Disentangling and modeling interactions in fish with burst-and-coast swimming reveal distinct alignment and attraction behaviors

We combine extensive data analyses with a modeling approach to measure, disentangle, and reconstruct the actual functional form of interactions involved in the coordination of swimming in Rummy-nose tetra (Hemigrammus rhodostomus). This species of fish performs burst-and-coast swimming behavior that consists of sudden heading changes combined with brief accelerations followed by quasi-passive, straight decelerations. We quantify the spontaneous stochastic behavior of a fish and the interactions that govern wall avoidance and the attraction and alignment to a neighboring fish, the latter by exploiting general symmetry constraints for the interactions. In contrast with previous experimental works, we find that both attraction and alignment behaviors control the reaction of fish to a neighbor. We then exploit these results to build a model of spontaneous burst-and-coast swimming and interactions of fish, with all parameters being estimated or directly measured from experiments. This model quantitatively reproduces the key features of the motion and spatial distributions observed in experiments with a single fish and with two fish. This demonstrates the power of our method that exploits large amounts of data for disentangling and fully characterizing the interactions that govern collective behaviors in animals groups. Moreover, we introduce the notions of "dumb" and "intelligent" active matter and emphasize and clarify the strong differences between them.Comment: Supplementary Information (PDF text + 5 videos) can be downloaded at http://www.lpt.ups-tlse.fr/spip.php?action=acceder_document&arg=2240&cle=f7d43896e78b1b15dff009dc7769eac3c956c76a&file=zip%2FSI_Web.zi

Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm

During the last two decades, various models have been proposed for fish collective motion. These models are mainly developed to decipher the biological mechanisms of social interaction between animals. They consider very simple homogeneous unbounded environments and it is not clear that they can simulate accurately the collective trajectories. Moreover when the models are more accurate, the question of their scalability to either larger groups or more elaborate environments remains open. This study deals with learning how to simulate realistic collective motion of collective of zebrafish, using real-world tracking data. The objective is to devise an agent-based model that can be implemented on an artificial robotic fish that can blend into a collective of real fish. We present a novel approach that uses Quality Diversity algorithms, a class of algorithms that emphasise exploration over pure optimisation. In particular, we use CVT-MAP-Elites, a variant of the state-of-the-art MAP-Elites algorithm for high dimensional search space. Results show that Quality Diversity algorithms not only outperform classic evolutionary reinforcement learning methods at the macroscopic level (i.e. group behaviour), but are also able to generate more realistic biomimetic behaviours at the microscopic level (i.e. individual behaviour).Comment: 8 pages, 4 figures, 1 tabl

Spatio-Temporal Clustering Benchmark for Collective Animal Behavior

Various spatio-temporal clustering methods have been proposed to detect groups of jointly moving objects in space and time. However, such spatio-temporal clustering methods are rarely compared against each other to evaluate their performance in discovering moving clusters. Hence, in this work, we present a spatio-temporal clustering benchmark for the field of collective animal behavior. Our reproducible benchmark proposes synthetic datasets with ground truth and scalable implementations of spatio-temporal clustering methods. The benchmark reveals that temporal extensions of standard clustering algorithms are inherently useful for the scalable detection of moving clusters in collective animal behavior.publishe

Sex-Specific Effect of the Dietary Protein to Carbohydrate Ratio on Personality in the Dubia Cockroach

Animal personality, defined by behavioral variations among individuals consistent over contexts or time, is shaped by genetic and environmental factors. Among these factors, nutrition can play an important role. The Geometric Framework of Nutrition has promoted a better understanding of the role of the macronutrient proportion in animal development, survival, reproduction, and behavior, and can help to disentangle its modulatory effect on animal personality. In this study, we investigated the effects of protein to carbohydrate (P:C) ratio in the personality of the cockroach Blaptica dubia. Newly emerged adults were fed over a period of eight weeks on five different diets varying in their P:C ratio and their diet consumption, mass variation, survival, exploratory behavior, and mobility were assessed. We found that females, unlike males, were able to regulate their nutrient intake and preferred carbohydrate-rich diets. Females also gained more body mass and lived longer compared to males. In addition, their behavior and mobility were not affected by the diet. In males, however, high-protein diets induced a bolder personality. We suggest that the sex-specific effects observed on both survival and behavior are related to the nutrient intake regulation capacity and might improve the species’ fitness in adverse nutritional conditions.publishe

Collective response to perturbations in a data-driven fish school model

22 pages, 9 figures and 3 videos in the supplementary materialInternational audienceFish schools are able to display a rich variety of collective states and behav-ioural responses when they are confronted by threats. However, a school's response to perturbations may be different depending on the nature of its collective state. Here we use a previously developed data-driven fish school model to investigate how the school responds to perturbations depending on its different collective states, we measure its susceptibility to such perturbations, and exploit its relation with the intrinsic fluctuations in the school. In particular, we study how a single or a small number of perturbing individuals whose attraction and alignment parameters are different from those of the main population affect the long-term behaviour of a school. We find that the responsiveness of the school to the perturbations is maximum near the transition region between milling and schooling states where the school exhibits multistability and regularly shifts between these two states. It is also in this region that the susceptibility, and hence the fluctuations, of the polarization order parameter is maximal. We also find that a significant school's response to a perturbation only happens below a certain threshold of the noise to social interactions ratio

Average decay of the fish speed right after a kick.

<p>This decay can be reasonably described by an exponential decay with a relaxation time <i>τ</i>₀ ≈ 0.80s (violet dashed line).</p

A group of two fish from the study species <i>Hemigrammus rhodostomus</i>.

<p>Credits to David Villa ScienceImage/CBI/CNRS, Toulouse, 2015.</p

Tracking.

<p>A: Background image in grayscale extracted from a video file of an experiment with the biggest tank (radius <i>R</i> = 353 mm). B: Arena estimated from user-defined mask. The outer bold circle of radius <i>R</i> is derived from the mask drawn by the user of the tracking software and defining the area where tracking occurs. Inner dashed circle has arbitrary radius 0.85×<i>R</i>. C: Estimated walls of the tank. D: Estimation of the radius along the circle. Red line stands for cubic spline smoothing and extrapolation over 2000 angular points. The signal is repeated 3 times to improve estimation on limits (at 0 and 2<i>π</i>). The second period is kept to compute wall distances. Estimation of local polynomials is done on 30 equally spaced ranges over one period. Dashed line shows the average radius. E: Distribution of estimated radius in pixels. Red line stands for estimation of the average, used as radius approximation to compute the ratio of pixel to millimeters (PixelsToMm ratio is equal to 0.71 for this video). F: Trajectory of a fish during 40 seconds (2000 points) reported inside the estimated walls. Filled and empty circle respectively stand for start and end points.</p