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

Visual processing and collective motion-related decision-making in desert locusts

Collectively moving groups of animals rely on the decision-making of locally interacting individuals in order to maintain swarm cohesion. However, the complex and noisy visual environment poses a major challenge to the extraction and processing of relevant information. We addressed this challenge by studying swarming-related decision-making in desert locust last-instar nymphs. Controlled visual stimuli, in the form of random dot kinematograms, were presented to tethered locust nymphs in a trackball set-up, while monitoring movement trajectory and walking parameters. In a complementary set of experiments, the neurophysiological basis of the observed behavioural responses was explored. Our results suggest that locusts use filtering and discrimination upon encountering multiple stimuli simultaneously. Specifically, we show that locusts are sensitive to differences in speed at the individual conspecific level, and to movement coherence at the group level, and may use these to filter out non-relevant stimuli. The locusts also discriminate and assign different weights to different stimuli, with an observed interactive effect of stimulus size, relative abundance and motion direction. Our findings provide insights into the cognitive abilities of locusts in the domain of decision-making and visual-based collective motion, and support locusts as a model for investigating sensory-motor integration and motion-related decision-making in the intricate swarm environment.

Predictive Coding with Neural Transmission Delays: A Real-Time Temporal Alignment Hypothesis

Hierarchical predictive coding is an influential model of cortical organization, in which sequential hierarchical levels are connected by backward connections carrying predictions, as well as forward connections carrying prediction errors. To date, however, predictive coding models have largely neglected to take into account that neural transmission itself takes time. For a time-varying stimulus, such as a moving object, this means that backward predictions become misaligned with new sensory input. We present an extended model implementing both forward and backward extrapolation mechanisms that realigns backward predictions to minimize prediction error. This realignment has the consequence that neural representations across all hierarchical levels become aligned in real time. Using visual motion as an example, we show that the model is neurally plausible, that it is consistent with evidence of extrapolation mechanisms throughout the visual hierarchy, that it predicts several known motion-position illusions in human observers, and that it provides a solution to the temporal binding problem.

Three-dimensional shape and velocity changes affect responses of a locust visual interneuron to approaching objects

Adaptive collision avoidance behaviours require accurate detection of complex spatiotemporal properties of an object approaching in an animal's natural, three-dimensional environment. Within the locust, the lobula giant movement detector and its postsynaptic partner, the descending contralateral movement detector (DCMD), respond robustly to images that emulate an approaching two-dimensional object and exhibit firing rate modulation correlated with changes in object trajectory. It is not known how this pathway responds to visual expansion of a three-dimensional object or an approaching object that changes velocity, both of which represent natural stimuli. We compared DCMD responses with images that emulate the approach of a sphere with those elicited by a two-dimensional disc. A sphere evoked later peak firing and decreased sensitivity to the ratio of the half size of the object to the approach velocity, resulting in an increased threshold subtense angle required to generate peak firing. We also presented locusts with an approaching sphere that decreased or increased in velocity. A velocity decrease resulted in transition-associated peak firing followed by a firing rate increase that resembled the response to a constant, slower velocity. A velocity increase resulted in an earlier increase in the firing rate that was more pronounced with an earlier transition. These results further demonstrate that this pathway can provide motor circuits for behaviour with salient information about complex stimulus dynamics.

Complex object motion represented by context-dependent correlated activity of visual interneurones

Accurate and adaptive encoding of complex, dynamic visual information is critical for the survival of many animals. Studies across a range of taxa have investigated behavioral and neuronal responses to objects that represent a threat, such as a looming object approaching along a direct collision course. By investigating neural mechanisms of avoidance behaviors through recording multineuronal activity, it is possible to better understand how complex visual information is represented in circuits that ultimately drive behaviors. We used multichannel electrodes to record from the well-studied locust nervous system to explore how object motion is reflected in activity of correlated neural activity. We presented locusts (Locusta migratoria) with objects that moved along one of 11 unique trajectories and recorded from descending interneurons within the ventral nerve cord. Spike sorting resulted in 405 discriminated units across 20 locusts and we found that 75% of the units responded to some form of object motion. Dimensionality reduction through principal component (PCA) and dynamic factor (DFA) analyses revealed population vector responses within individuals and common firing trends across the pool of discriminated units, respectively. Population vector composition (PCA) varied with the stimulus and common trends (DFA) showed unique tuning related to changes in the visual size and trajectory of the object through time. These findings demonstrate that this well-described collision detection system is more complex than previously envisioned and will drive future experiments to explore fundamental principles of how visual information is processed through context-dependent dynamic ensembles of neurons to initiate and control complex behavior.

A sublethal dose of a neonicotinoid insecticide disrupts visual processing and collision avoidance behaviour in Locusta migratoria

Neonicotinoids are known to affect insect navigation and vision, however the mechanisms of these effects are not fully understood. A visual motion sensitive neuron in the locust, the Descending Contralateral Movement Detector (DCMD), integrates visual information and is involved in eliciting escape behaviours. The DCMD receives coded input from the compound eyes and monosynaptically excites motorneurons involved in flight and jumping. We show that imidacloprid (IMD) impairs neural responses to visual stimuli at sublethal concentrations, and these effects are sustained two and twenty-four hours after treatment. Most significantly, IMD disrupted bursting, a coding property important for motion detection. Specifically, IMD reduced the DCMD peak firing rate within bursts at ecologically relevant doses of 10 ng/g (ng IMD per g locust body weight). Effects on DCMD firing translate to deficits in collision avoidance behaviours: exposure to 10 ng/g IMD attenuates escape manoeuvers while 100 ng/g IMD prevents the ability to fly and walk. We show that, at ecologically-relevant doses, IMD causes significant and lasting impairment of an important pathway involved with visual sensory coding and escape behaviours. These results show, for the first time, that a neonicotinoid pesticide directly impairs an important, taxonomically conserved, motion-sensitive visual network.

Interaction of compass sensing and object-motion detection in the locust central complex

Goal-directed behavior is often complicated by unpredictable events, such as the appearance of a predator during directed locomotion. This situation requires adaptive responses like evasive maneuvers followed by subsequent reorientation and course correction. Here we study the possible neural underpinnings of such a situation in an insect, the desert locust. As in other insects, its sense of spatial orientation strongly relies on the central complex, a group of midline brain neuropils. The central complex houses sky compass cells that signal the polarization plane of skylight and thus indicate the animal's steering direction relative to the sun. Most of these cells additionally respond to small moving objects that drive fast sensory-motor circuits for escape. Here we investigate how the presentation of a moving object influences activity of the neurons during compass signaling. Cells responded in one of two ways: in some neurons, responses to the moving object were simply added to the compass response that had adapted during continuous stimulation by stationary polarized light. By contrast, other neurons disadapted, i.e., regained their full compass response to polarized light, when a moving object was presented. We propose that the latter case could help to prepare for reorientation of the animal after escape. A neuronal network based on central-complex architecture can explain both responses by slight changes in the dynamics and amplitudes of adaptation to polarized light in CL columnar input neurons of the system.NEW & NOTEWORTHY Neurons of the central complex in several insects signal compass directions through sensitivity to the sky polarization pattern. In locusts, these neurons also respond to moving objects. We show here that during polarized-light presentation, responses to moving objects override their compass signaling or restore adapted inhibitory as well as excitatory compass responses. A network model is presented to explain the variations of these responses that likely serve to redirect flight or walking following evasive maneuvers.

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.

Background visual motion affects responses of an insect motion-sensitive neuron to objects deviating from a collision course

Stimulus complexity affects the response of looming sensitive neurons in a variety of animal taxa. The Lobula Giant Movement Detector/Descending Contralateral Movement Detector (LGMD/DCMD) pathway is well-characterized in the locust visual system. It responds to simple objects approaching on a direct collision course (i.e., looming) as well as complex motion defined by changes in stimulus velocity, trajectory, and transitions, all of which are affected by the presence or absence of background visual motion. In this study, we focused on DCMD responses to objects transitioning away from a collision course, which emulates a successful locust avoidance behavior. We presented each of 20 locusts with a sequence of complex three-dimensional visual stimuli in simple, scattered, and progressive flow field backgrounds while simultaneously recording DCMD activity extracellularly. DCMD responses to looming stimuli were generally characteristic irrespective of stimulus background. However, changing background complexity affected, peak firing rates, peak time, and caused changes in peak rise and fall phases. The DCMD response to complex object motion also varied with the azimuthal approach angle and the dynamics of object edge expansion. These data fit with an existing correlational model that relates expansion properties to firing rate modulation during trajectory changes.

Burst Firing in a Motion-Sensitive Neural Pathway Correlates with Expansion Properties of Looming Objects that Evoke Avoidance Behaviors

The locust visual system contains a well-defined motion-sensitive pathway that transfers visual input to motor centers involved in predator evasion and collision avoidance. One interneuron in this pathway, the descending contralateral movement detector (DCMD), is typically described as using rate coding; edge expansion of approaching objects causes an increased rate of neuronal firing that peaks after a certain retinal threshold angle is exceeded. However, evidence of intrinsic DCMD bursting properties combined with observable oscillations in mean firing rates and tight clustering of spikes in raw traces, suggest that bursting may be important for motion detection. Sensory neuron bursting provides important timing information about dynamic stimuli in many model systems, yet no studies have rigorously investigated if bursting occurs in the locust DCMD during object approach. We presented repetitions of 30 looming stimuli known to generate behavioral responses to each of 20 locusts in order to identify and quantify putative bursting activity in the DCMD. Overall, we found a bimodal distribution of inter-spike intervals (ISI) with peaks of more frequent and shorter ISIs occurring from 1–8 ms and longer less frequent ISIs occurring from 40–50 ms. Subsequent analysis identified bursts and isolated single spikes from the responses. Bursting frequency increased in the latter phase of an approach and peaked at the time of collision, while isolated spiking was predominant during the beginning of stimulus approach. We also found that the majority of inter-burst intervals (IBIs) occurred at 40–50 ms (or 20–25 bursts/s). Bursting also occurred across varied stimulus parameters and suggests that burst timing may be a key component of looming detection. Our findings suggest that the DCMD uses two modes of coding to transmit information about looming stimuli and that these modes change dynamically with a changing stimulus at a behaviorally-relevant time.

Background complexity affects response of a looming-sensitive neuron to object motion

An increasing number of studies show how stimulus complexity affects the responses of looming-sensitive neurons across multiple animal taxa. Locusts contain a well-described, descending motion-sensitive pathway that is preferentially looming sensitive. However, the lobula giant movement detector/descending contralateral movement detector (LGMD/DCMD) pathway responds to more than simple objects approaching at constant, predictable trajectories. In this study, we presented Locusta migratoria with a series of complex three-dimensional visual stimuli presented while simultaneously recording DCMD activity extracellularly. In addition to a frontal looming stimulus, we used a combination of compound trajectories (nonlooming transitioning to looming) presented at different velocities and onto a simple, scattered, or progressive flow field background. Regardless of stimulus background, DCMD responses to looming were characteristic and related to previously described effects of azimuthal approach angle and velocity of object expansion. However, increasing background complexity caused reduced firing rates, delayed peaks, shorter rise phases, and longer fall phases. DCMD responded to transitions to looming with a characteristic drop in a firing rate that was relatively invariant across most stimulus combinations and occurred regardless of stimulus background. Spike numbers were higher in the presence of the scattered background and reduced in the flow field background. We show that DCMD response time to a transition depends on unique expansion parameters of the moving stimulus irrespective of background complexity. Our results show how background complexity shapes DCMD responses to looming stimuli, which is explained within a behavioral context.

Escape response of the crab Neohelice to computer generated looming and translational visual danger stimuli

Historically, arthropod behavior has been considered to be a collection of simple, automaton-like routines commanded by domain-specific brain modules working independently. Nowadays, it is evident that the extensive behavioral repertoire of these animals and its flexibility necessarily imply far more complex abilities than originally assumed. For example, even what was thought to be a straightforward behavior of crabs, the escape response to visual danger stimuli, proved to involve a number of sequential stages, each of which implying decisions made on the bases of stimulus and contextual information. Inspired in previous observations on how the stimulus trajectory can affect the escape response of crabs in the field, we investigated the escape response to images of objects approaching directly toward the crab (looming stimuli: LS) or moving parallel to it (translational stimuli: TS) in the laboratory. Computer simulations of moving objects were effective to elicit escapes. LS evoked escapes with higher probability and intensity (speed and distance of escape) than TS, but responses started later. In addition to the escape run, TS also evoked a defensive response of the animal with its claws. Repeated presentations of TS or LS were both capable of inducing habituation. Results are discussed in connection with the possibilities offered by crabs to investigate the neural bases of behaviors occurring in the natural environment.

Individual pause-and-go motion is instrumental to the formation and maintenance of swarms of marching locust nymphs

The principal interactions leading to the emergence of order in swarms of marching locust nymphs was studied both experimentally, using small groups of marching locusts in the lab, and using computer simulations. We utilized a custom tracking algorithm to reveal fundamental animal-animal interactions leading to collective motion. Uncovering this behavior introduced a new agent-based modeling approach in which pause-and-go motion is pivotal. The behavioral and modeling findings are largely based on motion-related visual sensory inputs obtained by the individual locust. Results suggest a generic principle, in which intermittent animal motion can be considered as a sequence of individual decisions as animals repeatedly reassess their situation and decide whether or not to swarm. This interpretation implies, among other things, some generic characteristics regarding the build-up and emergence of collective order in swarms: in particular, that order and disorder are generic meta-stable states of the system, suggesting that the emergence of order is kinetic and does not necessarily require external environmental changes. This work calls for further experimental as well as theoretical investigation of the neural mechanisms underlying locust coordinative behavior.