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Results for “Animal Behavior and Cognition”

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bioRxiv2018

Changes in social groups across reintroductions and effects on post-release survival

Reintroductions are essential to many conservation programmes, and thus much research has focussed on understanding what determines the success of these translocation interventions. However, while reintroductions disrupt both the abiotic and social environments, there has been less focus on the consequences of social disruption. Therefore, here we investigate if moving familiar social groups may help animals (particularly naive juveniles) adjust to their new environment and increase the chances of population establishment. We used social network analysis to study changes in group composition and individual sociality across a reintroduction of 40 juvenile hihi (Notiomystis cincta), a threatened New Zealand passerine. We collected observations of groups before a translocation to explore whether social behaviour before the reintroduction predicted associations after, and whether reintroduction influenced individual sociality (degree). We also assessed whether grouping familiar birds during temporary captivity in aviaries maintained group structure and individual sociality, compared to our normal translocation method (aviaries of random familiarity). Following release, we measured if survival depended on how individual sociality had changed. By comparing these analyses with birds that remained at the source site, we found that translocation lead to re-assortment of groups: non-translocated birds maintained their groups, but translocated juveniles formed groups with both familiar and unfamiliar birds. Aviary holding did not improve group cohesion; instead, juveniles were less likely to associate with aviary-mates. Finally, we found that translocated juveniles that lost the most associates experienced a small but significant tendency for higher mortality. This suggests sociality loss may have represented a disruption that affected their ability to adapt to a new site.

animal behavior and cognition↗

bioRxiv2018

Dynamic network partnerships and social contagion drive cooperation

Both reciprocity and positive assortment (like with like) are predicted to promote the evolution of cooperation, yet how partners influence each others behavior within dynamic networks is not well understood. One way to test this question is to partition phenotypic variation into differences among individuals in the expression of cooperative behavior (the \"direct effect\"), and plasticity within individuals in response to the social environment (the \"indirect effect\"). A positive correlation between these two sources of variation, such that more cooperative individuals elicit others to cooperate, is predicted to facilitate social contagion and selection on cooperative behavior. Testing this hypothesis is challenging, however, because it requires repeated measures of behavior across a dynamic social landscape. Here, we use an automated data-logging system to quantify the behavior of 179 wire-tailed manakins, birds that form cooperative male-male coalitions, and we use multiple-membership models to test the hypothesis that dynamic network partnerships shape within-individual variation in cooperative behavior. Our results show strong positive correlations between a birds own sociality and his estimated effect on his partners, consistent with the hypothesis that cooperation begets cooperation. These findings support the hypothesis that social contagion can facilitate selection for cooperative behavior within social networks.

animal behavior and cognition↗

bioRxiv2018

Social networks in the presence and absence of visual cues

We compared the social dynamics of two populations of the live-bearing Atlantic molly (Poecilia mexicana) that live in adjacent habitats with very different predator regimes: cave mollies that inhabit a low-predation environment inside a sulfidic cave with a low density of predatory water bugs (Belostoma sp.), and mollies that live directly outside the cave (henceforth called \"surface\" mollies) in a high-predation environment with a high density of fish-eating birds. We filmed the social interactions of marked fish in both environments and analysed their social network dynamics using a Markov model under two different fish densities of 12 and 6 fish per 0.36 m2. As expected, surface mollies spent overall much more time social than cave mollies. This difference in overall social time was a result of surface mollies being less likely to discontinue social contact (once they had a social partner) and being more likely to resume social contact (once alone) than cave mollies. Interestingly surface mollies were also less likely to leave a current social partner than cave mollies. At low density, mollies (in both environments) were expected to show reduced social encounters which should dramatically change their social dynamics. Surface mollies, however, displayed an ability to maintain their social dynamics at low density (primarily by reducing the convex polygon spanned by the group) which was not observed in cave mollies. Despite the fact that we only compared two populations, our data provide a mechanistic explanation for density compensations of social dynamics that have also been observed in other fish species and give an example of how comparisons between the social dynamics of different populations can be made that go beyond conventional network analyses.

animal behavior and cognition↗

bioRxiv2018

Velocity estimation in reinforcement learning

The current work aims to study how people make predictions, under a reinforcement learning framework, in an environment that fluctuates from trial to trial and is corrupted with Gaussian noise. A computer-based experiment was developed where subjects were required to predict the future location of a spaceship that orbited around planet Earth. Its position was sampled from a Gaussian distribution with the mean changing at a variable velocity and four different values of variance that defined our signal-to-noise conditions. Three error-driven algorithms using a Bayesian approach were proposed as candidates to describe our data. The first is the standard delta-rule. The second and third models are delta rules incorporating a velocity component which is updated using prediction errors. The third model additionally assumes a hierarchical structure where individual learning rates for velocity and decision noise come from Gaussian distributions with means following a hyperbolic function. We used leave-one-out cross-validation and the Widely Applicable Information Criterion to compare the predictive accuracy of these models. In general, our results provided evidence in favor of the hierarchical model and highlight two main conclusions. First, when facing an environment that fluctuates from trial to trial, people can learn to estimate its velocity to make predictions. Second, learning rates for velocity and decision noise are influenced by uncertainty constraints represented by the signal-to-noise ratio. This higher order control was modeled using a hierarchical structure, which qualitatively accounts for individual variability and is able to generalize and make predictions about new subjects on each experimental condition.

animal behavior and cognition↗

bioRxiv2018

Finding structure in multi-armed bandits

How do humans search for rewards? This question is commonly studied using multi-armed bandit tasks, which require participants to trade off exploration and exploitation. Standard multi-armed bandits assume that each option has an independent reward distribution. However, learning about options independently is unrealistic, since in the real world options often share an underlying structure. We study a class of structured bandit tasks, which we use to probe how generalization guides exploration. In a structured multi-armed bandit, options have a correlation structure dictated by a latent function. We focus on bandits in which rewards are linear functions of an options spatial position. Across 5 experiments, we find evidence that participants utilize functional structure to guide their exploration, and also exhibit a learning-to-learn effect across rounds, becoming progressively faster at identifying the latent function. Our experiments rule out several heuristic explanations and show that the same findings obtain with non-linear functions. Comparing several models of learning and decision making, we find that the best model of human behavior in our tasks combines three computational mechanisms: (1) function learning, (2) clustering of reward distributions across rounds, and (3) uncertainty-guided exploration. Our results suggest that human reinforcement learning can utilize latent structure in sophisticated ways to improve efficiency.

animal behavior and cognition↗

bioRxiv2018

Identification of C elegans strains using a fully convolutional neural network on behavioural dynamics

The nematode C. elegans is a promising model organism to understand the genetic basis of behaviour due to its anatomical simplicity. In this work, we present a deep learning model capable of discerning genetically diverse strains based only on their recorded spontaneous activity, and explore how its performance changes as different embeddings are used as input. The model outperforms hand-crafted features on strain classification when trained directly on time series of worm postures.

animal behavior and cognition↗

bioRxiv2018

Diverse food-sensing neurons trigger idiothetic local search in Drosophila

Resources are often sparsely clustered in nature. Thus, foraging animals may benefit from remembering the location of a newly discovered food patch while continuing to explore nearby [1, 2]. For example, after encountering a drop of yeast or sugar, hungry flies often perform a local search consisting of frequent departures and returns to the food site [3, 4]. Fruit flies, Drosophila melanogaster, can perform this food-centered search behavior in the absence of external stimuli or landmarks, instead relying solely on internal (idiothetic) cues to keep track of their location [5]. This path integration behavior may represent a deeply conserved navigational capacity in insects [6, 7], but the neural pathways underlying food-triggered searches remain unknown. Here, we used optogenetic activation to screen candidate cell classes and found that local searches can be initiated by diverse sensory neurons including sugar-sensors, water-sensors, olfactory-receptor neurons, as well as hunger-signaling neurons of the central nervous system. Optogenetically-induced searches resemble those triggered by actual food and are modulated by starvation state. Furthermore, search trajectories exhibit key features of path integration: searches remain tightly centered around the fictive-food site, even during long periods without reinforcement, and flies re-center their searches when they encounter a new fictive-food site. Flies can even perform elaborate local searches within a constrained maze. Together, these results suggest that flies enact local searches in response to a wide variety of food-associated cues, and that these sensory pathways may converge upon a common neural system for path integration. Optogenetically induced local searches in Drosophila can now serve as a tractable system for the study of spatial memory and navigation in insects.

animal behavior and cognition↗

bioRxiv2018

Conditional approach as cooperation in predator inspection: a role for serotonin?

In guppies (Poecilia reticulata), a small number of individuals break away from a shoal and approach a potential predator, a behavior termed "predator inspection". These animals often employ a "conditional approach" strategy, in which an individual approaches the predator in the first move and subsequently approaches it only if a second individual swims even with it during inspection. This strategy is analogous to the "tit-for-tat" strategy of the Prisoners Dilemma, suggesting that it could be used to study cooperation. Serotonin is thought to mediate cooperative behavior in other fish species. Exposure to the animated image of a predator in a tank that contained a parallel mirror - mimicking an equally cooperating conspecific - promoted inspection and decreased refuge use, but increased freezing, suggesting that conditional approach is also associated with fear. To understand whether serotonin participates in conditional approach in guppies, we treated animals with either vehicle (Cortlands salt solution), fluoxetine (2.5 mg/kg) or metergoline (1 mg/kg), and tested then in a predator inspection paradigm. Fluoxetine increased the time the animal spent inspecting the predator image, while metergoline decreased it. Fluoxetine also decreased time spent avoiding the predator and increased freezing, while metergoline decreased freezing. These results suggest that phasic increases in serotonin levels promote conditional approach, suggesting a role for this neurotransmitter in cooperation. Preprint: https://doi.org/10.1101/436345; Data and scripts: https://github.com/lanec-unifesspa/TFT

animal behavior and cognition↗

bioRxiv2018

Deep Convolutional Network for Animal Sound Classification and Source Attribution using Dual Audio Recordings

We introduce an end-to-end feedforward convolutional neural network that is able to reliably classify the source and type of animal calls in a noisy environment using two streams of audio data after being trained on a dataset of modest size and imperfect labels. The data consists of audio recordings from captive marmoset monkeys housed in pairs, with several other cages nearby. Our network can classify both the call type and which animal made it with a single pass through a single network using raw spectrogram images as input. The network vastly increases data analysis capacity for researchers interested in studying marmoset vocalizations, and allows data collection in the home cage, in group housed animals.

animal behavior and cognition↗

bioRxiv2018

A tagging method for very small fish

Identifying individuals over time and across contexts is essential in many scientific fields. There are a variety of well-established methods for uniquely marking individuals (e.g., visible implant elastomer, barcodes, paint). However, for some species, life history stages, and/or experiments, existing methods are not sufficient. Here, we describe procedures for how two tagging methods - a tattoo ink injection method and a fishing line piercing method - can be used with the youngest, smallest juveniles of the African cichlid fish, Astatotilapia burtoni, which are too small for the methods used with adults. With the tattoo method, we injected tattoo ink into the dorsal muscle. Different colors and injection locations can be used to distinguish among individuals over a period of weeks (up to 4 weeks, average 2.5-3 weeks under our conditions). Because fish this young and small are sensitive to handling and injection, we also include physiological data showing fish recover well from anesthetization and tagging. With the piercing method, very thin fishing line is threaded through the dorsal muscle and tied into a barbell or loop. Unique colors and patterns can be used to distinguish among individuals over a period of months. Because a physical tag might impede normal movement in a very small fish, we also include data from an open field exploration test showing similar behavior between tagged and control (non-tagged) juveniles. We expect these effective and inexpensive methods to be useful for a variety of small species and will facilitate early-life, developmental, and longitudinal research.

animal behavior and cognition↗

bioRxiv2018

Aggression and discrimination among closely versus distantly related species of Drosophila

Fighting between different species is widespread in the animal kingdom, yet this phenomenon has been relatively understudied in the field of aggression research. Particularly lacking are studies that test the effect of genetic distance, or relatedness, on aggressive behavior between species. Here we characterized male-male aggression within and between species of fruit flies across the Drosophila phylogeny. We show that male Drosophila discriminate between conspecifics and heterospecifics and show a bias for the target of aggression that depends on the genetic relatedness of opponent males. Specifically, males of closely related species treated conspecifics and heterospecifics equally, whereas males of distantly related species were overwhelmingly aggressive toward conspecifics. To our knowledge, this is the first study to quantify aggression between Drosophila species and to establish a behavioral bias for aggression against conspecifics versus heterospecifics. Our results suggest that future study of heterospecific aggression behavior in Drosophila is warranted to investigate the degree to which these trends in aggression among species extend to broader behavioral, ecological, and evolutionary contexts.

animal behavior and cognition↗

bioRxiv2018

Encoding of an engram for food location by satiety-promoting Drd2 hippocampal neurons

Associative learning guides feeding behavior in mammals in part by using cues that link location in space to food availability. However, the elements of the top-down circuitry encoding the memory of the location of food is largely unknown, as are the high-order processes that control satiety. Here we report that hippocampal dopamine 2 receptor (D2R) neurons are specifically activated by food and that modulation of their activity reduce food intake in mice. We also found that activation of these neurons interferes with the valence of food and the acquisition of a spatial memory linking food to a location via projections from the hippocampus to the lateral septum. Finally, we showed that inputs from lateral entorhinal cortex (LEC) to the hippocampus can also drive satiety via activation of D2R cells. These data describe a previously unidentified function for hippocampal D2R cells to regulate feeding behavior and identifies a LEC->Hippocampus->Septal high-order circuit that encodes the memory of food location.

animal behavior and cognition↗

bioRxiv2018

An inexpensive air stream temperature controller and its use to facilitate temperature controlled behavior in living Drosophila

Controlling the environment of an organism has many biologically relevant applications. Temperature-dependent inducible biological reagents have proven invaluable for elucidating signaling cascades and dissection of neural circuits. Here we develop a simple and affordable system for rapidly changing temperature in a chamber housing adult Drosophila melanogaster. Utilizing flies expressing the temperature inducible channel dTrpA1 in dopaminergic neurons, we show rapid and reproducible changes in locomotor behavior. This device should have wide application to temperature modulated biological reagents.\n\nMethod SummaryWe develop widely applicable and affordable solution to rapidly changing temperature within an enclosed chamber using commercially available components.

animal behavior and cognition↗

bioRxiv2018

Ablation of NMDA receptors in dopamine neurons disrupts attribution of incentive salience to reward-paired stimuli

Midbrain dopamine (DA) neurons play a crucial role in the formation of conditioned associations between environmental cues and appetitive events. Activation of N-methyl-D-aspartate (NMDA) receptors is a key mechanism responsible for the generation of conditioned responses of DA neurons to reward cues. Here, we tested the effects of the cell type-specific inactivation of NMDA receptors in DA neurons in adult mice on stimulus-reward learning. Animals were trained in a Pavlovian learning paradigm in which they had to learn the predictive value of two conditioned stimuli, one of which (CS+) was paired with the delivery of a water reward. Over the course of conditioning, mutant mice learned that the CS+ predicted reward availability, and they approached the reward receptacle more frequently during CS+ trials than CS- trials. However, conditioned responses to the CS+ were weaker in the mutant mice, possibly indicating that they did not attribute incentive salience to the CS+. To further assess whether the attribution of incentive salience was impaired by the mutation, animals were tested in a conditioned reinforcement test. The test revealed that mutant mice made fewer instrumental responses paired with CS+ presentation, confirming that the CS+ had a weaker incentive value. Taken together, these results indicate that reward prediction learning does occur in the absence of NMDA receptors in DA neurons, but the ability of reward-paired cues to invigorate and reinforce behavior is lost.

animal behavior and cognition↗

bioRxiv2018

Loose social organisation of AB strain zebrafish groups in a two-patch environment

We study the collective behaviour of zebrafish shoals of different numbers of individuals (1, 2, 3, 5, 7, 10 and 20 AB zebrafish Danio rerio) in a constraint environment composed of two identical square rooms connected by a corridor. This simple set-up is similar to a natural patchy environment. We track the positions and the identities of the fish and compute the metrics at the group and at the individual levels. First, we show that the number of fish affects the behaviour of each individual in a group, the cohesion of the groups, the preferential interactions and the transition dynamics between the two rooms. Second, during collective departures, we show that the rankings of exit correspond to the topological organisations of the fish prior to their collective departure. This spatial organisation appears in the group a few seconds before a collective departure. These results provide new evidences on the spatial organisation of the groups and the effect of the number of fish on individual and collective behaviours in a patchy environment.

animal behavior and cognition↗

bioRxiv2018

A confirmation bias in perceptual decision-making due to hierarchical approximate inference

Making good decisions requires updating beliefs according to new evidence. This is a dynamical process that is prone to biases: in some cases, beliefs become entrenched and resistant to new evidence (leading to primacy effects), while in other cases, beliefs fade over time and rely primarily on later evidence (leading to recency effects). How and why either type of bias dominates in a given context is an important open question. Here, we study this question in classic perceptual decision-making tasks, where, puzzlingly, previous empirical studies differ in the kinds of biases they observe, ranging from primacy to recency, despite seemingly equivalent tasks. We present a new model, based on hierarchical approximate inference and derived from normative principles, that not only explains both primacy and recency effects in existing studies, but also predicts how the type of bias should depend on the statistics of stimuli in a given task. We verify this prediction in a novel visual discrimination task with human observers, finding that each observers temporal bias changed as the result of changing the key stimulus statistics identified by our model. By fitting an extended drift-diffusion model to our data we rule out an alternative explanation for primacy effects due to bounded integration. Taken together, our results resolve a major discrepancy among existing perceptual decision-making studies, and suggest that a key source of bias in human decision-making is approximate hierarchical inference.

animal behavior and cognition↗

bioRxiv2018

Vocal motor experiences consolidate the vocal motor circuitry and accelerate future vocal skill development

Complex motor skills take considerable time and practice to learn. Without continued practice the level of skill performance quickly degrades, posing a problem for the timely utilization of skilled motor responses. Here we quantified the recurring development of vocal motor skills and the accompanying changes in synaptic connectivity in the brain of a songbird, while manipulating skill performance by consecutively administrating and withdrawing testosterone. We demonstrate that a songbird with prior singing experience can significantly accelerate the re-acquisition of vocal performance. We further demonstrate that an increase in vocal performance is accompanied by a pronounced synaptic pruning in the forebrain vocal motor area HVC, a reduction that is not reversed when birds stop singing. These results provide evidence that lasting synaptic changes in the motor circuitry are associated with the savings of motor skills, enabling a rapid recovery of motor performance under environmental time constraints.

animal behavior and cognition↗

bioRxiv2018

The allometry of brain size in mammals

Why some animals have big brains and others do not has intrigued scholars for millennia. Yet, the taxonomic scope of brain size research is limited to a few mammal lineages. Here we present a brain size dataset compiled from the literature for 1552 species with representation from 28 extant taxonomic orders. The brain-body size allometry across all mammals is (Brain) = -1.26 (Body)0.75. This relationship shows strong phylogenetic signal as expected due to shared evolutionary histories. Slopes using median species values for each order, family, and genus, to ensure evolutionary independence, approximate [~]0.75 scaling. Why brain size scales to the [3/4] power to body size across mammals is, to our knowledge, unknown. Slopes within taxonomic orders exhibiting smaller size ranges are often shallower than 0.75 and range from 0.24 to 0.81 with a median slope of 0.64. Published brain size data is lacking for the majority of extant mammals (>70% of species) with strong bias in representation from Primates, Carnivores, Perrisodactyla, and Australidelphian marsupials (orders Dasyuromorphia, Diprotodontia, Peramelemorphia). Several orders are particularly underrepresented. For example, brain size data are available for less than 20% of species in each of the following speciose lineages: Soricomorpha, Rodentia, Lagomorpha, Didelphimorphia, and Scandentia. Use of museum collections can decrease the current taxonomic bias in mammal brain size data and tests of hypothesis.

animal behavior and cognition↗