Versatile computerized system for tracking and analysis of water maze tests

Video tracking algorithm of long-term experiment using stand-alone recording system

Many medical and behavioral applications require the ability to monitor and quantify the behavior of small animals. In general these animals are confined in small cages. Often these situations involve very large numbers of cages. Modern research facilities commonly monitor simultaneously thousands of animals over long periods of time. However, conventional systems require one personal computer per monitoring platform, which is too complex, expensive, and increases power consumption for large laboratory applications. This paper presents a simplified video tracking algorithm for long-term recording using a stand-alone system. The feature of the presented tracking algorithm revealed that computation speed is very fast data storage requirements are small, and hardware requirements are minimal. The stand-alone system automatically performs tracking and saving acquired data to a secure digital card. The proposed system is designed for video collected at a 640 x 480 pixel with 16 bit color resolution. The tracking result is updated every 30 frames/s. Only the locomotive data are stored. Therefore, the data storage requirements could be minimized. In addition, detection via the designed algorithm uses the Cb and Cr values of a colored marker affixed to the target to define the tracked position and allows multiobject tracking against complex backgrounds. Preliminary experiment showed that such tracking information stored by the portable and stand-alone system could provide comprehensive information on the animal's activity.

Comparing the EthoVision 2.3 system and a new computerized multitracking prototype system to measure the swimming behavior in fry fish

Coming from the framework of unmarked fry tracking, we compared the capacities, advantages, and disadvantages of two recent video tracking systems: EthoVision 2.3 and a new prototype of multitracking. The EthoVision system has proved to be impressive for tracking a fry using the detection by gray scaling. Detection by subtraction has given less accurate results. Our video multitracking system is able to detect and track more than 100 unmarked fish by gray scaling technique. It permits an analysis at the group level as well as at the individual level. The multitracking program is able to attribute a number to each fish and to follow each one for the whole duration of the track. Our system permits the analysis of the movement of each individual, even if the trajectories of two fish cross each other. This is possible thanks to t hetheoretical estimation of th e trajectory of each fish, which can becompared with the real trajectory (analysis with feedback). However, the period of the track is limited for our system (about 1 min), whereas EthoVision is able to track for numerous hours. In spite of these limitations, these two systems allow an almost continuous automatic sampling of the movement behaviors during the track.

The Implementation of a Stand-alone Video Tracking and Analysis System for Animal Behavior Measurement in Morris Water Maze

In this paper, a digital image tracking and analysis system based on FPGA is presented. The goal of this research is to build an animal tracking system with a new algorithm for Morris water maze experiment application. Our tracking algorithm can track animal motion and is insensitive to environment brightness change. The system can process the high-resolution image up to 700X480 pixels in real-time speed. We can analyze tiny animal behavior change precisely. This system is very compact and is portable. Compare with other similar device, our system is standalone operation without the necessary of a personal computer.

Water maze swim path analysis based on tracking coordinates

In the Morris water maze, a task widely used to study spatial learning and memory in laboratory rodents, several parameters are employed to estimate cognitive abilities of animals by analyzing their swim path characteristics. An isolated view based on any one of these parameters is not always satisfactory, so multivariate procedures (factor analyses) are used to weight the parameters in context with the others. This method sheds light on some subtle differences in experimental animals' spatial memories or strategies. However, this approach has some subjective problems, because the definition of the parameters depends on the experimenter's opinion of appropriate measures; therefore, we suggest a bottom-up rather than a top-down analysis of swim paths by means of spatial coordinates. In the present study, swim paths were normalized to 100-element vectors and then subjected to a principal components analysis. Swim paths could be sufficiently described in terms of only three components, each of which accounted for specific characteristics of the trajectories. We found significant differences in swim path patterns between test groups of rats that could not be discriminated via standard water maze parameters. Thus, the components can be related to different aspects of spatial cognition not detectable by commonly used parameters.

A method for tracking rats in a complex and completely dark environment using computerized video analysis

The automated tracking of rodents in open field environments has become a standard laboratory technique for the investigation of the effects of drugs, novel therapeutic interventions and genetic mutations on behavior. Here, we develop an extension of this technique that permits tracking in full darkness through a complex ('enriched') environment comprising naturalistic structures such as tunnels and hides. To eliminate unwanted light reflections and tape noise, we developed a unique video filter that combines the advantages of differential and non-differential filtering. This filter enabled the tracking of albino rats against a relatively dark background to an accuracy of approximately 97% compared to hand tracking of the same animal, irrespective of whether the rat was inside a hide box or tunnel or out in the open field. The system as a whole can be easily deployed using standard PCs and inexpensive infrared cameras and lights.

An outdoor 3-D visual tracking system for the study of spatial navigation and memory in rhesus monkeys

Previous studies of the navigational abilities of nonhuman primates have largely been limited to what could be described by a human observer with a pen and paper. Consequently, we have developed a system that uses a pair of cameras to automatically obtain the three-dimensional trajectory of rhesus monkeys performing an outdoor spatial navigation and memory task. The system provides trajectories, path length, speed, and other variables that would be impossible for an unaided observer to note. From trajectory data, we computed and validated a path-length measurement. We use this measurement to compare the navigation abilities of several animals. In addition, we provide quantitative data on the accuracy of a method for automatic behavior detection. Currently, the system is being used to examine the sex differences in spatial navigation of rhesus monkeys. We expect that measures derived from the trajectory data will reveal strategies used by animals to solve spatial problems.

EthoVision: a versatile video tracking system for automation of behavioral experiments

The need for automating behavioral observations and the evolution of systems developed for that purpose is outlined. Video tracking systems enable researchers to study behavior in a reliable and consistent way and over longer time periods than if they were using manual recording. To overcome limitations of currently available systems, we have designed EthoVision, an integrated system for automatic recording of activity, movement, and interactions of animals. The EthoVision software is presented, highlighting some key features that separate EthoVision from other systems: easy file management, independent variable definition, flexible arena and zone design, several methods of data acquisition allowing identification and tracking of multiple animals in multiple arenas, and tools for visualization of the tracks and calculation of a range of analysis parameters. A review of studies using EthoVision is presented, demonstrating the system's use in a wide variety of applications. Possible future directions for development are discussed.