Most downloaded biology preprints, all time
in category animal behavior and cognition
1,718 results found. For more information, click each entry to expand.
1,698 downloads bioRxiv animal behavior and cognition
Like a moth into the flame - Phototaxis is an iconic example for innate preferences. Such preferences likely reflect evolutionary adaptations to predictable situations and have traditionally been conceptualized as hard-wired stimulus-response links. Perhaps therefore, the century-old discovery of flexibility in Drosophila phototaxis has received little attention. Here we report that across several different behavioral tests, light/dark preference tested in walking is dependent on various aspects of flight. If we temporarily compromise flying ability, walking photopreference reverses concomitantly. Neuronal activity in circuits expressing dopamine and octopamine, respectively, plays a differential role in photopreference, suggesting a potential involvement of these biogenic amines in this case of behavioral flexibility. We conclude that flies monitor their ability to fly, and that flying ability exerts a fundamental effect on action selection in Drosophila. This work suggests that even behaviors which appear simple and hard-wired comprise a value-driven decision-making stage, negotiating the external situation with the animal′s internal state, before an action is selected.
1,673 downloads bioRxiv animal behavior and cognition
Collective behaviors of groups of animals, such as schooling and shoaling of fish, are central to species survival, but genes that regulate these activities are not known. Here we parsed collective behavior of groups of adult zebrafish using computer vision and unsupervised machine learning into a set of highly reproducible, unitary, several hundred millisecond states and transitions, which together can account for the entirety of relative positions and postures of groups of fish. Using CRISPR-Cas9 we then targeted for knockout 35 genes associated with autism and schizophrenia. We found mutations in three genes had distinctive effects on the amount of time spent in the specific states or transitions between states. Mutation in immp2l (inner mitochondrial membrane peptidase 2-like gene) enhances states of cohesion, so increases shoaling; mutation in in the Nav1.1 sodium channel, scn1lab+/- causes the fish to remain scattered without evident social interaction; and mutation in the adrenergic receptor, adra1aa-/-, keeps fish close together and retards transitions between states, leaving fish motionless for long periods. Motor and visual functions seemed relatively well-preserved. This work shows that the behaviors of fish engaged in collective activities are built from a set of stereotypical states. Single gene mutations can alter propensities to collective actions by changing the proportion of time spent in these states or the tendency to transition between states. This provides an approach to begin dissection of the molecular pathways used to generate and guide collective actions of groups of animals.
1,666 downloads bioRxiv animal behavior and cognition
Jeremy Koster, Richard Mcelreath, Kim Hill, Douglas Yu, Glenn Shepard, Nathalie Van Vliet, Michael Gurven, Hillard Kaplan, Benjamin Trumble, Rebecca Bliege Bird, Douglas Bird, Brian Codding, Lauren Coad, Luis Pacheco-Cobos, Bruce Winterhalder, Karen Lupo, Dave Schmitt, Paul Sillitoe, Margaret Franzen, Michael Alvard, Vivek Venkataraman, Thomas Kraft, Kirk Endicott, Stephen Beckerman, Stuart A. Marks, Thomas Headland, Margaretha Pangau-Adam, Anders Siren, Karen Kramer, Russell Greaves, Victoria Reyes-García, Maximilien Guèze, Romain Duda, Álvaro Fernández-Llamazares, Sandrine Gallois, Lucentezza Napitupulu, Roy Ellen, John Ziker, Martin R. Nielsen, Elspeth Ready, Christopher Healey, Cody Ross
Human adaptation depends upon the integration of slow life history, complex production skills, and extensive sociality. Refining and testing models of the evolution of human life history and cultural learning will benefit from increasingly accurate measurement of knowledge, skills, and rates of production with age. We pursue this goal by inferring individual hunters' of hunting skill gain and loss from approximately 23,000 hunting records generated by more than 1,800 individuals at 40 locations. The model provides an improved picture of ages of peak productivity as well as variation within and among ages. The data reveal an average age of peak productivity between 30 and 35 years of age, though high skill is maintained throughout much of adulthood. In addition, there is substantial variation both among individuals and sites. Within study sites, variation among individuals depends more upon heterogeneity in rates of decline than in rates of increase. This analysis sharpens questions about the co-evolution of human life history and cultural adaptation. It also demonstrates new statistical algorithms and models that expand the potential inferences drawn from detailed quantitative data collected in the field.
1,664 downloads bioRxiv animal behavior and cognition
Absolute pitch (AP), the rare ability to name any musical note without the aid of a reference note, is thought to depend on acquisition during an early critical period of development. Although recent research has shown that adults can improve AP abilities in a brief (60 minute) training session, the best learners in that study still did not achieve note classification performance comparable to performance of a genuine AP possessor. For the first time, we demonstrate that genuine AP levels of performance can be trained in eight weeks for some adults, with the best learner passing all measures of AP ability after training and retaining this knowledge for at least four months after training. The AP measures included the same used in previous assessments of AP ability. These results reject strong critical period accounts of AP acquisition, demonstrating clearly that explicit perceptual training in adults can lead to AP performance that is indistinguishable from AP that results from childhood development.
1,635 downloads bioRxiv animal behavior and cognition
Perception is a subjective experience that depends on the expectations and beliefs of an observer. Psychophysical measures provide an objective yet indirect characterization of this experience by describing the dependency between the physical properties of a stimulus and the corresponding perceptually guided behavior. Two fundamental psychophysical measures characterize an observer's perception of a stimulus: how well the observer can discriminate the stimulus from similar ones (discrimination threshold) and how strongly the observer's perceived stimulus value deviates from the true stimulus value (perceptual bias). It has long been thought that these two perceptual characteristics are independent. Here we demonstrate that discrimination threshold and perceptual bias show a surprisingly simple mathematical relation. The relation, which we derived from assumptions of optimal sensory encoding and decoding, is well supported by a wide range of reported psychophysical data including perceptual changes induced by spatial and temporal context, and attention. The large empirical support suggests that the proposed relation represents a new law of human perception. Our results imply that universal rules govern the computational processes underlying human perception.
1,624 downloads bioRxiv animal behavior and cognition
In spite of its importance as a life-defining rhythmic movement and its constant rhythmic contraction and relaxation of the body, respiration has not received attention in Embodied Cognition (EC) literature. Our paper aims to show that (1) exerts significant and unexpected bottom-up influence on cognitive processes, and (2) it does so by modulating neural synchronization that underlies specific cognitive processes. Then, (3) we suggest that the particular example of respiration may function as a model for a general mechanism through which the body influences cognitive functioning. Finally, (4) we work out the implications for embodied cognition, draw a parallel to the role of gesture, and argue that respiration sometimes plays a double, pragmatic and epistemic, role, which reduces the cognitive load. In such cases, consistent with EC, the overall cognitive activity includes a loop-like interaction between neural and non-neural elements.
1,622 downloads bioRxiv animal behavior and cognition
We introduce the contextual multi-armed bandit task as a framework to investigate learning and decision making in uncertain environments. In this novel paradigm, participants repeatedly choose between multiple options in order to maximise their rewards. The options are described by a number of contextual features which are predictive of the rewards through initially unknown functions. From their experience with choosing options and observing the consequences of their decisions, participants can learn about the functional relation between contexts and rewards and improve their decision strategy over time. In three experiments, we find that participants' behaviour is surprisingly adaptive to the learning environment. We model participants' behaviour by context-blind (mean-tracking, Kalman filter) and contextual (Gaussian process regression parametrized with different kernels) learning approaches combined with different choice strategies. While participants generally learn about the context-reward functions, they tend to rely on a local learning strategy which generalizes previous experience only to highly similar instances. In a relatively simple task with binary features, they mostly combine this local learning with an “expected improvement” decision strategy which focuses on alternatives that are expected to improve the most upon a current favourite option. In a task with continuous features that are linearly related to the rewards, they combine local learning with a “upper confidence bound” decision strategy that more explicitly balances exploration and exploitation. Finally, in a difficult learning environment where the relation between features and rewards is non-linear, most participants learn locally as before, whereas others regress to more context-blind strategies.
1,620 downloads bioRxiv animal behavior and cognition
Geomagnetic field can be used by different magnetoreception mechanisms, for navigation and orientation by honeybees. The present study analyzed the effects of magnetic field on honeybees. This study was carried out in 2017 at the Bayburt University Beekeeping Application Station. In this study, the effect of Electro Magnetic field (EMF) and electric field (EF) on the time of finding the source of food of honeybees and the time of staying there were determined. The honeybees behaviors were analyzed in the presence of external magnetic fields generated by Helmholtz coils equipment. The Electro Magnetic field values of the coils were fixed to 0 T (90mV/m), 50 T (118 mV/m), 100 T (151 mV/m), 150 T (211 mV/m), 200 T (264 mV/m). Petri dishes filled with sugar syrup were placed in the center of the coils. According to the study, honeybees visited at most U1 (mean =21.0 17.89 bees) and at least U5 (mean =10.82 11.77 bees). Honeybees waited for the longest time in U1 (mean =35.27 6.97 seconds) and at least in U5 (mean =12.28 5.58 seconds). According to the results obtained from this first study showed that honeybees are highly affected by electromagnetic radiation and electric field.
1,593 downloads bioRxiv animal behavior and cognition
Animals display characteristic behavioral patterns when performing a task, such as the spiraling of a soaring bird or the surge-and-cast of a male moth searching for a female. Identifying such conserved patterns occurring rarely in noisy behavioral data is key to understanding the behavioral response to a distributed stimulus in unrestrained animals. Existing models seek to describe the dynamics of behavior or segment individual locomotor episodes rather than to identify occasional, transient irregularities that make up the behavioral response. To fill this gap, we develop a lexical, hierarchical model of behavior. We designed an unsupervised algorithm called "BASS" to efficiently identify and segment conserved behavioral action sequences transiently occurring in long behavioral recordings. When applied to navigating larval zebrafish, BASS extracts a dictionary of remarkably long, non-Markovian sequences consisting of repeats and mixtures of slow forward and turn bouts. Applied to a novel chemotaxis assay, BASS uncovers conserved chemotactic strategies deployed by zebrafish to avoid aversive cues consisting of sequences of fast large-angle turns and burst swims. In a simulated dataset of soaring gliders climbing thermals, BASS finds the spiraling patterns characteristic of soaring behavior. In both cases, BASS succeeds in identifying action sequences that are highly conserved but transient in the behavior deployed by freely moving animals. BASS can be easily incorporated into the pipelines of existing behavioral analyses across diverse species, and even more broadly used as a generic algorithm for pattern recognition in low-dimensional sequential data. ### Competing Interest Statement C.W. and O.M. disclose a potential conflict of interest with the commercialization of the tracking algorithm ZebraZoom (www.zebrazoom.org). The authors declare no conflict of interest otherwise.
1,589 downloads bioRxiv animal behavior and cognition
In recent years, the study of polarization vision in animals has seen numerous breakthroughs, not just in terms of what is known about the function of this sensory ability, but also in the experimental methods by which polarization can be controlled, presented and measured. Once thought to be limited to only a few animal species, polarization sensitivity is now known to be widespread across many taxonomic groups, and advances in experimental techniques are, in part, responsible for these discoveries. Nevertheless, its study remains challenging, perhaps because of our own poor sensitivity to the polarization of light, but equally as a result of the slow spread of new practices and methodological innovations within the field. In this review, we introduce the most important steps in designing and calibrating polarized stimuli, within the broader context of areas of current research and the applications of new techniques to key questions. Our aim is to provide a constructive guide to help researchers, particularly those with no background in the physics of polarization, to design robust experiments that are free from confounding factors.
1,583 downloads bioRxiv animal behavior and cognition
Human decisions are known to be systematically biased. A prominent example of such a bias occurs when integrating a sequence of sensory evidence over time. Previous empirical studies differ in the nature of the bias they observe, ranging from favoring early evidence (primacy), to favoring late evidence (recency). Here, we present a unifying framework that explains these biases and makes novel psychophysical and neurophysiological predictions. By explicitly modeling both the approximate and the hierarchical nature of inference in the brain, we show that temporal biases depend on the balance between ''sensory information'' and ''category information'' in the stimulus. Finally, we present new data from a human psychophysics task that confirm that temporal biases can be robustly changed within subjects as predicted by our models.
1,579 downloads bioRxiv animal behavior and cognition
The evolution of animal colouration is importantly driven by sexual selection operating on traits used to transmit information to rivals and potential mates, which therefore, have major impacts on fitness. Reflectance spectrometry has become a standard colour-measuring tool, especially after the discovery of tetrachromacy in birds and their ability to detect UV. Birds? plumage patterns may be invisible to humans, necessitating a reliable and objective way of assessing colouration not dependent on human vision. Plumage colouration measurements can be taken directly on live birds in the field or in the lab (e.g. on collected feathers). Therefore, it is essential to determine which sampling method yields more repeatable and reliable measures, and which of the available quantitative approaches best assess the repeatability of these measures. Using a spectrophotometer, we measured melanin-based colouration in barn swallows? (Hirundo rustica) plumage. We assessed the repeatability of measures obtained with both traditional sampling methods separately to quantitatively determine their reliability. We used the ANOVA-based method for calculating the repeatability of measurements from two years separately, and the GLMM-based method to calculate overall adjusted repeatabilities for both years. We repeated the assessment for the whole reflectance spectrum range and only the human-visible part, to assess the influence of the UV component on the reliabilities of sampling methodologies. Our results reveal very high repeatability for lab measurements and a lower, still moderate to high repeatability, for field measurements. Both increased when limited to only the human-visible part, for all plumage patches except the throat, where we observed the opposite trend. Repeatability between sampling methods was quite low including the whole spectrum, but moderate including only the human-visible part. Our results suggest higher reliability for measurements in the lab and higher power and accuracy of the GLMM-based method. They also suggest UV reflectance differences amongst different plumage patches.
1,566 downloads bioRxiv animal behavior and cognition
Animal behavior is often quantified through subjective, incomplete variables that may mask essential dynamics. Here, we develop a behavioral state space in which the full instantaneous state is smoothly unfolded as a combination of short-time posture dynamics. Our technique is tailored to multivariate observations and extends previous reconstructions through the use of maximal prediction. Applied to high-resolution video recordings of the roundworm C. elegans , we discover a low-dimensional state space dominated by three sets of cyclic trajectories corresponding to the worm's basic stereotyped motifs: forward, backward, and turning locomotion. In contrast to this broad stereotypy, we find variability in the presence of locally-unstable dynamics, and this unpredictability shows signatures of deterministic chaos: a collection of unstable periodic orbits together with a positive maximal Lyapunov exponent. The full Lyapunov spectrum is symmetric with positive, chaotic exponents driving variability balanced by negative, dissipative exponents driving stereotypy. The symmetry is indicative of damped, driven Hamiltonian dynamics underlying the worm's movement control.
1,547 downloads bioRxiv animal behavior and cognition
Making good decisions requires people to appropriately explore their available options and generalize what they have learned. While computational models have successfully explained exploratory behavior in constrained laboratory tasks, it is unclear to what extent these models generalize to complex real world choice problems. We investigate the factors guiding exploratory behavior in a data set consisting of 195,333 customers placing 1,613,967 orders from a large online food delivery service. We find important hallmarks of adaptive exploration and generalization, which we analyze using computational models. We find evidence for several theoretical predictions: (1) customers engage in uncertainty-directed exploration, (2) they adjust their level of exploration to the average restaurant quality in a city, and (3) they use feature-based generalization to guide exploration towards promising restaurants. Our results provide new evidence that people use sophisticated strategies to explore complex, real-world environments.
1,521 downloads bioRxiv animal behavior and cognition
The social network structure of animal populations has major implications for survival, reproductive success, sexual selection, and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output to data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance.
1,503 downloads bioRxiv animal behavior and cognition
Vocalization is an essential medium for social and sexual signaling in most birds and mammals. Consequently, the analysis of vocal behavior is of great interest to fields such as neuroscience and linguistics. A standard approach to analyzing vocalization involves segmenting the sound stream into discrete vocal elements, calculating a number of handpicked acoustic features, and then using the feature values for subsequent quantitative analysis. While this approach has proven powerful, it suffers from several crucial limitations: First, handpicked acoustic features may miss important dimensions of variability that are important for communicative function. Second, many analyses assume vocalizations fall into discrete vocal categories, often without rigorous justification. Third, a syllable-level analysis requires a consistent definition of syllable boundaries, which is often difficult to maintain in practice and limits the sorts of structure one can find in the data. To address these shortcomings, we apply a data-driven approach based on the variational autoencoder (VAE), an unsupervised learning method, to the task of characterizing vocalizations in two model species: the laboratory mouse ( Mus musculus ) and the zebra finch ( Taeniopygia guttata ). We find that the VAE converges on a parsimonious representation of vocal behavior that outperforms handpicked acoustic features on a variety of common analysis tasks, including representing acoustic similarity and recovering a known effect of social context on birdsong. Additionally, we use our learned acoustic features to argue against the widespread view that mouse ultrasonic vocalizations form discrete syllable categories. Lastly, we present a novel “shotgun VAE” that can quantify moment-by-moment variability in vocalizations. In all, we show that data-derived acoustic features confirm and extend existing approaches while offering distinct advantages in several critical applications.
1,500 downloads bioRxiv animal behavior and cognition
Avelino Javer, Michael Currie, Chee Wai Lee, Jim Hokanson, Kezhi Li, Céline N Martineau, Eviatar Yemini, Laura J Grundy, Chris Li, QueeLim Ch’ng, William R Schafer, Ellen A.A. Nollen, Rex Kerr, André E.X. Brown
Animal behavior is increasingly being recorded in systematic imaging studies that generate large data sets. To maximize the usefulness of these data there is a need for improved resources for analyzing and sharing behavior data that will encourage re-analysis and method development by computational scientists. However, unlike genomic or protein structural data, there are no widely used standards for behavior data. It is therefore desirable to make the data available in a relatively raw form so that different investigators can use their own representations and derive their own features. For computational ethology to approach the level of maturity of other areas of bioinformatics, we need to address at least three challenges: storing and accessing video files, defining flexible data formats to facilitate data sharing, and making software to read, write, browse, and analyze the data. We have developed an open resource to begin addressing these challenges using worm tracking as a model.
1,496 downloads bioRxiv animal behavior and cognition
We introduce the spatially correlated multi-armed bandit as a task coupling function learning with the exploration-exploitation trade-off. Participants interacted with bi-variate reward functions on a two-dimensional grid, with the goal of either gaining the largest average score or finding the largest payoff. By providing an opportunity to learn the underlying reward function through spatial correlations, we model to what extent people form beliefs about unexplored payoffs and how that guides search behavior. Participants adapted to assigned payoff conditions, performed better in smooth than in rough environments, and--surprisingly--sometimes performed equally well in short as in long search horizons. Our modeling results indicate a preference for local search options, which when accounted for, still suggests participants were best-described as forming local inferences about unexplored regions, combined with a search strategy that directly traded off between exploiting high expected rewards and exploring to reduce uncertainty about the spatial structure of rewards.
1,496 downloads bioRxiv animal behavior and cognition
Hunting mode or the distinct set of behavioural strategies that a predator employs while hunting can be an important determinant of the prey organism?s behavioural response. However, few studies have considered the predator?s hunting mode while describing differences in anti-predatory behaviours of a prey species. Here we document the influence of active hunters (zebra jumping spiders, Salticus scenicus) and ambush predators (Chinese praying mantids, Tenodera aridifolia sinensis) on the capture deterrence anti-predatory behavioural repertoire of the model organism, Drosophila melanogaster. We hypothesized that D. melanogaster would reduce overall locomotory activity in the presence of ambush predators, and increase them with active hunters. First we observed and described the behavioural repertoire of D. melanogaster in the presence of the predators. We documented three previously undescribed behaviours- abdominal lifting, stopping and retreat- which were performed at higher frequency by D. melanogaster in the presence of predators, and may aid in capture deterrence. Consistent with our predictions, we observed an increase in the overall activity of D. melanogaster in the presence of jumping spiders (active hunter). However, counter to our prediction, mantids (ambush hunter) had only a modest influence on activity. Given these new insights into Drosophila behaviour, and with the genetic tools available, dissecting the molecular mechanisms of anti-predator behaviours may now be feasible in this system.
1,486 downloads bioRxiv animal behavior and cognition
Cognitive models are a fundamental tool in computational neuroscience, embodying in software precise hypotheses about the algorithms by which the brain gives rise to behavior. The development of such models is often largely a hypothesis-first process, drawing on inspiration from the literature and the creativity of the individual researcher to construct a model, and afterwards testing the model against experimental data. Here, we adopt a complementary data-first approach, in which richly characterizing and summarizing the patterns present in a dataset reveals an appropriate cognitive model, without recourse to an a priori hypothesis. We apply this approach to a large behavioral dataset from rats performing a dynamic reward learning task. The model revealed suggests that behavior on this task can be understood as a mixture of three components with different timescales: a quick-learning reward-seeking component, a slower-learning perseverative component, and a very slow "gambler's fallacy" component.
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