Information theory and robotics meet to study predator-prey interactions

Lag and duration of leader-follower relationships in mixed traffic using causal inference

This study presents comprehensive analysis of car-following behavior on roads, utilizing Granger causality and transfer entropy techniques to enhance the validity of existing car-following models. It was found that most leader-follower relationships exhibit a delay in lateral movement by 4-5 s and last for short periods of around 3-5 s. These patterns are exhibited for all types of relationship found in the dataset, as well as for followers of all types. These findings imply that lateral movement reactions are governed by a different set of rules from braking and acceleration reactions, and the advantage in following lateral changes is short-lived. This also suggests that mixed traffic conditions may force drivers to slow down and calibrate reactions, as well as limiting the speed advantage gained by following a leader. Our methods were verified against random sampling as a method of selecting leader-follower pairs, decreasing the percent error in predicted speeds by 9.5% using the optimal velocity car-following model. The study concludes with a set of recommendations for future work, including the use of a diversity of car-following models for simulation and the use of causation entropy to distinguish between direct and indirect influences.

Entropy and Fractal Techniques for Monitoring Fish Behaviour and Welfare in Aquacultural Precision Fish Farming-A Review

In a non-linear system, such as a biological system, the change of the output (e.g., behaviour) is not proportional to the change of the input (e.g., exposure to stressors). In addition, biological systems also change over time, i.e., they are dynamic. Non-linear dynamical analyses of biological systems have revealed hidden structures and patterns of behaviour that are not discernible by classical methods. Entropy analyses can quantify their degree of predictability and the directionality of individual interactions, while fractal dimension (FD) analyses can expose patterns of behaviour within apparently random ones. The incorporation of these techniques into the architecture of precision fish farming (PFF) and intelligent aquaculture (IA) is becoming increasingly necessary to understand and predict the evolution of the status of farmed fish. This review summarizes recent works on the application of entropy and FD techniques to selected individual and collective fish behaviours influenced by the number of fish, tagging, pain, preying/feed search, fear/anxiety (and its modulation) and positive emotional contagion (the social contagion of positive emotions). Furthermore, it presents an investigation of collective and individual interactions in shoals, an exposure of the dynamics of inter-individual relationships and hierarchies, and the identification of individuals in groups. While most of the works have been carried out using model species, we believe that they have clear applications in PFF. The review ends by describing some of the major challenges in the field, two of which are, unsurprisingly, the acquisition of high-quality, reliable raw data and the construction of large, reliable databases of non-linear behavioural data for different species and farming conditions.

Ecology of fear in highly invasive fish revealed by robots

Invasive species threaten biodiversity and ecosystem functioning. We develop an innovative experimental approach, integrating biologically inspired robotics, time-series analysis, and computer vision, to build a detailed profile of the effects of non-lethal stress on the ecology and evolution of mosquitofish (Gambusia holbrooki)—a global pest. We reveal that brief exposures to a robotic predator alter mosquitofish behavior, increasing fear and stress responses, and mitigate the impact of mosquitofish on native tadpoles (Litoria moorei) in a cause-and-effect fashion. Effects of predation risk from the robot carry over to routine activity and feeding rate of mosquitofish weeks after exposure, resulting in weight loss, variation in body shape, and reduction in the fertility of both sexes—impairing survival, reproduction, and ecological success. We capitalize on evolved responses of mosquitofish to reduce predation risk—neglected in biological control practices—and provide scientific foundations for widespread use of state-of-the-art robotics in ecology and evolution research.

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Can robotic predators reveal the vulnerabilities of invasive and pest species?

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Our predator selectively targets invasive fish to protect native amphibians

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Stress from the robot compromises behavior, health, and reproduction of invaders

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We open new frontiers for robotics in ecology, evolution, and biocontrol research

Running away or running to? Do prey make decisions solely based on the landscape of fear or do they also include stimuli from a landscape of safety?

Predator-prey interactions are a key part of ecosystem function, and non-consumptive effects fall under the landscape of fear theory. Under the landscape of fear, the antipredator responses of prey are based on the spatial and temporal distribution of predatory cues in the environment. However, the aversive stimuli (fear) are not the only stimuli prey can utilize when making behavioral decisions. Prey might also be using attractive stimuli that represent safety to guide decision making. Using a novel, orthogonal design, we were able to spatially separate aversive and attractive stimuli to determine whether prey are utilizing safety cues to navigate their environment. Crayfish Faxonius rusticus were placed in the center of a behavioral arena. Aversive stimuli of either predatory bass Micropterus salmoides cues or conspecific alarm cues increased along the x-axis of the behavioral arena. Safety cues (shelters) increased along the y-axis by decreasing the number of shelter openings in this direction. Crayfish were allowed two phases to explore the arena: one without the fearful stimuli and one with the stimuli. Linear mixed models were conducted to determine whether movement behaviors and habitat utilization were affected by the phase of the trial and the type of aversive stimuli. Crayfish responded more strongly to alarm cues than to fear cues, with only alarm cues significantly impacting habitat utilization. When responding to alarm cues, crayfish used safety cues as well as fear cues to relocate themselves within the arena. Based on these results, we argue that crayfish utilize a landscape of safety in conjunction with a landscape of fear when navigating their environment.

Acute Citalopram administration modulates anxiety in response to the context associated with a robotic stimulus in zebrafish

BACKGROUND

Anxiety represents one of the most urgent health challenges in Western Countries, where it is associated with major medical and societal costs. A common therapeutic approach is the use of selective serotonin reuptake inhibitors, such as Citalopram. However, this treatment of choice is characterized by incomplete efficacy and potential side effects. Preclinical research is needed to detail the mechanisms underlying therapeutic efficacy of available treatments.

METHODS

Zebrafish, a rapidly emerging model species, constitutes an excellent candidate for high-throughput studies in behavioral pharmacology. Here, we present a robotics-based experimental paradigm to investigate the effects of acute Citalopram administration on conditioned place aversion. We trained adult subjects in a three-partitioned tank, consisting of one central and two lateral compartments: the latter were associated either with a fear eliciting robotic stimulus or with an empty environment. Following training, we implemented an automated three-dimensional tracking system to assess the spatial association and detail individual phenotype in a stimulus-free test session.

RESULTS

We observed a linear dose-response profile with respect to geotaxis, with increasing Citalopram concentrations reducing the tendency to swim near the bottom of the tank. Although control subjects failed to exhibit the predicted conditioned aversion, we found preliminary evidence that Citalopram may affect sexes differentially, with male subjects showing increased conditioned aversion at low Citalopram concentration.

CONCLUSIONS

Experimental paradigms based on robotics and three-dimensional tracking can contribute methodological advancements in zebrafish behavioral psychopharmacology.

Model-based feedback control of live zebrafish behavior via interaction with a robotic replica

The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.

Zebrafish exhibit associative learning for an aversive robotic stimulus

Zebrafish have quickly emerged as a species of choice in preclinical research, holding promise to advance the field of behavioral pharmacology through high-throughput experiments. Besides biological and heuristic considerations, zebrafish also constitute a fundamental tool that fosters the replacement of mammals with less sentient experimental subjects. Notwithstanding these features, experimental paradigms to investigate emotional and cognitive domains in zebrafish are still limited. Studies on emotional memories have provided sound methodologies to investigate fear conditioning in zebrafish, but these protocols may still benefit from a reconsideration of the independent variables adopted to elicit aversion. Here, we designed a fear-conditioning paradigm in which wild-type zebrafish were familiarized over six training sessions with an empty compartment and a fear-eliciting one. The fearful stimulus was represented by three zebrafish replicas exhibiting a fully synchronized and polarized motion as they were maneuvered along 3D trajectories by a robotic platform. When allowed to freely swim between the two compartments in the absence of the robotic stimulus (test session), zebrafish displayed a marked avoidance of the stimulus-paired one. To investigate whether fear conditioning was modulated by psychoactive compounds, two groups of zebrafish were administered ethanol (0.25% and 1.00%, ethanol/water, by volume) a few minutes before the test session. We observed that ethanol administration abolished the conditioned avoidance of the stimulus-paired compartment. Ultimately, this study confirms that robotic stimuli may be used in the design of fear-conditioning paradigms, which are sensitive to pharmacological manipulations.

Design and development of a robotic predator as a stimulus in conditioned place aversion for the study of the effect of ethanol and citalopram in zebrafish

Zebrafish are becoming a species of choice in psychopharmacology, laying a promising path to refined pharmacological manipulations and high-throughput behavioral phenotyping. The field of robotics has the potential to accelerate progress along this path, by offering unprecedented means for the design and development of accurate and reliable experimental stimuli. In this work, we demonstrate, for the first time, the integration of robotic predators in place conditioning experiments. We hypothesized zebrafish to be capable of forming a spatial association under a simulated predation risk. We repeatedly exposed experimental subjects to a robotic heron impacting the water surface and then evaluated their spatial avoidance within the experimental tank in a subsequent predator-free test session. To pharmacologically validate the paradigm, we tested zebrafish in drug-free conditions (control groups) or in response to three different concentrations of citalopram (30, 50, and 100 mg/L) and ethanol (0.25, 0.50, and 1.00%). Experimental data indicate that, when tested in the absence of the conditioning stimulus, zebrafish displayed a marked preference for the bottom of the test tank, that is, the farthest location from the simulated attacks by the robotic heron. This conditioned geotaxis was reduced by the administration of citalopram in a linear dose-response curve and ethanol at the low concentration. Ultimately, our data demonstrate that robotic stimuli may represent valid conditioning tools and, thereby, aid the field of zebrafish psychopharmacology.

Application of symbolic recurrence to experimental data, from firearm prevalence to fish swimming

Recurrence plots and recurrence quantification analysis are powerful tools to study the behavior of dynamical systems. What we learn through these tools is typically determined by the choice of a distance threshold in the phase space, which introduces arbitrariness in the definition of recurrence. Not only does symbolic recurrence overcome this difficulty, but also it offers a richer representation that book-keeps the recurrent portions of the phase space. Using symbolic recurrences, we can construct recurrence plots, perform quantification analysis, and examine causal links between dynamical systems from their time-series. Although previous efforts have demonstrated the feasibility of such a symbolic framework on synthetic data, the study of real time-series remains elusive. Here, we seek to bridge this gap by systematically examining a wide range of experimental datasets, from firearm prevalence and media coverage in the United States to the effect of sex on the interaction of swimming fish. This work offers a compelling demonstration of the potential of symbolic recurrence in the study of real-world applications across different research fields while providing a computer code for researchers to perform their own time-series explorations.

Behavioural and life-history responses of mosquitofish to biologically inspired and interactive robotic predators

Invasive alien species threaten biodiversity worldwide and contribute to biotic homogenization, especially in freshwaters, where the ability of native animals to disperse is limited. Robotics may offer a promising tool to address this compelling problem, but whether and how invasive species can be negatively affected by robotic stimuli is an open question. Here, we explore the possibility of modulating behavioural and life-history responses of mosquitofish by varying the degree of biomimicry of a robotic predator, whose appearance and locomotion are inspired by natural mosquitofish predators. Our results support the prediction that real-time interactions at varying swimming speeds evoke a more robust antipredator response in mosquitofish than simpler movement patterns by the robot, especially in individuals with better body conditions that are less prone to take risks. Through an information-theoretic analysis of animal-robot interactions, we offer evidence in favour of a causal link between the motion of the robotic predator and a fish antipredator response. Remarkably, we observe that even a brief exposure to the robotic predator of 15 min per week is sufficient to erode energy reserves and compromise the body condition of mosquitofish, opening the door for future endeavours to control mosquitofish in the wild.

Zebrafish Adjust Their Behavior in Response to an Interactive Robotic Predator

Zebrafish (Danio rerio) constitutes a valuable experimental species for the study of the biological determinants of emotional responses, such as fear and anxiety. Fear-related test paradigms traditionally entail the interaction between focal subjects and live predators, which may show inconsistent behavior throughout the experiment. To address this technical challenge, robotic stimuli are now frequently integrated in behavioral studies, yielding repeatable, customizable, and controllable experimental conditions. While most of the research has focused on open-loop control where robotic stimuli are preprogrammed to execute a priori known actions, recent work has explored the possibility of two-way interactions between robotic stimuli and live subjects. Here, we demonstrate a "closed-loop control" system to investigate fear response of zebrafish in which the response of the robotic stimulus is determined in real-time through a finite-state Markov chain constructed from independent observations on the interactions between zebrafish and their predator. Specifically, we designed a 3D-printed robotic replica of the zebrafish allopatric predator red tiger Oscar fish (Astronotus ocellatus), instrumented to interact in real-time with live subjects. We investigated the role of closed-loop control in modulating fear response in zebrafish through the analysis of the focal fish ethogram and the information-theoretic quantification of the interaction between the subject and the replica. Our results indicate that closed-loop control elicits consistent fear response in zebrafish and that zebrafish quickly adjust their behavior to avoid the predator's attacks. The augmented degree of interactivity afforded by the Markov-chain-dependent actuation of the replica constitutes a fundamental advancement in the study of animal-robot interactions and offers a new means for the development of experimental paradigms to study fear.

Detecting intermittent switching leadership in coupled dynamical systems

Leader-follower relationships are commonly hypothesized as a fundamental mechanism underlying collective behaviour in many biological and physical systems. Understanding the emergence of such behaviour is relevant in science and engineering to control the dynamics of complex systems toward a desired state. In prior works, due in part to the limitations of existing methods for dissecting intermittent causal relationships, leadership is assumed to be consistent in time and space. This assumption has been contradicted by recent progress in the study of animal behaviour. In this work, we leverage information theory and time series analysis to propose a novel and simple method for dissecting changes in causal influence. Our approach computes the cumulative influence function of a given individual on the rest of the group in consecutive time intervals and identify change in the monotonicity of the function as a change in its leadership status. We demonstrate the effectiveness of our approach to dissect potential changes in leadership on self-propelled particles where the emergence of leader-follower relationship can be controlled and on tandem flights of birds recorded in their natural environment. Our method is expected to provide a novel methodological tool to further our understanding of collective behaviour.

Symbolic dynamics of animal interaction

Since its introduction nearly two decades ago, transfer entropy has contributed to an improved understanding of cause-and-effect relationships in coupled dynamical systems from raw time series. In the context of animal behavior, transfer entropy might help explain the determinants of leadership in social groups and elucidate escape response to predator attacks. Despite its promise, the potential of transfer entropy in animal behavior is yet to be fully tested, and a number of technical challenges in information theory and statistics remain open. Here, we examine an alternative approach to the computation of transfer entropy based on symbolic dynamics. In this context, a symbol is associated with a specific locomotory bout across two or more consecutive time instants, such as reversing the swimming direction. Symbols encapsulate salient locomotory patterns and the associated permutation transfer entropy quantifies the ability to predict the patterns of an individual given those of another individual. We demonstrate this framework on an existing dataset on fish, for which we have knowledge of the underlying cause-and-effect relationship between the focal subject and the stimulus. Symbolic dynamics offers an intuitive and robust approach to study animal behavior, which could enable the inference of causal relationship from noisy experimental observations of limited duration.