Most downloaded biology preprints, all time
in category animal behavior and cognition
1,718 results found. For more information, click each entry to expand.
2,028 downloads bioRxiv animal behavior and cognition
Adult Drosophila melanogaster fruit flies were placed into one end of a tube near to repellents (benzaldehyde and heat) and away from the other end containing attractants (light and a favored temperature). They escaped from the repellents and went to the attractants. Five motile mutants that failed to do that were isolated. They did not respond to any external attractants tested or external repellents tested. In addition, they did not respond well to internal sensory stimuli like hunger, thirst, and sleep. The mutants, although motile, failed to respond to stimuli at both 34C and at room temperature. Some of the mutants have been mapped. It is proposed that the information from the different sensory receptors comes together at an intermediate, called "inbetween" (Inbet), that brings about a behavioral response. The Boss is defined here.
2,017 downloads bioRxiv animal behavior and cognition
In the current research on measuring complex behaviours/phenotyping in rodents, most of the experimental design requires the experimenter to remove the animal from its home-cage environment and place it in an unfamiliar apparatus (novel environment). This interaction may influence behaviour, general well-being, and the metabolism of the animal, affecting the phenotypic outcome even if the data collection method is automated. Most of the commercially available solutions for home-cage monitoring are expensive and usually lack the flexibility to be incorporated with existing home-cages. Here we present a low-cost solution for monitoring home-cage behaviour of rodents that can be easily incorporated to practically any available rodent home-cage. To demonstrate the use of our system, we reliably predict the sleep/wake state of mice in their home-cage using only video. We validate these results using hippocampal local field potential (LFP) and electromyography (EMG) data. Our approach provides a low-cost flexible methodology for high-throughput studies of sleep, circadian rhythm and rodent behaviour with minimal experimenter interference.
1,989 downloads bioRxiv animal behavior and cognition
Retrosplenial cortex (RSC) is a region within the posterior neocortical system, heavily interconnected with an array of brain networks, both cortical and subcortical, that is engaged by a myriad of cognitive tasks. Although there is no consensus as to its precise function, evidence from both human and animal studies clearly points to a role in spatial cognition. However, the spatial processing impairments that follow RSC damage are not straightforward to characterise, leading to difficulties in defining the exact nature of its role. In the present article we review this literature and classify the types of ideas that have been put forward into three broad, somewhat overlapping classes: (i) Learning of landmark location, stability and permanence; (ii) Integration between spatial reference frames, and (iii) Consolidation and retrieval of spatial knowledge ('schemas'). We evaluate these models and suggest ways to test them, before briefly discussing whether the spatial function may be a subset of a more general function in episodic memory.
1,976 downloads bioRxiv animal behavior and cognition
An infant's risk of developing neuromotor impairment is primarily assessed through visual examination by specialized clinicians. Therefore, many infants at risk for impairment go undetected, particularly in under-resourced environments. There is thus a need to develop automated, clinical assessments based on quantitative measures from widely-available sources, such as video cameras. Here, we automatically extract body poses and movement kinematics from the videos of at-risk infants (N=19). For each infant, we calculate how much they deviate from a group of healthy infants (N=85 online videos) using Naive Gaussian Bayesian Surprise. After pre-registering our Bayesian Surprise calculations, we find that infants that are at higher risk for impairments deviate considerably from the healthy group. Our simple method, provided as an open-source toolkit, thus shows promise as the basis for an automated and low-cost assessment of risk based on video recordings.
1,971 downloads bioRxiv animal behavior and cognition
Several recent longitudinal studies have investigated the hormonal correlates of both young adult women's general sexual desire and, more specifically, their desire for uncommitted sexual relationships. Findings across these studies have been mixed, potentially because each study tested only small samples of women (Ns = 43, 33, and 14). Here we report results from a much larger (N = 375) longitudinal study of hormonal correlates of young adult women's general sexual desire and their desire for uncommitted sexual relationships. Our analyses suggest that within-woman changes in general sexual desire are negatively related to progesterone, but are not related to testosterone or cortisol. We observed some positive relationships for estradiol, but these were generally only significant for solitary sexual desire. By contrast with our results for general sexual desire, analyses showed no evidence that changes in women's desire for uncommitted sexual relationships are related to their hormonal status. Together, these results suggest that changes in hormonal status contribute to changes in women's general sexual desire, but do not influence women's desire for uncommitted sexual relationships.
1,958 downloads bioRxiv animal behavior and cognition
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.
1,955 downloads bioRxiv animal behavior and cognition
Martin Bulla, Mihai Valcu, Adriaan M. Dokter, Alexei G. Dondua, András Kosztolányi, Anne Rutten, Barbara Helm, Brett K. Sandercock, Bruce Casler, Bruno J. Ens, Caleb S. Spiegel, Chris J. Hassell, Clemens Küpper, Clive Minton, Daniel Burgas, David B. Lank, David C. Payer, Egor Y. Loktinov, Erica Nol, Eunbi Kwon, Fletcher Smith, H. River Gates, Hana Vitnerová, Hanna Prüter, James A. Johnson, James J. H. St Clair, Jean-François Lamarre, Jennie Rausch, Jeroen Reneerkens, Jesse R. Conklin, Joana Burger, Joe Liebezeit, Joël Bêty, Jonathan T. Coleman, Jordi Figuerola, Jos C. E. W. Hooijmeijer, José A Alves, Joseph A. M. Smith, Karel Weidinger, Kari Koivula, Ken Gosbell, Klaus-Michael Exo, Larry Niles, Laura Koloski, Laura McKinnon, Libor Praus, Marcel Klaassen, Marie-Andrée Giroux, Martin Sládeček, Megan L. Boldenow, Michael I. Goldstein, Miroslav šálek, Nathan Senner, Nelli Rönkä, Nicolas Lecomte, Olivier Gilg, Orsolya Vincze, Oscar W. Johnson, Paul A. Smith, Paul F. Woodard, Pavel S. Tomkovich, Phil F. Battley, Rebecca Bentzen, Richard B. Lanctot, Ron Porter, Sarah T. Saalfeld, Scott Freeman, Stephen C. Brown, Stephen Yezerinac, Tamás Székely, Tomás Montalvo, Theunis Piersma, Vanessa Loverti, Veli-Matti Pakanen, Wim Tijsen, Bart Kempenaers
The behavioural rhythms of organisms are thought to be under strong selection, influenced by the rhythmicity of the environment1-4. Such behavioural rhythms are well studied in isolated individuals under laboratory conditions1,5, but free-living individuals have to temporally synchronize their activities with those of others, including potential mates, competitors, prey and predators6-10. Individuals can temporally segregate their daily activities (e.g. prey avoiding predators, subordinates avoiding dominants) or synchronize their activities (e.g. group foraging, communal defence, pairs reproducing or caring for offspring)6,9-11. The behavioural rhythms that emerge from such social synchronization and the underlying evolutionary and ecological drivers that shape them remain poorly understood5-7,9. Here, we address this in the context of biparental care, a particularly sensitive phase of social synchronization12 where pair members potentially compromise their individual rhythms. Using data from 729 nests of 91 populations of 32 biparentally-incubating shorebird species, where parents synchronize to achieve continuous coverage of developing eggs, we report remarkable within- and between-species diversity in incubation rhythms. Between species, the median length of one parent′s incubation bout varied from 1-19 hours, while period length - the time in which a parent′s probability to incubate cycles once between its highest and lowest value - varied from 6-43 hours. The length of incubation bouts was unrelated to variables reflecting energetic demands, but species relying on crypsis (the ability to avoid detection by other animals) had longer incubation bouts than those that are readily visible or actively protect their nest against predators. Rhythms entrainable to the 24-h light dark cycle were less prevalent at high latitudes and absent in 18 species. Our results indicate that even under similar environmental conditions and despite 24-h environmental cues, social synchronization can generate far more diverse behavioural rhythms than expected from studies of individuals in captivity5-7,9. The risk of predation, not the risk of starvation, may be a key factor underlying the diversity in these rhythms.
1,945 downloads bioRxiv animal behavior and cognition
Homare Yamahachi, Anja T. Zai, Ryosuke O. Tachibana, Anna E. Stepien, Diana I. Rodrigues, Sophie Cavé-Lopez, Gagan Narula, Juneseung Lee, Ziqiang Huang, Heiko Hörster, Daniel Düring, Richard H. R. Hahnloser
Over the past 50 years, songbirds have become a valuable model organism for scientists studying vocal communication from its behavioral, hormonal, neuronal, and genetic perspectives. Many advances in our understanding of vocal learning result from research using the zebra finch, a close-ended vocal learner. We review some of the manipulations used in zebra finch research, such as isolate housing, transient/irreversible impairment of hearing/vocal organs, implantation of small devices for chronic electrophysiology, head fixation for imaging, aversive song conditioning using sound playback, and mounting of miniature backpacks for behavioral monitoring. We highlight the use of these manipulations in scientific research, and estimate their impact on animal welfare, based on the literature and on data from our past and ongoing work. The assessment of harm-benefits tradeoffs is a legal prerequisite for animal research in Switzerland. We conclude that a diverse set of known stressors reliably lead to suppressed singing rate, and that by contraposition, increased singing rate may be a useful indicator of welfare. We hope that our study can contribute to answering some of the most burning questions about zebra finch welfare in research on vocal behaviors.
1,929 downloads bioRxiv animal behavior and cognition
Neuroscience needs behavior, and behavioral experiments require the coordination of large numbers of heterogeneous hardware components and data streams. Currently available tools strongly limit the complexity and reproducibility of experiments. Here we introduce Autopilot, an open-source Python framework that distributes experiments over networked swarms of Raspberry Pis. Autopilot enables qualitatively greater experimental flexibility by allowing arbitrary numbers of hardware components to be combined in arbitrary experimental designs. Research is made reproducible by documenting all data and task design parameters in a human-readable and publishable format at the time of collection. Autopilot provides an order-of-magnitude performance improvement over existing tools while also being an order of magnitude less costly to implement. Autopilot's flexible, scalable architecture allows neuroscientists to design the next generation of experiments to investigate the behaving brain.
1,924 downloads bioRxiv animal behavior and cognition
Spatial navigation, active sensing, and most cognitive functions rely on a tight link between motor output and sensory input. Virtual reality (VR) systems simulate the sensorimotor loop, allowing flexible manipulation of enriched sensory input. Conventional rodent VR systems provide 3D visual cues linked to restrained locomotion on a treadmill, leading to a mismatch between visual and most other sensory inputs, sensory-motor conflicts, as well as restricted naturalistic behavior. To rectify these limitations, we developed a VR system (ratCAVE) that provides realistic and low-latency visual feedback directly to head movements of completely unrestrained rodents. Immersed in this VR system, rats displayed naturalistic behavior by spontaneously interacting with and hugging virtual walls, exploring virtual objects, and avoiding virtual cliffs. We further illustrate the effect of ratCAVE-VR manipulation on hippocampal place fields. The newly-developed methodology enables a wide range of experiments involving flexible manipulation of visual feedback in freely-moving behaving animals.
1,912 downloads bioRxiv animal behavior and cognition
We present ethoscopes, machines for high-throughput analysis of behaviour in Drosophila and other animals. Ethoscopes provide a software and hardware solution that is reproducible and easily scalable; they perform, in real-time, tracking and profiling of behaviour using a supervised machine learning algorithm; they can deliver behaviourally-triggered stimuli to flies in a feedback-loop mode; and they are highly customisable and open source. Ethoscopes can be built easily using 3D printing technology and rely on Raspberry Pi microcomputers and Arduino boards to provide affordable and flexible hardware. All software and construction specifications are available at http://lab.gilest.ro/ethoscope .
1,832 downloads bioRxiv animal behavior and cognition
Stress-related illnesses such as major depressive and anxiety disorders are characterized by maladaptive responses to stressful life events. Chronic stress-based animal models have provided critical insight into the understanding of these responses. Currently available assays measuring chronic stress-induced behavioral states in mice are limited in their design (short, not repeatable, sensitive to experimenter-bias) and often inconsistent. Using the Noldus PhenoTyper apparatus, we identified a new readout that repeatedly assesses behavioral changes induced by chronic stress in two mouse models i.e. chronic restraint stress (CRS) and chronic unpredictable mild stress (UCMS). The PhenoTyper test consists of overnight monitoring of animals’ behavior in home-cage setting before, during and after a 1hr light challenge applied over a designated food zone. We tested the reproducibility and reliability of the PhenoTyper test in assessing the effects of chronic stress exposure, and compared outcomes with commonly-used tests. While chronic stress induced heterogeneous profiles in classical tests, CRS- and UCMS-exposed mice showed a very consistent response in the PhenoTyper test. Indeed, CRS and UCMS mice continue avoiding the lit zone in favor of the shelter zone. This “residual avoidance” after the light challenge, lasted for hours beyond termination of the challenge, was not observed after acute stress and was consistently found throughout stress exposure in both models. Chronic stress-induced residual avoidance was alleviated by chronic imipramine treatment but not acute diazepam administration. This behavioral index should be instrumental for studies aiming to better understand the trajectory of chronic stress-induced deficits and potentially screen novel anxiolytics and antidepressants.
1,809 downloads bioRxiv animal behavior and cognition
Retrieving a memory can modify its influence on subsequent behavior. Whether this phenomenon arises from modification of the contents of the memory trace or its accessibility is a matter of considerable debate. We develop a computational theory that incorporates both mechanisms. Modification of the contents of the memory trace occurs through classical associative learning, but which memory trace is accessed (and thus made eligible for modification) depends on a structure learning mechanism that discovers the units of association by segmenting the stream of experience into statistically distinct clusters (latent causes). New memories are formed when the structure learning mechanism infers that a new latent cause underlies current sensory observations. By the same token, old memories are modified when old and new sensory observations are inferred to have been generated by the same latent cause. We derive this framework from probabilistic principles, and present a computational implementation. Simulations demonstrate that our model can reproduce the major experimental findings from studies of memory modification in the Pavlovian conditioning literature, including dependence on the strength and age of memories, the interval between memory retrieval and extinction, and prediction errors following retrieval.
1,787 downloads bioRxiv animal behavior and cognition
We develop an extension of the Rescorla-Wagner model of associative learning. In addition to learning from the current trial, the new model supposes that animals store and replay previous trials, learning from the replayed trials using the same learning rule. This simple idea provides a unified explanation for diverse phenomena that have proved challenging to earlier associative models, including spontaneous recovery, latent inhibition, retrospective revaluation, and trial spacing effects. For example, spontaneous recovery is explained by supposing that the animal replays its previous trials during the interval between extinction and test. These include earlier acquisition trials as well as recent extinction trials, and thus there is a gradual re-acquisition of the conditioned response. We present simulation results for the simplest version of this replay idea, where the trial memory is assumed empty at the beginning of an experiment, all experienced trials are stored and none removed, and sampling from the memory is performed at random. Even this minimal replay model is able to explain the challenging phenomena, illustrating the explanatory power of an associative model enhanced by learning from remembered as well as real experiences.
1,777 downloads bioRxiv animal behavior and cognition
A navigating animal's sensory experience is shaped not just by its surroundings, but by its movements within them, which in turn are influenced by its past experiences. Studying the intertwined roles of sensation, experience and directed action in navigation has been made easier by the development of virtual reality (VR) environments for head-fixed animals, which allow for quantitative measurements of behavior in well-controlled sensory conditions. VR has long featured in studies of Drosophila melanogaster, but these experiments have typically relied on one-dimensional (1D) VR, effectively allowing the fly to change only its heading in a visual scene, and not its position. Here we explore how flies navigate in a two-dimensional (2D) visual VR environment that more closely resembles their experience during free behavior. We show that flies' interaction with landmarks in 2D environments cannot be automatically derived from their behavior in simpler 1D environments. Using a novel paradigm, we then demonstrate that flies in 2D VR adapt their behavior in a visual environment in response to optogenetically delivered appetitive and aversive stimuli. Much like free-walking flies after encounters with food, head-fixed flies respond to optogenetic activation of sugar-sensing neurons by initiating a local search behavior. Finally, by pairing optogenetic activation of heat-sensing cells to the flies' presence near visual landmarks of specific shapes, we elicit selective learned avoidance of landmarks associated with aversive "virtual heat". These head-fixed paradigms set the stage for an interrogation of fly brain circuitry underlying flexible navigation in complex visual environments.
1,771 downloads bioRxiv animal behavior and cognition
Putative associations between sex hormones and attractive physical characteristics in women are central to many theories of human physical attractiveness and mate choice. Although such theories have become very influential, evidence that physically attractive and unattractive women have different hormonal profiles is equivocal. Consequently, we investigated hypothesized relationships between salivary estradiol and progesterone and two aspects of women's physical attractiveness that are commonly assumed to be correlated with levels of these hormones: facial attractiveness (N=249) and waist-to-hip ratio (N=247). Our analyses revealed no compelling evidence that women with more attractive faces or lower (i.e., more attractive) waist-to-hip ratios had higher levels of estradiol or progesterone. One analysis did suggest that women with more attractive waist-to-hip ratios had significantly higher progesterone, but the relationship was weak and the relationship not significant in other analyses. These results do not support the influential hypothesis that between-women differences in physical attractiveness are related to estradiol and/or progesterone.
1,747 downloads bioRxiv animal behavior and cognition
Auditory perceptual learning of pure tones causes tonotopic map expansion in the primary auditory cortex (A1), but the function this plasticity sub-serves is unclear. We developed an automated training platform called the "Educage", which was used to train mice on a go/no-go auditory discrimination task to their perceptual limits, for difficult discriminations among pure tones or natural sounds. Spiking responses of excitatory and inhibitory L2/3 neurons in mouse A1 revealed learning-induced overrepresentation of the learned frequencies, in accordance with previous literature. Using a novel computational model to study auditory tuning curves we show that overrepresentation does not necessarily improve discrimination performance of the network to the learned tones. In contrast, perceptual learning of natural sounds induced "sparsening" and decorrelation of the neural response, and consequently improving discrimination of these complex sounds. The signature of plasticity in A1 highlights its central role in coding natural sounds as compared to pure tones.
1,740 downloads bioRxiv animal behavior and cognition
Why groups of individuals sometimes exhibit collective 'wisdom' and other times maladaptive 'herding' is an enduring conundrum. Here we show that this conflict is regulated by the social learning strategies deployed. We examined the patterns of human social learning through an interactive online experiment with 699 participants, varying both task uncertainty and group size, then used hierarchical Bayesian model-fitting to identify the individual learning strategies exhibited by participants. Challenging tasks elicit greater conformity amongst individuals, with rates of copying increasing with group size, leading to high probabilities of maladaptive herding amongst large groups confronted with uncertainty. Conversely, the reduced social learning of small groups, and the greater probability that social information would be accurate for less-challenging tasks, generated 'wisdom of the crowd' effects in other circumstances. Our model-based approach provides novel evidence that the likelihood of swarm intelligence versus herding can be predicted, resolving a longstanding puzzle in the literature.
1,719 downloads bioRxiv animal behavior and cognition
In this paper a formal model of associative learning is presented which incorporates representational and computational mechanisms that, as a coherent corpus, empower it to make accurate predictions of a wide variety of phenomena that so far have eluded a unified account in learning theory. In particular, the Double Error model introduces: 1) a fully-connected network architecture in which stimuli are represented as temporally distributed elements that associate to each other, which naturally implements neutral stimuli associations and mediated learning; 2) a predictor error term within the traditional error correction rule (the double error), which reduces the rate of learning for expected predictors; 3) a revaluation associability rate that operates on the assumption that the outcome predictiveness is tracked over time so that prolonged uncertainty is learned, reducing the levels of attention to initially surprising outcomes; and critically 4) a biologically plausible variable asymptote, which encapsulates the principle of Hebbian learning, leading to stronger associations for similar levels of element activity. The outputs of a set of simulations of the Double Error model are presented along with empirical results from the literature. Finally, the predictive scope of the model is discussed.
1,707 downloads bioRxiv animal behavior and cognition
Declarative memory encompasses representations of specific events as well as knowledge extracted by accumulation over multiple episodes. To investigate how these different sorts of memories are created, we developed a new behavioral task in rodents. The task consists of three distinct conditions (stable, overlapping, random). Rodents are exposed to multiple sample trials, in which they explore objects in specific spatial arrangements. In the stable condition, the locations are constant during all sample trials; in the test trial, one objects location is changed. In the random condition, object locations are presented in the sample phase without a specific spatial pattern. In the overlapping condition, one location is shared (overlapping) between all trials while the other location changes during sample trials. We show that in the overlapping condition, instead of only remembering the last sample trial, rodents form a cumulative memory of the sample trials. Here we could show that both mice and rats can accumulate information across multiple trials and express a long-term abstracted memory.
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