SEARCH · Search bioRxiv

Results for “Animal Behavior and Cognition”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 595 records · Page 33Linked to original sources

bioRxiv2018

Genetic distance and social compatibility in the aggregation behavior of Japanese toad tadpoles

From microorganism to vertebrates, living things often exhibit social aggregation. One of anuran larvae, dark-bodied toad tadpoles (genus Bufo) are known to aggregate against predators. When individuals share genes from a common ancestor for whom social aggregation was a functional trait, they are also likely to share common recognition cues regarding association preferences, while greater genetic distances make cohesive aggregation difficult. In this study, we conducted quantitative analyses to examine aggregation behavior among three lineages of toad tadpoles: Bufo japonicus japonicus, B. japonicus formosus, and B. gargarizans miyakonis. To determine whether there is a correlation between cohesiveness and genetic similarity among group members, we conducted an aggregation test using 42 cohorts consisting of combinations drawn from a laboratory-reared set belonging to distinct clutches. As genetic indices, we used mitochondrial DNA (mtDNA) and major histocompatibility complex (MHC) class II alleles. The results clearly indicated that aggregation behavior in toad tadpoles is directly influenced by genetic distances based on mtDNA sequences and not on MHC haplotypes. Cohesiveness among heterogeneous tadpoles is negatively correlated with the geographic dispersal of groups. Our findings suggest that social incompatibility among toad tadpoles reflects phylogenetic relationships.

animal behavior and cognition↗

bioRxiv2018

Efficiency of island homing by sea turtles under multimodal navigating strategies

A dot in the vastness of the Atlantic, Ascension Island remains a lifelong goal for the green sea turtles that hatched there, returning as adults every three or four years to nest. This navigating puzzle was brought to the scientific communitys attention by Charles Darwin and remains a topic of considerable speculation. Various cues have been suggested, with orientation to geomagnetic field elements and following odour plumes to their island source among the most compelling. Via a comprehensive in silico investigation we test the hypothesis that multimodal cue following, in which turtles utilise multiple guidance cues, is the most effective strategy. Specifically, we combine agent-based and continuous-level modelling to simulate displaced virtual turtles as they attempt to return to the island. Our analysis shows how population homing efficiency improves as the number of utilised cues is increased, even under \"extreme\" scenarios where the overall strength of navigating information decreases. Beyond the paradigm case of green turtles returning to Ascension Island, we believe this could commonly apply throughout animal navigation.

animal behavior and cognition↗

bioRxiv2018

Testosterone drives status-specific patterns of cooperation and transmission of behavior in a social network

Stable cooperation requires plasticity whereby individuals are able to express competitive or cooperative behaviors depending on social context. To date, however, the physiological mechanisms that underlie behavioral variation in cooperative systems are poorly understood. We studied hormone-mediated behavior in the wire-tailed manakin (Pipra filicauda), a gregarious songbird whose cooperative partnerships are crucial for fitness. We used automated telemetry to monitor > 36,000 cooperative interactions among male manakins over three field seasons, and we examined how circulating testosterone affects cooperation using > 500 hormone samples. Observational data show that in non-territorial floater males, high testosterone is associated with increased cooperative behaviors and subsequent ascension to territorial status. In territory-holding males, however, both observational and experimental evidence demonstrate that high testosterone antagonizes cooperation. Moreover, circulating testosterone explains significant variation (2-8%) in social behavior within each status class. Collectively, our findings show that the hormonal control of cooperation depends on a males social status. We propose that the status-dependent reorganization of hormone-regulatory pathways can facilitate stable cooperative partnerships, and thus provide direct fitness benefits for males.

animal behavior and cognition↗

bioRxiv2018

Access schedules mediate the impact of high fat diet on ethanol intake in mice.

Alcoholism and high fat diet (HFD)-induced obesity individually promote insulin resistance and glucose intolerance in clinical populations, increasing risk for metabolic diseases. Conversely, animal studies, typically utilizing forced/continuous alcohol (EtOH) access, tend to show that EtOH intake mitigates HFD-induced effects on insulin and glucose function, while HFD decreases voluntary EtOH intake in continuous access models. However, the impact of HFD on intermittent EtOH intake and resultant changes to metabolic function are not well characterized. The present studies sought to determine if HFD alters EtOH intake in male C57Bl/6J mice given differing two-bottle choice EtOH access schedules, and to assess resultant impact on insulin sensitivity and glucose tolerance. In the first experiment, mice had Unlimited Access EtOH (UAE)+HFD (n=15; HFD=60% calories from fat, 10% EtOH v/v, ad libitum) or UAE+Chow (n=15; control diet=16% calories from fat, ad libitum) for 6 weeks. UAE+HFD mice had lower EtOH preference, consumed significantly less EtOH, and were insulin resistant and hyperglycemic compared with UAE+Chow mice. In the second experiment, mice had Limited Access EtOH (LAE, 4 hrs/d; 3 d/wk)+HFD (n=15) or LAE+Chow (n=15) with increasing EtOH concentrations (10%, 15%, 20%). LAE+HFD mice had no difference in total EtOH consumption compared to LAE+Chow mice, but exhibited hyperglycemia, insulin resistance, and glucose intolerance. In the third experiment, mice had intermittent HFD access (single 24 hr session/week) with limited access to EtOH (iHFD-E, 4hrs/d; 4 d/wk) (n=10). iHFD-E mice displayed binge eating behaviors and consumed significantly more EtOH than mice given ad libitum chow or HFD, suggesting transfer of binge eating to binge drinking behaviors. Although iHFD-E mice did not have significantly altered body composition, they developed insulin insensitivity and glucose intolerance. These results suggest that access schedules determine the impact of HFD on EtOH consumption and resultant metabolic dysfunction.

animal behavior and cognition↗

bioRxiv2018

Red squirrels mitigate costs of territory defence through social plasticity

For territorial species, the ability to be behaviourally plastic in response to changes in their social environment may be beneficial by allowing individuals to mitigate conflict with conspecifics and reduce the costs of territoriality. Here we investigated whether North American red squirrels (Tamiasciurus hudsonicus) were able to minimize costs of territory defence by adjusting behaviour in response to the familiarity of neighbouring conspecifics. Since red squirrels living in familiar neighbourhoods face reduced intrusion risk, we predicted that increasing familiarity among territorial neighbours would allow squirrels to spend less time on territorial defence and more time in the nest. Long-term behavioural data (1995-2004) collected from the same squirrels across several different social environments indicated that red squirrels reduced rates of territorial vocalizations and increased nest use in response to increasing familiarity with neighbours. In contrast, cross-sectional data (2015-2016), which provided observations from each individual in a single social environment, did not provide evidence of this plasticity. Post-hoc analyses revealed that evidence of social plasticity in this system was primarily due to within-individual changes in behaviour, which we were unable to estimate in the cross-sectional data. Our results demonstrate that red squirrels can reduce the costs of territoriality by appropriately adjusting behaviour in response to changes in their social environment. However, our results also suggest that estimating plasticity by comparing behaviour among individuals (i.e. cross-sectional analyses) may not always be reliable. Our ability to detect these effects may therefore depend on having data with multiple observations from the same individuals across different social environments.

animal behavior and cognition↗

bioRxiv2018

Computer vision and deep learning automates nocturnal rainforest ant tracking to provide insight into behavior and disease risk

Determining how ant colonies optimize foraging while mitigating disease risk provides insight into how the ants have achieved ecological success. Fungal infected cadavers surround the main foraging trails of the carpenter ant Camponotus rufipes, offering a system to study how foragers behave given the persistent occurrence of disease threats. Studies on social insect foraging behavior typically require many hours of human labor due to the high density of individuals. To overcome this, we developed deep learning based computer vision algorithms to track foraging ants, frame-by-frame, from video footage. We found foragers can be divided into behavioral categories based on how straight they walk across the trail. Eighty percent of ants walk directly across the trail, while 20% wander or circle when crossing the trail. Departure from the main trail encourages exploration of new areas and could enhance discovery of new food resources. Conversely, results from our agent-based model simulations suggest deviation from a straight path exposes foragers to more infectious fungal spores. Consistency in walking behavior may protect most ants from infection, while the foragers with increased exposure due to their mode of walking could be a sufficient number of new hosts to sustain disease in this environment.

animal behavior and cognition↗

bioRxiv2026

Copulation calls indicate fertility but do not reflect female mate competition in wild Guinea baboons

Across different modalities, signals play a core role in attracting mates and influencing mating success. In several non-human primate species, females produce calls during mating that are thought to promote male competition over receptive females. The extent to which social system characteristics modulate the function of copulation calls remains less clear. We studied copulation calls in wild Guinea baboons (Papio papio), who live in a multilevel society structured around units in which females associate and mate almost exclusively with a single male. We hypothesised that females use copulation calls as an indirect form of mate competition, with competition increasing in larger units. In addition, we hypothesised that females are more likely to mate again after calling. We analysed 6116 copulations between 2014 and 2025, involving 99 reproductively active females and 78 subadult and adult males. Females produced copulation calls in 72.7% of copulations, with large inter-individual variation. Neither unit size nor its interaction with the female's swelling size or the presence of simultaneously receptive females affected the probability of calling. A survival analysis with a subset of the data (2353 copulations) revealed no effect of calling on the latency to the next mating. Our results render the hypothesis that female Guinea baboons use calls in indirect mate competition unlikely. Yet, the probability of calling varied with sexual swelling size, suggesting that calls signal female fertility. Possibly, Guinea baboon copulation calls represent an evolutionary remnant, no longer under selective pressure, and can be considered index signals of female fertility.

animal behavior and cognition↗

bioRxiv2026

Detection of Frustration-related Operant Behavior in Rats via Machine Learning Methods

Despite its strong link to neuropsychiatric conditions, frustration remains critically understudied in humans and animals alike. Therefore, there is an urgent need to develop tools to understand and therapeutically target frustration-related functions. Interestingly, humans and rats respond similarly during frustrative nonreward by increasing barpress durations. We previously validated barpress duration in rat operant tasks as a reliable measure of frustration-related behavior; however, it is wellknown that in addition to duration of responding, emotional states such as frustration alter other aspects of responding such as force of pressing. One-dimensional, static measures such as maximum force could miss rich information contained within operant data. Thus, the objective of this study is to apply machine learning (ML) to force/time profiles to discriminate frustration-related barpresses from non-frustration-related barpresses. Results showed an AUROC for FR1 (i.e., non-frustrated) vs. extinction (frustrated condition) for individual barpresses of 0.65 that improved to 0.84 with a chunk size of 10. The model generalized well to progressive ratio responding, a different kind of frustration procedure. We conclude that force/time profiling does provide utility beyond one dimensional measures of duration or force separately, meaning that we can indeed infer the internal state of frustration from behavior using ML techniques. Importantly, this project will also serve as proof-of-concept for applying ML to predict other internal states from barpress data.

animal behavior and cognition↗

bioRxiv2026

Rapid phase resetting of Aedes aegypti circadian rhythms by transient alterations in light exposure

Circadian clocks enable mosquitoes to anticipate recurring environmental variations and coordinate behaviors critical for survival and disease transmission, such as locomotion, reproduction, host-seeking, and blood-feeding, with times of day when performance is maximal. In Aedes aegypti, locomotor activity follows a robust diurnal rhythm shaped by endogenous circadian clocks and environmental cues, among which light has been shown to be the primary source of temporal information. While early studies established the role of light in regulating locomotor activity, behavior, oviposition and pupation, it remains unclear which features of a light cycle drive changes in circadian rhythms. This question is increasingly relevant as Ae. aegypti is frequently exposed to artificial and dynamic lighting conditions in urban environments. Here, we investigated how transient changes in light schedules influence circadian rhythms in locomotor activity by systematically manipulating the timing, duration, and direction of light exposure. Using a high-throughput assay, we tested over 1900 individuals, including wild-type and timeless knockout mutants, and showed that a single day of al tered lighting is sufficient to induce robust phase shifts, with no evidence of masking effects. A 6-hour light pulse was sufficient to re-entrain mosquitoes regardless of the timing of the pulse, and phase shifts were primarily driven by the offset time of the light pulse, indicating that light-offset acts as a major zeitgeber. Together, these findings challenge conventional assumptions about the timescale of circadian synchronization and highlight the remarkable plasticity of mosquito behavior in response to anthropogenic light. Eventually, these effects could explain the rapid adaptation of the species to urban environments and have potential consequences for disease transmission dynamics.

animal behavior and cognition↗

bioRxiv2026

Autism-risk gene mutations convergently disrupt sexually dimorphic oxytocin circuits to lower social engagement

Autism arises from diverse genetic risk factors, yet how they converge to produce core symptoms and contribute to its sex bias remains unestablished. Oxytocin increases sociability in multiple murine autism models, presenting an opportunity to identify a potentially shared mechanistic basis across etiologies. Here we show that spontaneous social investigation triggers overlapping patterns of aberrant functional connectivity across social and sensory brain regions in two knockout (KO) mouse models, which are rescued by oxytocin. We also report that, during social investigation, wildtype mice exhibit sexually dimorphic oxytocin release and neuronal activity dynamics in the nucleus accumbens and the amygdala. These patterns are disrupted in both KO models, but can be restored by sex- and circuit-specific stimulation of endogenous oxytocin release, accompanied by enhanced social engagement. These findings identify impaired oxytocin recruitment of sexually dimorphic social circuits as a convergent consequence of autism-risk gene mutations that may underlie low sociability.

animal behavior and cognition↗

bioRxiv2026

Who rests with whom? Sex composition and group demography shape resting associations in free-ranging dogs

Free-ranging dogs frequently rest near conspecifics, but the demographic factors structuring their resting associations remain poorly understood. We quantified dyadic resting associations in 26 free-ranging dog groups in West Bengal, India, observed between 2019 and 2023. Association strength was estimated from scan based resting co-occurrences using the Half-Weight Index. We tested whether dyadic association strength varied with dyad sex composition, dyad life stage composition, group size, and group sex ratio using a generalised additive model for location, scale and shape that accounted for group identity and repeated occurrence of individuals across dyads. Male-male dyads had lower association strengths than female-female dyads, whereas mixed-sex dyads did not differ from female-female dyads. Association strength decreased with increasing group size but increased as the male-to-female ratio within the group increased, while life-stage composition had no detectable effect. Individual level network metrics, including strength, reach, clustering coefficient, affinity, and eigenvector centrality, did not vary with sex or season. Mixed-sex pairs were also frequently represented among the strongest dyadic associations within groups. These findings indicate that resting associations in free-ranging dogs vary with dyad sex composition and group demography. Further opportunity-controlled analyses are required to determine whether the prominence of mixed-sex dyads reflects preferential association rather than group composition alone.

animal behavior and cognition↗

bioRxiv2026

Exploring rhythmic and melodic preferences in budgerigars: Individual and possible sex-related variation

Budgerigars (Melopsittacus undulatus) are vocal-learning birds with well-developed auditory abilities, but how they behaviorally evaluate melodic and rhythmic structure in sound sequences remains unclear. We examined whether budgerigars show preferences for these acoustic features and whether such preferences differ between the sexes. Three male and three female budgerigars were presented with four 8-s sound sequences in a preference apparatus: Simple (no pitch or temporal variation), Melody (pitch variation only), Rhythm (temporal variation only), and Complex (both pitch and temporal variation). Preference was quantified as the time spent in the area associated with each stimulus. No statistically significant differences among the four stimuli were detected within individuals. However, effect-size estimates indicated that two females spent more time with sequences containing rhythmic structure, whereas males showed no consistent preference related to either melodic or rhythmic components. Multidimensional scaling further suggested greater separation among stimulus conditions in females than in males. Consistent with this pattern, condition differentiation indices were higher in all three females than in all three males, although the sex difference was not statistically significant. These results suggest a possible sex-related difference in how budgerigars behaviorally weight temporal structure, with females showing greater differentiation among auditory sequence types under the present testing conditions.

animal behavior and cognition↗

bioRxiv2017

Control of recollection by slow gamma dominating medium gamma in hippocampus CA1

Behavior is used to assess memory and cognitive deficits in animals like Fmrl-null mice that model Fragile X Syndrome, but behavior is a proxy for unknown neural events that define cognitive variables like recollection. We identified an electrophysiological signature of recollection in mouse dorsal CA1 hippocampus. During a shocked-place avoidance task, slow gamma (SG: 30-50 Hz) dominates mid-frequency gamma (MG: 70-90 Hz) oscillations 2-3 seconds before successful avoidance, but not failures. Wild-type but not Fmrl-null mice rapidly adapt to relocating the shock; concurrently, SG/MG maxima (SGdominance) decrease in wild-type but not in cognitively inflexible Fmrl-null mice. During SGdominance, putative pyramidal cell ensembles represent distant locations; during place avoidance, these are avoided places. During shock relocation, wild-type ensembles represent distant locations near the currently-correct shock zone but Fmrl-null ensembles represent the formerly-correct zone. These findings indicate that recollection occurs when CA1 slow gamma dominates mid-frequency gamma, and that accurate recollection of inappropriate memories explains Fmrl-null cognitive inflexibility.

neuroscience↗

bioRxiv2017

Effects of Human-Animal Interaction on Dog Salivary and Plasma Oxytocin and Vasopressin

Oxytocin (OT) and Vasopressin (AVP) are neuropeptides with diverse effects on social behavior, cognition and stress responses. Recent studies suggest that OT facilitates and responds to affiliative forms of human-animal interaction (HAI). However, previous studies measuring OT and AVP in dogs have been limited to measures from blood or urine, which present concerns related to the invasiveness of sample collection, the potential for matrix interference in immunoassays, and whether samples can be collected at precise time points to assess event-linked endocrine responses. Previous studies from our laboratory validated salivary measures of OT and AVP in dogs, however, it is currently unknown whether these measures respond dynamically to aspects of HAI. Here, we investigated the effects of affiliative forms of HAI on both plasma and salivary OT and AVP in dogs. We employed a between-subjects design with a group of Labrador retrievers and Labrador retriever X golden retriever crosses (23 females, 15 males). Half of the dogs engaged in 10 minutes of free-form friendly interaction with a human experimenter (HAI condition), and the other half rested quietly in the same environment, without human interaction (control condition). We collected blood and saliva samples before, and immediately following both experimental conditions, and all samples were analyzed using enzyme-linked immunosorbent assays (ELISAs) following previously validated protocols. Dogs participating in HAI exhibited a significant increase in both salivary OT (+39%) and plasma OT (+5.7%) whereas dogs in the control group did not. Salivary AVP showed no change in the HAI group but increased significantly (+33%) in the control group. Plasma AVP decreased significantly following HAI (-13%) but did not change across time in the control condition. Within the dogs exposed to HAI, increases in salivary OT, and decreases in plasma AVP, were predicted by the extent of affiliative behaviour between the dog and human (indexed by scores from a principal components analysis of social behaviours between the dog and human). Collectively our results suggest that measures of salivary OT and AVP provide useful biomarkers in studies of HAI, and afford a flexible and noninvasive toolkit than can be employed in diverse research contexts.

animal behavior and cognition↗

bioRxiv2018

Wide and Deep Imaging of Neuronal Activities by a Wearable NeuroImager Reveals Premotor Activity in the Whole Motor Cortex

Wearable technologies for functional whole brain imaging in freely moving animals would advance our understanding of cognitive processing and adaptive behavior. Fluorescence imaging can visualize the activity of individual neurons in real time, but conventional microscopes have limited sample coverage in both the width and depth of view. Here we developed a novel head-mounted laser camera (HLC) with macro and deep-focus lenses that enable fluorescence imaging at cellular resolution for comprehensive imaging in mice expressing a layer- and cell type-specific calcium probe. We visualized orientation selectivity in individual excitatory neurons across the whole visual cortex of one hemisphere, and cell assembly expressing the premotor activity that precedes voluntary movement across the motor cortex of both hemispheres. Including options for multiplex and wireless interfaces, our wearable, wide- and deep-imaging HLC technology could enable simple and economical mapping of neuronal populations underlying cognition and behavior.

neuroscience↗

bioRxiv2018

A single-cell level and connectome-derived computational model of the Drosophila brain

Computer simulations play an important role in testing hypotheses, integrating knowledge, and providing predictions of neural circuit functions. While considerable effort has been dedicated into simulating primate or rodent brains, the fruit fly (Drosophila melanogaster) is becoming a promising model animal in computational neuroscience for its small brain size, complex cognitive behavior, and abundancy of data available from genes to circuits. Moreover, several Drosophila connectome projects have generated a large number of neuronal images that account for a significant portion of the brain, making a systematic investigation of the whole brain circuit possible. Supported by FlyCircuit (http://www.flycircuit.tw), one of the largest Drosophila neuron image databases, we began a long-term project with the goal to construct a whole-brain spiking network model of the Drosophila brain. In this paper, we report the outcome of the first phase of the project. We developed the Flysim platform, which 1) identifies the polarity of each neuron arbor, 2) predicts connections between neurons, 3) translates morphology data from the database into physiology parameters for computational modeling, 4) reconstructs a brain-wide network model, which consists of 20,089 neurons and 1,044,020 synapses, and 5) performs computer simulations of the resting state. We compared the reconstructed brain network with a randomized brain network by shuffling the connections of each neuron. We found that the reconstructed brain can be easily stabilized by implementing synaptic short-term depression, while the randomized one exhibited seizure-like firing activity under the same treatment. Furthermore, the reconstructed Drosophila brain was structurally and dynamically more diverse than the randomized one and exhibited both Poisson-like and patterned firing activities. Despite being at its early stage of development, this single-cell level brain model allows us to study some of the fundamental properties of neural networks including network balance, critical behavior, long-term stability, and plasticity.

bioinformatics↗

bioRxiv2018

Animal learning in amultidimensional discrimination task as explained by dimension-specific allocation of attention

Reinforcement learning describes the process by which during a series of trial-and-error attempts, actions that culminate in reward are strengthened. When the actions are based on sensory stimuli, an association is formed between the stimulus, the action and the reward. Computational, behavioral and neurobiological accounts of this process successfully explain simple stimulus-response learning. However, if the cue is multi-dimensional, identifying which of its features are relevant for the reward is not trivial, and the underlying cognitive process is poorly understood. To study this we adapted an intra-dimensional/ extra-dimensional set-shifting paradigm to train rodents on a multidimensional sensory discrimination task. In our setup, stimuli of different modalities (spatial, olfactory and visual) are combined into complex cues and manipulated independently. In each set, only a single stimulus dimension is relevant for reward. To distinguish between learning and decision-making we suggest a weighted attention model (WAM). It combines a learning model where each feature-dimension is reinforced separately with a decision rule that chooses an alternative according to a weighted average of learnt values, in which weight is associated with each dimension. We estimated the parameters of the WAM (decision weights, learning rate and noise) and demonstrated that is outperforms an alternative model in which a value learnt is assigned to each combination of features, or every state. Estimated decision weights of WAM reveal an experience-based bias in learning. The intra-dimensional set shift separated the decision weights. While in the first phase of the experiment the weights were roughly the same, in the second phase the weight on the dimension that was key to finding the reward became higher than others. After the extra-dimensional shift this dimension became irrelevant, however its decision weight remained high for the early learning stage in this last phase, providing an explanation for the poor performance of the animals. By the end of the phase when the rats performance improved, the weights for the two dimensions converged. Thus, estimated weights can be viewed as a possible way to quantify the experience-based bias.

animal behavior and cognition↗

bioRxiv2018

Considerations in using recurrent neural networks to probe neural dynamics

Recurrent neural networks (RNNs) are increasingly being used to model complex cognitive and motor tasks performed by behaving animals. Here, RNNs are trained to reproduce animal behavior while also recapitulating key statistics of empirically recorded neural activity. In this manner, the RNN can be viewed as an in silico circuit whose computational elements share similar motifs with the cortical area it is modeling. Further, as the RNN's governing equations and parameters are fully known, they can be analyzed to propose hypotheses for how neural populations compute. In this context, we present important considerations when using RNNs to model motor behavior in a delayed reach task. First, by varying the network's nonlinear activation and rate regularization, we show that RNNs reproducing single neuron firing rate motifs may not adequately capture important population motifs. Second, by visualizing the RNN's dynamics in low-dimensional projections, we demonstrate that even when RNNs recapitulate key neurophysiological features on both the single neuron and population levels, it can do so through distinctly different dynamical mechanisms. To militate between these mechanisms, we show that an RNN consistent with a previously proposed dynamical mechanism is more robust to noise. Finally, we show that these dynamics are sufficient for the RNN to generalize to a target switch task it was not trained on. Together, these results emphasize important considerations when using RNN models to probe neural dynamics.

neuroscience↗