Closed-loop control of zebrafish behaviour in three dimensions using a robotic stimulus

Proactivity of fish and leadership of self-propelled robotic fish during interaction

Fish interacting with biomimetic robotic fish is beneficial for animal behavior research, particularly in the study of collective behavior. Compared with passive-dragging robotic fish, self-propelled robotic fish floats in water, and its movement matches the flow field formed by the caudal fin oscillation, leading to more realistic interaction with animals. In this paper, we propose a self-propelled koi-mimicking robotic fish entity, develop a system for robotic fish and koi fish interaction, and conduct extensive experiments on quantity variation and parameter variation. The results showed that fish exhibited significantly lower proactivity when alone, and the most proactive case is one robotic fish interacting with two real fish. The experiments on parameter variation indicated that fish may respond more proactivity to robotic fish that swim with high frequency and low amplitude, but may also move together with high-frequency and high-amplitude swimming robotic fish. These findings could provide insights into fish collective behavior, guide the design of further fish-robot interaction experiments, and suggest directions for future improvements in goal-oriented robotic fish platforms.

[Design and preliminary application of outdoor flying pigeon-robot]

Control at beyond-visual ranges is of great significance to animal-robots with wide range motion capability. For pigeon-robots, such control can be done by the way of onboard preprogram, but not constitute a closed-loop yet. This study designed a new control system for pigeon-robots, which integrated the function of trajectory monitoring to that of brain stimulation. It achieved the closed-loop control in turning or circling by estimating pigeons' flight state instantaneously and the corresponding logical regulation. The stimulation targets located at the formation reticularis medialis mesencephali (FRM) in the left and right brain, for the purposes of left- and right-turn control, respectively. The stimulus was characterized by the waveform mimicking the nerve cell membrane potential, and was activated intermittently. The wearable control unit weighted 11.8 g totally. The results showed a 90% success rate by the closed-loop control in pigeon-robots. It was convenient to obtain the wing shape during flight maneuver, by equipping a pigeon-robot with a vivo camera. It was also feasible to regulate the evolution of pigeon flocks by the pigeon-robots at different hierarchical level. All of these lay the groundwork for the application of pigeon-robots in scientific researches.

Naïve individuals promote collective exploration in homing pigeons

Group-living animals that rely on stable foraging or migratory routes can develop behavioural traditions to pass route information down to inexperienced individuals. Striking a balance between exploitation of social information and exploration for better alternatives is essential to prevent the spread of maladaptive traditions. We investigated this balance during cumulative route development in the homing pigeon Columba livia. We quantified information transfer within pairs of birds in a transmission-chain experiment and determined how birds with different levels of experience contributed to the exploration-exploitation trade-off. Newly introduced naïve individuals were initially more likely to initiate exploration than experienced birds, but the pair soon settled into a pattern of alternating leadership with both birds contributing equally. Experimental pairs showed an oscillating pattern of exploration over generations that might facilitate the discovery of more efficient routes. Our results introduce a new perspective on the roles of leadership and information pooling in the context of collective learning.

Archerfish respond to a hunting robotic conspecific

While the unique hunting behavior of archerfish has received considerable scientific attention, the specific social cues that govern behaviors like intraspecific kleptoparasitism in the species are less understood. This paper asks whether the use of a robotic facsimile representing an archerfish can elicit a social response if it approximates an archerfish's appearance, along with key features of its hunting behavior. We found that the fish respond to the robot when it hunted, as indicated by decreasing distances between the robot and fish (and among the fish) during the robot's hunting behavior sequence, as well as higher net transfer entropy when the robot was hunting. These effects were present even when the robot's "hunt" was unproductive and did not result in food. The temporal pattern of fish approach to the robot and each other indicated that the segment of robot hunting behavior proximal to the robotic facsimile shot elicited fish behavior initially. However, earlier cues in the robot's hunting sequence became important following more experience with a food contingency. This indicates that further studies could use a robotic facsimile to conduct a detailed stimulus analysis, changing aspects of the robot's appearance and behavior to uncover the basic mechanisms of information transfer among individuals in a social hunting scenario.

Steps towards a computational ethology: an automatized, interactive setup to investigate filial imprinting and biological predispositions

Soon after hatching, the young of precocial species, such as domestic chicks or ducklings, learn to recognize their social partner by simply being exposed to it (imprinting process). Even artificial objects or stimuli displayed on monitor screens can effectively trigger filial imprinting, though learning is canalized by spontaneous preferences for animacy signals, such as certain kinds of motion or a face-like appearance. Imprinting is used as a behavioural paradigm for studies on memory formation, early learning and predispositions, as well as number and space cognition, and brain asymmetries. Here, we present an automatized setup to expose and/or test animals for a variety of imprinting experiments. The setup consists of a cage with two high-frequency screens at the opposite ends where stimuli are shown. Provided with a camera covering the whole space of the cage, the behaviour of the animal is recorded continuously. A graphic user interface implemented in Matlab allows a custom configuration of the experimental protocol, that together with Psychtoolbox drives the presentation of images on the screens, with accurate time scheduling and a highly precise framerate. The setup can be implemented into a complete workflow to analyse behaviour in a fully automatized way by combining Matlab (and Psychtoolbox) to control the monitor screens and stimuli, DeepLabCut to track animals' behaviour, Python (and R) to extract data and perform statistical analyses. The automated setup allows neuro-behavioural scientists to perform standardized protocols during their experiments, with faster data collection and analyses, and reproducible results.

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.

Opposite valence social information provided by bio-robotic demonstrators shapes selection processes in the green bottle fly

Social learning represents a high-level complex process to acquire information about the environment, which is increasingly reported in invertebrates. The animal-robot interaction paradigm turned out to be an encouraging strategy to unveil social learning in vertebrates, but it has not been fully exploited in invertebrates. In this study, Lucilia sericata adults were induced to observe bio-robotic conspecific and predator demonstrators to reproduce different flower foraging choices. Can a fly manage two flows of social information with opposite valence? Herein, we attempt a reply. The selection process of L. sericata was affected by social information provided through different bio-robotic demonstrators, by avoiding coloured discs previously visited by a bio-robotic predator and preferring coloured discs previously visited by a bio-robotic conspecific. When both bio-robotic demonstrators visited the same disc, the latency duration increased and the flies significantly tended to avoid this disc. This indicates the complex risk-benefit evaluation process carried out by L. sericata during the acquisition of such social information. Overall, this article provides a unique perspective on the behavioural ecology of social learning in non-social insects; it also highlights the high potential of the animal-robot interaction approach for unveiling the full spectrum of invertebrates' abilities in using social information.

Zebrafish Neighbor Distance Changes Relative to Conspecific Size, Position in the Water Column, and the Horizon: A Video-Playback Experiment

Many fish form schools and maintain visual contact with their neighbors in a three-dimensional environment. In this study, we assessed whether zebrafish modified their spacing and interaction time in an additive or multiplicative way relative to multiple sources of social information using computer animations. We simultaneously manipulated: (a) the size of the virtual conspecific (as a proxy of social cue magnitude), (b) the position of the virtual conspecific in the water column (as a proxy of the level of perceived risk), and (c) the absence/presence of the visual horizon (as a proxy of depth perception). We found that the size of the virtual conspecific independently affected spacing behavior (zebrafish increased their separation distance as conspecific size increased). However, some of these factors interacted significantly, such that their effects on social behavior depended on each other. For instance, zebrafish increased their separation distance under high risk conditions when the virtual conspecific was larger, but this risk effect disappeared when the conspecific was the same size or smaller, likely to avoid aggression. Also, zebrafish increased their separation distance when depth perception was enhanced under low risk conditions, but the effect of depth perception disappeared under high risk conditions. Overall, we found that certain dimensions of the visual social environment affected zebrafish spacing behavior in different ways, but they did not affect social interaction time. We discuss the implications of these findings for the spatial organization of fish schools.

Behavioral Teleporting of Individual Ethograms onto Inanimate Robots: Experiments on Social Interactions in Live Zebrafish

Social behavior is widespread in the animal kingdom, and it remarkably influences human personal and professional lives. However, a thorough understanding of the mechanisms underlying social behavior is elusive. Integrating the seemingly different fields of robotics and preclinical research could bring new insight on social behavior. Toward this aim, we established "behavioral teleporting" as an experimental solution to independently manipulate multiple factors underpinning social interactions. Behavioral teleporting consists of real-time transfer of the complete ethogram of a live zebrafish onto a remotely-located robotic replica. Through parallel and simultaneous behavioral teleporting, we studied the interaction between two live fish swimming in remotely-located tanks: each live fish interacted with an inanimate robot that mirrored the behavior of the other fish, and the morphology of each robot was independently tailored. Our results indicate that behavioral teleporting can preserve natural interaction between two live animals, while allowing fine control over morphological features that modulate social behavior.

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.

Revealing the structure of information flows discriminates similar animal social behaviors

Behavioral correlations stretching over time are an essential but often neglected aspect of interactions among animals. These correlations pose a challenge to current behavioral-analysis methods that lack effective means to analyze complex series of interactions. Here we show that non-invasive information-theoretic tools can be used to reveal communication protocols that guide complex social interactions by measuring simultaneous flows of different types of information between subjects. We demonstrate this approach by showing that the tandem-running behavior of the ant Temnothorax rugatulus and that of the termites Coptotermes formosanus and Reticulitermes speratus are governed by different communication protocols. Our discovery reconciles the diverse ultimate causes of tandem running across these two taxa with their apparently similar signaling mechanisms. We show that bidirectional flow of information is present only in ants and is consistent with the use of acknowledgement signals to regulate the flow of directional information.

Real-Time Selective Markerless Tracking of Forepaws of Head Fixed Mice Using Deep Neural Networks

Here, we describe a system capable of tracking specific mouse paw movements at high frame rates (70.17 Hz) with a high level of accuracy (mean = 0.95, SD < 0.01). Short-latency markerless tracking of specific body parts opens up the possibility of manipulating motor feedback. We present a software and hardware scheme built on DeepLabCut—a robust movement-tracking deep neural network framework—which enables real-time estimation of paw and digit movements of mice. Using this approach, we demonstrate movement-generated feedback by triggering a USB-GPIO (general-purpose input/output)-controlled LED when the movement of one paw, but not the other, selectively exceeds a preset threshold. The mean time delay between paw movement initiation and LED flash was 44.41 ms (SD = 36.39 ms), a latency sufficient for applying behaviorally triggered feedback. We adapt DeepLabCut for real-time tracking as an open-source package we term DeepCut2RealTime. The ability of the package to rapidly assess animal behavior was demonstrated by reinforcing specific movements within water-restricted, head-fixed mice. This system could inform future work on a behaviorally triggered “closed loop” brain–machine interface that could reinforce behaviors or deliver feedback to brain regions based on prespecified body movements.

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system

The objective of this study is to integrate biomimetic robots into small groups of zebrafish and to modulate their collective behaviours. A possible approach is to have the robots behave like sheepdogs. In this case, the robots would behave like a different species than the fish and would present different relevant behaviours. In this study, we explore different strategies that use biomimetic zebrafish behaviours. In past work, we have shown that robots biomimicking zebrafish can be socially integrated into zebrafish groups. We have also shown that a fish-like robot can modulate the rotation choice of zebrafish groups in a circular set-up. Here, we further study the modulation capabilities of such robots in a more complex set-up. To do this, we exploit zebrafish social behaviours we identified in previous studies. We first modulate collective departure by replicating the leadership mechanisms with the robot in a set-up composed of two rooms connected by a corridor. Then, we test different behavioural strategies to drive the fish groups towards a predefined target room. To drive the biohybrid groups towards a predefined choice, they have to adopt some specific fish-like behaviours. The first strategy is based on a single robot using the initiation behaviour. In this case, the robot keeps trying to initiate a group transition towards the target room. The second strategy is based on two robots, one initiating and one staying in the target room as a social attractant. The third strategy is based on a single robot behaving like a zebrafish but staying in the target room as a social attractant. The fourth strategy uses two robots behaving like zebrafish but staying in the target room. We conclude that robots can modulate zebrafish group behaviour by adopting strategies based on existing fish behaviours. Under these conditions, robots enable the testing of hypotheses about the behaviours of fish.

Guppies Prefer to Follow Large (Robot) Leaders Irrespective of Own Size

Body size is often assumed to determine how successfully an individual can lead others with larger individuals being better leaders than smaller ones. But even if larger individuals are more readily followed, body size often correlates with specific behavioral patterns and it is thus unclear whether larger individuals are more often followed than smaller ones because of their size or because they behave in a certain way. To control for behavioral differences among differentially-sized leaders, we used biomimetic robotic fish (Robofish) of different sizes. Live guppies (Poecilia reticulata) are known to interact with Robofish in a similar way as with live conspecifics. Consequently, Robofish may serve as a conspecific-like leader that provides standardized behaviors irrespective of its size. We asked whether larger Robofish leaders are preferentially followed and whether the preferences of followers depend on own body size or risk-taking behavior ("boldness"). We found that live female guppies followed larger Robofish leaders in closer proximity than smaller ones and this pattern was independent of the followers' own body size as well as risk-taking behavior. Our study shows a "bigger is better" pattern in leadership that is independent of behavioral differences among differentially-sized leaders, followers' own size and risk-taking behavior.

Open-source five degree of freedom motion platform for investigating fish-robot interaction

This paper presents the design, construction, operation, and validation of a robotic gantry platform specifically designed for studying fish-robot interaction. The platform has five degrees of freedom to manipulate the three-dimensional position, yaw angle, and the pitch of a lure. Additionally, it has a four-conductor slip ring that allows power and data to be transmitted to the lure for the operation of fins and other actuators that increase realism or act as stimuli to focal fish during an ethorobotic experiment. The design is open-source, low-cost, and includes purpose-built electronics, software, and hardware to make it extensible and customizable for a number of applications with varying requirements.

Decoding collective communications using information theory tools

Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.

Improving on transfer entropy-based network reconstruction using time-delays: Approach and validation

Transfer entropy constitutes a viable model-free tool to infer causal relationships between two dynamical systems from their time-series. In an information-theoretic sense, transfer entropy associates a cause-and-effect relationship with directed information transfer, such that one may improve the prediction of the future of a dynamical system from the history of another system. Recent studies have proposed the use of transfer entropy to reconstruct networks, but the inherent dyadic nature of this metric challenges the development of a robust approach that can discriminate direct from indirect interactions between nodes. In this paper, we seek to fill this methodological gap through the cogent integration of time-delays in the transfer entropy computation. By recognizing that information transfer in the network is bound by a finite speed, we relate the value of the time-delayed transfer entropy between two nodes to the number of walks between them. Upon this premise, we lay out the foundation of an alternative framework for network reconstruction, which we illustrate through closed-form results on three-node networks and numerically validate on larger networks, using examples of Boolean models and chaotic maps.

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.

Real-time contextual feedback for close-loop control of navigation

OBJECTIVE

Close-loop control of brain and behavior will benefit from real-time detection of behavioral events to enable low-latency communication with peripheral devices. In animal experiments, this is typically achieved by using sparsely distributed (embedded) sensors that detect animal presence in select regions of interest. High-speed cameras provide high-density sampling across large arenas, capturing the richness of animal behavior, however, the image processing bottleneck prohibits real-time feedback in the context of rapidly evolving behaviors.

APPROACH

Here we developed an open-source software, named PolyTouch, to track animal behavior in large arenas and provide rapid close-loop feedback in ~5.7 ms, ie. average latency from the detection of an event to analog stimulus delivery, e.g. auditory tone, TTL pulse, when tracking a single body. This stand-alone software is written in JAVA. The included wrapper for MATLAB provides experimental flexibility for data acquisition, analysis and visualization.

MAIN RESULTS

As a proof-of-principle application we deployed the PolyTouch for place awareness training. A user-defined portion of the arena was used as a virtual target; visit (or approach) to the target triggered auditory feedback. We show that mice develop awareness to virtual spaces, tend to stay shorter and move faster when they reside in the virtual target zone if their visits are coupled to relatively high stimulus intensity (⩾49 dB). Thus, close-loop presentation of perceived aversive feedback is sufficient to condition mice to avoid virtual targets within the span of a single session (~20 min).

SIGNIFICANCE

Neuromodulation techniques now allow control of neural activity in a cell-type specific manner in spiking resolution. Using animal behavior to drive closed-loop control of neural activity would help to address the neural basis of behavioral state and environmental context-dependent information processing in the brain.

Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio

Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed groups of sensor-rich robots and animals and study collective interactions from the within a bio-hybrid group. In recent work, scientists showed that a robot-controlled lure is capable of influencing the collective decisions of zebrafish Danio rerio shoals moving in a ring and a two-room setup. Here, we study a closely related topic, that is, the collective behavior patterns that emerge when different behavioral models are reproduced through the use of a robotic lure. We design a behavioral model that alternates between obeying and disobeying the collective motion decisions in order to become socially accepted by the shoal members. Subsequently, we compare it against two extreme cases: a reactive and an imposing decision model. For this, we use spatial, directional and information theoretic metrics to measure the degree of integration of the robotic agent. We show that our model leads to similar information flow as in freely roaming shoals of zebrafish and exhibits leadership skills more often than the open-loop models. Thus, in order for the robot to achieve higher degrees of integration in the zebrafish shoal, it must, like any other shoal member, be bidirectionally involved in the decision making process. These findings provide insight on the ability to form mixed societies of animals and robots and yield promising results on the degree to which a robot can influence the collective decision making.

A Comparison of Individual Learning and Social Learning in Zebrafish Through an Ethorobotics Approach

Social learning is ubiquitous across the animal kingdom, where animals learn from group members about predators, foraging strategies, and so on. Despite its prevalence and adaptive benefits, our understanding of social learning is far from complete. Here, we study observational learning in zebrafish, a popular animal model in neuroscience. Toward fine control of experimental variables and high consistency across trials, we developed a novel robotics-based experimental test paradigm, in which a robotic replica demonstrated to live subjects the correct door to join a group of conspecifics. We performed two experimental conditions. In the individual training condition, subjects learned the correct door without the replica. In the social training condition, subjects observed the replica approaching both the incorrect door, to no effect, and the correct door, which would open after spending enough time close to it. During these observations, subjects could not actively follow the replica. Zebrafish increased their preference for the correct door over the course of 20 training sessions, but we failed to identify evidence of social learning, whereby we did not register significant differences in performance between the individual and social training conditions. These results suggest that zebrafish may not be able to learn a route by observation, although more research comparing robots to live demonstrators is needed to substantiate this claim.

Transfer entropy on symbolic recurrences

Recurrence quantification analysis offers a powerful framework to investigate complexity in dynamical systems. While several studies have demonstrated the possibility of multivariate recurrence quantification analysis, information-theoretic tools for the discovery of causal links remain elusive. Particularly enticing is to formulate information-theoretic tools on symbolic recurrence plots, which alleviate some of the methodological challenges of traditional recurrence plots and offer a richer representation of recurrences. Toward this aim, we establish a probability space in which we ground a theory of information that encodes information in the recurrences of the symbols. We introduce transfer entropy on symbolic recurrences as a tool to guide the inference of the strength and direction of the interaction between dynamical systems. We demonstrate statistically reliable discovery of causal links on synthetic and experimental time series, from only two time series or a larger dataset with multiple realizations. The proposed approach brings together recurrence plots, information theory, and symbolic dynamics to empower researchers and practitioners with effective means to visualize and quantify interactions in dynamical systems.

A review on animal-robot interaction: from bio-hybrid organisms to mixed societies

Living organisms are far superior to state-of-the-art robots as they have evolved a wide number of capabilities that far encompass our most advanced technologies. The merging of biological and artificial world, both physically and cognitively, represents a new trend in robotics that provides promising prospects to revolutionize the paradigms of conventional bio-inspired design as well as biological research. In this review, a comprehensive definition of animal-robot interactive technologies is given. They can be at animal level, by augmenting physical or mental capabilities through an integrated technology, or at group level, in which real animals interact with robotic conspecifics. Furthermore, an overview of the current state of the art and the recent trends in this novel context is provided. Bio-hybrid organisms represent a promising research area allowing us to understand how a biological apparatus (e.g. muscular and/or neural) works, thanks to the interaction with the integrated technologies. Furthermore, by using artificial agents, it is possible to shed light on social behaviours characterizing mixed societies. The robots can be used to manipulate groups of living organisms to understand self-organization and the evolution of cooperative behaviour and communication.

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.

The Olfactory System of Zebrafish as a Model for the Study of Neurotoxicity and Injury: Implications for Neuroplasticity and Disease

The olfactory system, composed of the olfactory organs and the olfactory bulb, allows organisms to interact with their environment and through the detection of odor signals. Olfaction mediates behaviors pivotal for survival, such as feeding, mating, social behavior, and danger assessment. The olfactory organs are directly exposed to the milieu, and thus are particularly vulnerable to damage by environmental pollutants and toxicants, such as heavy metals, pesticides, and surfactants, among others. Given the widespread occurrence of olfactory toxicants, there is a pressing need to understand the effects of these harmful compounds on olfactory function. Zebrafish (Danio rerio) is a valuable model for studying human physiology, disease, and toxicity. Additionally, the anatomical components of the zebrafish olfactory system are similar to those of other vertebrates, and they present a remarkable degree of regeneration and neuroplasticity, making it an ideal model for the study of regeneration, reorganization and repair mechanisms following olfactory toxicant exposure. In this review, we focus on (1) the anatomical, morphological, and functional organization of the olfactory system of zebrafish; (2) the adverse effects of olfactory toxicants and injury to the olfactory organ; and (3) remodeling and repair neuroplasticity mechanisms following injury and degeneration by olfactory toxicant exposure.

Robots mediating interactions between animals for interspecies collective behaviors

Self-organized collective behavior has been analyzed in diverse types of gregarious animals. Such collective intelligence emerges from the synergy between individuals, which behave at their own time and spatial scales and without global rules. Recently, robots have been developed to collaborate with animal groups in the pursuit of better understanding their decision-making processes. These biohybrid systems make cooperative relationships between artificial systems and animals possible, which can yield new capabilities in the resulting mixed group. However, robots are currently tailor-made to successfully engage with one animal species at a time. This limits the possibilities of introducing distinct species-dependent perceptual capabilities and types of behaviors in the same system. Here, we show that robots socially integrated into animal groups of honeybees and zebrafish, each one located in a different city, allowing these two species to interact. This interspecific information transfer is demonstrated by collective decisions that emerge between the two autonomous robotic systems and the two animal groups. The robots enable this biohybrid system to function at any distance and operates in water and air with multiple sensorimotor properties across species barriers and ecosystems. These results demonstrate the feasibility of generating and controlling behavioral patterns in biohybrid groups of multiple species. Such interspecies connections between diverse robotic systems and animal species may open the door for new forms of artificial collective intelligence, where the unrivaled perceptual capabilities of the animals and their brains can be used to enhance autonomous decision-making, which could find applications in selective "rewiring" of ecosystems.

Iterative subtraction facilitates automated, quantitative analysis of multiple pollen tube growth features

In flowering plants, successful reproduction and generation of seed depends on the delivery of immotile sperm to female gametes via the pollen tube. As reproduction in flowering plants is the cornerstone of our agricultural industry, there is a need to uncover the genes, small molecules, and environmental conditions that affect pollen tube growth dynamics. However, methods for measuring pollen tube phenotypes are labor intensive, and suffer from a tradeoff between workload and resolution. To approach these problems, we use an image analysis technique called Automated Stack Iterative Subtraction (ASIST). Our tool converts growing pollen tube tips into closed particles, making the automated simultaneous extraction of multiple pollen tube phenotypes from hundreds of individual cells tractable via existing particle identification technology. Here we use our tool to analyze growth dynamics of pollen tubes in vitro, and semi in vivo. We show that ASIST provides a framework for robust, high throughput analysis of pollen tube growth behaviors in populations of cells, thus facilitating pollen tube phenomics.

Aggregating behaviour in invasive Caribbean lionfish is driven by habitat complexity

Caribbean lionfish (Pterois spp.) are considered the most heavily impacting invasive marine vertebrate ever recorded. However, current management is largely inadequate, relying on opportunistic culling by recreational SCUBA divers. Culling efficiency could be greatly improved by exploiting natural aggregations, but to date this behaviour has only been recorded anecdotally, and the drivers are unknown. We found aggregations to be common in situ, but detected no conspecific attraction through visual or olfactory cues in laboratory experiments. Aggregating individuals were on average larger, but showed no further differences in morphology or life history. However, using visual assessments and 3D modelling we show lionfish prefer broad-scale, but avoid fine-scale, habitat complexity. We therefore suggest that lionfish aggregations are coincidental based on individuals’ mutual attraction to similar reef structure to maximise hunting efficiency. Using this knowledge, artificial aggregation devices might be developed to concentrate lionfish densities and thus improve culling efficiency.

Encoding lateralization of jump kinematics and eye use in a locust via bio-robotic artifacts

The effect of previous exposure to lateral sensory stimuli in shaping the response to subsequent symmetric stimuli represents an important overlooked issue in neuroethology, with special reference to arthropods. In this research, we investigated the hypothesis to 'programme' jumping escape direction as well as surveillance orientation in young and adult individuals of Locusta migratoria as an adaptive consequence of prior exposure to directional-biased predator approaches generated by a robotic leopard gecko representing Eublepharis macularius The manipulation of the jumping escape direction was successfully achieved in young locusts, although young L. migratoria did not exhibit innately lateralized jumping escapes. Jumping escape direction was also successfully manipulated in adult locusts, which exhibited innate lateralized jumping escape at the individual level. The innate lateralization of each instar of L. migratoria in using a preferential eye during surveillance was not affected by prior lateralized exposure to the robotic gecko. Our results indicate a high plasticity of the escape motor outputs that are occurring almost in real time with the perceived stimuli, making them greatly adaptable and compliant to environmental changes in order to be effective and reliable. In addition, surveillance lateralization innately occurs at population level in each instar of L. migratoria Therefore, its low forgeability by environmental factors would avoid disorganization at swarm level and improve swarm coordination during group tasks. These findings are consistent with the fact that, as in vertebrates, in insects the right hemisphere is specialized in controlling fear and escape functions.

Closed-Loop Control of Active Sensing Movements Regulates Sensory Slip

Active sensing involves the production of motor signals for the purpose of acquiring sensory information [1-3]. The most common form of active sensing, found across animal taxa and behaviors, involves the generation of movements-e.g., whisking [4-6], touching [7, 8], sniffing [9, 10], and eye movements [11]. Active sensing movements profoundly affect the information carried by sensory feedback pathways [12-15] and are modulated by both top-down goals (e.g., measuring weight versus texture [1, 16]) and bottom-up stimuli (e.g., lights on or off [12]), but it remains unclear whether and how these movements are controlled in relation to the ongoing feedback they generate. To investigate the control of movements for active sensing, we created an experimental apparatus for freely swimming weakly electric fish, Eigenmannia virescens, that modulates the gain of reafferent feedback by adjusting the position of a refuge based on real-time videographic measurements of fish position. We discovered that fish robustly regulate sensory slip via closed-loop control of active sensing movements. Specifically, as fish performed the task of maintaining position inside the refuge [17-22], they dramatically up- or downregulated fore-aft active sensing movements in relation to a 4-fold change of experimentally modulated reafferent gain. These changes in swimming movements served to maintain a constant magnitude of sensory slip. The magnitude of sensory slip depended on the presence or absence of visual cues. These results indicate that fish use two controllers: one that controls the acquisition of information by regulating feedback from active sensing movements and another that maintains position in the refuge, a control structure that may be ubiquitous in animals [23, 24].

Using a robotic fish to investigate individual differences in social responsiveness in the guppy

Responding towards the actions of others is one of the most important behavioural traits whenever animals of the same species interact. Mutual influences among interacting individuals may modulate the social responsiveness seen and thus make it often difficult to study the level and individual variation in responsiveness. Here, open-loop biomimetic robots that provide standardized, non-interactive social cues can be a useful tool. These robots are not affected by the live animal's actions but are assumed to still represent valuable and biologically relevant social cues. As this assumption is crucial for the use of biomimetic robots in behavioural studies, we hypothesized (i) that meaningful social interactions can be assumed if live animals maintain individual differences in responsiveness when interacting with both a biomimetic robot and a live partner. Furthermore, to study the level of individual variation in social responsiveness, we hypothesized (ii) that individual differences should be maintained over the course of multiple tests with the robot. We investigated the response of live guppies (Poecilia reticulata) when allowed to interact either with a biomimetic open-loop-controlled fish robot-'Robofish'-or with a live companion. Furthermore, we investigated the responses of live guppies when tested three times with Robofish. We found that responses of live guppies towards Robofish were weaker compared with those of a live companion, most likely as a result of the non-interactive open-loop behaviour of Robofish. Guppies, however, were consistent in their individual responses between a live companion and Robofish, and similar individual differences in response towards Robofish were maintained over repeated testing even though habituation to the test environment was detectable. Biomimetic robots like Robofish are therefore a useful tool for the study of social responsiveness in guppies and possibly other small fish species.

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.