Order in spontaneous behavior

The effect of heterospecific and conspecific competition on inter-individual differences in tungara frog tadpole (Engystomops pustulosus) behavior

Repeated social interactions with conspecifics and/or heterospecifics during early development may drive the differentiation of behavior among individuals. Competition is a major form of social interaction and its impacts can depend on whether interactions occur between conspecifics or heterospecifics and the directionality of a response could be specific to the ecological context that they are measured in. To test this, we reared tungara frog tadpoles (Engystomops pustulosus) either in isolation, with a conspecific tadpole or with an aggressive heterospecific tadpole, the whistling frog tadpole (Leptodactylus fuscus). In each treatment, we measured the body size and distance focal E. pustulosus tadpoles swam in familiar, novel and predator risk contexts six times during development. We used univariate and multivariate hierarchical mixed effect models to investigate the effect of treatment on mean behavior, variance among and within individuals, behavioral repeatability and covariance among individuals in their behavior between contexts. There was a strong effect of competition on behavior, with different population and individual level responses across social treatments. Within a familiar context, the variance in the distance swam within individuals decreased under conspecific competition but heterospecific competition caused more variance in the average distance swam among individuals. Behavioral responses were also context specific as conspecific competition caused an increase in the distance swam within individuals in novel and predator risk contexts. The results highlight that the impact of competition on among and within individual variance in behavior is dependent on both competitor species identity and context.

Interpersonal synchronization of spontaneously generated body movements

Interpersonal movement synchrony (IMS) is central to social behavior in several species. In humans, IMS is typically studied using structured tasks requiring participants to produce specific body movements. Instead, spontaneously generated (i.e., not instructed) movements have received less attention. To test whether spontaneous movements synchronize interpersonally, we recorded full-body kinematics from dyads of participants who were only asked to sit face-to-face and to look at each other. We manipulated interpersonal (i) visual contact and (ii) spatial proximity. We found that spontaneous movements synchronized across participants only when they could see each other and regardless of interpersonal spatial proximity. This synchronization emerged very rapidly and did not selectively entail homologous body parts (as in mimicry); rather, the synchrony generalized to nearly all possible combinations of body parts. Hence, spontaneous behavior alone can lead to IMS. More generally, our results highlight that IMS can be studied under natural and unconstrained conditions.

Approximations of algorithmic and structural complexity validate cognitive-behavioral experimental results

Being able to objectively characterize the intrinsic complexity of behavioral patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems. Yet complexity is difficult in practice, particularly when strings are short. By numerically approximating algorithmic (Kolmogorov) complexity (K), we establish an objective tool to characterize behavioral complexity. Next, we approximate structural (Bennett's Logical Depth) complexity (LD) to assess the amount of computation required for generating a behavioral string. We apply our toolbox to three landmark studies of animal behavior of increasing sophistication and degree of environmental influence, including studies of foraging communication by ants, flight patterns of fruit flies, and tactical deception and competition (e.g., predator-prey) strategies. We find that ants harness the environmental condition in their internal decision process, modulating their behavioral complexity accordingly. Our analysis of flight (fruit flies) invalidated the common hypothesis that animals navigating in an environment devoid of stimuli adopt a random strategy. Fruit flies exposed to a featureless environment deviated the most from Levy flight, suggesting an algorithmic bias in their attempt to devise a useful (navigation) strategy. Similarly, a logical depth analysis of rats revealed that the structural complexity of the rat always ends up matching the structural complexity of the competitor, with the rats' behavior simulating algorithmic randomness. Finally, we discuss how experiments on how humans perceive randomness suggest the existence of an algorithmic bias in our reasoning and decision processes, in line with our analysis of the animal experiments. This contrasts with the view of the mind as performing faulty computations when presented with randomized items. In summary, our formal toolbox objectively characterizes external constraints on putative models of the "internal" decision process in humans and animals.

Bioinspired Design in Research: Evolution as Beta-Testing

Modern fishes represent over 400 million years of evolutionary processes that, in many cases, resulted in selection for phenotypes with particular performance advantages. While this certainly occurred without a trajectory for optimization, it cannot be denied that some morphologies allow organisms to be more effective than others at tasks like evading predation, securing food, and ultimately passing on their genes. In this way, evolution generates a series of iterative prototypes with varying but measurable success in accomplishing objectives. Therefore, careful analysis of fundamental properties underlying biological phenomena allow us to fast-track development of bioinspired technologies aiming to accomplish similar objectives. At the same time, bioinspired designs can be a way to explore evolutionary processes, by better understanding the performance space within which a given morphology operates. Through strong interdisciplinary collaborations, we can develop novel bioinspired technologies that not only excel as robotic devices but that teach us something about biology and the rules of life in the process.

An Embodied Intelligence-Based Biologically Inspired Strategy for Searching a Moving Target

Bacterial chemotaxis in unicellular Escherichia coli, the simplest biological creature, enables it to perform effective searching behaviour even with a single sensor, achieved via a sequence of "tumbling" and "swimming" behaviours guided by gradient information. Recent studies show that suitable random walk strategies may guide the behaviour in the absence of gradient information. This article presents a novel and minimalistic biologically inspired search strategy inspired by bacterial chemotaxis and embodied intelligence concept: a concept stating that intelligent behaviour is a result of the interaction among the "brain," body morphology including the sensory sensitivity tuned by the morphology, and the environment. Specifically, we present bacterial chemotaxis inspired searching behaviour with and without gradient information based on biological fluctuation framework: a mathematical framework that explains how biological creatures utilize noises in their behaviour. Via extensive simulation of a single sensor mobile robot that searches for a moving target, we will demonstrate how the effectiveness of the search depends on the sensory sensitivity and the inherent random walk strategies produced by the brain of the robot, comprising Ballistic, Levy, Brownian, and Stationary search. The result demonstrates the importance of embodied intelligence even in a behaviour inspired by the simplest creature.

Peripheral NOD-like receptor deficient inflammatory macrophages trigger neutrophil infiltration into the brain disrupting daytime locomotion

Inflammation is known to disrupt normal behavior, yet the underlying neuroimmune interactions remain elusive. Here, we investigated whether inappropriate macrophage-evoked inflammation alters CNS control of daily-life animal locomotion using a set of zebrafish mutants selected for specific macrophage dysfunction and microglia deficiency. Large-scale genetic and computational analyses revealed that NOD-like receptor nlrc3l mutants are capable of normal motility and visuomotor response, but preferentially swim less in the daytime, suggesting possible low motivation rather than physical impairment. Examining their brain activities and structures implicates impaired dopaminergic descending circuits, where neutrophils abnormally infiltrate. Furthermore, neutrophil depletion recovered daytime locomotion. Restoring wild-type macrophages reversed behavioral and neutrophil aberrations, while three other microglia-lacking mutants failed to phenocopy nlrc3l mutants. Overall, we reveal how peripheral inflammatory macrophages with elevated pro-inflammatory cues (including il1β, tnfα, cxcl8a) in the absence of microglia co-opt neutrophils to infiltrate the brain, thereby potentially enabling local circuitry modulation affecting daytime locomotion.

Suppression of motion vision during course-changing, but not course-stabilizing, navigational turns

From mammals to insects, locomotion has been shown to strongly modulate visual-system physiology. Does the manner in which a locomotor act is initiated change the modulation observed? We performed patch-clamp recordings from motion-sensitive visual neurons in tethered, flying Drosophila. We observed motor-related signals in flies performing flight turns in rapid response to looming discs and also during spontaneous turns, but motor-related signals were weak or non-existent in the context of turns made in response to brief pulses of unidirectional visual motion (i.e., optomotor responses). Thus, the act of a locomotor turn is variably associated with modulation of visual processing. These results can be understood via the following principle: suppress visual responses during course-changing, but not course-stabilizing, navigational turns. This principle is likely to apply broadly-even to mammals-whenever visual cells whose activity helps to stabilize a locomotor trajectory or the visual gaze angle are targeted for motor modulation.

Collective action or individual choice: Spontaneity and individuality contribute to decision-making in Drosophila

Our own unique character traits make our behavior consistent and define our individuality. Yet, this consistency does not entail that we behave repetitively like machines. Like humans, animals also combine personality traits with spontaneity to produce adaptive behavior: consistent, but not fully predictable. Here, we study an iconically rigid behavioral trait, insect phototaxis, that nevertheless also contains both components of individuality and spontaneity. In a light/dark T-maze, approximately 70% of a group of Drosophila fruit flies choose the bright arm of the T-Maze, while the remaining 30% walk into the dark. Taking the photopositive and the photonegative subgroups and re-testing them reveals the spontaneous component: a similar 70–30 distribution emerges in each of the two subgroups. Increasing the number of choices to ten choices, reveals the individuality component: flies with an extremely negative series of first choices were more likely to show photonegative behavior in subsequent choices and vice versa. General behavioral traits, independent of light/dark preference, contributed to the development of this individuality. The interaction of individuality and spontaneity together explains why group averages, even for such seemingly stereotypical behaviors, are poor predictors of individual choices.

Selective disappearance does not underlie age-related changes in trait repeatability in red squirrels

Understanding the causes and consequences of repeatable among-individual differences in behavior (i.e., animal personality) is a major area of research in behavioral and evolutionary ecology. Recently, attention has turned to understanding the processes behind changes in repeatability through ontogeny because of their implications for populations. We evaluated the relative importance of selective disappearance (i.e., differential mortality), an among-individual mechanism, in generating age-related changes in the repeatability of aggression and activity in juvenile North American red squirrels (Tamiasciurus hudsonicus). We observed age-related decreases in the repeatability of aggression across ages, arising from lower among-individual variance. Although we found evidence for directional selection on aggressiveness, it was insufficient to erode among-individual variance. Thus, ontogenetic decreases in the repeatability of aggression do not appear to be due to selective disappearance. In contrast, the repeatability of activity was higher across ages due to higher among-individual variance in activity, but there was no support for selective disappearance based on activity. Taken together, our results suggest that age-related changes in trait repeatability in red squirrels are not the result of selective disappearance and instead may be the result of within-individual developmental processes, such as individual differences in developmental trajectories.

Reconstructing the Intrinsic Statistical Properties of Intermittent Locomotion Through Corrections for Boundary Effects

Locomotion characteristics are often recorded within bounded spaces, a constraint which introduces geometry-specific biases and potentially complicates the inference of behavioural features from empirical observations. We describe how statistical properties of an uncorrelated random walk, namely the steady-state stopping location probability density and the empirical step probability density, are affected by enclosure in a bounded space. The random walk here is considered as a null model for an organism moving intermittently in such a space, that is, the points represent stopping locations and the step is the displacement between them. Closed-form expressions are derived for motion in one dimension and simple two-dimensional geometries, in addition to an implicit expression for arbitrary (convex) geometries. For the particular choice of no-go boundary conditions, we demonstrate that the empirical step distribution is related to the intrinsic step distribution, i.e. the one we would observe in unbounded space, via a multiplicative transformation dependent solely on the boundary geometry. This conclusion allows in practice for the compensation of boundary effects and the reconstruction of the intrinsic step distribution from empirical observations.

Internal-Clock Models and Misguided Views of Mechanistic Explanations: A Reply to Eckard & Lattal (2020)

Eckard and Lattal's Perspectives on Behavior Science, 43(1), 5-19 (2020) critique of internal clock (IC) mechanisms is based on narrow concepts of clocks, of their internality, of their mechanistic nature, and of scientific explanations in general. This reply broadens these concepts to characterize all timekeeping objects-physical and otherwise-as clocks, all intrinsic properties of such objects as internal to them, and all simulatable explanations of such properties as mechanisms. Eckard and Lattal's critique reflects a restrictive billiard-ball view of causation, in which environmental manipulations and behavioral effects are connected by a single chain of contiguous events. In contrast, this reply offers a more inclusive stochastic view of causation, in which environmental manipulations are probabilistically connected to behavioral effects. From either view of causation, computational ICs are hypothetical and unobservable, but their heuristic value and parsimony can only be appreciated from a stochastic view of causation. Billiard-ball and stochastic views have contrasting implications for potential explanations of interval timing. As illustrated by accounts of the variability in start times in fixed-interval schedules of reinforcement, of the two views of causality examined, only the stochastic account supports falsifiable predictions beyond simple replications. It is thus not surprising that the experimental analysis of behavior has progressively adopted a stochastic view of causation, and that it has reaped its benefits. This reply invites experimental behavior analysts to continue on that trajectory.

Hybrid visual control in fly flight: insights into gaze shift via saccades

Flies fly by alternating between periods of fixation and body saccades, analogous to how our own eyes move. Gaze fixation via smooth movement in fly flight has been studied extensively, but comparatively less is known about the mechanism by which flies trigger and control body saccades to shift their gaze. Why do flies implement a hybrid fixate-and-saccade locomotion strategy? Here we review recent developments that provide new insights into this question. We focus on the interplay between smooth movement and saccades, the trigger classes of saccades, and the timeline of saccade execution. We emphasize recent mechanistic advances in Drosophila, where genetic tools have enabled cellular circuit analysis at an unprecedented level in a flying insect. In addition, we review trade-offs in behavioral paradigms used to study saccades. Throughout we highlight exciting avenues for future research in the control of fly flight.

Animal intermittent locomotion: A null model for the probability of moving forward in bounded space

We present a null model to be compared with biological data to test for intrinsic persistence in movement between stops during intermittent locomotion in bounded space with different geometries and boundary conditions. We describe spatio-temporal properties of the sequence of stopping points r₁,r₂,r₃,… visited by a Random Walker within a bounded space. The path between stopping points is not considered, only the displacement. Since there are no intrinsic correlations in the displacements between stopping points, there is no intrinsic persistence in the movement between them. Hence, this represents a null-model against which to compare empirical data for directional persistence in the movement between stopping points when there is external bias due to the bounded space. This comparison is a necessary first step in testing hypotheses about the function of the stops that punctuate intermittent locomotion in diverse organisms. We investigate the probability of forward movement, defined as a deviation of less than 90° between two successive displacement vectors, as a function of the ratio between the largest displacement between stops that could be performed by the random walker and the system size, α=Δℓ/L_max. As expected, the probability of forward movement is 1/2 when α→0. However, when α is finite, this probability is less than 1/2 with a minimum value when α=1. For certain boundary conditions, the minimum value is between 1/3 and 1/4 in 1D while it can be even lower in 2D. The probability of forward movement in 1D is calculated exactly for all values 0<α⩽1 for several boundary conditions. Analytical calculations for the probability of forward movement are performed in 2D for circular and square bounded regions with one boundary condition. Numerical results for all values 0<α⩽1 are presented for several boundary conditions. The cases of rectangle and ellipse are also considered and an approximate model of the dependence of the forward movement probability on the aspect ratio is provided. Finally, some practical points are presented on how these results can be utilised in the empirical analysis of animal movement in two-dimensional bounded space.

The Readiness Potential reflects planning-based expectation, not uncertainty, in the timing of action

Actions are guided by a combination of external cues, internal intentions, and stored knowledge. Self-initiated voluntary actions, produced without immediate external cues, may be preceded by a slow EEG Readiness Potential (RP) that progressively increases prior to action. The cognitive significance of this neural event is controversial. Some accounts link the RP to the fact that timing of voluntary actions is generated endogenously, without external constraints. Others link it to the unique role of a planning process, and therefore of temporal expectation, in voluntary actions. In many previous experiments, actions are unconstrained by external cues, but also potentially involve preplanning and anticipation. To separate these factors, we developed a reinforcement learning paradigm where participants learned, through trial and error, the optimal time to act. If the RP reflects freedom from external constraint, its amplitude should be greater early in learning, when participants do not yet know when to act. Conversely, if the RP reflects planning, it should be greater later on, when participants have learned, and plan in advance, the time of action. We found that RP amplitudes grew with learning, suggesting that this neural activity reflects planning and anticipation for the forthcoming action, rather than freedom from external constraint.

Development of an automatic turntable-type multiple T-maze device and observation of pill bug behavior

In recent years, various animal observation instruments have been developed to support long-term measurement and analysis of animal behaviors. This study proposes an automatic observation instrument that specializes for turning behaviors of pill bugs and aims to obtain new knowledge in the field of ethology. Pill bugs strongly tend to turn in the opposite direction of a preceding turn. This alternation of turning is called turn alternation reaction. However, a repetition of turns in the same direction is called turn repetition reaction and has been considered a malfunction of turn alternation. In this research, the authors developed an automatic turntable-type multiple T-maze device and observed the turning behavior of 34 pill bugs for 6 h to investigate whether turn repetition is a malfunction. As a result, most of the pill bug movements were categorized into three groups: sub-diffusion, Brownian motion, and Lévy walk. This result suggests that pill bugs do not continue turn alternation mechanically but elicit turn repetition moderately, which results in various movement patterns. In organisms with relatively simple nervous systems such as pill bugs, stereotypical behaviors such as turn alternation have been considered mechanical reactions and variant behaviors such as turn repetition have been considered malfunctions. However, our results suggest that a moderate generation of turn repetition is involved in the generation of various movement patterns. This study is expected to provide a new perspective on the conventional view of the behaviors of simple organisms.

Functional advantages of Lévy walks emerging near a critical point

A special class of random walks, so-called Lévy walks, has been observed in a variety of organisms ranging from cells, insects, fishes, and birds to mammals, including humans. Although their prevalence is considered to be a consequence of natural selection for higher search efficiency, some findings suggest that Lévy walks might also be epiphenomena that arise from interactions with the environment. Therefore, why they are common in biological movements remains an open question. Based on some evidence that Lévy walks are spontaneously generated in the brain and the fact that power-law distributions in Lévy walks can emerge at a critical point, we hypothesized that the advantages of Lévy walks might be enhanced by criticality. However, the functional advantages of Lévy walks are poorly understood. Here, we modeled nonlinear systems for the generation of locomotion and showed that Lévy walks emerging near a critical point had optimal dynamic ranges for coding information. This discovery suggested that Lévy walks could change movement trajectories based on the magnitude of environmental stimuli. We then showed that the high flexibility of Lévy walks enabled switching exploitation/exploration based on the nature of external cues. Finally, we analyzed the movement trajectories of freely moving Drosophila larvae and showed empirically that the Lévy walks may emerge near a critical point and have large dynamic range and high flexibility. Our results suggest that the commonly observed Lévy walks emerge near a critical point and could be explained on the basis of these functional advantages.

Hierarchical Compression Reveals Sub-Second to Day-Long Structure in Larval Zebrafish Behavior

Animal behavior is dynamic, evolving over multiple timescales from milliseconds to days and even across a lifetime. To understand the mechanisms governing these dynamics, it is necessary to capture multi-timescale structure from behavioral data. Here, we develop computational tools and study the behavior of hundreds of larval zebrafish tracked continuously across multiple 24-h day/night cycles. We extracted millions of movements and pauses, termed bouts, and used unsupervised learning to reduce each larva’s behavior to an alternating sequence of active and inactive bout types, termed modules. Through hierarchical compression, we identified recurrent behavioral patterns, termed motifs. Module and motif usage varied across the day/night cycle, revealing structure at sub-second to day-long timescales. We further demonstrate that module and motif analysis can uncover novel pharmacological and genetic mutant phenotypes. Overall, our work reveals the organization of larval zebrafish behavior at multiple timescales and provides tools to identify structure from large-scale behavioral datasets.

Why behavioral neuroscience still needs diversity?: A curious case of a persistent need

In the past few decades, a substantial portion of neuroscience research has moved from studies conducted across a spectrum of animals to reliance on a few species. While this undoubtedly promotes consistency, in-depth analysis, and a better claim to unraveling molecular mechanisms, investing heavily in a subset of species also restricts the type of questions that can be asked, and impacts the generalizability of findings. A conspicuous body of literature has long advocated the need to expand the diversity of animal systems used in neuroscience research. Part of this need is utilitarian with respect to translation, but the remaining is the knowledge that historically, a diverse set of species were instrumental in obtaining transformative understanding. We argue that diversifying matters also because the current approach limits the scope of what can be discovered. Technological advancements are already bridging several practical gaps separating these two worlds. What remains is a wholehearted embrace by the community that has benefitted from past history. We suggest the time for it is now.

Insights from the study of complex systems for the ecology and evolution of animal populations

Populations of animals comprise many individuals, interacting in multiple contexts, and displaying heterogeneous behaviors. The interactions among individuals can often create population dynamics that are fundamentally deterministic yet display unpredictable dynamics. Animal populations can, therefore, be thought of as complex systems. Complex systems display properties such as nonlinearity and uncertainty and show emergent properties that cannot be explained by a simple sum of the interacting components. Any system where entities compete, cooperate, or interfere with one another may possess such qualities, making animal populations similar on many levels to complex systems. Some fields are already embracing elements of complexity to help understand the dynamics of animal populations, but a wider application of complexity science in ecology and evolution has not occurred. We review here how approaches from complexity science could be applied to the study of the interactions and behavior of individuals within animal populations and highlight how this way of thinking can enhance our understanding of population dynamics in animals. We focus on 8 key characteristics of complex systems: hierarchy, heterogeneity, self-organization, openness, adaptation, memory, nonlinearity, and uncertainty. For each topic we discuss how concepts from complexity theory are applicable in animal populations and emphasize the unique insights they provide. We finish by outlining outstanding questions or predictions to be evaluated using behavioral and ecological data. Our goal throughout this article is to familiarize animal ecologists with the basics of each of these concepts and highlight the new perspectives that they could bring to variety of subfields.

Optimal searching behaviour generated intrinsically by the central pattern generator for locomotion

Efficient searching for resources such as food by animals is key to their survival. It has been proposed that diverse animals from insects to sharks and humans adopt searching patterns that resemble a simple Lévy random walk, which is theoretically optimal for 'blind foragers' to locate sparse, patchy resources. To test if such patterns are generated intrinsically, or arise via environmental interactions, we tracked free-moving Drosophila larvae with (and without) blocked synaptic activity in the brain, suboesophageal ganglion (SOG) and sensory neurons. In brain-blocked larvae, we found that extended substrate exploration emerges as multi-scale movement paths similar to truncated Lévy walks. Strikingly, power-law exponents of brain/SOG/sensory-blocked larvae averaged 1.96, close to a theoretical optimum (µ ≅ 2.0) for locating sparse resources. Thus, efficient spatial exploration can emerge from autonomous patterns in neural activity. Our results provide the strongest evidence so far for the intrinsic generation of Lévy-like movement patterns.

The influence of environmental gradients on individual behaviour: Individual plasticity is consistent across risk and temperature gradients

The expression of individual behaviour as a function of environmental variation (behavioural plasticity) is recognized as a means for animals to modify their phenotypes in response to changing conditions. Plasticity has been studied extensively in recent years, leading to an accumulation of evidence for behavioural plasticity within natural populations. Despite the recent attention given to studying individual variation in behavioural plasticity, there is still a lack of consensus regarding its causes and constraints. One pressing question related to this is whether individual plasticity carries over across temporal and environmental gradients. That is, are some individuals more plastic (responsive) than others in general? Here, we examined the influence of temporal and environmental gradients on individual behavioural responses in a marine gastropod, Littoraria irrorata. We measured individual boldness repeatedly over time and in response to tidal cycle (high vs. low, an index of risk) and daily temperature fluctuations (known to affect metabolism), in a controlled field experiment. On average, boldness increased from high to low tide and with increasing temperature but decreased marginally over time. Individuals also differed in their responses to variation in tide and temperature, but not over time. Those which were relatively bold at high tide (when predation risk is greater) were similarly bold at low tide, whereas shy individuals became much more "bold" at low tide. Most notably, individuals that were more responsive to tide (and thus risk) were also more responsive to temperature changes, indicating that plasticity was correlated across contexts (r = 0.57) and that bolder individuals were least plastic overall. This study provides a rare and possibly first example of consistency of individual behavioural plasticity across contexts, suggesting underlying physiology as a common mechanism, and raises the possibility of correlational selection on plasticity.

Mind Control: How Parasites Manipulate Cognitive Functions in Their Insect Hosts

Neuro-parasitology is an emerging branch of science that deals with parasites that can control the nervous system of the host. It offers the possibility of discovering how one species (the parasite) modifies a particular neural network, and thus particular behaviors, of another species (the host). Such parasite-host interactions, developed over millions of years of evolution, provide unique tools by which one can determine how neuromodulation up-or-down regulates specific behaviors. In some of the most fascinating manipulations, the parasite taps into the host brain neuronal circuities to manipulate hosts cognitive functions. To name just a few examples, some worms induce crickets and other terrestrial insects to commit suicide in water, enabling the exit of the parasite into an aquatic environment favorable to its reproduction. In another example of behavioral manipulation, ants that consumed the secretions of a caterpillar containing dopamine are less likely to move away from the caterpillar and more likely to be aggressive. This benefits the caterpillar for without its ant bodyguards, it is more likely to be predated upon or attacked by parasitic insects that would lay eggs inside its body. Another example is the parasitic wasp, which induces a guarding behavior in its ladybug host in collaboration with a viral mutualist. To exert long-term behavioral manipulation of the host, parasite must secrete compounds that act through secondary messengers and/or directly on genes often modifying gene expression to produce long-lasting effects.

Multi-stability with ambiguous visual stimuli in Drosophila orientation behavior

It is widely accepted for humans and higher animals that vision is an active process in which the organism interprets the stimulus. To find out whether this also holds for lower animals, we designed an ambiguous motion stimulus, which serves as something like a multi-stable perception paradigm in Drosophila behavior. Confronted with a uniform panoramic texture in a closed-loop situation in stationary flight, the flies adjust their yaw torque to stabilize their virtual self-rotation. To make the visual input ambiguous, we added a second texture. Both textures got a rotatory bias to move into opposite directions at a constant relative angular velocity. The results indicate that the fly now had three possible frames of reference for self-rotation: either of the two motion components as well as the integrated motion vector of the two. In this ambiguous stimulus situation, the flies generated a continuous sequence of behaviors, each one adjusted to one or another of the three references.

Vision is considered an active process in humans and higher animals in which the stimulus is interpreted by the subject and can be perceived in different ways if it is ambiguous. We aimed to find out whether this also holds for lower animals, such as the fruit fly Drosophila melanogaster. To provide ambiguity, we exposed flies to transparent motion stimuli in a flight simulator and found their behavior to be multi-stable. These results show that the visual system of the fly can separate the individual components of a transparent motion stimulus, and that this kind of stimulus is ambiguous to the fly. The extent to which the fly shows component selectivity in its behavior depends on several properties of the stimulus, like pattern contrast and element density. The alternations between the different behaviors exhibit a stochasticity reminiscent of the temporal dynamics in human multi-stable perception.

Abolishment of Spontaneous Flight Turns in Visually Responsive Drosophila

Animals react rapidly to external stimuli, such as an approaching predator, but in other circumstances, they seem to act spontaneously, without any obvious external trigger. How do the neural processes mediating the execution of reflexive and spontaneous actions differ? We studied this question in tethered, flying Drosophila. We found that silencing a large but genetically defined set of non-motor neurons virtually eliminates spontaneous flight turns while preserving the tethered flies' ability to perform two types of visually evoked turns, demonstrating that, at least in flies, these two modes of action are almost completely dissociable.

Media Portrayal of a Landmark Neuroscience Experiment on Free Will

The concept of free will has been heavily debated in philosophy and the social sciences. Its alleged importance lies in its association with phenomena fundamental to our understandings of self, such as autonomy, freedom, self-control, agency, and moral responsibility. Consequently, when neuroscience research is interpreted as challenging or even invalidating this concept, a number of heated social and ethical debates surface. We undertook a content analysis of media coverage of Libet's et al.'s (Brain 106(Pt 3):623-642, 1983) landmark study, which is frequently interpreted as posing a serious challenge to the existence of free will. Media descriptions of Libet et al.'s experiment provided limited details about the original study. Overall, many media articles reported that Libet et al.'s experiments undermined the existence of free will, despite acknowledging that several methodological limitations had been identified in the literature. A propensity to attribute greater credibility than warranted to neurobiological explanations could be at stake.

Anomalous diffusion on the servosphere: A potential tool for detecting inherent organismal movement patterns

Tracking animal movements such as walking is an essential task for understanding how and why animals move in an environment and respond to external stimuli. Different methods that implemented image analysis and a data logger such as GPS have been used in laboratory experiments and in field studies, respectively. Recently, animal movement patterns without stimuli have attracted an increasing attention in search for common innate characteristics underlying all of their movements. However, it is difficult to track the movements in a vast and homogeneous environment without stimuli because of space constraints in laboratories or environmental heterogeneity in the field, hindering our understanding of inherent movement patterns. Here, we applied an omnidirectional treadmill mechanism, or a servosphere, as a tool for tracking two-dimensional movements of small animals that can provide both a homogenous environment and a virtual infinite space for walking. To validate the use of our tracking system for assessment of the free-walking behavior, we compared walking patterns of individual pillbugs (Armadillidium vulgare) on the servosphere with that in two types of experimental flat arenas. Our results revealed that the walking patterns on the servosphere showed similar diffusive characteristics to those observed in the large arena simulating an open space, and we demonstrated that our mechanism provides more robust measurements of diffusive properties compared to a small arena with enclosure. Moreover, we showed that anomalous diffusion properties, including Lévy walk, can be detected from the free-walking behavior on our tracking system. Thus, our novel tracking system is useful to measure inherent movement patterns, which will contribute to the studies of movement ecology, ethology, and behavioral sciences.

Nonstationary Stochastic Dynamics Underlie Spontaneous Transitions between Active and Inactive Behavioral States

The neural basis of spontaneous movement generation is a fascinating open question. Long-term monitoring of fish, swimming freely in a constant sensory environment, has revealed a sequence of behavioral states that alternate randomly and spontaneously between periods of activity and inactivity. We show that key dynamical features of this sequence are captured by a 1-D diffusion process evolving in a nonlinear double well energy landscape, in which a slow variable modulates the relative depth of the wells. This combination of stochasticity, nonlinearity, and nonstationary forcing correctly captures the vastly different timescales of fluctuations observed in the data (∼1 to ∼1000 s), and yields long-tailed residence time distributions (RTDs) also consistent with the data. In fact, our model provides a simple mechanism for the emergence of long-tailed distributions in spontaneous animal behavior. We interpret the stochastic variable of this dynamical model as a decision-like variable that, upon reaching a threshold, triggers the transition between states. Our main finding is thus the identification of a threshold crossing process as the mechanism governing spontaneous movement initiation and termination, and to infer the presence of underlying nonstationary agents. Another important outcome of our work is a dimensionality reduction scheme that allows similar segments of data to be grouped together. This is done by first extracting geometrical features in the dataset and then applying principal component analysis over the feature space. Our study is novel in its ability to model nonstationary behavioral data over a wide range of timescales.

The Function and Organization of the Motor System Controlling Flight Maneuvers in Flies

Animals face the daunting task of controlling their limbs using a small set of highly constrained actuators. This problem is particularly demanding for insects such as Drosophila, which must adjust wing motion for both quick voluntary maneuvers and slow compensatory reflexes using only a dozen pairs of muscles. To identify strategies by which animals execute precise actions using sparse motor networks, we imaged the activity of a complete ensemble of wing control muscles in intact, flying flies. Our experiments uncovered a remarkably efficient logic in which each of the four skeletal elements at the base of the wing are equipped with both large phasically active muscles capable of executing large changes and smaller tonically active muscles specialized for continuous fine-scaled adjustments. Based on the responses to a broad panel of visual motion stimuli, we have developed a model by which the motor array regulates aerodynamically functional features of wing motion. VIDEO ABSTRACT.

Control of Movement Initiation Underlies the Development of Balance

Balance arises from the interplay of external forces acting on the body and internally generated movements. Many animal bodies are inherently unstable, necessitating corrective locomotion to maintain stability. Understanding how developing animals come to balance remains a challenge. Here we study the interplay among environment, sensation, and action as balance develops in larval zebrafish. We first model the physical forces that challenge underwater balance and experimentally confirm that larvae are subject to constant destabilization. Larvae propel in swim bouts that, we find, tend to stabilize the body. We confirm the relationship between locomotion and balance by changing larval body composition, exacerbating instability and eliciting more frequent swimming. Intriguingly, developing zebrafish come to control the initiation of locomotion, swimming preferentially when unstable, thus restoring preferred postures. To test the sufficiency of locomotor-driven stabilization and the developing control of movement timing, we incorporate both into a generative model of swimming. Simulated larvae recapitulate observed postures and movement timing across early development, but only when locomotor-driven stabilization and control of movement initiation are both utilized. We conclude the ability to move when unstable is the key developmental improvement to balance in larval zebrafish. Our work informs how emerging sensorimotor ability comes to impact how and why animals move when they do.

Variability in individual activity bursts improves ant foraging success

Using experimental and computational methods, we study the role of behavioural variability in activity bursts (or temporal activity patterns) for individual and collective regulation of foraging in A. senilis ants. First, foraging experiments were carried out under special conditions (low densities of ants and food and absence of external cues or stimuli) where individual-based strategies are most prevalent. By using marked individuals and recording all foraging trajectories, we were then able to precisely quantify behavioural variability among individuals. Our main conclusions are that (i) variability of ant trajectories (turning angles, speed, etc.) is low compared with variability of temporal activity profiles, and (ii) this variability seems to be driven by plasticity of individual behaviour through time, rather than the presence of fixed behavioural stereotypes or specialists within the group. The statistical measures obtained from these experimental foraging patterns are then used to build a general agent-based model (ABM) which includes the most relevant properties of ant foraging under natural conditions, including recruitment through pheromone communication. Using the ABM, we are able to provide computational evidence that the characteristics of individual variability observed in our experiments can provide a functional advantage (in terms of foraging success) to the group; thus, we propose the biological basis underpinning our observations. Altogether, our study reveals the potential utility of experiments under simplified (laboratory) conditions for understanding information-gathering in biological systems.

Generalized CNS arousal: An elementary force within the vertebrate nervous system

Why do animals and humans do anything at all? Arousal is the most powerful and essential function of the brain, a continuous function that accounts for the ability of animals and humans to respond to stimuli in the environment by producing muscular responses. Following decades of psychological, neurophysiological and molecular investigations, generalized CNS arousal can now be analyzed using approaches usually applied to physical systems. The concept of "criticality" is a state that illustrates an advantage for arousal systems poised near a phase transition. This property provides speed and sensitivity and facilitates the transition of the system into different brain states, especially as the brain crosses a phase transition from less aroused to more aroused states. In summary, concepts derived from applied mathematics of physical systems will now find their application in this area of neuroscience, the neurobiology of CNS arousal.

PKC in motorneurons underlies self-learning, a form of motor learning in Drosophila

Tethering a fly for stationary flight allows for exquisite control of its sensory input, such as visual or olfactory stimuli or a punishing infrared laser beam. A torque meter measures the turning attempts of the tethered fly around its vertical body axis. By punishing, say, left turning attempts (in a homogeneous environment), one can train a fly to restrict its behaviour to right turning attempts. It was recently discovered that this form of operant conditioning (called operant self-learning), may constitute a form of motor learning in Drosophila. Previous work had shown that Protein Kinase C (PKC) and the transcription factor dFoxP were specifically involved in self-learning, but not in other forms of learning. These molecules are specifically involved in various forms of motor learning in other animals, such as compulsive biting in Aplysia, song-learning in birds, procedural learning in mice or language acquisition in humans. Here we describe our efforts to decipher which PKC gene is involved in self-learning in Drosophila. We also provide evidence that motorneurons may be one part of the neuronal network modified during self-learning experiments. The collected evidence is reminiscent of one of the simplest, clinically relevant forms of motor learning in humans, operant reflex conditioning, which also relies on motorneuron plasticity.

Signatures of chaos in animal search patterns

One key objective of the emerging discipline of movement ecology is to link animal movement patterns to underlying biological processes, including those operating at the neurobiological level. Nonetheless, little is known about the physiological basis of animal movement patterns, and the underlying search behaviour. Here we demonstrate the hallmarks of chaotic dynamics in the movement patterns of mud snails (Hydrobia ulvae) moving in controlled experimental conditions, observed in the temporal dynamics of turning behaviour. Chaotic temporal dynamics are known to occur in pacemaker neurons in molluscs, but there have been no studies reporting on whether chaotic properties are manifest in the movement patterns of molluscs. Our results suggest that complex search patterns, like the Lévy walks made by mud snails, can have their mechanistic origins in chaotic neuronal processes. This possibility calls for new research on the coupling between neurobiology and motor properties.

Experimental evidence for inherent Lévy search behaviour in foraging animals

Recently, Lévy walks have been put forward as a new paradigm for animal search and many cases have been made for its presence in nature. However, it remains debated whether Lévy walks are an inherent behavioural strategy or emerge from the animal reacting to its habitat. Here, we demonstrate signatures of Lévy behaviour in the search movement of mud snails (Hydrobia ulvae) based on a novel, direct assessment of movement properties in an experimental set-up using different food distributions. Our experimental data uncovered clusters of small movement steps alternating with long moves independent of food encounter and landscape complexity. Moreover, size distributions of these clusters followed truncated power laws. These two findings are characteristic signatures of mechanisms underlying inherent Lévy-like movement. Thus, our study provides clear experimental evidence that such multi-scale movement is an inherent behaviour rather than resulting from the animal interacting with its environment.

Brain-wide mapping of neural activity controlling zebrafish exploratory locomotion

In the absence of salient sensory cues to guide behavior, animals must still execute sequences of motor actions in order to forage and explore. How such successive motor actions are coordinated to form global locomotion trajectories is unknown. We mapped the structure of larval zebrafish swim trajectories in homogeneous environments and found that trajectories were characterized by alternating sequences of repeated turns to the left and to the right. Using whole-brain light-sheet imaging, we identified activity relating to the behavior in specific neural populations that we termed the anterior rhombencephalic turning region (ARTR). ARTR perturbations biased swim direction and reduced the dependence of turn direction on turn history, indicating that the ARTR is part of a network generating the temporal correlations in turn direction. We also find suggestive evidence for ARTR mutual inhibition and ARTR projections to premotor neurons. Finally, simulations suggest the observed turn sequences may underlie efficient exploration of local environments.

Ants determine their next move at rest: motor planning and causality in complex systems

To find useful work to do for their colony, individual eusocial animals have to move, somehow staying attentive to relevant social information. Recent research on individual Temnothorax albipennis ants moving inside their colony's nest found a power-law relationship between a movement's duration and its average speed; and a universal speed profile for movements showing that they mostly fluctuate around a constant average speed. From this predictability it was inferred that movement durations are somehow determined before the movement itself. Here, we find similar results in lone T. albipennis ants exploring a large arena outside the nest, both when the arena is clean and when it contains chemical information left by previous nest-mates. This implies that these movement characteristics originate from the same individual neural and/or physiological mechanism(s), operating without immediate regard to social influences. However, the presence of pheromones and/or other cues was found to affect the inter-event speed correlations. Hence we suggest that ants' motor planning results in intermittent response to the social environment: movement duration is adjusted in response to social information only between movements, not during them. This environmentally flexible, intermittently responsive movement behaviour points towards a spatially allocated division of labour in this species. It also prompts more general questions on collective animal movement and the role of intermittent causation from higher to lower organizational levels in the stability of complex systems.

Depressive-like immobility behavior and genotype × stress interactions in male mice of selected strains

In this study, we investigated whether basal immobility time of C57BL/6J mice, which are commonly used in transgenesis, interferes with detection of depressive-like behavior in the tail suspension test (TST) after chronic restraint stress (CRS). We included in the study mice of the C57BL/6N strain, not previously compared with C57BL/6J for behavior in the TST, and contrasted both strains with NMRI mice which exhibit low basal immobility. NMRI, C57BL/6J, and C57BL/6N male mice (n = 20 per strain) were tested under basal conditions and after CRS (2 h daily for 14 d). NMRI and C57BL/6J mice were differentiated in the TST by low and high basal immobility times, respectively, while the C57BL/6N and NMRI mice showed similar levels of basal immobility. CRS extended the immobility time of NMRI mice in the TST, whereas both C57BL/6J and C57BL/6N mice were unaffected regardless of their initial phenotype. We explored whether detailed analysis of activity microstructure revealed effects of CRS in the TST, which are not apparent in the overall comparison of total immobility time. Interestingly, unlike C57BL/6J and/6N strains which showed no sensitivity to CRS, stressed NRMI mice displayed distinct activity microstructure. In contrast to behavioral differences, all stressed mice showed significant retardation in body weight gain, decreased thymus weight and increased adrenal cortex size. However, after CRS, enlargement of the adrenal medulla was observed in both C57BL/6J and C57BL/6N mice, suggesting similar sympatho-medullary activation and stress coping mechanism in these substrains.

The opposite effects of routine metabolic rate and metabolic rate during startle responses on variation in the predictability of behaviour in hermit crabs

Studies on animal behaviour have suggested a link between personality and energy expenditure. However, most models assume constant variation within individuals, even though individuals vary between observations. Such variation is called intraindividual variation in behaviour (IIV). We investigate if IIV in the duration of the startle response is associated with metabolic rates (MR) in the hermit crabPagurus bernhardus. We repeatedly measured startle response durations and MR during each observation. We used double hierarchical generalized linear models to ask whether among and IIV in behaviour was underpinned by MR. We found no association between the mean duration of the startle responses and either routine MR or MR during startle response. Nevertheless, we found that IIV increased with MR during startle responses and decreased with routine MR. These results indicate that crabs with higher MR during startle responses behave less predictably, and that predictability is reduced during exposure to elevated temperatures.

Computational Methods for Tracking, Quantitative Assessment, and Visualization of C. elegans Locomotory Behavior

The nematode Caenorhabditis elegans provides a unique opportunity to interrogate the neural basis of behavior at single neuron resolution. In C. elegans, neural circuits that control behaviors can be formulated based on its complete neural connection map, and easily assessed by applying advanced genetic tools that allow for modulation in the activity of specific neurons. Importantly, C. elegans exhibits several elaborate behaviors that can be empirically quantified and analyzed, thus providing a means to assess the contribution of specific neural circuits to behavioral output. Particularly, locomotory behavior can be recorded and analyzed with computational and mathematical tools. Here, we describe a robust single worm-tracking system, which is based on the open-source Python programming language, and an analysis system, which implements path-related algorithms. Our tracking system was designed to accommodate worms that explore a large area with frequent turns and reversals at high speeds. As a proof of principle, we used our tracker to record the movements of wild-type animals that were freshly removed from abundant bacterial food, and determined how wild-type animals change locomotory behavior over a long period of time. Consistent with previous findings, we observed that wild-type animals show a transition from area-restricted local search to global search over time. Intriguingly, we found that wild-type animals initially exhibit short, random movements interrupted by infrequent long trajectories. This movement pattern often coincides with local/global search behavior, and visually resembles Lévy flight search, a search behavior conserved across species. Our mathematical analysis showed that while most of the animals exhibited Brownian walks, approximately 20% of the animals exhibited Lévy flights, indicating that C. elegans can use Lévy flights for efficient food search. In summary, our tracker and analysis software will help analyze the neural basis of the alteration and transition of C. elegans locomotory behavior in a food-deprived condition.

Lévy Walks Suboptimal under Predation Risk

A key challenge in movement ecology is to understand how animals move in nature. Previous studies have predicted that animals should perform a special class of random walks, called Lévy walk, to obtain more targets. However, some empirical studies did not support this hypothesis, and the relationship between search strategy and ecological factors is still unclear. We focused on ecological factors, such as predation risk, and analyzed whether Lévy walk may not be favored. It was remarkable that the ecological factors often altered an optimal search strategy from Lévy walk to Brownian walk, depending on the speed of the predator's movement, density of predators, etc. This occurred because higher target encounter rates simultaneously led searchers to higher predation risks. Our findings indicate that animals may not perform Lévy walks often, and we suggest that it is crucial to consider the ecological context for evaluating the search strategy performed by animals in the field.