Frontiers in Behavioral Neuroscience

The binary choice chamber (T-maze) assay has been used as a standard behavioural screen in Drosophila research to test mutants in terms of sensory discrimination skills and synaptic plasticity during memory consolidation and decay. Typically, ca. 100 individuals are tested as a group at the same time and the behavioural readout consists in counting the number of individuals in the testing tube exposed to a stimulus versus the number of flies in the control tube, with the normalized difference in fly count being defined as the batch preference index (PI). Unfortunately, the batch PI has widely been taken as a precise metric of group behaviour, to the point where ANOVA/t-tests have been considered the most powerful statistical tests for analyzing samples in terms of batch PI values, which has led to a hyperinflation of apparently very highly significant effects for small differences in PI values (e.g. -0.1 vs 0.1), leading to problems with replicability. Here it is shown on the basis of a well-established statistical model for binary decisions that application of the t-test to PI data implicitly assumes that each fly in a batch is an independent biological replicate in the extremely strict sense that the decision of each individual was interrogated independently of the other flies. Therefore, t-test analysis of PI data obtained with the intrinsically pseudoreplicative group assay is the cause of extremely optimistic P-values, as suggested recently by Bassetto et al. (2023) on the basis of effect size considerations for proportions. Thus, rather than using inferential statistics, PI data should be assessed on the basis of effect size. A more fundamental problem with the batch PI value is the uncertainty in whether it measures the mean individual preference and if so, with what precision, given the simple readout? This aspect is illustrated here by modelling distributions of flies in the T-maze, which suggest that the effective precision of the PI value is clearly worse than the nominal precision of +/- 0.01 for 100 flies, so that the batch PI can only serve as a rough indicator of group tendencies.

Deficits in social motivation are a core feature of many neurodevelopmental disorders, including autism spectrum disorders. While a range of tools have been developed to quantify social motivation in rodents, most rely on brief tests in dedicated apparatuses that can introduce stress and novelty, potentially reducing test reliability. Most current approaches are also typically not suited to studying learning across days or circadian rhythms of social motivation. To address these challenges, we developed a social operant task that can run around-the-clock for multiple days in the mouse homecage, continuously monitoring social motivation around the circadian cycle. The task consists of a custom-built automated door that was installed between two rodent homecages and configured so one mouse could trigger the door to open with a nose-poke action from within their cage. When open, the door allows for social interaction with the neighboring mouse through a perforated stainless-steel panel, which did not allow the mice to cross over into the neighboring cage. Mice opened the door multiple times each day, allowing us to quantify their amount and daily rhythms of social motivation. In our first experiment, C57BL/6J mice (both sexes) were individually housed with an empty adjacent cage for five days, after which a same-sex social partner was introduced for another nine days. Mice opened the door at significantly higher rates when the social partner was present vs. absent, confirming that mice were motivated to earn social interaction. This task also revealed a circadian rhythm to social motivation that peaked about 2 hours after the peak in their feeding rhythm. We speculate that mice first addressed their caloric needs each day before changing their priority to social behavior. Given prior literature implicating the dopamine system in social motivation, we also tested whether dopamine antagonists would block social motivation in our task in a new group of 14 mice (both sexes). The dopamine D1 receptor antagonist SCH23390 (delivered systemically at 0.3mg/kg SC) reduced social seeking without affecting locomotor activity or food intake, demonstrating a selective role for dopamine D1 receptors in social motivation. The dopamine D2 receptor antagonist haloperidol (delivered systemically at 0.3mg/kg SC) also reduced social seeking, but reduced locomotor activity and food intake as well, demonstrating a general reduction in behavior that was not specific to social motivation. Overall, our task offers a way for studying social motivation in the rodent homecage, which has advantages for studying disorders that involve both social and circadian disruptions.

Estimating time and making predictions is integral to our experience of the world. Given the importance of timing to most behaviors, disruptions in temporal processing and timed performance are reported in a number of neuropsychiatric disorders such as Schizophrenia, Autism Spectrum Disorder (ASD), Fragile X Syndrome (FXS), and Attention-deficit Hyperactivity Disorder (ADHD). Symptoms that implicitly include disruption in timing are atypical turn-taking during social interactions, unusual verbal intonations, poor reading, speech and language skills, inattention, delays in learning, and difficulties making predictions. Currently, there are no viable treatments for these symptoms, the reason being the underlying neural dysfunction that contributes to timing deficits in neuropsychiatric disorders is unknown. To address this unknown, we have designed a novel Temporal Pattern Discrimination Task (TPSD) for awake-behaving mice. Stimuli consist of audiovisual stimuli that differ in duration. Compared to Wild-Type (WT) mice, Fmr1-/- mice, a well-established mouse model of FXS, showed significant impairment in learning the TPSD task, as evidenced by reduced discriminability indices and atypical licking patterns. Often sensory information is multimodal and indeed studies show that learning in humans and rodents improves with multimodal stimuli than with unimodal stimuli. To test how the multimodal nature of stimuli impacted performance of Fmr1-/- mice, following training on the audiovisual stimuli, we tested mice on audio-only or visual-only stimuli. While WT mice showed significant disruption in performance when tested on unimodal stimuli, Fmr1-/- mice displayed equivalent performance on visual-only stimuli when compared to the multimodal task. Our novel task captures timing difficulties and multisensory integration issues in Fmr1-/- mice and provides an assay to examine the associated neural dysfunction.

Early life environment influences the development of various aspects of social behavior, particularly during sensitive developmental periods. Here, we aimed to study how challenges in the early postnatal period or (early) adolescence affect pro-social behavior. To this end, we adapted an existing paw operated liberation task to an automated operant task, to measure motivation (by progressively increasing required lever pressing) to liberate a trapped conspecific. Liberation of the trapped rat resulted either in social contact, or in liberation into a separate compartment. Additionally, a condition was tested in which both rats could freely move in two separate compartments and lever pressing resulted in social contact. When partners were not trapped, rats were more motivated to press the lever for opening the door than in either of the trapped configurations. Contrary to our expectation, the trapped configuration resulted in a reduced motivation to act. Early postnatal stress (24h maternal deprivation on postnatal day 3) did not affect behavior in the liberation task. However, rearing rats from early adolescence onwards in complex housing conditions (Marlau cages) reduced the motivation to door opening, both in the trapped and freely moving conditions, while motivation for a sucrose reward was not affected.

The zebrafish is increasingly being employed as an experimental platform to model neuropsychiatric diseases and to screen for novel neuro-active compounds. While the superb genetic and optical access that this system offers has long been recognized, these features have not been fully exploited to investigate disease mechanisms and possible therapeutic interventions. Here we introduce a light-sheet imaging and graph-theoretical analysis pipeline to determine the effects of the known or suspected antidepressant compounds fluoxetine, ketamine and cycloserine on brain-wide neural activity patterns. We imaged the brains of both wildtype fish and grs357 mutants, which harbor a missense mutation that abolishes glucocorticoid receptor transcriptional activity. The grs357 mutation results in a chronically elevated stress axis together with behavioral endophenotypes of depression. Consistent with broad expression of the glucocorticoid receptor throughout the brain, we show that the mutant fish exhibit an altered correlational structure of resting-state brain activity. Intriguingly, in grs357 mutant fish, an increased modularity, which represents the degree of segregation of the network into highly clustered modules, was restored by acute fluoxetine administration to wildtype levels. Ketamine and cycloserine also normalized specific parameters of the graph. Fluoxetine altered network function in the same direction in mutant and wildtype, while ketamine and cycloserine had effects that were opposite for the two genotypes. We propose that light-sheet imaging, followed by graph analysis, is a content-rich and scalable first-pass approach for studying the neural consequences of drug effects and drug x genotype interactions in zebrafish models of psychiatric disorders.

BackgroundMaladaptive aggression in humans is associated with several psychiatric conditions and lacks effective treatment. Nevertheless, aggression constitutes an essential behavior throughout the animal kingdom as long as it is tightly regulated. Studying how social dominance hierarchies (SDH) regulate aggression and access to resources in an enriched environment (EE) can narrow the translational gap between aggression in animal models and humans normal and pathological behavior. MethodsThe social box (SB) is a semi-natural setup for automatic and prolonged monitoring of mouse group dynamics. We utilized the SB to decipher complex tradeoffs between aggression, social avoidance, resource allocation, and dominance in two mouse models of increased aggression: (i) a model of early exposure to EE and (ii) a model of oxytocin receptor deficiency (OxtR-/-). While EE increases aggression as an adaptive response to external stimuli, hyper-aggression in OxtR-/- mice is accompanied by marked abnormalities in social behavior. ResultsEE groups exhibited significant social avoidance, and an increased proportion of their encounters developed into aggressive interactions, resulting in lower levels of exploratory activity and overall aggression. The hierarchy in EE was more stable than in control groups, and dominance was correlated with access to resources. In OxtR-/- groups, mice engaged in excessive social encounters and aggressive chasing, accompanied by increased overall activity. In OxtR-/- groups, dominance hierarchies existed but were not correlated with access to resources. ConclusionMeasuring aggression and social dominance hierarchies in a semi-natural setup reveals the adaptive value of aggression in EE and OxtR-/- mice, respectively. This approach can enhance translational research of pathological aggression.

Domesticated mice and rats have shown to be powerful model systems for biomedical research, but there are cases in which the biology of species is a poor match for the hypotheses under study. The California mouse (Peromyscus californicus) has unique physiological and behavioral traits and has emerged as a powerful model for studying sex differences in the biology of psychiatric disease, which is particularly relevant considering the new NIH guidelines that require the inclusion of sex as a biological variable. Despite its growing role in preclinical research, there is a lack of studies assessing species-specific housing needs, which presents a challenge for research facilities seeking to ensure good welfare and obtaining high-quality experimental data. Indeed, captive California mice present a high prevalence of stereotypic backflipping behavior, a common consequence of suboptimal housing and a potential source of experimental outcome variability. Using three different cage systems, the present studies show that increasing housing space as well as social and environmental complexity can delay the development of stereotypic behavior in male and female California mice. Critically, this reduction in stereotypy is accompanied by increased effect sizes of stress in an established model for social anxiety. These results suggest that increased cage size and enrichment could enhance welfare in California mice while simultaneously increasing the quality of behavioral experiments.

We present a highly reproducible method for investigating the startle flight responses of wild type Drosophila melanogaster to light-off stimuli, using the automated Zantiks MWP unit. The built-in, live video-tracking of the Zantiks unit measured distance travelled between frames for 24 flies after light-off stimuli, whilst providing video-recordings of each startle. Using light-off stimuli which elicited peak startling, we found evidence for habituation of the startle response after only a few consecutive trials. Distance travelled on startle trials was reduced when a prepulse stimulus of shorter duration was introduced before the light-off stimulus, providing behavioural evidence for prepulse inhibition (PPI). Deficits in habituation and PPI are linked to various psychiatric disorders and our method holds great potential for use alongside genetic and pharmacological manipulations. Here, we demonstrate the capability of this highly automated, high throughput technology to streamline behavioural research on Drosophila, using a replicable, controlled environment.

In the rapidly evolving field of rodent behavior research, observer-independent methods facilitate data collection within a social, stress-reduced, and thus more natural environment. A prevalent system in this research area is the IntelliCage, which empowers experimenters to design individual tasks and higher cognitive challenges for mice, driven by their motivation to access reward. The extensive amount and diversity of data provided by the IntelliCage system explains the growing demand for automated analysis among users. Here, we introduce IntelliR, a standardized pipeline for analyzing raw data generated by the IntelliCage software, as well as novel parameters including the cognition index, which enables comparison of performance across various challenges. With IntelliR, we provide the tools to implement and automatically analyze 3 challenges that we designed, encompassing spatial, episodic-like, and working memory with their respective reversal tests. Using results from 3 independent control cohorts of adult female wildtype mice, we demonstrate their ability to comprehend and learn the tasks, thereby improving their proficiency over time. To validate the sensitivity of our approach for detecting cognitive impairment, we used adult female NexCreERT2xRosa26-eGFP-DTA mice after tamoxifen induced diphtheria toxin-mediated ablation of pyramidal neurons in cortex and hippocampus. We observed deterioration in learning capabilities and cognition index across several tests. IntelliR can be readily integrated into and adapted for individual research, thereby improving time management and reproducibility of data analysis. HIGHLIGHTSO_LIIntelliR is a standardized pipeline for analyzing raw data of IntelliCage software. C_LIO_LIDomains include spatial, episodic-like, and working memory with reversals. C_LIO_LIWT mice (3 cohorts) comprehend, learn and improve proficiency over time. C_LIO_LICognition index permits comparison of performance across cognitive domains. C_LIO_LIMice with ablation of pyramidal neurons decline mainly in working memory. C_LI

Behavioral copying is a key process in group actions, but it is challenging for individuals with Autism Spectrum Disorder (ASD). We investigated behavioral contagion, or instinctual replication of behaviors, in Krushinky-Molodkina (KM) rats (n=16), a new rodent model for ASD, compared to control Wistar rats (n=15). A randomly chosen healthy Wistar male ("demonstrator rat") was introduced to the homecage of experimental rats ("observers") 10-14 days before the experiments to become a member of the group. For the implementation of the behavioral contagion experiment, we used the IntelliCage system, where rats can live in a group of 5-6 rats and their water visits can be fully controlled. During the experiment, the demonstrator was taken out of IntelliCage for 24 hours of water deprivation and then placed back. As a result, a drinking behavior of the water-deprived demonstrator rat prompted activated behaviors in the whole group. Unlike the Wistar controls, KM observers showed fewer visits to the drinking bottles, particularly lacking inspection visits. The control group, in contrast, exhibited a dynamic, cascade-like visiting of the water corners. The proportion of activated observers in KM rats was significantly lower, as compared to Wistar ones, and they did not mimic other observer rats. KM rats, therefore, displayed an attenuated pattern of behavioral contagion, highlighting social deficits in this ASD model. This study suggests that measuring group dynamics of behavioral contagion in an automated, non-invasive setup offers valuable insights into social behavior in rodents, particularly for studying social deficits in ASD models. HighlightsO_LIThirsty demonstrators triggered an avalanche of observers visits to the water corners C_LIO_LIThe contaged behavior was attenuated in observer KM rats C_LIO_LIBehavioral contagion test provides a new tool for objective, automated phenotyping in rodent models of social deficits C_LI

Prosocial behaviors, actions that benefit others, are an essential part of the social life of humans and other animals, by promoting bonding and cohesion among individuals and groups. Here we present a new behavioural paradigm to assess prosociality in food foraging contexts in laboratory mice, based in our paradigm previously developed for rats. In this task, the decision-maker can choose between two options, one that will only provide rewards to itself (selfish choice) or one that will reward both itself and its cagemate (prosocial choice). Our work reveals that prosocial choices in male mice are not widespread and are only observed in a small proportion of animals. Using detailed analysis of behavior, we describe that recipients of help express different social cues in prosocial and selfish trials, but decision makers do not take them into account to guide their choices. Furthermore, we assess how the level of individual training and the physical layout of the paradigm might affect the performance in this social task. Only those mice with increased social attention (16% of the animals) display prosocial preferences, suggesting these to be rooted in similar behavioural factors and social interactions that we previously described in other work with rats.

Animals avoid predators and find the best food and mates by learning from the consequences of their behavior. However, reinforcers are not always uniquely appetitive or aversive but can have complex properties. Most intoxicating substances fall within this category; provoking aversive sensory and physiological reactions while simultaneously inducing overwhelming appetitive properties. Here we describe the subtle behavioral features associated with continued seeking for alcohol despite aversive consequences. We developed an automated runway apparatus to measure how Drosophila respond to consecutive exposures of a volatilized substance. Behavior within this Behavioral Expression of Ethanol Reinforcement Runway (BEER Run) demonstrated a defined shift from aversive to appetitive responses to volatilized ethanol. Behavioral metrics attained by combining computer vision and machine learning methods, reveal that a subset of 9 classified behaviors and component behavioral features associate with this shift. We propose this combination of 9 behaviors can be used to navigate the complexities of operant learning to reveal motivated goal-seeking behavior.

During childhood and adolescence, exploring the unknown is important to build a better model of the world. This means that youths have to regularly solve the exploration-exploitation trade-off, a dilemma in which adults are known to deploy a mixture of computationally light and heavy exploration strategies. In this developmental study, we investigated how youths (aged 8 to 17) performed an exploration task that allows us to dissociate these different exploration strategies. Using computational modelling, we demonstrate that tabula-rasa exploration, a computationally light exploration heuristic, is used to a higher degree in children and younger adolescents compared to older adolescents. Additionally, we show that this tabula-rasa exploration is more extensively used by youths with high attention-deficit/hyperactivity disorder (ADHD) traits. In the light of ongoing brain development, our findings show that children and younger adolescents use computationally less burdensome strategies, but that an excessive use thereof might be a risk for mental health conditions.

Stress-related disorders encompass diverse behavioral alterations, including impaired social functioning. The zebrafish (Danio rerio) is a valuable model for studying these phenomena, particularly because of its robust and ethologically conserved social behaviors. Unpredictable chronic stress (UCS) produces behavioral, physiological, and molecular changes in zebrafish that parallel core features of human anxiety and depressive disorders; however, its impact on social outcomes remains unclear. Here, we examined whether a 14-day UCS protocol alters social behavior in adult zebrafish using two complementary assays: the social preference test and the shoal cohesion test. Across two independent experiments, UCS did not elicit detectable changes in individual social approach or group-level cohesion. In contrast, UCS induced clear anxiety-like behavior in the novel tank test, validating the stress manipulation, with stressed fish displaying reduced vertical exploration and decreased time in the upper zone. Shoal cohesion measures showed a time-dependent decrease in both groups, consistent with habituation to the testing environment rather than a stress-specific effect. Together, these results suggest that social behavior in adult zebrafish is relatively resilient to UCS under the conditions tested, whereas anxiety-like responses are markedly affected. Future work should investigate whether factors such as stressor intensity, developmental stage, sex composition, or social hierarchy modulate the sensitivity of social behavior to chronic stress.

Quantifying animal behavior is pivotal for identifying the underlying neuronal and genetic mechanisms involved. Computational approaches have enabled automated analysis of complex behaviors such as aggression and courtship in Drosophila. However, existing approaches rely on rigid, rule-based algorithms and expensive hardware, limiting sensitivity to behavioral variations and accessibility. Here, we describe the Drosophila Aggression and Courtship Evaluator (DANCE), a low-cost, open-source platform that combines machine learning-based classifiers and inexpensive hardware to quantify aggression and courtship. DANCE consists of six novel behavioral classifiers trained using a supervised machine learning algorithm. DANCE classifiers address key limitations of rule-based algorithms, capturing dynamic behavioral variations more effectively. DANCE hardware is constructed using repurposed medicine blister packs and acrylic sheets, with recordings performed using smartphones, making it affordable and accessible. Benchmarking demonstrated that DANCE hardware performs comparably to sophisticated, high-cost setups. We validated DANCE in diverse contexts, including social isolation versus enrichment, which modulates aggression and courtship; RNAi-mediated downregulation of the neuropeptide Dsk; and optogenetic silencing of dopaminergic neurons, which promotes aggression. DANCE provides a cost-effective and portable solution for studying Drosophila behaviors in resource-limited settings or near natural habitats. Its accessibility and robust performance democratize behavioral neuroscience, enabling rapid screening of genes and neuronal circuits underlying complex social behaviors.

Motivation-based symptoms occur in an array of neurological and neurodegenerative disorders, including Schizophrenia and Parkinsons Disease. Unfortunately, there is, as yet, no agreed treatment approach. To establish a better understanding of motivation, and so highlight potential avenues for treatment, motivation is often investigated using operant behavioural paradigms such as the Effort for Reward (EfR) task. Performance on these tasks is thought to be influenced by reinforcement learning (RL) mechanisms, such that disorders of motivation can be described in terms of altered interactions with RL processes. Recently, foraging behaviour has been increasingly adopted as an ethologically valid approach to investigating cognitive mechanisms, including motivation. One example of this is the recently developed Effort Based Foraging task (EBF). Foraging behaviour, unlike the strictly controlled and contrived operant behavioural paradigms, involves a series of complex behavioural processes, each potentially driven by different cognitive processes. It is therefore important to identify which portion of the foraging behavioural sequence is driven by the same RL mechanisms as classical operant behavioural paradigms, and therefore can be used to investigate motivation. In this work we set out to establish whether the same RL mechanisms could be used to account for behaviours observed in both EfR and EBF tasks. We identified where, within the EBF task, RL mechanisms were no long sufficient and developed a novel hybrid model of the behaviour. This model successfully accounted for external influences on motivation, including previously unpredicted effects of clinically used dopaminergic drugs. This work reveals that motivation in complex, naturalistic tasks cannot be fully explained by learning-based models alone. Incorporating intrinsic behavioural drives may be needed as neuroscience moves toward more ethological behavioural assays.

Simple behavioral tests like the forced swim test (FST) and tail suspension test (TST) are widely used to assess depression-like behaviors in rodents, primarily measuring immobility time. However, this approach oversimplifies behavioral readouts and overlooks the cognitive processes driving behavior, leaving the relationship between increased immobility and cognitive biases unclear. Here, we developed the SwimStruggleTracker (SST) to extract fine-grained behavioral trajectories and integrate computational modeling to methodically analyze behavior. Our findings reveal that behavior in the FST and TST follows reinforcement learning principles involving learning, consequence perception, and decision-making. Notably, the cognitive processes underlying behavior differ between the two tests, challenging the assumption that they are interchangeable for cross-validation. Regression analyses identify distinct behavior phases: early behavior is primarily influenced by learning-related factors, while later stages are more affected by consequence sensitivity. These findings suggest traditional analyses focusing final minutes may underestimate the role of learning and overemphasize consequence sensitivity. MotivationThe forced swim test (FST) and tail suspension test (TST) are among the most widely used paradigms for assessing depression-like behaviors in rodents. Yet, traditional analyses typically quantify only immobility during the final minutes, discarding rich temporal structure in the data and hindering efforts to uncover the cognitive mechanisms underlying these behaviors. To address this gap, we developed an automated tool that captures behavioral trajectories with fine temporal resolution and integrates computational modeling to dissect the cognitive processes driving behavior. Using this approach, we demonstrate that the FST and TST engage overlapping but partially distinct cognitive processes, and that the dominant cognitive components shift across different stages of the tests. HighlightsO_LISwimStruggleTracker (SST) accurately rejects passive movements, such as pendulum-like motion. C_LIO_LIReinforcement learning models capture the behavioral dynamics of mice in the FST and TST. C_LIO_LIDistinct winning models indicate that the FST and TST engage partially dissociable cognitive processes. C_LIO_LILearning factors dominate early stages, whereas consequence-sensitivity factors dominate later stages. C_LI

The midsession reversal (MSR) task is frequently used to study behavioral flexibility and decision strategies in animals. In a typical version of the task, subjects complete 80 trials in which they choose between two simultaneously presented stimuli, S1 and S2. During the first 40 trials, responses to S1 are reinforced, whereas responses to S2 are not. The contingencies then reverse without warning: From trial 41 to 80, only responses to S2 are reinforced. In birds, performance in this task is often characterized by anticipatory and perseverative errors around the reversal point, suggesting a reliance on elapsed time since the session began. In contrast, rats tested in operant conditioning chambers typically show near-optimal performance with few errors, a pattern often interpreted as evidence that rats rely primarily on local reinforcement cues rather than temporal information. The present study investigated whether rats exclusively rely on local cues in the MSR task or whether temporal information also contributes to the decision process. Two groups of rats were trained with different intertrial intervals (ITIs; 5 s or 10 s) while the reversal point remained fixed at Trial 41. During acquisition, both groups diplayed similar learning rates and near-optimal steady-state performance with minimal anticipatory or perseverative errors. However, when the ITI was manipulated in probe sessions, systematic shifts in switching behavior emerged. Rats adjusted their choices according to the temporal midpoint experienced during training rather than the nominal trial number of the reversal. These results suggest that rats rely on a mixed strategy that integrates local reinforcement cues with global timing information. Temporal control may therefore be present even when it is not expressed during standard training conditions.

The rapid serial visual presentation (RSVP) task and continuous performance tasks (CPT) are used to assess attentional impairments in patients with psychiatric and neurological conditions. This study developed a novel touchscreen task for rats based on the structure of a human RSVP task and used pharmacological manipulations to investigate their effects on different performance measures. Normal animals were trained to respond to a target image and withhold responding to distractor images presented within a continuous sequence. In a second version of the task a false-alarm image was included so performance could be assessed relative to two types of non-target distractors. The effects of acute administration of the stimulant and non-stimulant treatments for ADHD (amphetamine and atomoxetine) were tested in both tasks. Methylphenidate, ketamine and nicotine were tested in the first task only. Amphetamine made animals more impulsive and decreased overall accuracy but increased accuracy when the target was presented early in the image sequence. Atomoxetine improved accuracy overall with a specific reduction in false-alarm responses and a shift in the attentional curve reflecting improved accuracy for targets later in the image sequence. However, atomoxetine also slowed responding and increased omissions. Ketamine, nicotine and methylphenidate had no specific effects at the doses tested. These results suggest that stimulant versus non-stimulant treatments have different effects on attention and impulsive behaviour in this rat version of an RSVP task. These results also suggest that RSVP-like tasks have the potential to be used to study attention in rodents.

Over the past decade, several studies have demonstrated that idiosyncratic animal behaviors remain consistent over long time periods. The consistency of individually variable behaviors over time is often referred to as an animals individuality, or if consisting of multiple traits personality. However, most experimental studies have focused on individuality in a single, well-defined environmental context, whereas it is well-established from population studies that animal behavior is highly context-dependent. The person-situation debate in humans and decades of observations of animal individuality under intrinsically variable natural conditions raise the question of whether and to what extent animal behavior remains consistent across different situations, such as changing environmental contexts. For instance, one individual might be generally more visually guided than another, or rely only on one particular visual cue, or even on this very cue only in a specific environmental context. Here, we use a combination of both well-established and novel behavioral assays to demonstrate the relationship between individual behavior and variable environmental context under tightly controlled laboratory conditions in the model system Drosophila melanogaster. The consistency of three individual traits (termed exploration, attention, and anxiety) was investigated under changing environmental contexts (temperature, visual cues, arena shape), in both walking and flying flies. We find that individuality is highly context-dependent, but even under the most extreme environmental alterations tested, consistency of behavioral individuality always persisted in at least one of the traits. Furthermore, our quantification reveals a hierarchical order of environmental features influencing individuality. We confirmed this hierarchy using a generalized linear model and a hierarchical linear mixed model. In summary, our work demonstrates that, similar to humans, fly individuality persists across different contexts (albeit worse than across time), and individual differences shape behavior across variable environments. The presence of consistency across situations in flies makes the underlying developmental and functional mechanisms amenable to genetic dissection.