stimuli. Yet, the neuron retains the ability to discriminate stimulus coherence for checkered stimuli of mixed ON/OFF polarity. The coarser mapping and processing of ON stimuli thus has a minimal impact, while reducing the total energetic cost of the circuit. Further, we show that these differences in ON/OFF neuronal processing are behaviorally relevant, being tightly correlated with the animal's escape behavior to light and dark stimuli of variable coherence. Our results show that the synaptic mapping of excitatory inputs affects the fine stimulus discrimination ability of single neurons and document the resulting functional impact on behavior.

A model of feedforward, global, and lateral inhibition in the locust visual system predicts responses to looming stimuli

Detection of looming obstacles is a vital task for both natural and artificial systems. Locusts possess a visual nervous system with an extensively studied obstacle detection pathway, culminating in the lobula giant movement detector (LGMD) neuron. While numerous models of this system exist, none to date have incorporated recent data on the anatomy and function of feedforward and global inhibitory systems in the input network of the LGMD. Moreover, the possibility that global and lateral inhibition shape the feedforward inhibitory signals to the LGMD has not been investigated. To address these points, a novel model of feedforward inhibitory neurons in the locust optic lobe was developed based on the recent literature. This model also incorporated global and lateral inhibition into the afferent network of these neurons, based on their observed behaviour in existing data and the posited role of these mechanisms in the inputs to the LGMD. Tests with the model showed that it accurately replicates the behaviour of feedforward inhibitory neurons in locusts; the model accurately coded for stimulus angular size in an overall linear fashion, with decreasing response saturation and increasing linearity as stimulus size increased or approach velocity decreased. The model also exhibited only phasic responses to the appearance of a grating, along with sustained movement by it at constant speed. By observing the effects of altering inhibition schemes on these responses, it was determined that global inhibition serves primarily to normalize growing excitation as collision approaches, and keeps coding for subtense angle linear. Lateral inhibition was determined to suppress tonic responses to wide-field stimuli translating at constant speed. Based on these features being shared with characterizations of the LGMD input network, it was hypothesized that the feedforward inhibitory neurons and the LGMD share the same excitatory afferents; this necessitates further investigation.

Active membrane conductances and morphology of a collision detection neuron broaden its impedance profile and improve discrimination of input synchrony

How neurons filter and integrate their complex patterns of synaptic inputs is central to their role in neural information processing. Synaptic filtering and integration are shaped by the frequency-dependent neuronal membrane impedance. Using single and dual dendritic recordings in vivo, pharmacology, and computational modeling, we characterized the membrane impedance of a collision detection neuron in the grasshopper Schistocerca americana. This neuron, the lobula giant movement detector (LGMD), exhibits consistent impedance properties across frequencies and membrane potentials. Two common active conductances g_H and g_M, mediated respectively by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels and by muscarine-sensitive M-type K⁺ channels, promote broadband integration with high temporal precision over the LGMD's natural range of membrane potentials and synaptic input frequencies. Additionally, we found that a model based on the LGMD's branching morphology increased the gain and decreased the delay associated with the mapping of synaptic input currents to membrane potential. More generally, this was true for a wide range of model neuron morphologies, including those of neocortical pyramidal neurons and cerebellar Purkinje cells. These findings show the unexpected role played by two widespread active conductances and by dendritic morphology in shaping synaptic integration.NEW & NOTEWORTHY Neuronal filtering and integration of synaptic input patterns depend on the electrochemical properties of dendrites. We used an identified collision detection neuron in grasshoppers to examine how its morphology and two conductances affect its membrane impedance in relation to the computations it performs. The neuronal properties examined are ubiquitous and therefore promote a general understanding of neuronal computations, including those in the human brain.

Biophysics of object segmentation in a collision-detecting neuron

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K⁺ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns.

Two identified looming detectors in the locust: ubiquitous lateral connections among their inputs contribute to selective responses to looming objects

In locusts, two lobula giant movement detector neurons (LGMDs) act as looming object detectors. Their reproducible responses to looming and their ethological significance makes them models for single neuron computation. But there is no comprehensive picture of the neurons that connect directly to each LGMD. We used high-through-put serial block-face scanning-electron-microscopy to reconstruct the network of input-synapses onto the LGMDs over spatial scales ranging from single synapses and small circuits, up to dendritic branches and total excitatory input. Reconstructions reveal that many trans-medullary-afferents (TmAs) connect the eye with each LGMD, one TmA per facet per LGMD. But when a TmA synapses with an LGMD it also connects laterally with another TmA. These inter-TmA synapses are always reciprocal. Total excitatory input to the LGMD 1 and 2 comes from 131,000 and 186,000 synapses reaching densities of 3.1 and 2.6 synapses per μm² respectively. We explored the computational consequences of reciprocal synapses between each TmA and 6 others from neighbouring columns. Since any lateral interactions between LGMD inputs have always been inhibitory we may assume these reciprocal lateral connections are most likely inhibitory. Such reciprocal inhibitory synapses increased the LGMD’s selectivity for looming over passing objects, particularly at the beginning of object approach.

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

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

A look into the cockpit of the developing locust: looming detectors and predator avoidance

For many animals, the visual detection of looming stimuli is crucial at any stage of their lives. For example, human babies of only 6 days old display evasive responses to looming stimuli (Bower et al. [1971]: Percept Psychophys 9: 193-196). This means the neuronal pathways involved in looming detection should mature early in life. Locusts have been used extensively to examine the neural circuits and mechanisms involved in sensing looming stimuli and triggering visually evoked evasive actions, making them ideal subjects in which to investigate the development of looming sensitivity. Two lobula giant movement detectors (LGMD) neurons have been identified in the lobula region of the locust visual system: the LGMD1 neuron responds selectively to looming stimuli and provides information that contributes to evasive responses such as jumping and emergency glides. The LGMD2 responds to looming stimuli and shares many response properties with the LGMD1. Both neurons have only been described in the adult. In this study, we describe a practical method combining classical staining techniques and 3D neuronal reconstructions that can be used, even in small insects, to reveal detailed anatomy of individual neurons. We have used it to analyze the anatomy of the fan-shaped dendritic tree of the LGMD1 and the LGMD2 neurons in all stages of the post-embryonic development of Locusta migratoria. We also analyze changes seen during the ontogeny of escape behaviors triggered by looming stimuli, specially the hiding response.

Spatiotemporal stimulus properties modulate responses to trajectory changes in a locust looming-sensitive pathway

The lobula giant movement detector (LGMD) and descending contralateral movement detector (DCMD) constitute one motion-sensitive pathway in the locust visual system that is implicated in collision-avoidance behaviors. While this pathway is thought to respond preferentially to objects approaching on a direct collision course, emerging studies suggest the firing rate is able to monitor more complicated movements that would occur under natural conditions. While previous studies have compared the response of the DCMD to objects on collision courses that travel at different speeds, velocity has not been manipulated for other simple or compound trajectories. Here we test the possibility that the LGMD/DCMD pathway is capable of responding uniquely to complex aspects of object motion, including translation and trajectory changes at different velocities. We found that the response of the DCMD to translational motion initiated in the caudal visual field was a low-amplitude peak in firing rate that occurred before the object crossed 90° azimuth that was invariant to different object velocities. Direct looms at different velocities resulted in peak firing rates that occurred later in time and with greater amplitude for higher velocities. In response to transitions from translational motion to a collision course, the firing rate change depended on both the location within the visual field and the velocity. These results suggest that this pathway is capable of conveying information about multiple properties of a moving object's trajectory.

Looming detection by identified visual interneurons during larval development of the locust Locusta migratoria

Insect larvae clearly react to visual stimuli, but the ability of any visual neuron in a newly hatched insect to respond selectively to particular stimuli has not been directly tested. We characterised a pair of neurons in locust larvae that have been extensively studied in adults, where they are known to respond selectively to objects approaching on a collision course: the lobula giant motion detector (LGMD) and its postsynaptic partner, the descending contralateral motion detector (DCMD). Our physiological recordings of DCMD axon spikes reveal that at the time of hatching, the neurons already respond selectively to objects approaching the locust and they discriminate between stimulus approach speeds with differences in spike frequency. For a particular approaching stimulus, both the number and peak frequency of spikes increase with instar. In contrast, the number of spikes in responses to receding stimuli decreases with instar, so performance in discriminating approaching from receding stimuli improves as the locust goes through successive moults. In all instars, visual movement over one part of the visual field suppresses a response to movement over another part. Electron microscopy demonstrates that the anatomical substrate for the selective response to approaching stimuli is present in all larval instars: small neuronal processes carrying information from the eye make synapses both onto LGMD dendrites and with each other, providing pathways for lateral inhibition that shape selectivity for approaching objects.

A looming-sensitive pathway responds to changes in the trajectory of object motion

Two identified locust neurons, the lobula giant movement detector (LGMD) and its postsynaptic partner, the descending contralateral movement detector (DCMD), constitute one motion-sensitive pathway in the visual system that responds preferentially to objects that approach on a direct collision course and are implicated in collision-avoidance behavior. Previously described responses to the approach of paired objects and approaches at different time intervals (Guest BB, Gray JR. J Neurophysiol 95: 1428–1441, 2006) suggest that this pathway may also be affected by more complicated movements in the locust's visual environment. To test this possibility we presented stationary locusts with disks traveling along combinations of colliding (looming), noncolliding (translatory), and near-miss trajectories. Distinctly different responses to different trajectories and trajectory changes demonstrate that DCMD responds to complex aspects of local visual motion. DCMD peak firing rates associated with the time of collision remained relatively invariant after a trajectory change from translation to looming. Translatory motion initiated in the frontal visual field generated a larger peak firing rate relative to object motion initiated in the posterior visual field, and the peak varied with simulated distance from the eye. Transition from translation to looming produced a transient decrease in the firing rate, whereas transition away from looming produced a transient increase. The change in firing rate at the time of transition was strongly correlated with unique expansion parameters described by the instantaneous angular acceleration of the leading edge and subtense angle of the disk. However, response time remained invariant. While these results may reflect low spatial resolution of the compound eye, they also suggest that this motion-sensitive pathway may be capable of monitoring dynamic expansion properties of objects that change the trajectory of motion.

Somato-dendritic morphology and dendritic signal transfer properties differentiate between fore- and hindlimb innervating motoneurons in the frog Rana esculenta

Background

The location specific motor pattern generation properties of the spinal cord along its rostro-caudal axis have been demonstrated. However, it is still unclear that these differences are due to the different spinal interneuronal networks underlying locomotions or there are also segmental differences in motoneurons innervating different limbs. Frogs use their fore- and hindlimbs differently during jumping and swimming. Therefore we hypothesized that limb innervating motoneurons, located in the cervical and lumbar spinal cord, are different in their morphology and dendritic signal transfer properties. The test of this hypothesis what we report here.

Results

Discriminant analysis classified segmental origin of the intracellularly labeled and three-dimensionally reconstructed motoneurons 100% correctly based on twelve morphological variables. Somata of lumbar motoneurons were rounder; the dendrites had bigger total length, more branches with higher branching orders and different spatial distributions of branch points. The ventro-medial extent of cervical dendrites was bigger than in lumbar motoneurons. Computational models of the motoneurons showed that dendritic signal transfer properties were also different in the two groups of motoneurons. Whether log attenuations were higher or lower in cervical than in lumbar motoneurons depended on the proximity of dendritic input to the soma. To investigate dendritic voltage and current transfer properties imposed by dendritic architecture rather than by neuronal size we used standardized distributions of transfer variables. We introduced a novel combination of cluster analysis and homogeneity indexes to quantify segmental segregation tendencies of motoneurons based on their dendritic transfer properties. A segregation tendency of cervical and lumbar motoneurons was detected by the rates of steady-state and transient voltage-amplitude transfers from dendrites to soma at all levels of synaptic background activities, modeled by varying the specific dendritic membrane resistance. On the other hand no segregation was observed by the steady-state current transfer except under high background activity.

Conclusions

We found size-dependent and size-independent differences in morphology and electrical structure of the limb moving motoneurons based on their spinal segmental location in frogs. Location specificity of locomotor networks is therefore partly due to segmental differences in motoneurons driving fore-, and hindlimbs.

Impact of neural noise on a sensory-motor pathway signaling impending collision

Noise is a major concern in circuits processing electrical signals, including neural circuits. There are many factors that influence how noise propagates through neural circuits, and there are few systems in which noise levels have been studied throughout a processing pathway. We recorded intracellularly from multiple stages of a sensory-motor pathway in the locust that detects approaching objects. We found that responses are more variable and that signal-to-noise ratios (SNRs) are lower further from the sensory periphery. SNRs remain low even with the use of stimuli for which the pathway is most selective and for which the neuron representing its final sensory level must integrate many synaptic inputs. Modeling of this neuron shows that variability in the strength of individual synaptic inputs within a large population has little effect on the variability of the spiking output. In contrast, jitter in the timing of individual inputs and spontaneous variability is important for shaping the responses to preferred stimuli. These results suggest that neural noise is inherent to the processing of visual stimuli signaling impending collision and contributes to shaping neural responses along this sensory-motor pathway.

Collision detection as a model for sensory-motor integration

Visually guided collision avoidance is critical for the survival of many animals. The execution of successful collision-avoidance behaviors requires accurate processing of approaching threats by the visual system and signaling of threat characteristics to motor circuits to execute appropriate motor programs in a timely manner. Consequently, visually guided collision avoidance offers an excellent model with which to study the neural mechanisms of sensory-motor integration in the context of a natural behavior. Neurons that selectively respond to approaching threats and brain areas processing them have been characterized across many species. In locusts in particular, the underlying sensory and motor processes have been analyzed in great detail: These animals possess an identified neuron, called the LGMD, that responds selectively to approaching threats and conveys that information through a second identified neuron, the DCMD, to motor centers, generating escape jumps. A combination of behavioral and in vivo electrophysiological experiments has unraveled many of the cellular and network mechanisms underlying this behavior.

Synchronized neural input shapes stimulus selectivity in a collision-detecting neuron

How higher-order sensory neurons generate complex selectivity from their simpler inputs is a fundamental question in neuroscience. The lobula giant movement detector (LGMD) is such a visual neuron in the locust Schistocerca americana that responds selectively to objects approaching on a collision course or their two-dimensional projections, looming stimuli [1-4]. To study how this selectivity arises, we designed an apparatus allowing us to stimulate, individually and independently, a sizable fraction of the ∼15,000 elementary visual inputs impinging retinotopically onto the LGMD's dendritic fan [5-7] (Figure 1Ai). We then recorded intracellularly in vivo throughout the visual pathway, assessing the LGMD's activity and that of all three successive presynaptic stages conveying local excitatory inputs. Our results suggest that as collision becomes increasingly imminent, the strength of these inputs increases, whereas their latency decreases. This latency decrease favors summation of inputs activated sequentially throughout the looming sequence, making the neuron maximally sensitive to collision-bound trajectories. Thus, the LGMD's selectivity arises partially from presynaptic mechanisms that synchronize a large population of inputs during a looming stimulus and subsequent detection by postsynaptic mechanisms within the neuron itself. Analogous mechanisms are likely to underlie the tuning properties of visual neurons in other species as well.

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

Drosophila melanogster is a model organism rich in genetic tools to manipulate and identify neural circuits involved in specific behaviors. Here we present a novel technique for two-photon calcium imaging in the central brain of head-fixed Drosophila walking on an air-supported ball. The ball’s motion is tracked at high resolution and can be treated as a proxy for the fly’s own movements. We used the genetically encoded calcium sensor, GCaMP3.0, to record from important elements of the motion-processing pathway, the horizontal-system (HS) lobula plate tangential cells (LPTCs) in the fly optic lobe. We presented motion stimuli to the tethered fly and found that calcium transients in HS-neurons correlated with robust optomotor behavior during walking. Our technique allows an entirely new set of questions to be addressed by monitoring behavior and physiology in identified neurons in a powerful genetic model organism with an extensive repertoire of walking behaviors.

Non-linear neuronal responses as an emergent property of afferent networks: a case study of the locust lobula giant movement detector

In principle it appears advantageous for single neurons to perform non-linear operations. Indeed it has been reported that some neurons show signatures of such operations in their electrophysiological response. A particular case in point is the Lobula Giant Movement Detector (LGMD) neuron of the locust, which is reported to locally perform a functional multiplication. Given the wide ramifications of this suggestion with respect to our understanding of neuronal computations, it is essential that this interpretation of the LGMD as a local multiplication unit is thoroughly tested. Here we evaluate an alternative model that tests the hypothesis that the non-linear responses of the LGMD neuron emerge from the interactions of many neurons in the opto-motor processing structure of the locust. We show, by exposing our model to standard LGMD stimulation protocols, that the properties of the LGMD that were seen as a hallmark of local non-linear operations can be explained as emerging from the dynamics of the pre-synaptic network. Moreover, we demonstrate that these properties strongly depend on the details of the synaptic projections from the medulla to the LGMD. From these observations we deduce a number of testable predictions. To assess the real-time properties of our model we applied it to a high-speed robot. These robot results show that our model of the locust opto-motor system is able to reliably stabilize the movement trajectory of the robot and can robustly support collision avoidance. In addition, these behavioural experiments suggest that the emergent non-linear responses of the LGMD neuron enhance the system's collision detection acuity. We show how all reported properties of this neuron are consistently reproduced by this alternative model, and how they emerge from the overall opto-motor processing structure of the locust. Hence, our results propose an alternative view on neuronal computation that emphasizes the network properties as opposed to the local transformations that can be performed by single neurons.

The tiny brains of insects of about 1mm³ smoothly control a flying platform while avoiding obstacles, regulating its distance to objects and search for objects of interest. This is largely achieved through a complex hierarchical processing of signals from the multitude of ommatidia in their eye to a set of highly specialized neurons that are optimized to respond to specific properties of the visual world. One of these neurons, the Lobula Giant Movement Detector (LGMD) of the locust, has been recently shown to perform a functional multiplication of its synaptic inputs. If true, that would make the LGMD neuron a unique and highly sophisticated neuron that raises questions about the non-linear operations other neurons in other neuronal systems would be able to perform. Hence it is crucial to understand its properties, its role in behaviour and to evaluate whether its responses can be explained in simpler terms. Our results emphasize the role of network architecture and distributed computation as opposed to local complex non-linear computation. We show that our model reliably reproduces the known properties of the LGMD and can be used to control a high-speed robot.

Spatiotemporal receptive field properties of a looming-sensitive neuron in solitarious and gregarious phases of the desert locust

Desert locusts (Schistocerca gregaria) can transform reversibly between the swarming gregarious phase and a solitarious phase, which avoids other locusts. This transformation entails dramatic changes in morphology, physiology, and behavior. We have used the lobula giant movement detector (LGMD) and its postsynaptic target, the descending contralateral movement detector (DCMD), which are visual interneurons that detect looming objects, to analyze how differences in the visual ecology of the two phases are served by altered neuronal function. Solitarious locusts had larger eyes and a greater degree of binocular overlap than those of gregarious locusts. The receptive field to looming stimuli had a large central region of nearly equal response spanning 120 degrees x 60 degrees in both phases. The DCMDs of gregarious locusts responded more strongly than solitarious locusts and had a small caudolateral focus of even further sensitivity. More peripherally, the response was reduced in both phases, particularly ventrally, with gregarious locusts showing greater proportional decrease. Gregarious locusts showed less habituation to repeated looming stimuli along the eye equator than did solitarious locusts. By contrast, in other parts of the receptive field the degree of habituation was similar in both phases. The receptive field organization to looming stimuli contrasts strongly with the receptive field organization of the same neurons to nonlooming local-motion stimuli, which show much more pronounced regional variation. The DCMDs of both gregarious and solitarious locusts are able to detect approaching objects from across a wide expanse of visual space, but phase-specific changes in the spatiotemporal receptive field are linked to lifestyle changes.

Precise subcellular input retinotopy and its computational consequences in an identified visual interneuron

The Lobula Giant Movement Detector (LGMD) is a higher-order visual interneuron of Orthopteran insects that responds preferentially to objects approaching on a collision course. It receives excitatory input from an entire visual hemifield that anatomical evidence suggests is retinotopic. We show that this excitatory projection activates calcium-permeable nicotinic acetylcholine receptors. In vivo calcium imaging reveals that the excitatory projection preserves retinotopy down to the level of a single ommatidium. Examining the impact of retinotopy on the LGMD's computational properties, we show that sublinear synaptic summation can explain orientation preference in this cell. Exploring retinotopy's impact on directional selectivity leads us to infer that the excitatory input to the LGMD is intrinsically directionally selective. Our results show that precise retinotopy has implications for the dendritic integration of visual information in a single neuron.

Role of spike-frequency adaptation in shaping neuronal response to dynamic stimuli

Spike-frequency adaptation is the reduction of a neuron's firing rate to a stimulus of constant intensity. In the locust, the Lobula Giant Movement Detector (LGMD) is a visual interneuron that exhibits rapid adaptation to both current injection and visual stimuli. Here, a reduced compartmental model of the LGMD is employed to explore adaptation's role in selectivity for stimuli whose intensity changes with time. We show that supralinearly increasing current injection stimuli are best at driving a high spike count in the response, while linearly increasing current injection stimuli (i.e., ramps) are best at attaining large firing rate changes in an adapting neuron. This result is extended with in vivo experiments showing that the LGMD's response to translating stimuli having a supralinear velocity profile is larger than the response to constant or linearly increasing velocity translation. Furthermore, we show that the LGMD's preference for approaching versus receding stimuli can partly be accounted for by adaptation. Finally, we show that the LGMD's adaptation mechanism appears well tuned to minimize sensitivity for the level of basal input.

Signal propagation in Drosophila central neurons

Drosophila is an important model organism for investigating neural development, neural morphology, neurophysiology, and neural correlates of behaviors. However, almost nothing is known about how electrical signals propagate in Drosophila neurons. Here, we address these issues in antennal lobe projection neurons, one of the most well studied classes of Drosophila neurons. We use morphological and electrophysiological data to deduce the passive membrane properties of these neurons and to build a compartmental model of their electrotonic structure. We find that these neurons are electrotonically extensive and that a somatic recording electrode can only imperfectly control the voltage in the rest of the cell. Simulations predict that action potentials initiate at a location distant from the soma, in the proximal portion of the axon. Simulated synaptic input to a single dendritic branch propagates poorly to the rest of the cell and cannot match the size of real unitary synaptic events, but we can obtain a good fit to data when we model unitary input synapses as dozens of release sites distributed across many dendritic branches. We also show that the true resting potential of these neurons is more hyperpolarized than previously thought, attributable to the experimental error introduced by the electrode seal conductance. A leak sodium conductance also contributes to the resting potential. Together, these findings have fundamental implications for how these neurons integrate their synaptic inputs. Our results also have important consequences for the design and interpretation of experiments aimed at understanding Drosophila neurons and neural circuits.

Spike frequency adaptation mediates looming stimulus selectivity in a collision-detecting neuron

How active membrane conductance dynamics tunes neurons for specific time-varying stimuli remains poorly understood. We studied the biophysical mechanisms by which spike frequency adaptation shapes visual stimulus selectivity in an identified visual interneuron of the locust. The lobula giant movement detector (LGMD) responds preferentially to objects approaching on a collision course with the locust. Using calcium imaging, pharmacology and modeling, we show that spike frequency adaptation in the LGMD is mediated by a Ca(2+)-dependent potassium conductance closely resembling those associated with 'small-conductance' (SK) channels. Intracellular block of this conductance minimally affected the LGMD's response to approaching stimuli, but substantially increased its response to translating ones. Thus, spike frequency adaptation contributes to the neuron's tuning by selectively decreasing its responses to nonpreferred stimuli. Our results identify a new mechanism by which spike frequency adaptation may tune visual neurons to behaviorally relevant stimuli.

Spike frequency adaptation mediates looming stimulus selectivity in a collision-detecting neuron

How active membrane conductance dynamics tunes neurons for specific time-varying stimuli remains poorly understood. We studied the biophysical mechanisms by which spike frequency adaptation shapes visual stimulus selectivity in an identified visual interneuron of the locust. The lobula giant movement detector (LGMD) responds preferentially to objects approaching on a collision course with the locust. Using calcium imaging, pharmacology and modeling, we show that spike frequency adaptation in the LGMD is mediated by a Ca(2+)-dependent potassium conductance closely resembling those associated with 'small-conductance' (SK) channels. Intracellular block of this conductance minimally affected the LGMD's response to approaching stimuli, but substantially increased its response to translating ones. Thus, spike frequency adaptation contributes to the neuron's tuning by selectively decreasing its responses to nonpreferred stimuli. Our results identify a new mechanism by which spike frequency adaptation may tune visual neurons to behaviorally relevant stimuli.

Arousal facilitates collision avoidance mediated by a looming sensitive visual neuron in a flying locust

Locusts have two large collision-detecting neurons, the descending contralateral movement detectors (DCMDs) that signal object approach and trigger evasive glides during flight. We sought to investigate whether vision for action, when the locust is in an aroused state rather than a passive viewer, significantly alters visual processing in this collision-detecting pathway. To do this we used two different approaches to determine how the arousal state of a locust affects the prolonged periods of high-frequency spikes typical of the DCMD response to approaching objects that trigger evasive glides. First, we manipulated arousal state in the locust by applying a brief mechanical stimulation to the hind leg; this type of change of state occurs when gregarious locusts accumulate in high-density swarms. Second, we examined DCMD responses during flight because flight produces a heightened physiological state of arousal in locusts. When arousal was induced by either method we found that the DCMD response recovered from a previously habituated state; that it followed object motion throughout approach; and--most important--that it was significantly more likely to generate the maintained spike frequencies capable of evoking gliding dives even with extremely short intervals (1.8 s) between approaches. Overall, tethered flying locusts responded to 41% of simulated approaching objects (sets of 6 with 1.8 s ISI). When we injected epinastine, the neuronal octopamine receptor antagonist, into the hemolymph responsiveness declined to 12%, suggesting that octopamine plays a significant role in maintaining responsiveness of the DCMD and the locust to visual stimuli during flight.