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Female mosquitoes use odor and heat as cues to navigate to a suitable landing site on their blood host. The way these cues affect flight behavior and modulate anemotactic responses, however, is poorly understood. We studied in-flight behavioral responses of females of the nocturnal malaria mosquito Anopheles gambiae sensu stricto to human odor and heat. Flight-path characteristics in a wind tunnel (flow 20 cm/s) were quantified in three dimensions. With wind as the only stimulus (control), short and close to straight upwind flights were recorded. With heat alone, flights were similarly short and direct. The presence of human odor, in contrast, caused prolonged and highly convoluted flight patterns. The combination of odor+heat resulted in longer flights with more landings on the source than to either cue alone. Flight speed was greatest (mean groundspeed 27.2 cm/s) for odor+heat. Odor alone resulted in decreased flight speed when mosquitoes arrived within 30 cm of the source whereas mosquitoes exposed to odor+heat maintained a high flight speed while flying in the odor plume, until they arrived within 15 cm of the source. Human odor evoked an increase in crosswind flights with an additive effect of heat at close range (<15 cm) to the source. This was found for both horizontal and vertical flight components. However, mosquitoes nevertheless made upwind progress when flying in the odor+heat generated plume, suggesting that mosquitoes scan their environment intensively while they progress upwind towards their host. These observations may help to improve the efficacy of trapping systems for malaria mosquitoes by (1) optimizing the site of odor release relative to trap entry and (2) adding a heat source which enhances a landing response.

The establishment of robust and replicable behavioural testing paradigms with translational value for psychiatric diseases is a major step forward in developing and testing etiology-directed treatment for these complex disorders. Based on the existing literature, we have generated an inventory of applied rodent behavioural testing paradigms relevant to autism spectrum disorders (ASD). This inventory focused on previously used paradigms that assess behavioural domains that are affected in ASD, such as social interaction, social communication, repetitive behaviours and behavioural inflexibility, cognition as well as anxiety behaviour. A wide range of behavioural testing paradigms for rodents were identified. However, the level of face and construct validity is highly variable. The predictive validity of these paradigms is unknown, as etiology-directed treatments for ASD are currently not on the market. To optimise these studies, future efforts should address aspects of reproducibility and take into account data about the neurodevelopmental underpinnings and trajectory of ASD. In addition, with the increasing knowledge of processes underlying ASD, such as sensory information processes and synaptic plasticity, phenotyping efforts should include multi-level automated analysis of, for example, representative task-related behavioural and electrophysiological read-outs.

Automated gait assessment tests are used in studies of disorders characterized by gait impairment. CatWalk XT is one of the first commercially available automated systems for analyzing the gait of rodents and is currently the most used system in peer-reviewed publications. This automated gait analysis system can generate a large number of gait parameters. However, this creates a new challenge in selecting relevant parameters that describe the changes within a particular disease model. Here, for the first time, we performed a multi-disorder review on published CatWalk XT data. We identify commonly reported CatWalk XT gait parameters derived from 91 peer-reviewed experimental studies in mice, covering six disorders of the central nervous system (CNS) and peripheral nervous system (PNS). The disorders modeled in mice were traumatic brain injury (TBI), stroke, sciatic nerve injury (SNI), spinal cord injury (SCI), Parkinson’s disease (PD), and ataxia. Our review consisted of parameter selection, clustering, categorization, statistical evaluation, and data visualization. It suggests that certain gait parameters serve as potential indicators of gait dysfunction across multiple disease models, while others are specific to particular models. The findings also suggest that the more site-specific the injury is, the fewer parameters are reported to characterize its gait abnormalities. This study strives to present a clearly organized picture of gait parameters used in each one of the different mouse models, potentially helping novel CatWalk XT users to apply this information to similar or related mouse models they are working on.

Background Piercing-sucking insects cause severe damage in crops. Breeding for host-plant resistance can significantly reduce the yield losses caused by these insects, but host-plant resistance is a complex trait that is difficult to phenotype quickly and reliably. Current phenotyping methods mainly focus on labor-intensive and time-consuming end-point measurements of plant fitness. Characterizing insect behavior as a proxy for host-plant resistance could be a promising time-saving alternative to end-point measurements. Results We present a phenotyping platform that allows screening for host-plant resistance against Western flower thrips (WFT, Frankliniella occidentalis (Pergande)) in a parallel two-choice setup using automated video tracking of thrips behavior. The platform was used to establish host-plant preference of WFT with a large plant population of 345 wild Arabidopsis accessions and the method was optimized with two extreme accessions from this population that differed in resistance towards WFT. To this end, the behavior of 88 WFT individuals was simultaneously tracked in 88 parallel two-choice arenas during 8 h. Host-plant preference of WFT was established both by the time thrips spent on either accession and various behavioral parameters related to movement (searching) and non-movement (feeding) events. Conclusion In comparison to 6-day end-point choice assays with whole plants or detached leaves, the automated video-tracking choice assay developed here delivered similar results, but with higher time- and resource efficiency. This method can therefore be a reliable and effective high throughput phenotyping tool to assess host-plant resistance to thrips in large plant populations.

The Observer was originally developed as a manual event recorder for the collection, management, analysis, and presentation of observational data in animals. Because of the flexibility of later versions, it became clear that The Observer was suitable for almost any study involving collection of observational data in both animals and humans. Furthermore, the most recent version of The Observer (The Observer XT) allows the integration and synchronization of multimodal signals from various sources, such as observational, video, tracking, and physiological data. This article describes how The Observer XT was used to integrate and synchronize video, observational, tracking, and physiological data from an experiment carried out in 2001 at the Wageningen Institute of Animal Sciences of Wageningen University and Research Centre. The integration and synchronization of these multimodal signals in The Observer XT allows the user to draw a more complete picture of the phenomena under study.

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 enables 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 including their history and evolution, current engagement through use cases, and impact of digital biomarkers 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 technologies in preclinical research.

Automated observation and analysis of behavior is important to facilitate progress in many fields of science. Recent developments in deep learning have enabled progress in object detection and tracking, but rodent behavior recognition struggles to exceed 75–80% accuracy for ethologically relevant behaviors. We investigate the main reasons why and distinguish three aspects of behavior dynamics that are difficult to automate. We isolate these aspects in an artificial dataset and reproduce effects with the state-of-the-art behavior recognition models. Having an endless amount of labeled training data with minimal input noise and representative dynamics will enable research to optimize behavior recognition architectures and get closer to human-like recognition performance for behaviors with challenging dynamics.

Inconsistent findings between laboratories are hampering scientific progress and are of increasing public concern. Differences in laboratory environment is a known factor contributing to poor reproducibility of findings between research sites, and well-controlled multisite efforts are an important next step to identify the relevant factors needed to reduce variation in study outcome between laboratories. Through harmonization of apparatus, test protocol, and aligned and non-aligned environmental variables, the present study shows that behavioral pharmacological responses in Shank2 knockout (KO) rats, a model of synaptic dysfunction relevant to autism spectrum disorders, were highly replicable across three research centers. All three sites reliably observed a hyperactive and repetitive behavioral phenotype in KO rats compared to their wild-type littermates as well as a dose-dependent phenotype attenuation following acute injections of a selective mGluR1 antagonist. These results show that reproducibility in preclinical studies can be obtained and emphasizes the need for high quality and rigorous methodologies in scientific research. Considering the observed external validity, the present study also suggests mGluR1 as potential target for the treatment of autism spectrum disorders.

Speed is a key trait of animal movement, and while much is already known about vertebrate speed and how it scales with body mass, studies on invertebrates are sparse, especially across diverse taxonomic groups. Here, we used automated image-based tracking to characterize the exploratory (voluntary) speed of 173 invertebrates comprising 57 species across six taxonomic groups (Arachnida, Chilopoda, Diplopoda, Entognatha, Insecta, Malacostraca) and four feeding types (carnivore, detritivore, herbivore, omnivore). Across all individuals, exploratory speed (mm/s) scaled with body mass (g) following a power-law relationship with a scaling exponent of 0.19 ± 0.04 (mean ± SE) and an intercept of 14.33 ± 1.2. These parameters varied substantially with taxonomic group and feeding type. For the first time, we provide general empirically derived allometric scaling relationships of exploratory speed across broad taxonomic groups of invertebrates. As exploratory speed drives key components of species interactions, such as encounter and attack rates, or competition, our study contributes to a deeper understanding of the role of individual movement in population and community level processes.

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.