Neurobehavioral assessment in the information age

Toxicity evaluation of neonicotinoids to earthworm (Eisenia fetida) behaviors by a novel locomotion tracking assay

Pesticides are substances used for controlling, preventing, and repelling pests in agriculture. Among them, neonicotinoids have become the fastest-growing class of insecticides because of their efficiency in targeting pests. They work by strongly binding to nicotinic acetylcholine receptors (nAChRs) in the central nervous system of insects, leading to receptor blockage, paralysis, and death. Despite their selectivity for insects, these substances may be hazardous to non-target creatures, including earthworms. Although earthworms may be invasive in some regions like north America, they contribute to the development of soil structure, water management, nutrient cycling, pollution remediation, and cultural services, positively impacting the environment, particularly in the soil ecosystem. Thus, this study aimed to develop a novel earthworm behavior assay since behavior is a sensitive marker for toxicity assay, and demonstrated its application in evaluating the toxicity of various neonicotinoids. Here, we exposed Eisenia fetida to 1 and 10 ppb of eight neonicotinoids (acetamiprid, clothianidin, dinotefuran, imidacloprid, nitenpyram pestanal, thiacloprid, thiametoxam, and sulfoxaflor) for 3 days to observe their behavior toxicities. Overall, all of the neonicotinoids decreased their locomotion, showed by a reduction of average speed by 24.94-68.63% and increment in freezing time movement ratio by 1.51-4.25 times, and altered their movement orientation and complexity, indicated by the decrement in the fractal dimension value by 24-70%. Moreover, some of the neonicotinoids, which were acetamiprid, dinotefuran, imidacloprid, nitenpyram, and sulfoxaflor, could even alter their exploratory behaviors, which was shown by the increment in the time spent in the center area value by 6.94-12.99 times. Furthermore, based on the PCA and heatmap clustering results, thiametoxam was found as the neonicotinoid that possessed the least pronounced behavior toxicity effects among the tested pesticides since these neonicotinoid-treated groups in both concentrations were grouped in the same major cluster with the control group. Finally, molecular docking was also conducted to examine neonicotinoids' possible binding mechanism to Acetylcholine Binding Protein (AChBP), which is responsible for neurotransmission. The molecular docking result confirmed that each of the neonicotinoids has a relatively high binding energy with AChBP, with the lowest binding energy was possessed by thiametoxam, which consistent with its relatively low behavior toxicities. Thus, these molecular docking results might hint at the possible mechanism behind the observed behavior alterations. To sum up, the present study demonstrated that all of the neonicotinoids altered the earthworm behaviors which might be due to their ability to bind with some specific neurotransmitters and the current findings give insights into the toxicities of neonicotinoids to the environment, especially animals in a soil ecosystem.

A systematic review of the development and application of home cage monitoring in laboratory mice and rats

BACKGROUND

Traditionally, in biomedical animal research, laboratory rodents are individually examined in test apparatuses outside of their home cages at selected time points. However, the outcome of such tests can be influenced by various factors and valuable information may be missed when the animals are only monitored for short periods. These issues can be overcome by longitudinally monitoring mice and rats in their home cages. To shed light on the development of home cage monitoring (HCM) and the current state-of-the-art, a systematic review was carried out on 521 publications retrieved through PubMed and Web of Science.

RESULTS

Both the absolute (~ × 26) and relative (~ × 7) number of HCM-related publications increased from 1974 to 2020. There was a clear bias towards males and individually housed animals, but during the past decade (2011-2020), an increasing number of studies used both sexes and group housing. In most studies, animals were kept for short (up to 4 weeks) time periods in the HCM systems; intermediate time periods (4-12 weeks) increased in frequency in the years between 2011 and 2020. Before the 2000s, HCM techniques were predominantly applied for less than 12 h, while 24-h measurements have been more frequent since the 2000s. The systematic review demonstrated that manual monitoring is decreasing in relation to automatic techniques but still relevant. Until (and including) the 1990s, most techniques were applied manually but have been progressively replaced by automation since the 2000s. Independent of the year of publication, the main behavioral parameters measured were locomotor activity, feeding, and social behaviors; the main physiological parameters were heart rate and electrocardiography. External appearance-related parameters were rarely examined in the home cages. Due to technological progress and application of artificial intelligence, more refined and detailed behavioral parameters have been investigated in the home cage more recently.

CONCLUSIONS

Over the period covered in this study, techniques for HCM of mice and rats have improved considerably. This development is ongoing and further progress as well as validation of HCM systems will extend the applications to allow for continuous, longitudinal, non-invasive monitoring of an increasing range of parameters in group-housed small rodents in their home cages.

EDDSN-MRT: multiple rodent tracking based on ear detection and dual siamese network for rodent social behavior analysis

BACKGROUND

Rodent social behavior is a commonly used preclinical model to interrogate the mechanisms underpinning various human neurological conditions. To investigate the interplay between neural systems and social behaviors, neuroscientists need a precise quantitative measure for multi-rodent tracking and behavior assessment in laboratory settings. However, identifying individual differences across multiple rodents due to visual occlusion precludes the generation of stable individual tracks across time.

METHODS

To overcome the present limitations of multi-rodent tracking, we have developed an Ear Detection and Dual Siamese Network for Multiple Rodent Tracking (EDDSN-MRT). The aim of this study is to validate the EDDSN-MRT system in mice using a publicly available dataset and compare it with several current state-of-the-art methods for behavioral assessment. To demonstrate its application and effectiveness in the assessment of multi-rodent social behavior, we implemented an intermittent fasting intervention experiment on 4 groups of mice (each group is with different ages and fasting status and contains 8 individuals). We used the EDDSN-MRT system to track multiple mice simultaneously and for the identification and analysis of individual differences in rodent social behavior and compared our proposed method with Toxtrac and idtracker.ai.

RESULTS

The locomotion behavior of up to 4 mice can be tracked simultaneously using the EDDSN-MRT system. Unexpectedly, we found intermittent fasting led to a decrease in the spatial distribution of the mice, contrasting with previous findings. Furthermore, we show that the EDDSN-MRT system can be used to analyze the social behavior of multiple mice of different ages and fasting status and provide data on locomotion behavior across multiple mice simultaneously.

CONCLUSIONS

Compared with several state-of-the-art methods, the EDDSN-MRT system provided better tracking performance according to Multiple Object Tracking Accuracy (MOTA) and ID Correct Rate (ICR). External experimental validation suggests that the EDDSN-MRT system has sensitivity to distinguish the behaviors of mice on different intermittent fasting regimens. The EDDSN-MRT system code is freely available here: https://github.com/fliessen/EDDSN-MRT .

Blueprints for measuring natural behavior

Until recently laboratory tasks for studying behavior were highly artificial, simplified, and designed without consideration for the environmental or social context. Although such an approach offers good control over behavior, it does not allow for researching either voluntary responses or individual differences. Importantly for neuroscience studies, the activity of the neural circuits involved in producing unnatural, artificial behavior is variable and hard to predict. In addition, different ensembles may be activated depending on the strategy the animal adopts to deal with the spurious problem. Thus, artificial and simplified tasks based on responses, which do not occur spontaneously entail problems with modeling behavioral impairments and underlying brain deficits. To develop valid models of human disorders we need to test spontaneous behaviors consistently engaging well-defined, evolutionarily conserved neuronal circuits. Such research focuses on behavioral patterns relevant for surviving and thriving under varying environmental conditions, which also enable high reproducibility across different testing settings.

Modeling Parkinson's disease-related symptoms in alpha-synuclein overexpressing mice

BACKGROUND

Intracellular deposition of alpha-synuclein (α-syn) as Lewy bodies and Lewy neurites is a central event in the pathogenesis of Parkinson's disease (PD) and other α-synucleinopathies. Transgenic mouse models overexpressing human α-syn, are useful research tools in preclinical studies of pathogenetic mechanisms. Such mice develop α-syn inclusions as well as neurodegeneration with a topographical distribution that varies depending on the choice of promoter and which form of α-syn that is overexpressed. Moreover, they display motor symptoms and cognitive disturbances that to some extent resemble the human conditions.

PURPOSE

One of the main motives for assessing behavior in these mouse models is to evaluate the potential of new treatment strategies, including their impact on motor and cognitive symptoms. However, due to a high within-group variability with respect to such features, the behavioral studies need to be applied with caution. In this review, we discuss how to make appropriate choices in the experimental design and which tests that are most suitable for the evaluation of PD-related symptoms in such studies.

METHODS

We have evaluated published results on two selected transgenic mouse models overexpressing wild type (L61) and mutated (A30P) α-syn in the context of their validity and utility for different types of behavioral studies.

CONCLUSIONS

By applying appropriate behavioral tests, α-syn transgenic mouse models provide an appropriate experimental platform for studies of symptoms related to PD and other α-synucleinopathies.

Development of behavioral patterns in young C57BL/6J mice: a home cage-based study

Evidence exists that behavioral patterns only stabilize once mice reach adulthood. Detailed information about the course of behavioral patterns is of particular relevance for neuroscientific research and for the assessment of cumulative severity in genetically modified mice. The analysis considered five age groups focusing on behavioral assessments in the animals’ familiar home cage environment during the adolescence phase. We confirmed age- and sex-specific differences for several of the behavioral parameters and fecal corticosterone metabolites. Interestingly, an age-dependent decline in saccharin preference was detected in female mice. Regardless of sex, relevant levels of burrowing activity were only observed during later developmental phases. The development of nest complexity following the offer of new material was affected by age in female mice. In female and male mice, an age-dependency was evident for wheel running reaching a peak at P 50. A progressive increase with age was also observed for Open field activity. The data sets provide guidance for behavioral studies and for development of composite measure schemes for evidence-based severity assessment in young mice. Except for the burrowing test, the different behavioral tests can be applied in different age groups during post-weaning development. However, age- and sex-specific characteristics need to be considered.

Emerging Role of Translational Digital Biomarkers Within Home Cage Monitoring Technologies in Preclinical Drug Discovery and Development

In drug discovery and development, traditional assessment of human patients and preclinical subjects occurs at limited time points in potentially stressful surroundings (i.e., the clinic or a test arena), which can impact data quality and welfare. However, recent advances in remote digital monitoring technologies enable the assessment of human patients and preclinical subjects across multiple time points in familiar surroundings. The ability to monitor a patient throughout disease progression provides an opportunity for more relevant and efficient diagnosis as well as improved assessment of drug efficacy and safety. In preclinical in vivo animal models, these digital technologies allow for continuous, longitudinal, and non-invasive monitoring in the home environment. This manuscript provides an overview of digital monitoring technologies for use in preclinical studies including their history and evolution, current engagement through use cases, and impact of digital biomarkers (DBs) on drug discovery and the 3Rs. We also discuss barriers to implementation and strategies to overcome them. Finally, we address data consistency and technology standards from the perspective of technology providers, end-users, and subject matter experts. Overall, this review establishes an improved understanding of the value and implementation of digital biomarker (DB) technologies in preclinical research.

Measuring Behavior in the Home Cage: Study Design, Applications, Challenges, and Perspectives

The reproducibility crisis (or replication crisis) in biomedical research is a particularly existential and under-addressed issue in the field of behavioral neuroscience, where, in spite of efforts to standardize testing and assay protocols, several known and unknown sources of confounding environmental factors add to variance. Human interference is a major contributor to variability both within and across laboratories, as well as novelty-induced anxiety. Attempts to reduce human interference and to measure more "natural" behaviors in subjects has led to the development of automated home-cage monitoring systems. These systems enable prolonged and longitudinal recordings, and provide large continuous measures of spontaneous behavior that can be analyzed across multiple time scales. In this review, a diverse team of neuroscientists and product developers share their experiences using such an automated monitoring system that combines Noldus PhenoTyper® home-cages and the video-based tracking software, EthoVision® XT, to extract digital biomarkers of motor, emotional, social and cognitive behavior. After presenting our working definition of a "home-cage", we compare home-cage testing with more conventional out-of-cage tests (e.g., the open field) and outline the various advantages of the former, including opportunities for within-subject analyses and assessments of circadian and ultradian activity. Next, we address technical issues pertaining to the acquisition of behavioral data, such as the fine-tuning of the tracking software and the potential for integration with biotelemetry and optogenetics. Finally, we provide guidance on which behavioral measures to emphasize, how to filter, segment, and analyze behavior, and how to use analysis scripts. We summarize how the PhenoTyper has applications to study neuropharmacology as well as animal models of neurodegenerative and neuropsychiatric illness. Looking forward, we examine current challenges and the impact of new developments. Examples include the automated recognition of specific behaviors, unambiguous tracking of individuals in a social context, the development of more animal-centered measures of behavior and ways of dealing with large datasets. Together, we advocate that by embracing standardized home-cage monitoring platforms like the PhenoTyper, we are poised to directly assess issues pertaining to reproducibility, and more importantly, measure features of rodent behavior under more ethologically relevant scenarios.

Three Pillars of Automated Home-Cage Phenotyping of Mice: Novel Findings, Refinement, and Reproducibility Based on Literature and Experience

Animal models of neurodegenerative and neuropsychiatric disorders require extensive behavioral phenotyping. Currently, this presents several caveats and the most important are: (i) rodents are nocturnal animals, but mostly tested during the light period; (ii) the conventional behavioral experiments take into consideration only a snapshot of a rich behavioral repertoire; and (iii) environmental factors, as well as experimenter influence, are often underestimated. Consequently, serious concerns have been expressed regarding the reproducibility of research findings on the one hand, and appropriate welfare of the animals (based on the principle of 3Rs-reduce, refine and replace) on the other hand. To address these problems and improve behavioral phenotyping in general, several solutions have been proposed and developed. Undisturbed, 24/7 home-cage monitoring (HCM) is gaining increased attention and popularity as demonstrating the potential to substitute or complement the conventional phenotyping methods by providing valuable data for identifying the behavioral patterns that may have been missed otherwise. In this review, we will briefly describe the different technologies used for HCM systems. Thereafter, based on our experience, we will focus on two systems, IntelliCage (NewBehavior AG and TSE-systems) and Digital Ventilated Cage (DVC®, Tecniplast)-how they have been developed and applied during recent years. Additionally, we will touch upon the importance of the environmental/experimenter artifacts and propose alternative suggestions for performing phenotyping experiments based on the published evidence. We will discuss how the integration of telemetry systems for deriving certain physiological parameters can help to complement the description of the animal model to offer better translation to human studies. Ultimately, we will discuss how such HCM data can be statistically interpreted and analyzed.

Mouse model systems of autism spectrum disorder: Replicability and informatics signature

Phenotyping mouse model systems of human disease has proven to be a difficult task, with frequent poor inter- and intra-laboratory replicability, particularly in behavioral domains such as social and cognitive function. However, establishing robust animal model systems with strong construct validity is of fundamental importance as they are central tools for understanding disease pathophysiology and developing therapeutics. To complete our studies of mouse model systems relevant to autism spectrum disorder (ASD), we present a replication of the main findings from our two published studies of five genetic mouse model systems of ASD. To assess the intra-laboratory robustness of previous results, we chose the two model systems that showed the greatest phenotypic differences, the Shank3/F and Cntnap2, and repeated assessments of general health, activity and social behavior. We additionally explored all five model systems in the same framework, comparing all results obtained in this three-yearlong effort using informatics techniques to assess commonalities and differences. Our results showed high intra-laboratory replicability of results, even for those with effect sizes that were not particularly large, suggesting that discrepancies in the literature may be dependent on subtle but pivotal differences in testing conditions, housing enrichment, or background strains and less so on the variability of the behavioral phenotypes. The overall informatics analysis suggests that in our behavioral assays we can separate the set of tested mouse model system into two main classes that in some aspects lie on opposite ends of the behavioral spectrum, supporting the view that autism is not a unitary concept.

The Reconfigurable Maze Provides Flexible, Scalable, Reproducible, and Repeatable Tests

Multiple mazes are routinely used to test the performance of animals because each has disadvantages inherent to its shape. However, the maze shape cannot be flexibly and rapidly reproduced in a repeatable and scalable way in a single environment. Here, to overcome the lack of flexibility, scalability, reproducibility, and repeatability, we develop a reconfigurable maze system that consists of interlocking runways and an array of accompanying parts. It allows experimenters to rapidly and flexibly configure a variety of maze structures along the grid pattern in a repeatable and scalable manner. Spatial navigational behavior and hippocampal place coding were not impaired by the interlocking mechanism. As a proof-of-principle demonstration, we demonstrate that the maze morphing induces location remapping of the spatial receptive field. The reconfigurable maze thus provides flexibility, scalability, repeatability, and reproducibility, therefore facilitating consistent investigation into the neuronal substrates for learning and memory and allowing screening for behavioral phenotypes.

Prenatal light exposure influences gait performance and body composition in bobwhite quail chicks

Maternal nesting behavior, which includes periods of patterned inattention, provides key elements essential for avian embryonic development, including regulation of temperature and light. For example, avian research consistently shows the importance of prenatal light exposure for several developmental processes; however, this research has primarily focused on artificial light regimens (i.e. 24 hr, 0 hr light). Comparatively less is known about how exposure to naturally occurring light patterns during incubation influence motor performance, body composition (i.e. body mass, bone length), and developmental age (incubation length). Here we conducted two experiments which investigated the effects of prenatal light exposure on developmental age, body composition, and gait performance in 1-day-old bobwhite quail. Experiment 1 investigated crepuscular light exposure during the last two days of incubation under two light duration treatments (2 hr & 6 hr) compared to a 12 hr continuous light schedule. Results indicated crepuscular prenatal light experience extended the incubation period for 2 hr exposed embryos, but not for 6 hr exposed embryos and negatively influenced postnatal body composition and postnatal gait performance when compared to 12 hr continuous light embryos. Experiment 2 examined the influence of prenatal light duration (2 hr vs 6 hr) and light presentation (crepuscular vs sporadic). Results demonstrated sporadic light presentation improved gait performance in 2 hr exposed hatchlings, but not 6 hr exposed hatchlings, improved body composition in 6 hr exposed hatchlings, but not 2 hr exposed hatchlings, and did not alter incubation length when compared to crepuscular light counterparts. This study provides further evidence for the importance of maternally regulated sensory stimulation during the prenatal period on early postnatal motor development.

Low-cost solution for rodent home-cage behaviour monitoring

In the current research on measuring complex behaviours/phenotyping in rodents, most of the experimental design requires the experimenter to remove the animal from its home-cage environment and place it in an unfamiliar apparatus (novel environment). This interaction may influence behaviour, general well-being, and the metabolism of the animal, affecting the phenotypic outcome even if the data collection method is automated. Most of the commercially available solutions for home-cage monitoring are expensive and usually lack the flexibility to be incorporated with existing home-cages. Here we present a low-cost solution for monitoring home-cage behaviour of rodents that can be easily incorporated to practically any available rodent home-cage. To demonstrate the use of our system, we reliably predict the sleep/wake state of mice in their home-cage using only video. We validate these results using hippocampal local field potential (LFP) and electromyography (EMG) data. Our approach provides a low-cost flexible methodology for high-throughput studies of sleep, circadian rhythm and rodent behaviour with minimal experimenter interference.

Impaired Reversal Learning in APPPS1-21 Mice in the Touchscreen Visual Discrimination Task

Preclinical-clinical translation of cognitive functions has been difficult in Alzheimer's disease (AD) research but is crucial to the (predictive) validity of AD animal models. Reversal learning, a representation of flexibility and adaptability to a changing environment, might represent such a translatable feature of human cognition. We, therefore, examined visual discrimination (VD) and reversal learning in the APPPS1-21 mouse model of amyloid-based AD pathology. We used touchscreen operant cages in novel and translationally valid, as well as objective testing methodology that minimizes within- or between-trial handling. Mice were trained to associate a visual cue with a food reward (VD learning), and subsequently learned to adjust their response when this rule changed (reversal learning). We assessed performance at two different ages, namely at 6 months of age, considered an early disease stage, and at 9 months, a stage of established pathology. Both at 6 and 9 months, transgenic animals needed more sessions to reach criterion performance, compared to wild-type controls. Overall, transgenic animals do not show a general cognitive, motivational or motor deficit, but experience specific difficulties to adapt to reward contingency changes, already at an early pathology stage.

Pros and Cons of Clinically Relevant Methods to Assess Pain in Rodents

The primary objective of preclinical pain research is to improve the treatment of pain. Decades of research using pain-evoked tests has revealed much about mechanisms but failed to deliver new treatments. Evoked pain-tests are often limited because they ignore spontaneous pain and motor or disruptive side effects confound interpretation of results. New tests have been developed to focus more closely on clinical goals such as reducing pathological pain and restoring function. The objective of this review is to describe and discuss several of these tests. We focus on: Grimace Scale, Operant Behavior, Wheel Running, Burrowing, Nesting, Home Cage Monitoring, Gait Analysis and Conditioned Place Preference/ Aversion. A brief description of each method is presented along with an analysis of the advantages and limitations. The pros and cons of each test will help researchers identify the assessment tool most appropriate to meet their particular objective to assess pain in rodents. These tests provide another tool to unravel the mechanisms underlying chronic pain and help overcome the translational gap in drug development.

Behavioral models in psychopathology: epistemic and semantic considerations

The use of animals in neurosciences has a long history. It is considered indispensable in areas in which “translational” research is deemed invaluable, such as behavioral pharmacology and comparative psychology. Animal models are being used in pharmacology and genetics to screen for treatment targets, and in the field of experimental psychopathology to understand the neurobehavioral underpinnings of a disorder and of its putative treatment. The centrality of behavioral models betrays the complexity of the epistemic and semantic considerations which are needed to understand what a model is. In this review, such considerations are made, and the breadth of model building and evaluation approaches is extended to include theoretical considerations on the etiology of mental disorders. This expansion is expected to help improve the validity of behavioral models and to increase their translational value. Moreover, the role of theory in improving construct validity creates the need for behavioral scientists to fully engage this process.

Context-Aware Mouse Behavior Recognition Using Hidden Markov Models

Automated recognition of mouse behaviors is crucial in studying psychiatric and neurologic diseases. To achieve this objective, it is very important to analyze the temporal dynamics of mouse behaviors. In particular, the change between mouse neighboring actions is swift in a short period. In this paper, we develop and implement a novel hidden Markov model (HMM) algorithm to describe the temporal characteristics of mouse behaviors. In particular, we here propose a hybrid deep learning architecture, where the first unsupervised layer relies on an advanced spatial-temporal segment Fisher vector encoding both visual and contextual features. Subsequent supervised layers based on our segment aggregate network are trained to estimate the state-dependent observation probabilities of the HMM. The proposed architecture shows the ability to discriminate between visually similar behaviors and results in high recognition rates with the strength of processing imbalanced mouse behavior datasets. Finally, we evaluate our approach using JHuang's and our own datasets, and the results show that our method outperforms other state-of-the-art approaches.

Social interactions impact on the dopaminergic system and drive individuality

Individuality is a striking feature of animal behavior. Individual animals differ in traits and preferences which shape their interactions and their prospects for survival. However, the mechanisms underlying behavioral individuation are poorly understood and are generally considered to be genetic-based. Here, we devised a large environment, Souris City, in which mice live continuously in large groups. We observed the emergence of individual differences in social behavior, activity levels, and cognitive traits, even though the animals had low genetic diversity (inbred C57BL/6J strain). We further show that the phenotypic divergence in individual behaviors was mirrored by developing differences in midbrain dopamine neuron firing properties. Strikingly, modifying the social environment resulted in a fast re-adaptation of both the animal's traits and its dopamine firing pattern. Individuality can rapidly change upon social challenges, and does not just depend on the genetic status or the accumulation of small differences throughout development.

An automated behavior analysis system for freely moving rodents using depth image

A rodent behavior analysis system is presented, capable of automated tracking, pose estimation, and recognition of nine behaviors in freely moving animals. The system tracks three key points on the rodent body (nose, center of body, and base of tail) to estimate its pose and head rotation angle in real time. A support vector machine (SVM)-based model, including label optimization steps, is trained to classify on a frame-by-frame basis: resting, walking, bending, grooming, sniffing, rearing supported, rearing unsupported, micro-movements, and "other" behaviors. Compared to conventional red-green-blue (RGB) camera-based methods, the proposed system operates on 3D depth images provided by the Kinect infrared (IR) camera, enabling stable performance regardless of lighting conditions and animal color contrast with the background. This is particularly beneficial for monitoring nocturnal animals' behavior. 3D features are designed to be extracted directly from the depth stream and combined with contour-based 2D features to further improve recognition accuracies. The system is validated on three freely behaving rats for 168 min in total. The behavior recognition model achieved a cross-validation accuracy of 86.8% on the rat used for training and accuracies of 82.1 and 83% on the other two "testing" rats. The automated head angle estimation aided by behavior recognition resulted in 0.76 correlation with human expert annotation. Graphical abstract Top view of a rat freely behaving in a standard homecage, captured by Kinect-v2 sensors. The depth image is used for constructing a 3D topography of the animal for pose estimation, behavior recognition, and head angle calculation. Results of the processed data are displayed on the user interface in various forms.

Behavioural characterization of C57BL/6N and BALB/c female mice in social home cage - Effect of mixed housing in complex environment

Developing reliable mouse models for social behaviour is challenging. Different tests have been proposed, but most of them consist of rather artificial confrontations of unfamiliar mice in novel arenas or are relying on social stress induced by aggressive conspecifics. Natural social interaction in home cage in laboratory has not been investigated well. IntelliCage is a fully automated home-cage system, where activity of the group-housed mice can be monitored along with various cognitive tasks. Here we report the behavioural profile of C57BL/6N (B6) and BALB/c (BALB) female mice in IntelliCage when separated by strain, followed by monitoring of activity and formation of 'home-base' after mixing two strains. For that purpose, 3 cages were connected. Significant differences between the strains were established in baseline behaviour in conventional tests and in IntelliCage. The B6 mice showed reduced anxiety-like behaviour in open field and light-dark box, slightly enhanced exploratory activity in IntelliCage during initial adaptation and clearly distinct circadian activity. Mixing of two strains resulted in reduction of body weight and anhedonia in B6 mice. In addition, the B6 mice showed clear preference to previous home-cage, and formed a new home-base faster than BALB mice. In contrast, BALB mice showed enhanced activity and moving between the cages without showing any preference to previous home-cage. It could be argued that social challenge caused changes in both strains and different coping styles are responsible for behavioural manifestations. Altogether, this approach could be useful in modelling and validating mouse models for disorders with disturbed social behaviour.

Active State Organization of Spontaneous Behavioral Patterns

We report the development and validation of a principled analytical approach to reveal the manner in which diverse mouse home cage behaviors are organized. We define and automate detection of two mutually-exclusive low-dimensional spatiotemporal units of behavior: “Active” and “Inactive” States. Analyses of these features using a large multimodal 16-strain behavioral dataset provide a series of novel insights into how feeding, drinking, and movement behaviors are coordinately expressed in Mus Musculus. Moreover, we find that patterns of Active State expression are exquisitely sensitive to strain, and classical supervised machine learning incorporating these features provides 99% cross-validated accuracy in genotyping animals using behavioral data alone. Altogether, these findings advance understanding of the organization of spontaneous behavior and provide a high-throughput phenotyping strategy with wide applicability to behavioral neuroscience and animal models of disease.

Receptor Binding Assays and Drug Discovery

Although Solomon Snyder authored hundreds of research reports and several books covering a broad range of topics in the neurosciences, he is best known by many as the person who developed neurotransmitter receptor radioligand binding assays. By demonstrating the utility of this approach for studying transmitter receptors in brain, Dr. Snyder provided the scientific community with a powerful new tool for identifying and characterizing these sites, for defining their relationship to neurological and psychiatric disorders, and their involvement in mediating the actions of psychotherapeutics. Although it was hoped the receptor binding technique could also be used as a primary screen to speed and simplify the identification of novel drug candidates, experience has taught that ligand binding is most useful for drug discovery when it is used in conjunction with functional, phenotypic assays. The incorporation of ligand binding assays into the drug discovery process played a significant role in altering the search for new therapeutics from solely an empirical undertaking to a mechanistic and hypothesis-driven enterprise. This illustrates the impact of Dr. Snyder's work, not only on neuroscience research but on the discovery, development, and characterization of drugs for treating a variety of medical conditions.

Home-cage anxiety levels in a transgenic rat model for Spinocerebellar ataxia type 17 measured by an approach-avoidance task: The light spot test

BACKGROUND

Measuring anxiety in a reliable manner is essential for behavioural phenotyping of rodent models such as the rat model for Spinocerebellar ataxia type 17 (SCA17) where anxiety is reported in patients. An automated tool for assessing anxiety within the home cage can minimize human intervention, stress of handling, transportation and novelty.

NEW METHOD

We applied the anxiety test "light spot" (LS) (white led directed at the food-hopper) to our transgenic SCA17 rat model in the PhenoTyper 4500^® to extend the knowledge of this automated tool for behavioural phenotyping and to verify an anxiety-like phenotype at three different disease stages for use in future therapeutic studies.

RESULTS

Locomotor activity was increased in SCA17 rats at 6 and 9 months during the first 15min of the LS, potentially reflecting increased risk assessment. Both genotypes responded to the test with lower duration in the LS zone and higher time spent inside the shelter compared to baseline.

COMPARISON WITH EXISTING METHODS

We present the first data of a rat model subjected to the LS. The LS can be considered more biologically relevant than a traditional test as it measures anxiety in a familiar situation.

CONCLUSIONS

The LS successfully evoked avoidance and shelter-seeking in rats. SCA17 rats showed a stronger approach-avoidance conflict reflected by increased activity in the area outside the LS. This home cage test, continuously monitoring pre- and post-effects, provides the opportunity for in-depth analysis, making it a potentially useful tool for detecting subtle or complex anxiety-related traits in rodents.

Developmental neurotoxicity test guidelines: problems and perspectives

Epidemiologic evidence has demonstrated associations between early life exposure to industrial chemicals and the occurrence of disease states, including cognitive and behavioral abnormalities, in children. The developing brain in the fetal and infantile periods is extremely vulnerable to chemicals because the blood-brain barrier is not completely formed during these periods. The Organisation for Economic Co-operation and Development (OECD) developmental neurotoxicity (DNT) test guideline, TG426, updated in 2007, comprises in vivo behavioral observational tests and other tests intended to assess DNT induced by exposure to industrial chemicals. These chemicals may enter the market without having been subjected to DNT testing, as DNT test data is not mandated by law at the time of chemical registration. In addition, proprietary rights have led to problems concerning the non-disclosure of industrial chemical toxicity test data, including DNT test data. To overcome the disadvantages of high-cost and low time efficiency of in vivo DNT tests, in vitro or in silico tests are the proposed alternatives, but it is unlikely that the results of such tests would reflect changes in higher brain functions. Accordingly, the current DNT test guidelines need to be revised to avoid overlooking or neglecting the occurrence of DNT induced by exposure to low doses of chemicals. This review also proposes the introduction of novel in vivo DNT testing methods in light of a cost-performance analysis.

Automated classification of self-grooming in mice using open-source software

BACKGROUND

Manual analysis of behavior is labor intensive and subject to inter-rater variability. Although considerable progress in automation of analysis has been made, complex behavior such as grooming still lacks satisfactory automated quantification.

NEW METHOD

We trained a freely available, automated classifier, Janelia Automatic Animal Behavior Annotator (JAABA), to quantify self-grooming duration and number of bouts based on video recordings of SAPAP3 knockout mice (a mouse line that self-grooms excessively) and wild-type animals.

RESULTS

We compared the JAABA classifier with human expert observers to test its ability to measure self-grooming in three scenarios: mice in an open field, mice on an elevated plus-maze, and tethered mice in an open field. In each scenario, the classifier identified both grooming and non-grooming with great accuracy and correlated highly with results obtained by human observers. Consistently, the JAABA classifier confirmed previous reports of excessive grooming in SAPAP3 knockout mice.

COMPARISON WITH EXISTING METHODS

Thus far, manual analysis was regarded as the only valid quantification method for self-grooming. We demonstrate that the JAABA classifier is a valid and reliable scoring tool, more cost-efficient than manual scoring, easy to use, requires minimal effort, provides high throughput, and prevents inter-rater variability.

CONCLUSION

We introduce the JAABA classifier as an efficient analysis tool for the assessment of rodent self-grooming with expert quality. In our "how-to" instructions, we provide all information necessary to implement behavioral classification with JAABA.

A smart homecage system with 3D tracking for long-term behavioral experiments

A wirelessly-powered homecage system, called the EnerCage-HC, that is equipped with multi-coil wireless power transfer, closed-loop power control, optical behavioral tracking, and a graphic user interface (GUI) is presented for long-term electrophysiology experiments. The EnerCage-HC system can wirelessly power a mobile unit attached to a small animal subject and also track its behavior in real-time as it is housed inside a standard homecage. The EnerCage-HC system is equipped with one central and four overlapping slanted wire-wound coils (WWCs) with optimal geometries to form 3-and 4-coil power transmission links while operating at 13.56 MHz. Utilizing multi-coil links increases the power transfer efficiency (PTE) compared to conventional 2-coil links and also reduces the number of power amplifiers (PAs) to only one, which significantly reduces the system complexity, cost, and dissipated heat. A Microsoft Kinect installed 90 cm above the homecage localizes the animal position and orientation with 1.6 cm accuracy. An in vivo experiment was conducted on a freely behaving rat by continuously delivering 24 mW to the mobile unit for > 7 hours inside a standard homecage.

The water maze paradigm in experimental studies of chronic cognitive disorders: Theory, protocols, analysis, and inference

An instrumental step in assessing the validity of animal models of chronic cognitive disorders is to document disease-related deficits in learning/memory capacity. The water maze (WM) is a popular paradigm because of its low cost, relatively simple protocol and short procedure time. Despite being broadly accepted as a spatial learning task, inference of generalized, bona fide "cognitive" dysfunction can be challenging because task accomplishment is also reliant on non-cognitive processes. We review theoretical background, testing procedures, confounding factors, as well as approaches to data analysis and interpretation. We also describe an extended protocol that has proven useful in detecting early performance deficits in murine models of neuropsychiatric lupus and Alzheimer's disease. Lastly, we highlight the need for standardization of inferential criteria on "cognitive" dysfunction in experimental rodents and exclusion of preparations of a limited scientific merit. A deeper appreciation for the multifactorial nature of performance in WM may also help to reveal other deficits that herald the onset of neurodegenerative brain disorders.

Update of neurotrophic factors in neurobiology of addiction and future directions

Drug addiction is a chronic brain disease and drugs of abuse cause long lasting neuroadaptations. Addiction is characterized by the loss of control over drug use despite harmful consequences, and high rates of relapse even after long periods of abstinence. Neurotrophic factors (NTFs) are well known for their actions on neuronal survival in the peripheral nervous system. Moreover, NTFs have been shown to be involved in synaptic plasticity in the brain. Brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF) are two of the most studied NTFs and both of them have been reported to increase craving when administered into the mesocorticolimbic dopaminergic system after drug self-administration. Here we review recent data on BDNF and GDNF functions in addiction-related behavior and discuss them in relation to previous findings. Finally, we give an insight into how new technologies could aid in further elucidating the role of these factors in drug addiction.

Zebrafish neurobehavioral phenomics for aquatic neuropharmacology and toxicology research

Zebrafish (Danio rerio) are rapidly emerging as an important model organism for aquatic neuropharmacology and toxicology research. The behavioral/phenotypic complexity of zebrafish allows for thorough dissection of complex human brain disorders and drug-evoked pathological states. As numerous zebrafish models become available with a wide spectrum of behavioral, genetic, and environmental methods to test novel drugs, here we discuss recent zebrafish phenomics methods to facilitate drug discovery, particularly in the field of biological psychiatry. Additionally, behavioral, neurological, and endocrine endpoints are becoming increasingly well-characterized in zebrafish, making them an inexpensive, robust and effective model for toxicology research and pharmacological screening. We also discuss zebrafish behavioral phenotypes, experimental considerations, pharmacological candidates and relevance of zebrafish neurophenomics to other 'omics' (e.g., genomic, proteomic) approaches. Finally, we critically evaluate the limitations of utilizing this model organism, and outline future strategies of research in the field of zebrafish phenomics.

Neurobiology of rodent self-grooming and its value for translational neuroscience

Self-grooming is a complex innate behaviour with an evolutionarily conserved sequencing pattern and is one of the most frequently performed behavioural activities in rodents. In this Review, we discuss the neurobiology of rodent self-grooming, and we highlight studies of rodent models of neuropsychiatric disorders--including models of autism spectrum disorder and obsessive compulsive disorder--that have assessed self-grooming phenotypes. We suggest that rodent self-grooming may be a useful measure of repetitive behaviour in such models, and therefore of value to translational psychiatry. Assessment of rodent self-grooming may also be useful for understanding the neural circuits that are involved in complex sequential patterns of action.

Spontaneous Behaviors and Wall-Curvature Lead to Apparent Wall Preference in Planarian

The planarian Dugesia japonica tends to stay near the walls of its breeding containers and experimental dishes in the laboratory, a phenomenon called “wall preference”. This behavior is thought to be important for environmental adaptation, such as hiding by planarians in nature. However, the mechanisms regulating wall-preference behavior are not well understood, since this behavior occurs in the absence of any particular stimulation. Here we show the mechanisms of wall-preference behavior. Surprisingly, planarian wall-preference behavior was also shown even by the head alone and by headless planarians. These results indicate that planarian “wall-preference” behavior only appears to be a “preference” behavior, and is actually an outcome of spontaneous behaviors, rather than of brain function. We found that in the absence of environmental cues planarians moved basically straight ahead until they reached a wall, and that after reaching a wall, they changed their direction of movement to one tangential to the wall, suggesting that this spontaneous behavior may play a critical role in the wall preference. When we tested another spontaneous behavior, the wigwag movement of the planarian head, using computer simulation with various wigwag angles and wigwag intervals, large wigwag angle and short wigwag interval reduced wall-preference behavior. This indicated that wigwag movement may determine the probability of staying near the wall or leaving the wall. Furthermore, in accord with this simulation, when we tested planarian wall-preference behavior using several assay fields with different curvature of the wall, we found that concavity and sharp curvature of walls negatively impacted wall preference by affecting the permissible angle of the wigwag movement. Together, these results indicate that planarian wall preference may be involuntarily caused by the combination of two spontaneous planarian behaviors: moving straight ahead until reaching a wall and then moving along it in the absence of environmental cues, and wigwag movements of the head.

A Smart Wirelessly Powered Homecage for Long-Term High-Throughput Behavioral Experiments

A wirelessly powered homecage system, called the EnerCage-HC, that is equipped with multicoil wireless power transfer, closed-loop power control, optical behavioral tracking, and a graphic user interface is presented for longitudinal electrophysiology and behavioral neuroscience experiments. The EnerCage-HC system can wirelessly power a mobile unit attached to a small animal subject and also track its behavior in real-time as it is housed inside a standard homecage. The EnerCage-HC system is equipped with one central and four overlapping slanted wire-wound coils with optimal geometries to form three- and four-coil power transmission links while operating at 13.56 MHz. Utilizing multicoil links increases the power transfer efficiency (PTE) compared with conventional two-coil links and also reduces the number of power amplifiers to only one, which significantly reduces the system complexity, cost, and heat dissipation. A Microsoft Kinect installed 90 cm above the homecage localizes the animal position and orientation with 1.6-cm accuracy. Moreover, a power management ASIC, including a high efficiency active rectifier and automatic coil resonance tuning, was fabricated in a 0.35-μm 4M2P standard CMOS process for the mobile unit. The EnerCage-HC achieves a max/min PTE of 36.3%/16.1% at the nominal height of 7 cm. In vivo experiments were conducted on freely behaving rats by continuously delivering 24 mW to the mobile unit for >7 h inside a standard homecage.

Ethological concepts enhance the translational value of animal models

The translational value of animal models is an issue of ongoing discussion. We argue that 'Refinement' of animal experiments is needed and this can be achieved by exploiting an ethological approach when setting up and conducting experiments. Ethology aims to assess the functional meaning of behavioral changes, due to experimental manipulation or treatment, in animal models. Although the use of ethological concepts is particularly important for studies involving the measurement of animal behavior (as is the case for most studies on neuro-psychiatric conditions), it will also substantially benefit other disciplines, such as those investigating the immune system or inflammatory response. Using an ethological approach also involves using more optimal testing conditions are employed that have a biological relevance to the animal. Moreover, using a more biological relevant analysis of the data will help to clarify the functional meaning of the modeled readout (e.g. whether it is psychopathological or adaptive in nature). We advocate for instance that more behavioral studies should use animals in group-housed conditions, including the recording of their ultrasonic vocalizations, because (1) social behavior is an essential feature of animal models for human 'social' psychopathologies, such as autism and schizophrenia, and (2) social conditions are indispensable conditions for appropriate behavioral studies in social species, such as the rat. Only when taking these elements into account, the validity of animal experiments and, thus, the translation value of animal models can be enhanced.

Toward a science of computational ethology

The new field of “Computational Ethology” is made possible by advances in technology, mathematics, and engineering that allow scientists to automate the measurement and the analysis of animal behavior. We explore the opportunities and long-term directions of research in this area.

A 1-night operant learning task without food-restriction differentiates among mouse strains in an automated home-cage environment

Individuals are able to change their behavior based on its consequences, a process involving instrumental learning. Studying instrumental learning in mice can provide new insights in this elementary aspect of cognition. Conventional appetitive operant learning tasks that facilitate the study of this form of learning in mice, as well as more complex operant paradigms, require labor-intensive handling and food deprivation to motivate the animals. Here, we describe a 1-night operant learning protocol that exploits the advantages of automated home-cage testing and circumvents the interfering effects of food restriction. The task builds on behavior that is part of the spontaneous exploratory repertoire during the days before the task. We compared the behavior of C57BL/6J, BALB/cJ and DBA/2J mice and found various differences in behavior during this task, but no differences in learning curves. BALB/cJ mice showed the largest instrumental learning response, providing a superior dynamic range and statistical power to study instrumental learning by using this protocol. Insights gained with this home-cage-based learning protocol without food restriction will be valuable for the development of other, more complex, cognitive tasks in automated home-cages.

Sheltering behavior and locomotor activity in 11 genetically diverse common inbred mouse strains using home-cage monitoring

Functional genetic analyses in mice rely on efficient and in-depth characterization of the behavioral spectrum. Automated home-cage observation can provide a systematic and efficient screening method to detect unexplored, novel behavioral phenotypes. Here, we analyzed high-throughput automated home-cage data using existing and novel concepts, to detect a plethora of genetic differences in spontaneous behavior in a panel of commonly used inbred strains (129S1/SvImJ, A/J, C3H/HeJ, C57BL/6J, BALB/cJ, DBA/2J, NOD/LtJ, FVB/NJ, WSB/EiJ, PWK/PhJ and CAST/EiJ). Continuous video-tracking observations of sheltering behavior and locomotor activity were segmented into distinguishable behavioral elements, and studied at different time scales, yielding a set of 115 behavioral parameters of which 105 showed highly significant strain differences. This set of 115 parameters was highly dimensional; principal component analysis identified 26 orthogonal components with eigenvalues above one. Especially novel parameters of sheltering behavior and parameters describing aspects of motion of the mouse in the home-cage showed high genetic effect sizes. Multi-day habituation curves and patterns of behavior surrounding dark/light phase transitions showed striking strain differences, albeit with lower genetic effect sizes. This spontaneous home-cage behavior study demonstrates high dimensionality, with a strong genetic contribution to specific sets of behavioral measures. Importantly, spontaneous home-cage behavior analysis detects genetic effects that cannot be studied in conventional behavioral tests, showing that the inclusion of a few days of undisturbed, labor extensive home-cage assessment may greatly aid gene function analyses and drug target discovery.

Current approaches for the discovery of drugs that deter substance and drug abuse

INTRODUCTION

Much has been presented and debated on the topic of drug abuse and its multidimensional nature, including the role of society and its customs and laws, economical factors, and the magnitude and nature of the burden. Given the complex nature of the receptors and pathways implicated in regulation of the cognitive and behavioral processes associated with addiction, a large number of molecular targets have been interrogated during recent years to discover starting points for development of small-molecule interventions.

AREAS COVERED

This review describes recent developments in the field of early drug discovery for drug abuse interventions with an emphasis on the advances published during the 2012 - 2014 period.

EXPERT OPINION

Technologically, the processes/platforms utilized in drug abuse drug discovery are nearly identical to those used in the other disease areas. A key complicating factor in drug abuse research is the enormous biological complexity surrounding the brain processes involved and the associated difficulty in finding 'good' targets and achieving exquisite selectivity of treatment agents. While tremendous progress has been made during recent years to use the power of high-throughput technologies to discover proof-of-principle molecules for many new targets, next-generation models will be especially important in this field. Examples include: seeking advantageous drug-drug combinations, the use of automated whole-animal behavioral screening systems, advancing our understanding of the role of epigenetics in drug addiction and the employment of organoid-level 3D test platforms (also referred to as tissue-chip or organs-on-chip).

Assessment of attention and inhibitory control in rodent developmental neurotoxicity studies

In designing screens to assess potential neurotoxicants, the paramount goal is that the selected assessment tools detect dysfunction if it exists. This goal is particularly challenging in the case of cognitive assessments. Cognition is not a unitary phenomenon, and indeed there is growing evidence that different aspects of cognitive functioning are subserved by distinct neural systems. As a result, if a particular neurotoxicant selectively damages certain neural systems but not others, it can impair some cognitive, sensory, or affective functions, but leave many others intact. Accordingly, studies with human subjects use batteries of cognitive tests, cognizant of the fact that no one test is capable of detecting all forms of cognitive dysfunction. In contrast, assessment of cognitive functioning in non-human animal developmental neurotoxicity (DNT) studies typically consists of a single, presumably representative, "learning and memory" task that is expected to detect all potential effects on cognitive functioning. Streamlining the cognitive assessment in these studies saves time and money, but these shortcuts can have serious consequences if the aspect of cognitive functioning that is impaired is not tapped by the single selected task. In particular, executive functioning - a constellation of cognitive functions which enables the organism to focus on multiple streams of information simultaneously, and revise plans as necessary - is poorly assessed in most animal DNT studies. The failure to adequately assess these functions - which include attention, working memory, inhibitory control, and planning - is particularly worrisome in light of evidence that the neural systems that subserve these functions may be uniquely vulnerable to early developmental insults. We illustrate the importance of tapping these areas of functioning in DNT studies by describing the pattern of effects produced by early developmental Pb exposure. Rats exposed to lead (Pb) early in development were tested on a series of automated attention tasks, as well as on a radial arm maze task. The lead-exposed rats were not impaired in this demanding radial arm maze task, despite conditions which tapped the limits of both working and long-term memory. In contrast, the automated tests designed to assess rodent executive functioning revealed selective and functionally important deficits in attention and regulation of emotion or negative affect (produced by committing an error or not receiving an expected reward). This example underscores the importance of including tasks to specifically tap executive functioning in DNT batteries. Such tasks are not only sensitive but can also shed light on the specific nature of the dysfunction, and they can implicate dysfunction of specific neural systems, information which can be used to design therapeutic interventions. Although the use of such tasks increases the time and effort needed to complete the battery, the benefits outweigh the cost, in light of the greater sensitivity of the battery and the more complete characterization of effects.