Frontiers in Behavioral Neuroscience

Social aversion is a key feature of numerous mental health disorders such as Social Anxiety and Autism Spectrum Disorders. Nevertheless, the biobehavioral mechanisms underlying social aversion remain poorly understood. Progress in understanding the etiology of social aversion has been hindered by the lack of comprehensive tools to assess social aversion in model systems. Here, we created a new behavioral task - Selective Access to Unrestricted Social Interaction (SAUSI), which integrates elements of social motivation, hesitancy, decision-making, and free interaction to enable the wholistic assessment of social aversion in mice. Using this novel assay, we found that social isolation-induced social aversion in mice is largely driven by increases in social fear and social motivation. Deep learning analyses revealed a unique behavioral footprint underlying the socially aversive state produced by isolation, demonstrating the compatibility of modern computational approaches with SAUSI. Social aversion was further assessed using traditional assays - including the 3-chamber sociability assay and the resident intruder assay - which were sufficient to reveal fragments of a social aversion phenotype, including changes to either social motivation or social interaction, but which failed to provide a wholistic assessment of social aversion. Critically, these assays were not sufficient to reveal key components of social aversion, including social freezing and social hesitancy behaviors. Lastly, we demonstrated that SAUSI is generalizable, as it can be used to assess social aversion induced by non-social stressors, such as foot shock. Our findings debut a novel task for the behavioral toolbox - one which overcomes limitations of previous assays, allowing for both social choice as well as free interaction, and offers a new approach for assessing social aversion in rodents.

Behavioral responses to threat -- such as fleeing, freezing, or fighting--can be innate, learned, and strongly shaped by context or competing goals. Here, we asked whether exposure to an ecologically relevant predator obligatorily elicits canonical defensive behaviors across behavioral contexts. We examined predator responses in mice across four experimental conditions: one novel head-fixed reward-driven foraging task and three established paradigms in freely moving animals. In the head-fixed condition, water-deprived mice were trained to walk on a treadmill controlling a virtual environment and water reward delivery and were subsequently exposed to a live rat positioned above the lick spout. Despite the presence of the predator, most mice (5 of 7) maintained foraging performance at baseline levels. However, individual mice exhibited significant, coordinated changes in running speed, pupil diameter, eye movements, and posture, indicating engagement with the threat. To assess how context influences predator responses, we exposed 36 naive, freely moving mice to fear-inducing stimuli, including looming visual cues, rat odor, and a live rat. Even under these conditions, defensive behaviors were variable: only a subset of mice displayed avoidance or escape, and when presented with a freely moving rat, approximately half of the mice avoided the predator. Together, these findings show that predator threat does not elicit a uniform or obligatory defensive repertoire in mice. Instead, defensive responses are expressed flexibly, and are shaped by environmental constraints, task demands, and individual variability. These results challenge the assumption that innate fear behaviors are automatically triggered by predator encounters. Graphical AbstractUsing a head-fixed, reward-based foraging task and complementary freely moving paradigms, we show that mouse responses to predator-related stimuli are variable and context dependent, with limited expression of canonical defensive behaviors such as freezing or flight. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/658679v3_ufig1.gif" ALT="Figure 1"> View larger version (65K): org.highwire.dtl.DTLVardef@1fa4570org.highwire.dtl.DTLVardef@1e4c33borg.highwire.dtl.DTLVardef@1cd6bf9org.highwire.dtl.DTLVardef@16bdeb3_HPS_FORMAT_FIGEXP M_FIG C_FIG

The description and quantification of social behavior in laboratory rodents is central to basic and translational research. Conventional ethological approaches to social behavior are fraught with challenges including bias, significant human effort and temporal accuracy. Here we show proof of principle that machine learning can be applied to laboratory tests of social decision making. Rats underwent social novelty preference tests which were scored both by hand and again by a convolutional neural network generated in the DeepLabCut computer vision package of Mathis and colleagues. The CNN generated temporally (30Hz) and locally (<5pixels) accurate identification of rat nose, eye and ear positions which were then used to compute social interaction and topography heat maps. In sum, hand- and computer-scoring were strongly correlated, and each identified significant preferences to interact with novel conspecifics which sets the stage for applying DeepLabCut analysis to other types of social interaction in the future.

Contextual fear conditioning is a classical laboratory task that tests associative memory formation and recall. Techniques such as multi-photon microscopy and holographic stimulation offer tremendous opportunities to understand the neural underpinnings of these memories. However, these techniques generally require animals to be head-fixed. There are few paradigms that test contextual fear conditioning in head-fixed mice, and none where the behavioral outcome following fear conditioning is freezing, the most common measure of fear in freely moving animals. To address this gap, we developed a contextual fear conditioning paradigm in head-fixed mice using virtual reality (VR) environments. We designed an apparatus to deliver tail shocks (unconditioned stimulus, US) while mice navigated a VR environment (conditioned stimulus, CS). The acquisition of contextual fear was tested when the mice were reintroduced to the shock-paired VR environment the following day. We tested three different versions of this paradigm and, in all of them, observed an increased conditioned fear response characterized by increased freezing behavior. This was especially prominent during the first trial in the shock-paired VR environment, compared to a neutral environment where the mice received no shocks. Our results demonstrate that head-fixed mice can be fear conditioned in VR, discriminate between a feared and neutral VR context, and display freezing as a conditioned response, similar to freely behaving animals. Furthermore, using a two-photon microscope, we imaged from large populations of hippocampal CA1 neurons before, during, and following contextual fear conditioning. Our findings reconfirmed those from the literature on freely moving animals, showing that CA1 place cells undergo remapping and show narrower place fields following fear conditioning. Our approach offers new opportunities to study the neural mechanisms underlying the formation, recall, and extinction of contextual fear memories. As the head-fixed preparation is compatible with multi-photon microscopy and holographic stimulation, it enables long-term tracking and manipulation of cells throughout distinct memory stages and provides subcellular resolution for investigating axonal, dendritic, and synaptic dynamics in real-time.

Motor learning and flexibility allow animals to perform routine actions efficiently while keeping them flexible. There is a number of paradigms used to test cognitive flexibility but not many of them focus specifically on learning of complex motor sequences and their flexibility. While many tests use operant or touchscreen boxes that offer high throughput and reproducibility, the motor actions themselves are mostly simple presses of a designated lever. To focus more on motor actions during the operant task and to probe the flexibility of these well-trained actions, we developed a new operant paradigm for mice, the, "timed sequence task". The task requires mice to learn a sequence of lever presses that have to be emitted in precisely defined time limits. After training, the required pressing sequence and/or timing of individual presses is modified to test the ability of mice to alter their previously trained motor actions. We provide a code for the new protocol that can be used and adapted to common types of operant boxes. In addition, we provide a set of scripts that allow automatic extraction and analysis of numerous parameters recorded during each session. We demonstrate that the analysis of multiple performance parameters is necessary for detailed insight into animals behavior during the task. We validate our paradigm in an experiment using the valproate model of autism as a model of cognitive inflexibility. We show that the valproate mice show superior performance at specific stages of the task, paradoxically due to their propensity to more stereotypic behavior. Significance StatementCognitive flexibility impairment is a crucial component of many neurological disorders and it is frequently evaluated in animal models. As the commonly used tests usually do not focus on motor learning and the ability to adapt motor sequences, we designed a new paradigm to evaluate motor learning and its flexibility. The timed sequence task is automatized and easily accessible as it is based on widely available operant boxes. During the training, the task requires precise timing of each action to force stereotypic performance. Its relative complexity allows detailed analysis of multiple parameters and therefore detailed insight into animals behavior. The task can be used to reveal and understand subtle differences in motor and operant learning and flexibility. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/547172v2_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@ced388org.highwire.dtl.DTLVardef@a19792org.highwire.dtl.DTLVardef@e60f49org.highwire.dtl.DTLVardef@1f5bfa1_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundUnderstanding the neurobiological substrates of psychiatric disorders requires comprehensive evaluations of cognitive and motivational functions in preclinical research settings. The translational validity of such evaluations will be supported by (1) tasks with high construct validity that are engaging and easy to teach to human and nonhuman participants, (2) software that enables efficient switching between multiple tasks in single sessions, (3) software that supports tasks across a broad range of physical experimental setups, and (4) by platform architectures that are easily extendable and customizable to encourage future optimization and development. New MethodWe describe the Multi-task Universal Suite for Experiments (M-USE), a software platform designed to meet these requirements. It leverages the Unity video game engine and C# programming language to (1) support immersive and engaging tasks for humans and nonhuman primates, (2) allow experimenters or participants to switch between multiple tasks within-session, (3) generate builds that function across computers, tablets, and websites, and (4) is freely available online with documentation and tutorials for users and developers. M-USE includes a task library with seven pre-existing tasks assessing cognitive and motivational constructs of perception, attention, working memory, cognitive flexibility, motivational and affective self-control, relational long-term memory, and visuo-spatial problem solving. ResultsM-USE was used to test NHPs on up to six tasks per session, all available as part of the Task Library, and to extract performance metrics for all major cognitive and motivational constructs spanning the Research Domain Criteria (RDoC) of the National Institutes of Mental Health. Comparison with Existing MethodsOther experiment design and control systems exist, but do not provide the full range of features available in M-USE, including a pre-existing task library for cross-species assessments; the ability to switch seamlessly between tasks in individual sessions; cross-platform build capabilities; license-free availability; and its leveraging of video-engine capabilities used to gamify tasks. ConclusionsThe new multi-task platform facilitates cross-species translational research for understanding the neurobiological substrates of higher cognitive and motivational functions.

The ability to generate and recall memory is a behavior that is evolutionarily conserved across the animal kingdom from humans to jellyfish. Memory not only allows previous experiences to inform future decision making, but it also amasses information essential to life, such as memory of quality food sources, shelter, and predator-related associations. Associative memory forms a relationship between two or more distinct and initially unrelated stimuli and can be defined by its temporal characteristics, such as short- and long-term duration, as well as the memory being appetitive or aversive, generating approach or avoidance behavior, respectively. Since its introduction as a memory model in the 1970s, the fruit fly, Drosophila melanogaster, has emerged as a powerful tool for the investigation of memory-related processes. While a variety of memory paradigms have been used extensively in Drosophila, such as appetitive and aversive olfactory memory, the use of appetitive visual memory remains infrequent. A previous study introduced a visual short-term memory (STM) paradigm that could be used for the study of both appetitive and aversive visual memory in Drosophila. However, this protocol required 50+ flies per condition, with three conditions per experiment, and 15 or more replications were frequently used to assess memory. As a result, this paradigm requires substantial numbers of flies, time, and is impractical for large genetic screens. Here, building upon this previous work, we describe an optimized appetite visual STM paradigm in freely moving Drosophila. Using recently published data on sexual dimorphism, innate color preferences, and borrowing practices from related appetitive assays, we have established an approach that minimizes confounding factors, such as sexually dimorphic starvation survival and sucrose preference, as well as pre-training color preference variation between groups. In doing so, we present an appetitive visual STM paradigm requiring substantially fewer replicates and numbers of flies to produce significant learning.

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.

Emotions, defined as transient states preparing organisms for adaptive responses, are thought to be based on evolutionarily conserved building blocks ("emotion primitives") that are present across mammalian and other vertebrate species. Whether and to which extent these building blocks are found in insects is largely undefined. In this study, we employ the open field test in fruit flies and focus on wall-following and total walking activity as behavioural indicators of emotion-like states. Wildtype and transgenic flies were subjected to various conditions, including social isolation, starvation, and exposure to anxiolytic substances prior to behavioural testing in the open field test. The results indicate that wall-following and total walking activity are modulated by these conditions, with generally increased wall-following observed under aversive stimuli and decreased values under positive conditions. Notably, the behaviour was consistent across different times of the day and independent of circadian rhythms. Genetic manipulation of neuromodulatory systems, such as serotonin, dopamine, and neuropeptide F, supports the role of these pathways in modulating emotion-like states in the fruit fly. Activation of reward-related neurons decreased wall-following, while inhibition increased it, aligning with known effects in mammalian models. Additionally, pharmacological treatments with ethanol and diazepam produced predictable changes in wall-following and total walking activity, reinforcing the validity of the open field test as a measure of emotion-like states in the fly. The findings suggest that Drosophila exhibits core emotion-like states, with wall-following and total walking activity serving as reliable indicators of emotional valence and arousal. Our results promote the use of Drosophila as a powerful genetic model to dissect the neuronal and neurochemical substrates of emotion primitives, shedding light on the evolution of basic emotional processing mechanisms.

BackgroundChronic social defeat stress (CSDS) leads to persistent behavioral deficits, such as social avoidance and abnormal stress responses, including freezing. Despite these fear-based responses observed during and after social defeat, the effects of prolonged exposure (PE) treatment - a well-established therapy for post-traumatic stress disorder (PTSD)--have not been thoroughly investigated in this context. MethodsSocially defeated male mice were subjected to 12 days of PE treatment. We determined the efficacy of PE treatment in physically defeated mice by measuring stress responses, including freezing, jump escape, and social interaction, before and after the intervention. ResultsAfter 12 days of PE treatment, male mice that had been physically defeated showed a marked decrease in freezing behavior. Furthermore, PE treatment changed the phenotype of mice from susceptible to resilient by reducing social avoidance during the social interaction test. ConclusionsThese results provide a new preclinical method for investigating behavioral recovery and adaptation by showing that PE treatment can reverse significant behavioral deficits caused by social defeat stress. A new framework for examining individual variability in therapeutic outcomes after chronic stress exposure is provided by the emergence of both treatment-responsive and treatment-resistant phenotypes.

Over the past two decades, the vast majority of circadian behavior in Drosophila has been recorded in Drosophila Activity Monitor (DAM) boards. Though simple and robust, locomotor behavior recording via DAM boards can be prohibitively expensive, especially when taking incubator costs into consideration. Furthermore, their simplicity limits their experimental options and resolution. Here, we present the FlyBox: a simple, open-source benchtop locomotor activity recording system. FlyBox was designed to monitor activity in animals loaded into a standard laboratory multi-well plate. It features light-tight construction and multiple programmable LEDs for simulating day/night cycles and optogenetic manipulation. In total, a single FlyBox costs approximately $750 to build and around two days of labor. In addition, we also present the FlyBoxScanner software to simplify activity monitoring while maintaining compatibility with DAM analysis software. FlyBox is an attractive and affordable package for behavior monitoring that also offers considerable room for customization. Materials and instructions for the FlyBox are available at https://github.com/Rosbash-Lab-FlyBox/FlyBox, and FlyBoxScanner is available at https://github.com/jose-elias-alvarez/flybox-scanner.

Social isolation causes profound changes in social behaviour in a variety of species including humans, monkeys, mice, bees, and vinegar flies. However, the genetic and molecular mechanisms modulating behavioural responses to both social isolation and social recovery remain to be elucidated. In this study, we quantified the behavioural response of vinegar flies to social isolation through the use of two distinct protocols, one involving flies social space preference and the other assessing flies sociability, defined as their spontaneous tendencies to form groups. We found that social isolation increased social space and reduced sociability. These effects of social isolation, however, were reversible and could be reduced after 3 days of group housing. Flies with a loss of function of neuroligin3 (ortholog of autism-related neuroligin genes) with known increased social space in a socially enriched environment, were still able to recover from social isolation. Using a UAS-TH-RNAi driven in all neurons, we show that dopamine is important for a response to social isolation and recovery in males but not in females. Furthermore, only in males, dopamine levels are reduced after isolation and are not recovered after group housing. Finally, in socially enriched flies with a loss of function of neuroligin3, dopamine levels are reduced in males, but not in females. We propose a model to explain how dopamine and neuroligin3 are involved in the behavioural response to social isolation and its recovery in a dynamic and sex-specific manner.

Experimentation with mouse and rat models has become a central strategy for discovering mammalian gene function, and for preclinical testing of pharmacological treatments, yet the utility of any findings critically depends on their replicability in other laboratories. In previous publications we proposed a statistical approach for estimating the inter-laboratory replicability of novel discoveries made in a single laboratory. We demonstrated that previous phenotyping results from multi-lab databases can be used to derive a Genotype-by-Lab (GxL) adjustment factor to greatly enhance the replicability of the single-lab findings, for similarly measured phenotypes, even before making the effort of replicating these finding in additional laboratories. This demonstration, however, still raised several important questions that could only be answered by an additional large-scale prospective experiment: 1) Does GxL-adjustment work in single-lab experiments that were not intended to be standardized across laboratories, and with genotypes that were not included in the previous experiments? And 2) Can it be used to adjust the results of pharmacological experiments? We investigated these questions by attempting to replicate, across three laboratories, results from five single-lab studies in the Mouse Phenome Database (MPD), offering 212 comparisons, including 60 involving a pharmacological treatment: 18 mg/kg/day fluoxetine. In addition, we define and use a dimensionless GxL factor, by dividing the GxL variance by the standard deviation between animals within groups, as a more robust vehicle to transfer the adjustment from the multi-lab analysis to very different labs and genotypes. For genotype comparisons, GxL-adjustment reduced the rate of non-replicable discoveries from 60% to 12%, for the price of reducing the power to make replicable discoveries from 87% to 66%. In absolute numbers, the adjustment prevented 23 non-replicable discoveries for the price of missing only three replicated ones. Tools and data needed for deployment of this method across other mouse experiments are publicly available in MPD. Our results further point at some phenotypes as more prone to produce non-replicable results, while others, known to be more difficult to measure, are as likely to produce replicable results (once adjusted) such as the physiological measure, body weight.

Rationale16p11.2 duplication is associated with numerous neuropsychiatric conditions at a genome-wide level, including psychosis. Mice modeling 16p11.2 duplication may provide important insights into cognitive risk factors, in particular in reward-guided decision making. NMDAR function has also been implicated in psychosis phenotypes, but whether these phenotypes differ by genetic risk factor is unknown. ObjectivesWe aimed to: 1) identify sex and genotype differences in early operant training and two-arm spatial restless bandit task performance; 2) examine the effects of an NMDAR antagonist on task performance and strategy across genotypes. Methods16p11.2 duplication and wildtype mice completed a series of training schedules of escalating difficulty followed by bandit tasks. MK-801 and saline were administered in alternating sessions prior to later bandit task performance. ResultsLarge sex differences in early operant training revealed some male-biased impacts of 16p11.2 duplication, contingent on training schedule difficulty. Once on the two-arm spatial restless bandit task, 16p11.2 duplication was no longer a strong contributor to decision making. However, MK-801 decreased the tendency to stay with a rewarded choice, lowered the probability of selecting the highest rewarded option, and decreased the influence of prior outcomes on choice. ConclusionsThe male-biased vulnerability in early operant training suggests that strategies for learning early schemas or in novel environments may be impacted by 16p11.2 duplication in males. In contrast, NMDAR are influential in the ability to flexibly switch between choices, and disrupting this function significantly impairs decision making in all animals.

Cognitive flexibility, the ability to adapt behavior in response to changing contingencies, is a key component of adaptive decision-making and is impaired in multiple neuropsychiatric disorders. Traditional rodent assays of cognitive flexibility are conducted in experimenter-controlled sessions in restrictive environments, limiting ecological validity and temporal resolution. Here, we developed a fully automated, home-cage paradigm using the Feeding Experimentation Device 3 (FED3) and a companion open-source analysis pipeline, the Feeding Experimentation Device Users Processing Package (FEDUPP), to assess learning and cognitive flexibility with minimal experimenter intervention. The paradigm combines a single-day fixed-ratio 1 (FR1) task with a multi-day, reversal learning task in which active port assignment switches every 25 pellets collected. FEDUPP implements multi-scale learning metrics, including overall accuracy, an 80% accuracy milestone, and a machine learning-based classification of meal accuracy to capture motivated, goal-directed feeding. In wild-type mice, the paradigm detected rapid FR1 acquisition and progressive within-block adaptation during reversal. Application to mice with dorsal hippocampal knockdown of the scaffolding protein CASK revealed faster FR1 acquisition and higher accuracy than controls but a delayed onset of the first accurate meal after reversal, suggesting a selective deficit in updating goal-directed feeding behavior. These findings demonstrate that FEDUPP enables high-resolution, continuous assessment of learning and cognitive flexibility in ethologically relevant settings, and that meal-based accuracy provides a sensitive metric for detecting subtle flexibility impairments not captured by traditional measures.

Post-traumatic stress disorder and other mental disorders can be treated by an established psychotherapy called Eye Movement Desensitization and Reprocessing (EMDR). In EMDR, patients are confronted with traumatic memories while they are stimulated with alternating bilateral stimuli (ABS). How ABS affect the brain and whether ABS could be adapted to different patients or mental disorders is unknown. Interestingly, ABS reduced conditioned fear in mice. Yet, an approach to systematically test complex visual stimuli and compare respective differences in emotional processing based on (semi-)automated behavioral analysis is lacking. We developed 3MDR (Model for MultiModal visual stimulation to Desensitize Rodents) - a novel, open-source, low-cost, customizable device that can be integrated in and TTL-controlled by commercial rodent behavioral setups. 3MDR allows to design and precisely steer multimodal visual stimuli in the head direction of freely-moving mice. Optimized videography allows to semi-automatically analyze rodent behavior during visual stimulation. Detailed building, integration, and treatment instructions along with open-source software provide easy access for inexperienced users. Using 3MDR, we confirmed that EMDR-like ABS persistently improve fear extinction in mice and showed for the first time that ABS-mediated anxiolytic effects strongly depend on physical stimulus properties such as ABS brightness. 3MDR not only enables researchers to interfere with mouse behavior in an EMDR-like setting, but demonstrates that visual stimuli can be used as a noninvasive brain stimulation to differentially alter emotional processing in mice. SIGNIFICANCE STATEMENTAlternating bilateral stimuli (ABS) reduce fear in post-traumatic stress disorder patients and in mice. The mechanism of how classic ABS - typically used in Eye Movement Desensitization and Reprocessing (EMDR) - reduce fear is enigmatic. We provide detailed resources to build a cost-effective, computer-controlled device called 3MDR to perform and semi-automatically analyze EMDR-like treatments in freely-moving mice and to test behavioral effects of multiple ABS variants. Using the 3MDR device, this study confirmed that classic ABS strongly and persistently improve the extinction of conditioned fear in mice - an effect that depended on the brightness of ABS. This novel method may ultimately contribute to a deeper translational and neurobiological understanding of how visual stimuli affect emotional processing in mice.

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

Socio-professional pressures push people to sleep less which leads to chronic sleep debt (CSD) for a significant percentage of the population. Although the health consequences of CSD are well known, research shows that high-level cognitive processes in humans are more affected by acute sleep debt (ASD) rather than CSD (Drake et al., 2001). We have previously shown that ASD has deleterious effects on decision-making in mice and that some mice were more sensitive to ASD than others (Pittaras et al., 2018) by using a rodent version of the Iowa Gambling Task (Bechara et al., 1994). In this study, we showed that, as in humans, CSD has fewer effects on decision-making compared to ASD. We hypothesize that this observation was due to the set-up of a compensatory mechanism.

Externalizing disorders (EDs) are characterized by outward-directed behaviors such as aggression and hyperactivity. They are influenced by gene-environment interactions, yet our understanding of the genetic predispositions and environmental contexts that give rise to them is incomplete. Additionally, people with EDs often exhibit comorbid internalizing symptoms, which can complicate the clinical presentation and treatment strategies. Following on from our previous studies, we examined genes x environment interaction as a risk factor for EDs by looking at internalizing and externalizing behaviors after social isolation. Specifically, we subjected adgrl3.1 knockout zebrafish -- characterized by hyperactivity and impulsivity -- to a 2-week social isolation protocol. We subsequently assessed the impact on anxiety-like behavior, abnormal repetitive behaviors, working memory, and social interactions. Genotype-specific additive effects emerged, with socially isolated adgrl3.1 knockout fish exhibiting intensified comorbid phenotypes, including increased anxiety, abnormal repetitive behaviors, reduced working memory, and altered shoaling, when compared to WT fish. The findings demonstrate that genetic predispositions interact with environmental stressors, such as social isolation, to exacerbate both externalizing and internalizing symptoms. This underlines the necessity for comprehensive diagnostic and intervention strategies.

The neural basis of behaviour is identified by systematically disrupting the activity of specific neurons and screening for loss in phenotype. Robust, high-scoring behavioural assays are thus necessary for identifying the neural circuits of novel behaviours. Here, we report the design and use of a Y-maze based classical olfactory learning and memory assay in Drosophila. Appetitive memory scores in our Y-mazes are considerably better and longer-lasting than that from a commonly used T-maze design. We found that the mechanism that traps flies in their choice of an odour is mainly responsible for the improving scores in the Y-mazes. Using Y-mazes, we could assay significant 24 h gustatory aversive memories in flies. These aversive memories are susceptible to protein synthesis inhibitor cycloheximide (CXM) and therefore embodies long-term memory (LTM). When anaesthesia resistant memory (ARM) deficient radish mutant flies are trained with dry sucrose, 24 h memory is severely disrupted. However, when we trained with 2 M sucrose-agar and tested in Y-mazes, radish mutants exhibited a residual 24 appetitive memory. This memory is not ARM, and we show that it is not CXM sensitive LTM either. It could be a third form of appetitive consolidated memory in flies. The Y-maze assembly described here is particularly sensitive and will thus enable the study of new memory phenotypes in Drosophila.