Automated Home-Cage Behavioural Phenotyping of Mice

Neurobehavioral analysis of mouse phenotypes requires the monitoring of mouse behavior over long periods of time. Here, we describe a trainable computer vision system enabling the automated analysis of complex mouse behaviors. We provide software and an extensive manually annotated video database used for training and testing the system. Our system performs on par with human scoring, as measured from ground-truth manual annotations of thousands of clips of freely behaving mice. As a validation of the system, we characterized the home-cage behaviors of two standard inbred and two non-standard mouse strains. From this data we were able to predict in a blind test the strain identity of individual animals with high accuracy. Our video-based software will complement existing sensor based automated approaches and enable an adaptable, comprehensive, high-throughput, fine-grained, automated analysis of mouse behavior.McGovern Institute for Brain ResearchCalifornia Institute of Technology. Broad Fellows Program in Brain CircuitryNational Science Council (China) (TMS-094-1-A032

Incipient Social Groups: An Analysis via In-Vivo Behavioral Tracking

Social psychology is fundamentally the study of individuals in groups, yet there remain basic unanswered questions about group formation, structure, and change. We argue that the problem is methodological. Until recently, there was no way to track who was interacting with whom with anything approximating valid resolution and scale. In the current study we describe a new method that applies recent advances in image-based tracking to study incipient group formation and evolution with experimental precision and control. In this method, which we term "in vivo behavioral tracking," we track individuals' movements with a high definition video camera mounted atop a large field laboratory. We report results of an initial study that quantifies the composition, structure, and size of the incipient groups. We also apply in-vivo spatial tracking to study participants' tendency to cooperate as a function of their embeddedness in those crowds. We find that participants form groups of seven on average, are more likely to approach others of similar attractiveness and (to a lesser extent) gender, and that participants' gender and attractiveness are both associated with their proximity to the spatial center of groups (such that women and attractive individuals are more likely than men and unattractive individuals to end up in the center of their groups). Furthermore, participants' proximity to others early in the study predicted the effort they exerted in a subsequent cooperative task, suggesting that submergence in a crowd may predict social loafing. We conclude that in vivo behavioral tracking is a uniquely powerful new tool for answering longstanding, fundamental questions about group dynamics

Combining motion analysis and microfluidics--a novel approach for detecting whole-animal responses to test substances.

Small, early life stages, such as zebrafish embryos are increasingly used to assess the biological effects of chemical compounds in vivo. However, behavioural screens of such organisms are challenging in terms of both data collection (culture techniques, drug delivery and imaging) and data evaluation (very large data sets), restricting the use of high throughput systems compared to in vitro assays. Here, we combine the use of a microfluidic flow-through culture system, or BioWell plate, with a novel motion analysis technique, (sparse optic flow - SOF) followed by spectral analysis (discrete Fourier transformation - DFT), as a first step towards automating data extraction and analysis for such screenings. Replicate zebrafish embryos housed in a BioWell plate within a custom-built imaging system were subject to a chemical exposure (1.5% ethanol). Embryo movement was videoed before (30 min), during (60 min) and after (60 min) exposure and SOF was then used to extract data on movement (angles of rotation and angular changes to the centre of mass of embryos). DFT was subsequently used to quantify the movement patterns exhibited during these periods and Multidimensional Scaling and ANOSIM were used to test for differences. Motion analysis revealed that zebrafish had significantly altered movements during both the second half of the alcohol exposure period and also the second half of the recovery period compared to their pre-treatment movements. Manual quantification of tail flicking revealed the same differences between exposure-periods as detected using the automated approach. However, the automated approach also incorporates other movements visible in the organism such as blood flow and heart beat, and has greater power to discern environmentally-driven changes in the behaviour and physiology of organisms. We suggest that combining these technologies could provide a highly efficient, high throughput assay, for assessing whole embryo responses to various drugs and chemicals

Knots: Attractive Places with High Path Tortuosity in Mouse Open Field Exploration

When introduced into a novel environment, mammals establish in it a preferred place marked by the highest number of visits and highest cumulative time spent in it. Examination of exploratory behavior in reference to this “home base” highlights important features of its organization. It might therefore be fruitful to search for other types of marked places in mouse exploratory behavior and examine their influence on overall behavior

Analysis of dogs’ sleep patterns using convolutional neural networks

Video-based analysis is one of the most important tools of animal behavior and animal welfare scientists. While automatic analysis systems exist for many species, this problem has not yet been adequately addressed for one of the most studied species in animal science—dogs. In this paper we describe a system developed for analyzing sleeping patterns of kenneled dogs, which may serve as indicator of their welfare. The system combines convolutional neural networks with classical data processing methods, and works with very low quality video from cameras installed in dogs shelters

Social anxiety symptoms in young children:Investigating the interplay of theory of mind and expressions of shyness

Children’s early onset of social anxiety may be associated with their social understanding, and their ability to express emotions adaptively. We examined whether social anxiety in 48-month-old children (N = 110; 54 boys) was related to: a) a lower level of theory of mind (ToM); b) a lower proclivity to express shyness in a positive way (adaptive); and c) a higher tendency to express shyness in a negative way (non-adaptive). In addition, we investigated to what extent children’s level of social anxiety was predicted by the interaction between ToM and expressions of shyness. Children’s positive and negative expressions of shyness were observed during a performance task. ToM was measured with a validated battery, and social anxiety was assessed using both parents’ reports on questionnaires. Socially anxious children had a lower level of ToM, and displayed more negative and less positive shy expressions. However, children with a lower level of ToM who expressed more positive shyness were less socially anxious. Additional results show that children who displayed shyness only in a negative manner were more socially anxious than children who expressed shyness only in a positive way and children who did not display any shyness. Moreover, children who displayed both positive and negative expressions of shyness were more socially anxious than children who displayed shyness only in a positive way. These findings highlight the importance of ToM development and socio-emotional strategies, and their interaction, on the early development of social anxiety

A Second-Generation Device for Automated Training and Quantitative Behavior Analyses of Molecularly-Tractable Model Organisms

A deep understanding of cognitive processes requires functional, quantitative analyses of the steps leading from genetics and the development of nervous system structure to behavior. Molecularly-tractable model systems such as Xenopus laevis and planaria offer an unprecedented opportunity to dissect the mechanisms determining the complex structure of the brain and CNS. A standardized platform that facilitated quantitative analysis of behavior would make a significant impact on evolutionary ethology, neuropharmacology, and cognitive science. While some animal tracking systems exist, the available systems do not allow automated training (feedback to individual subjects in real time, which is necessary for operant conditioning assays). The lack of standardization in the field, and the numerous technical challenges that face the development of a versatile system with the necessary capabilities, comprise a significant barrier keeping molecular developmental biology labs from integrating behavior analysis endpoints into their pharmacological and genetic perturbations. Here we report the development of a second-generation system that is a highly flexible, powerful machine vision and environmental control platform. In order to enable multidisciplinary studies aimed at understanding the roles of genes in brain function and behavior, and aid other laboratories that do not have the facilities to undergo complex engineering development, we describe the device and the problems that it overcomes. We also present sample data using frog tadpoles and flatworms to illustrate its use. Having solved significant engineering challenges in its construction, the resulting design is a relatively inexpensive instrument of wide relevance for several fields, and will accelerate interdisciplinary discovery in pharmacology, neurobiology, regenerative medicine, and cognitive science