An infrared range camera-based approach for three-dimensional locomotion tracking and pose reconstruction in a rodent

A Large-Scale Mouse Pose Dataset for Mouse Pose Estimation

Mouse pose estimations have important applications in the fields of animal behavior research, biomedicine, and animal conservation studies. Accurate and efficient mouse pose estimations using computer vision are necessary. Although methods for mouse pose estimations have developed, bottlenecks still exist. One of the most prominent problems is the lack of uniform and standardized training datasets. Here, we resolve this difficulty by introducing the mouse pose dataset. Our mouse pose dataset contains 40,000 frames of RGB images and large-scale 2D ground-truth motion images. All the images were captured from interacting lab mice through a stable single viewpoint, including 5 distinct species and 20 mice in total. Moreover, to improve the annotation efficiency, five keypoints of mice are creatively proposed, in which one keypoint is at the center and the other two pairs of keypoints are symmetric. Then, we created simple, yet effective software that works for annotating images. It is another important link to establish a benchmark model for 2D mouse pose estimations. We employed modified object detections and pose estimation algorithms to achieve precise, effective, and robust performances. As the first large and standardized mouse pose dataset, our proposed mouse pose dataset will help advance research on animal pose estimations and assist in application areas related to animal experiments.

Simultaneous assessment of spontaneous cage activity and voluntary wheel running in group-housed mice

Small animal models are frequently used to improve our understanding of the molecular and biological signaling pathways underlying the beneficial effects of physical activity and exercise. Unfortunately, when running wheels are employed, mice and rats are often kept single-housed to determine the individual running distance of each animal. However, social isolation can be stressful for rodents, and may alter an individual’s propensity for or response to exercise. For example, increased stress from single housing may significantly affect the results when investigating systemic metabolic responses to exercise. We have combined two already available and well-established systems, a radiotelemetry system and a running wheel, to determine spontaneous cage activity (SCA) as well as voluntary exercise (VE) levels of the individual animal in group-housed rodents. Further, we developed a simple software tool which allows monitoring and analyzing the data. Specifically, the radiotelemetry-system utilizes radio-frequency identification via a small, implanted chip to determine the location of each animal. Since, in addition to the animals’ position, also the location of the running wheel in the cage is known, the conclusion of which animal is exercising can be drawn. The developed software enables a fast and reliable assignment of the VE data to the individual animal and a simple analysis of the data collected. Hence, our combined method may be used to investigate the beneficial effects of physical activity, as well as the impact of therapeutic interventions on animal behavior in group-housed rodents.

Detecting fine and elaborate movements with piezo sensors provides non-invasive access to overlooked behavioral components

Behavioral phenotyping devices have been successfully used to build ethograms, but many aspects of behavior remain out of reach of available phenotyping systems. We now report on a novel device, which consists in an open-field platform resting on highly sensitive piezoelectric (electromechanical) pressure-sensors, with which we could detect the slightest movements (up to individual heart beats during rest) from freely moving rats and mice. The combination with video recordings and signal analysis based on time-frequency decomposition, clustering, and machine learning algorithms provided non-invasive access to previously overlooked behavioral components. The detection of shaking/shivering provided an original readout of fear, distinct from but complementary to behavioral freezing. Analyzing the dynamics of momentum in locomotion and grooming allowed to identify the signature of gait and neurodevelopmental pathological phenotypes. We believe that this device represents a significant progress and offers new opportunities for the awaited advance of behavioral phenotyping.

Reconstruction of Flight Parameters of a Bat for Flapping Robots

The flight of bats is comparatively less documented and understood than birds and insects and may provide novel inspiration for the design of flapping flight robots. This study captured the natural flight of short-nosed fruit bats (Cynopterus sphinx) by an optical motion capture system, 'OptiTrack', with pasted markers on the wings and body to reconstruct the flight parameters. Due to the self-occlusion at some moments, points on the membrane wings cannot be captured by any cameras. To draw a smooth trajectory, it is desired to reconstruct all missing data. Therefore, an algorithm is proposed by using numerical techniques, accompanied by modern mathematical and computational tools, to envisage the missing data from the captured flight. The least-square fitted polynomial engendered the parameter equations for x-, y- and z-coordinates of marked points which were used to reconstruct the trajectory of the flight. The parameter equations of position coordinates were also used to compute the morphological and aerodynamic characteristics of the flight. The most outstanding contribution of the work is that not only the trajectory, velocity and velocity field but also the morphing areas of the membrane wings were recreated using the reconstructed data. These data and reconstructed curves of trajectory and velocity field will be used for the further aerodynamic analysis and mechanism design of the flapping robot. This method can also be generalized to reconstruct the performance parameters of any other animals for bionic design.

Direct Measurements of the Wing Kinematics of a Bat in Straight Flight

Bat is the only mammal in the nature that can fly. Compared with birds and insects, bats are quite special in that their wings are formed by an elastic membrane, which renders that the airfoil deforms greatly during downstroke and upstroke. Due to the compliant skin of a bat, the movements of its wings are three-dimensionally complex during diverse flight behaviors. To understand the maneuverability and flight performance, three-dimensional reconstruction of the flight kinematics is essential. This study focuses on the reconstruction of the wing kinematics of the bat and identifies the primary relationship of parameters of aerodynamics in straight flight. With markers pasted on the wings and body of a bat, the motions of these points are recorded by a computerized optical motion capture system. The kinematic analysis shows that the motion of wings is very intricate. The digits of the wing display the sign of coupled motion. A novel approach was developed to measure the angle of attack and flapping angle of the wing. The angle of attack of leading edge differs with the overall angle of attack of the wing. The kinematics of the bat's wing is helpful to interpret the secret of the bat's flight.

Improved 3D tracking and automated classification of rodents' behavioral activity using depth-sensing cameras

Analysis of rodents' behavior/activity is of fundamental importance in many research fields. However, many behavioral experiments still rely on manual scoring, with obvious problems in reproducibility. Despite important advances in video-analysis systems and computational ethology, automated behavior quantification is still a challenge. The need for large training datasets, background stability requirements, and reduction to two-dimensional analysis (impairing full posture characterization), limit their use. Here we present a novel integrated solution for behavioral analysis of individual rats, combining video segmentation, tracking of body parts, and automated classification of behaviors, using machine learning and computer vision methods. Low-cost depth cameras (RGB-D) are used to enable three-dimensional tracking and classification in dark conditions and absence of color contrast. Our solution automatically tracks five anatomical landmarks in dynamic environments and recognizes seven distinct behaviors, within the accuracy range of human annotations. The developed free software was validated in experiments where behavioral differences between Wistar Kyoto and Wistar rats were automatically quantified. The results reveal the capability for effective automated phenotyping. An extended annotated RGB-D dataset is also made publicly available. The proposed solution is an easy-to-use tool, with low-cost setup and powerful 3D segmentation methods (in static/dynamic environments). The ability to work in dark conditions means that natural animal behavior is not affected by recording lights. Furthermore, automated classification is possible with only ~30 minutes of annotated videos. By creating conditions for high-throughput analysis and reproducible quantitative measurements of animal behavior experiments, we believe this contribution can greatly improve behavioral analysis research.

Assessment of nest building and social interaction behavior in mice exposed to acute social defeat stress using a three-dimensional depth camera

Nest building is an instinctive behavior toward protection from predators, body temperature regulation, and courtship. Previously, we discovered that acute and chronic social defeat stress suppresses the onset of nest-building behavior in male mice (C57BL/6J). Here, we analyzed nest building and other behavioral deficits induced by acute social defeat stress (ASDS). We utilized a customized cage and specifically developed observational programs for nest building, social avoidance, and other behaviors using an infrared depth camera to acquire three-dimensional (3D) data of animal behavior (Negura system). We determined the volume of nesting materials from these 3D depth images. Mice exposed to ASDS showed increased spontaneous activities, decreased rearing, and delayed nest building; however, nest-building activity was gradually recovered during the dark period of the 24 hr observation interval. At the endpoint following 24 hr, the ASDS and control groups showed no differences in nest volumes. Furthermore, we observed the time courses of both nest building and social avoidance behaviors and their relationship using the Negura system. Our data demonstrated a weak positive correlation between nest-building delay and social avoidance in ASDS mice. The Negura system can observe various behaviors that reflect the effects of social defeat stress.

Computer Methods for Automatic Locomotion and Gesture Tracking in Mice and Small Animals for Neuroscience Applications: A Survey

Neuroscience has traditionally relied on manually observing laboratory animals in controlled environments. Researchers usually record animals behaving freely or in a restrained manner and then annotate the data manually. The manual annotation is not desirable for three reasons; (i) it is time-consuming, (ii) it is prone to human errors, and (iii) no two human annotators will 100% agree on annotation, therefore, it is not reproducible. Consequently, automated annotation for such data has gained traction because it is efficient and replicable. Usually, the automatic annotation of neuroscience data relies on computer vision and machine learning techniques. In this article, we have covered most of the approaches taken by researchers for locomotion and gesture tracking of specific laboratory animals, i.e. rodents. We have divided these papers into categories based upon the hardware they use and the software approach they take. We have also summarized their strengths and weaknesses.

A noninterfering system to measure in-cage spontaneous physical activity in mice

Due to lack of low-cost and convenient measurement procedures, uncontrolled changes in spontaneous physical activity (SPA) level often are insufficiently considered as a confounding factor in rodent studies. Nonetheless, alterations in SPA can significantly impact on a wide range of physiological measurements. Therefore, we developed an accurate, low-cost video tracking procedure to allow routine assessment of SPA in the home cage of experimental animals (i.e., mice) and in the absence of any distress that might cause alterations in SPA. SPA parameters acquired (movement distance, movement time, and movement speed) with the novel tracking system were identical to those simultaneously obtained with a high-end and well-validated movement-tracking device (mean error = 0.15 ± 0.07%, r = 0.99, P < 0.001). To further validate the setup, we also demonstrated caffeine-induced stimulation of SPA (195% more activity compared with vehicle, P < 0.01), we adequately reproduced typical SPA fluctuations inherent to day/night cycles (146 and 702% more active during nocturnal compared with diurnal cycle for Balb/c and C57BL/6J mice, respectively, P < 0.001), and we confirmed previously documented SPA differences between animal strains (24% less activity in C57BL/6J mice compared with Balb/c mice, P < 0.05). Taken together, we provide data to prove that this novel low-cost methodology can be conveniently used in any mouse experiment where uncontrolled changes in SPA due to experimental interventions might confound data interpretation. By analogy, the system can be used to document a beneficial impact of therapeutic interventions on SPA in any disease mouse model. NEW & NOTEWORTHY We developed a low-cost procedure to routinely measure SPA in mice. The procedure maintains normal SPA because the animals continue to stay in their home cage in the absence of any external manipulation by the investigators and under habitual dark/light ambient conditions. This novel methodology can be conveniently used in any mouse experiment to quantify experimentally induced alterations in SPA or to assess natural variations in SPA that might confound data interpretation.

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.

The Mouse as a Model Organism for Assessing Anesthetic Sensitivity

The mouse has been used in many medical fields as a powerful model to reveal the genetic basis of human physiology and disease. The past two decades have witnessed an enormous wealth of genetic and informatic resources dedicated to this humble organism. With the ongoing revolution in mapping neural circuitry governing behavior, the mouse is an ideal model organism poised to unravel the mysteries of general anesthetic action. This chapter will describe and provide guidelines for anesthetic phenotyping in the mouse including both motor-dependent and motor-independent assessments.

Mouse Behavior Tracker: An economical method for tracking behavior in home cages

Analysis of mouse behavior often requires expensive equipment and transfer of the mice to new test environments, which could trigger confounding behavior alterations. Here, we describe a system for tracking mouse behavior in home cages using a low-cost USB webcam and free software (Fiji and wrMTrck). We demonstrate the effectiveness of this method by tracking differences in distance traveled, speed, and movement tracks between wild-type mice and amyotrophic lateral sclerosis (ALS) model mice (SOD1G93A).

Social factors affect motor and anxiety behaviors in the animal model of attention-deficit hyperactivity disorders: A housing-style factor

The present study examines whether housing style (e.g., single housing, same-strain-grouped housing, and different-strain-grouped housing) and rat strain (e.g., spontaneous hypertension rats [SHR] and Wistar-Kyoto rats [WKY]) mediate motor function and anxiety behavior in the open field task. From week 4 through week 10 following birth, the rats were measured 30min for locomotor activity and anxiety once per week in the open field task. The SHR rats exhibited hyperactivity in total distance traveled and movement time to form the animal model of ADHD. The SHR rats spent more time inside the square and crossed the inside-outside line more often than the WKY rats, indicating the SHR rats exhibited less anxiety behavior. The different-strain-grouped housing style (but neither the same-strain-grouped housing style nor the single housing style) decreased total distance traveled and facilitated anxiety behavior. The motor function was negatively correlated with anxiety behavior for SHR rats but not for WKY rats. Housing styles had a negative correlation between motor function and anxiety behavior. The present findings provide some insights regarding how social factors (such as housing style) affect motor function and anxiety behavior related to ADHD in a clinical setting.

A novel automated rodent tracker (ART), demonstrated in a mouse model of amyotrophic lateral sclerosis

BACKGROUND

Generating quantitative metrics of rodent locomotion and general behaviours from video footage is important in behavioural neuroscience studies. However, there is not yet a free software system that can process large amounts of video data with minimal user interventions.

NEW METHOD

Here we propose a new, automated rodent tracker (ART) that uses a simple rule-based system to quickly and robustly track rodent nose and body points, with minimal user input. Tracked points can then be used to identify behaviours, approximate body size and provide locomotion metrics, such as speed and distance.

RESULTS

ART was demonstrated here on video recordings of a SOD1 mouse model, of amyotrophic lateral sclerosis, aged 30, 60, 90 and 120days. Results showed a robust decline in locomotion speeds, as well as a reduction in object exploration and forward movement, with an increase in the time spent still. Body size approximations (centroid width), showed a significant decrease from P30.

COMPARISON WITH EXISTING METHOD(S)

ART performed to a very similar accuracy as manual tracking and Ethovision (a commercially available alternative), with average differences in coordinate points of 0.6 and 0.8mm, respectively. However, it required much less user intervention than Ethovision (6 as opposed to 30 mouse clicks) and worked robustly over more videos.

CONCLUSIONS

ART provides an open-source option for behavioural analysis of rodents, performing to the same standards as commercially available software. It can be considered a validated, and accessible, alternative for researchers for whom non-invasive quantification of natural rodent behaviour is desirable.

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.

A low-cost system to easily measure spontaneous physical activity in rodents

Spontaneous physical activity (SPA) can be responsible for variations of a lot of physiological parameters at the molecular, cellular, tissue, and systemic levels. It is increasingly recognized that good understanding of a large part of experimental results requires weighting them by SPA in order to reduce variability and thus to decrease the number of animals necessary to conduct a study. However, because of the high cost of this equipment, only a few laboratories are equipped with such equipment to measure the SPA of their animals. Here we present an effective, adaptable, and affordable system to measure SPA in rodents based on video acquisition of the animal in its own environment. We compared results obtained with our system to those collected at the same time with a commercial system of actimetry recording, and we found a high degree of correlation between these two approaches ( r = 0.93; P < 0.001). We also were able to detect small variations of SPA induced by a special environment like chronic hypoxia exposure (25% less spontaneous activity compared with animals in normoxia, P < 0.05) or during the circadian cycle (107% more activity during the nocturnal phase compared with the diurnal phase, P < 0.05).

Murine Depression Model and its Potential Applications for Discovering Foods and Farm Products with Antidepressant-Like Effects

Advanced societies face increased health problems related to various stresses. Chronic psychological stress is a major risk factor for psychiatric disorders such as depression. Although therapeutic agents reduce several symptoms of depression, most have side effects in a broad range of the population. Furthermore, some victims of depression do not show significant improvement with any drugs, so alternative approaches are needed. Good dietary habits may potentially reduce depressive symptoms, but there is little scientific evidence thus far. Murine depression models are useful to test nutritional approaches in vivo. Our model mice subjected to a subchronic mild social defeat stress (sCSDS) paradigm show several alterations in physiological parameters and social behavior. These stress-induced symptoms in sCSDS mice can be used as cues to identify antidepressant-like natural resources including foods and farm products. We previously discovered that sCSDS mice show more vulnerability to social stress by changing dietary condition. In addition, we developed a more objective system for analyzing mouse behavior using a 3D depth-sensing camera to understand relationships between diet and behavior. The combination of sCSDS mice with 3D behavioral analysis is a powerful method for screening ingredients in foods and farm products for antidepressant-like effects.

Mapping Sub-Second Structure in Mouse Behavior

Complex animal behaviors are likely built from simpler modules, but their systematic identification in mammals remains a significant challenge. Here we use depth imaging to show that 3D mouse pose dynamics are structured at the sub-second timescale. Computational modeling of these fast dynamics effectively describes mouse behavior as a series of reused and stereotyped modules with defined transition probabilities. We demonstrate this combined 3D imaging and machine learning method can be used to unmask potential strategies employed by the brain to adapt to the environment, to capture both predicted and previously hidden phenotypes caused by genetic or neural manipulations, and to systematically expose the global structure of behavior within an experiment. This work reveals that mouse body language is built from identifiable components and is organized in a predictable fashion; deciphering this language establishes an objective framework for characterizing the influence of environmental cues, genes and neural activity on behavior.

Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal models has limited progress toward understanding mechanisms underlying social interactions and their disorders such as autism. Here we present a new integrated hardware and software system that combines video tracking, depth sensing, and machine learning for automatic detection and quantification of social behaviors involving close and dynamic interactions between two mice of different coat colors in their home cage. We designed a hardware setup that integrates traditional video cameras with a depth camera, developed computer vision tools to extract the body "pose" of individual animals in a social context, and used a supervised learning algorithm to classify several well-described social behaviors. We validated the robustness of the automated classifiers in various experimental settings and used them to examine how genetic background, such as that of Black and Tan Brachyury (BTBR) mice (a previously reported autism model), influences social behavior. Our integrated approach allows for rapid, automated measurement of social behaviors across diverse experimental designs and also affords the ability to develop new, objective behavioral metrics.

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.

Strain differences in temporal changes of nesting behaviors in C57BL/6N, DBA/2N, and their F1 hybrid mice assessed by a three-dimensional monitoring system

Nest building is one of the innate behaviors that are widely observed throughout the animal kingdom. Previous studies have reported specific brain regions and genetic loci associated with nest building in mice. These studies mainly evaluated the nest structure, without observing the nesting process. In this study, we evaluated the effects of strain and learning on the nesting process of mice using a 3D depth camera. To determine the quality of the nest structure, a conventional scoring method, Deacon scores 1-5, was applied to the recorded depth images. The final score of the nest, latency to start nesting behavior, and latencies to reach Deacon scores 3-5, were determined using three genetically different mouse strains-C57BL/6NCrl (B6), DBA/2NCrlCrlj (DBA), and B6D2F1/Crl (B6D2F1). The final score of the DBA nest was significantly lower than that of the B6D2F1 nest, and DBA mice showed significantly longer latency to start nest building than the other two strains in the first trial. By observing the time course of nest building, we confirmed that DBA mice took significantly longer to build their nests than B6 and B6D2F1 mice. Although we did not find any significant differences between DBA and B6 mice in the final assessment of the nest based on the Deacon method, overnight monitoring of the nesting behavior using a 3D depth camera could elucidate the clear differences in the amount of time spent nesting between DBA and B6 mice. In addition, the learning effect was more evident in DBA mice than it was in B6 in terms of latencies to reach Deacon score 3-5 in five repeated trials. DBA mice showed a gradual decrease in latency to build, whereas nesting behaviors of B6 mice were relatively consistent throughout the five trials. Therefore, our 3D depth image method gives higher resolution and structural information regarding the nesting process in mice. Future genetic analyses using the 3D assessment system will provide novel insights into the complex genetic basis for nesting and other behaviors in animals.

Low-cost three-dimensional gait analysis system for mice with an infrared depth sensor

Three-dimensional (3D) open-field gait analysis of mice is an essential procedure in genetic and nerve regeneration research. Existing gait analysis systems are generally expensive and may interfere with the natural behaviors of mice because of optical markers and transparent floors. In contrast, the proposed system captures the subjects shape from beneath using a low-cost infrared depth sensor (Microsoft Kinect) and an opaque infrared pass filter. This means that we can track footprints and 3D paw-tip positions without optical markers or a transparent floor, thereby preventing any behavioral changes. Our experimental results suggest with healthy mice that they are more active on opaque floors and spend more time in the center of the open-field, when compared with transparent floors. The proposed system detected footprints with a comparable performance to existing systems, and precisely tracked the 3D paw-tip positions in the depth image coordinates.

Assessing nest-building behavior of mice using a 3D depth camera

We developed a novel method to evaluate the nest-building behavior of mice using an inexpensive depth camera. The depth camera clearly captured nest-building behavior. Using three-dimensional information from the depth camera, we obtained objective features for assessing nest-building behavior, including "volume," "radius," and "mean height". The "volume" represents the change in volume of the nesting material, a pressed cotton square that a mouse shreds and untangles in order to build its nest. During the nest-building process, the total volume of cotton fragments is increased. The "radius" refers to the radius of the circle enclosing the fragments of cotton. It describes the extent of nesting material dispersion. The "radius" averaged approximately 60mm when a nest was built. The "mean height" represents the change in the mean height of objects. If the nest walls were high, the "mean height" was also high. These features provided us with useful information for assessment of nest-building behavior, similar to conventional methods for the assessment of nest building. However, using the novel method, we found that JF1 mice built nests with higher walls than B6 mice, and B6 mice built nests faster than JF1 mice. Thus, our novel method can evaluate the differences in nest-building behavior that cannot be detected or quantified by conventional methods. In future studies, we will evaluate nest-building behaviors of genetically modified, as well as several inbred, strains of mice, with several nesting materials.

A 3D-video-based computerized analysis of social and sexual interactions in rats

A large number of studies have analyzed social and sexual interactions between rodents in relation to neural activity. Computerized video analysis has been successfully used to detect numerous behaviors quickly and objectively; however, to date only 2D video recording has been used, which cannot determine the 3D locations of animals and encounters difficulties in tracking animals when they are overlapping, e.g., when mounting. To overcome these limitations, we developed a novel 3D video analysis system for examining social and sexual interactions in rats. A 3D image was reconstructed by integrating images captured by multiple depth cameras at different viewpoints. The 3D positions of body parts of the rats were then estimated by fitting skeleton models of the rats to the 3D images using a physics-based fitting algorithm, and various behaviors were recognized based on the spatio-temporal patterns of the 3D movements of the body parts. Comparisons between the data collected by the 3D system and those by visual inspection indicated that this system could precisely estimate the 3D positions of body parts for 2 rats during social and sexual interactions with few manual interventions, and could compute the traces of the 2 animals even during mounting. We then analyzed the effects of AM-251 (a cannabinoid CB1 receptor antagonist) on male rat sexual behavior, and found that AM-251 decreased movements and trunk height before sexual behavior, but increased the duration of head-head contact during sexual behavior. These results demonstrate that the use of this 3D system in behavioral studies could open the door to new approaches for investigating the neuroscience of social and sexual behavior.

Functional imaging in freely moving animals

Uncovering the relationships between animal behavior and cellular activity in the brain has been one of the key aims of neuroscience research for decades, and still remains so. Electrophysiological approaches have enabled sparse sampling from electrically excitable cells in freely moving animals that has led to the identification of important phenomena such as place, grid and head-direction cells. Optical imaging in combination with newly developed labeling approaches now allows minimally invasive and comprehensive sampling from dense networks of electrically and chemically excitable cells such as neurons and glia during self-determined behavior. To achieve this two main imaging avenues have been followed: Optical recordings in head-restrained, mobile animals and miniature microscope-bearing freely moving animals. Here we review progress made toward functional cellular imaging in freely moving rodents, focusing on developments over the past few years. We discuss related challenges and biological applications.