The EthoVision video tracking system A tool for behavioral phenotyping of transgenic mice

Size: px
Start display at page:

Download "The EthoVision video tracking system A tool for behavioral phenotyping of transgenic mice"

Transcription

1 Physiology & Behavior 73 (2001) The EthoVision video tracking system A tool for behavioral phenotyping of transgenic mice A.J. Spink*, R.A.J. Tegelenbosch, M.O.S. Buma, L.P.J.J. Noldus Noldus Information Technology B.V., P.O. Box 268, 6700 AG Wageningen, the Netherlands Received 1 September 2000; accepted 21 December 2000 Abstract Video tracking systems enable behavior to be studied in a reliable and consistent way, and over longer time periods than if they are manually recorded. The system takes an analog video signal, digitizes each frame, and analyses the resultant pixels to determine the location of the tracked animals (as well as other data). Calculations are performed on a series of frames to derive a set of quantitative descriptors of the animal s movement. EthoVision (from Noldus Information Technology) is a specific example of such a system, and its functionality that is particularly relevant to transgenic mice studies is described. Key practical aspects of using the EthoVision system are also outlined, including tips about lighting, marking animals, the arena size, and sample rate. Four case studies are presented, illustrating various aspects of the system: (1) The effects of disabling the Munc 18-1 gene were clearly shown using the straightforward measure of how long the mice took to enter a zone in an open field. (2) Differences in exploratory behavior between short and long attack latency mice strains were quantified by measuring the time spent in inner and outer zones of an open field. (3) Mice with hypomorphic CREB alleles were shown to perform less well in a water maze, but this was only clear when a range of different variables were calculated from their tracks. (4) Mice with the trkb receptor knocked out in the forebrain also performed poorly in a water maze, and it was immediately apparent from examining plots of the tracks that this was due to thigmotaxis. Some of the latest technological developments and possible future directions for video tracking systems are briefly discussed. D 2001 Elsevier Science Inc. All rights reserved. Keywords: Video tracking; Automated observation; Water maze; Rodent 1. Introduction 1.1. Why automated observation? The behavior of animals, including transgenic mice, is commonly recorded in either a manual or semiautomated way. Traditionally, a researcher observes the animal, and if he or she considers that a certain behavior pattern is displayed, the behavior is noted either by writing it down, or by entering the data into an event-recording program such as The Observer [1,2]. Although manual recording of behavior can be implemented with a relatively low investment, and for some behaviors it may be the only way to detect and record their occurrence, automated observation (such as video tracking) can provide significant * Corresponding author. Tel.: ; fax: address: (L.P.J.J. Noldus). advantages. The behaviors are recorded more reliably because the computer algorithm always works in the same way, and the system does not suffer from observer fatigue or drift. In contrast to manual observation, video tracking carries out pattern analysis on a video image of the observed animals to extract quantitative measurements of the animals behavior (for more details about how this works, see below) The development of automated observation systems Technology for automated detection and recording of behaviors has evolved dramatically in the past decade. Early systems, using hard-wired electronics, were only able to track a single animal in highly artificial environments. For example, an open field can be sampled with a grid of infrared beams either as the sole detectors [3 5] or in combination with other methods such as placing a series of strain gauge transducers under the arena to estimate the animal s position [6]. The magnitude of an animal s motion can also be estimated using various types of touch-sensitive /01/$ see front matter D 2001 Elsevier Science Inc. All rights reserved. PII: S (01)

2 732 A.J. Spink et al. / Physiology & Behavior 73 (2001) sensors ranging from a crude estimate of movement by placing the animal on a bass loudspeaker and monitoring the loudspeaker s electrical output when its cone was moved by the rat [7], or measuring the movement of a mouse s wheel by attaching the wheel s axle in place of the ball of a computer mouse [8], to sensors that can also measure the position of the animal (and hence locomotion), for instance by changes in the capacitance of a plate when the animal is in proximity to it [9], or changes in body resistance [10]. Other comparable detection methods have included use of ultrasound [11] and microwave Doppler radar [12]. The position of a rat in an open field has been recorded by attaching the rat to a computer joystick via a series of rods attached by a collar to the rat s neck [13]. Animals behavior can also be measured using a computerized version of a Skinner box [14], in which the subject has to tap a touch-sensitive monitor [15,16]. The motion of individual limbs can be monitored automatically using actigraph sensors, which detect movement by means of a piezoelectric accelerometer [17]. Early video tracking systems offered clear advantages of flexibility, precision, and accuracy over the various hardware devices listed above. However, the actual path of the animal still had to be entered manually by the experimenter, either by following the track of the animal with the computer mouse [18] or joystick [19], or a digitizing tablet or similar device [20]. Another early method was to feed the analog video signal to a dedicated video tracking unit, which detected peaks in the voltage of the video signal (indicating a region of high contrast between the tracked animal and background), and used this to produce the x, y coordinates of the tracked animals as output which was then fed to the serial port of a computer [21,22]. These analog systems have the disadvantage of being relatively inflexible (dedicated to particular experimental setups) and can normally only track one animal, in rather restricted lighting and background conditions. The first video digitizers were of the column scan type. These had no internal memory of their own, and were only able to sample the video signal at rather low rates [23]. In contrast, a modern frame grabber uses a high-speed analog digital converter to enable real time conversion of the entire video image to a high-resolution grid of pixels [23]. It is also possible to acquire digitized video images by first converting the video input to a digital video format such as AVI, and then using the AVI file as the input for object detection [24]. However, this method has disadvantages that the AVI file quickly gets very large (and so only trials of a limited duration can be carried out), and the method does not allow for real-time live data acquisition. It is also possible to use a digital overlay board to obtain positional data of tracked animals without the need for a frame grabber [25,26]. Modern systems, which are based on full-color video frame grabbers and have flexible software, can track multiple animals simultaneously against a variety of complex backgrounds. Whereas an infrared detector system typically operates in an arena of m with beams (though systems do exist with a grid of beams, in an arena of 2 m diameter [4]), the frame grabber used by EthoVision has a resolution of pixels and can track a rat in an arena with a variable shape and up to 20 m diameter The application of video tracking Video tracking is particularly suitable for measuring three types of behaviors: behaviors that occur briefly and are then interspersed with long periods of inaction (rare behaviors [27]), behaviors that occur over many hours [24,28] (such as diurnal variation in behavior), and spatial measurements (e.g., Refs. [29,30]) (distance, speed, turning, etc.) that the human observer is unable to accurately estimate. If a behavior can be automatically detected using a video tracking system, that can greatly reduce the human effort required [28]. This not only reduces costs, but enables a larger and therefore statistically more responsible number of replicates to be used, whilst at the same time reducing the total number of animals used in an experiment (because each mouse can be used much more efficiently). This is particularly important for transgenic mice because in that case the experiment examines a Heredity Environment interaction and a larger sample size is required to test if interaction effects are significant [31]. It is usually obvious if an animal is experiencing an extreme behavior such as an epileptic seizure. However, certain other behaviors, such as behaving in a stressed manner, may be more open to interpretation in borderline cases. A key advantage of automated video tracking is that it forces researchers to define exactly what they mean by a given behavior, and so enables standardization of methodologies [32] which is one of the most pressing needs in mouse behavioral phenotyping [31,33,34]. In this paper we present EthoVision a general-purpose video tracking, movement analysis, and behavior-recognition system, and illustrate its use in behavioral phenotyping with a number of case studies. Noldus Information Technology introduced the first version of EthoVision in The system has undergone numerous updates over the years, based on feedback from users around the world, which has resulted in a very comprehensive package for studies of movement and behavior [35]. The software has recently been comprehensively redesigned for 32-bit Windows platforms, with a highly interactive graphical user interface for display of experimental design, experimental arena, and tracks of movement. 2. How video tracking works In a video tracking system such as EthoVision, the basis of the system is that a CCD video camera records the area in

3 A.J. Spink et al. / Physiology & Behavior 73 (2001) Fig. 1. The basic EthoVision setup. The analog image from the camera is fed into a frame grabber in the computer, which digitizes the image. EthoVision then analyzes the signal to produce quantitative descriptions of the tracked objects behavior. which the subject animals are (the scene). The camera s signal can either be fed directly to a computer, or via a video cassette recorder (see Fig. 1). In the case of an analog camera (the most practical option with current technology) the signal is then digitized (by a hardware device called a frame grabber) and passed on to the computer s memory. The video signal consists of a series of frames (25 or 30 a second, depending on the TV standard of the camera), and each digitized frame is composed of a grid of pixels. Each pixel has either a gray scale value (for a monochrome signal) or values describing the color of each pixel (red, green, and blue, or hue, saturation, and intensity [36]). The software then analyzes each frame in order to distinguish the tracked objects from the background. Having detected the objects, the software extracts the required features from each frame (in the case of EthoVision 2.0 this includes the position of the mathematical center of each object, and its surface area). Calculations are carried out on the features to produce quantified measurements of the animals behavior. For instance, if the position of an animal is known for each frame, and the whole series of frames is analyzed, the average speed of locomotion (velocity) of an animal during an experiment can be calculated. In addition, if certain regions are identified as being of interest (the center and edges of an open field experiment, for example), the proportion of time spent by the animals in those regions can also be calculated. Measurements such as average velocity and time in the center of an open field can be used as indicators of anxiety (e.g., Case Study 2) and so in this way an accurate quantified measure can be obtained of whether animals receiving a particular treatment were more stressed than other animals, and these measurements can be directly comparable with data from other workers with similar questions. 3. Practical aspects of video tracking When using a video tracking system such as EthoVision, the data obtained will only be as good as the quality of the experimental design. Of course, basic considerations such as sufficient replication and avoiding pseudoreplication [37] must still be adhered to. Likewise, the better the practical setup, the better the quality of the data obtained. If the video signal is of poor quality (for example, containing reflections), the tracked animals may not be detected, or other objects (such as the reflections) may be mistaken for the animals. A number of factors should (if possible) be optimized: 3.1. Illumination Lighting should be indirect and even. The level of illumination (brightness) is not so critical, provided that it is above the detection level of the camera (down to 0.01 lx for a good monochrome CCD camera, about 1 lx for a color CCD camera). Monochrome cameras can also detect light in the near infrared (to about 850 nm). However, if one part of the arena is brighter than another, or if the brightness changes during an experiment, this may cause problems; both technically and because it might affect the behavior of the mice [38]. Above all, reflections must be avoided. The easiest way to do this is to ensure that the light only reaches the scene by first bouncing off a mat surface (such as the wall of the laboratory). For instance, if

4 734 A.J. Spink et al. / Physiology & Behavior 73 (2001) Fig. 2. Possible lighting setup for a Morris water maze (after Ref. [39]). The lights are either placed so far away from the camera that the angle is too great to cause reflections (as in the diagram) or next to the pool and below the water level. an overhead light is used, a mat white wooden board can be suspended in between the light bulb and the scene. Alternatively the lights can be placed sufficiently far away from the camera so that they do not produce a reflection (see Fig. 2 [39]). If color tracking is used, the incident light source must contain a sufficient range of wavelengths to enable separation of the colors being tracked. Color cameras cannot detect infrared light Marking EthoVision distinguish between two mice in the same arena on the basis of size, for example an adult mouse and a pup. To distinguish two mice that are the same size, the researcher can color part of one of the mice the same grayness as the background, thus reducing its apparent size (Fig. 3). If the mouse is light-colored, dark hair dye can be used, if it is dark, a patch can be bleached on one. The procedure is to mix the hair bleach with dilute hydrogen peroxide, then leave it to soak for 30 min, and then rinse it thoroughly. Color tracking can be used to distinguish more than two mice (up to 16 per arena in the case of EthoVision [40]). If the mice being tracked are the same color, livestock markers can be used to paint blobs on the mice, which the system will be able to track. However, these blobs will only last 1 or 2 days, so can only be used for short-term experiments. Mice can also be colored with permanent marker pens or highlight markers for short-term experiments. For longerterm work the mice can be dyed with a brightly colored human hair dye. If the mouse has dark fur, it can first be bleached before the dye is applied, using the method described above. Colored fluorescent tags (illuminated with a UV light) can also be used to mark the animals. It is also possible to track mice in the dark by surgically attaching a small plastic cap to their sculls, and filling the cap with fluorescent dye. When tracking a relatively large number of mice, the marker colors must be as different from each other as possible, in terms of their hue and saturation. Colors should also be selected to be of a similar intensity (brightness) to each other, and to be not too low an intensity (that is, not too dull). Fig. 3. Mouse marked with dark coloring, to distinguish it from another mouse by reducing its apparent size.

5 A.J. Spink et al. / Physiology & Behavior 73 (2001) If different colored markers are applied to different parts of the body of an animal (head, back, and tail, for example), these parts can be tracked individually, and parameters such as orientation (in absolute terms of the body axis and in respect to other animals) or head contact can be calculated [41] Arena size When a video signal is digitized by a frame grabber, the resulting grid of pixels produced for each video frame will be of certain dimensions (determined by the hardware that digitizes the signal). The ratio of the minimum number of pixels of the mouse s image (usually 3), to the number of pixels in the entire image, determines the ratio of the actual size of the tracked mouse to the maximum size of the scene. If one cage is filmed, this is also the maximum size of that cage. If more than one cage is placed within the camera s field of view, so that they can be analyzed simultaneously, the maximum total of all the cages widths is the maximum size of the scene. For instance if a frame grabber has a image resolution of , and you are tracking mice that are 2 cm wide, the maximum size of the scene is 576/3 2 = 384 cm. If the cages are placed in a 4 2 grid under the camera, the external width of each cage can be no more than 384/4 = 96 cm. In practice, if a high-resolution frame grabber is used (such as the one in the EthoVision system), the size of the scene tends to be limited by how big an area the camera can see when suspended from the laboratory ceiling, with a lens that is not too wide-angle (less than 4 ), for a given size of the camera s image detector (CCD) Sampling rate The video camera produces frames at a rate of 25 or 30 per second (depending on its TV standard: NTSC in America and Japan, PAL in most of the rest of the world). Because a mouse usually does not move a significant distance in 1/25th of a second, this sample rate can usually be reduced to 5 10 samples/second if a measurement such as velocity or distance moved is required (5 s 1 was used in most of the case studies detailed below). 4. The EthoVision system The EthoVision for Windows software has a number of features that make it particularly suitable as a tool in studies such as those described in the Case Studies section (below) Data and experiment management Since a water maze experiment of different transgenic mice strains tends to be a large experiment with over 1000 data files as well as their associated profiles (which contain all the settings), data management within EthoVision is particularly important. The EthoVision Workspace Explorer (Fig. 5) enables the user to manage these files through a simple interface (similar to the Windows Explorer), so that, for instance, settings defining the acquisition method (the tracking profile) can be dragged and dropped from one experiment to another. An entire experiment or workspace can be backed up to a single file to facilitate both safekeeping of the data and transfer between different computers. In addition, users are able to find their way around the parts of the program by means of the Experiment menu. They can use the program s functions in a logical order starting with experiment design and arena and zone definition, then to data acquisition, followed by track visualization, and finally data analysis Independent variable definition As well as tracking objects, EthoVision allows a researcher to define a complete experimental protocol, in terms of the independent variables of an experiment, and their values. Up to 99 independent variables (such as treatment, room temperature, genetic strain of the mouse) can be defined, and in addition EthoVision automatically records a series of system independent variables such as the profile (setting file) used, time and date of the trial, trial duration, etc. These independent variables can be used to select, sort, and group data, both when plotting tracks and analyzing the data. For instance, you can select to plot all the tracks from mice of a particular genotype, or calculate the mean time taken to reach the target of a water maze by control mice compared with treated mice Object detection methods When studying different mouse strains, the object detection method is very important; each method has its advantages and disadvantages. EthoVision offers three detection methods. Gray scaling is the fastest. It defines all connecting pixels that are both brighter than a high gray scale threshold and darker than a low threshold as the animal, and all other pixels as the background. The thresholds can be set either manually by the user, or calculated automatically by the program. It is a fast method (giving the highest sample rate), but cannot be used if the same gray scale values are present both in the mouse s image and the background. The subtraction method first makes a reference image, with no mice present, then subtracts the gray scale value of each pixel of the reference image from the equivalent pixel of the live image. Any pixels which have a subtracted value other than zero are different between the reference and live images, due to the presence of the mouse. The user can define whether the mouse has to be lighter than or darker than the background, or just different. This method is more tolerant for differences in light intensity across the scene. The third detection method uses the hue and saturation of the tracked

6 736 A.J. Spink et al. / Physiology & Behavior 73 (2001) mouse (or a marker painted on it) to define its color, and pixels with the defined colors are tracked. Up to 16 different colors can be tracked in each arena at once. With all three methods, objects that are either smaller than the mouse (such as droppings) or larger (such as reflections) can be excluded on the basis of their size Arena and zone definitions Up to 16 enclosures can be placed under one camera, and each enclosure can be treated as a separate independent replicate (called an arena; see Fig. 4). The animals in these arenas can be tracked simultaneously. Multiple arena definitions and zone definitions can be defined for each experiment. This is particularly handy when, for instance, a water maze experiment is prepared, with multiple platform positions. When setting up the experiment, the user can assign the proper arena definition to each track file before the experiments are started. The user can define up to 99 regions of interest (zones; see Fig. 4). These can be used in the analysis (for example, the time taken for a mouse to reach the platform of a water maze, see Case study 1) and also for automatic start and stop conditions. For instance the trial can be stopped automatically when the mouse has reached the platform of a water maze. Zones can be added together to make a cumulative zone (for instance, if a maze has more than one target). Zones can also be defined as hidden zones, for use with nest boxes, burrows, etc. The system assumes that when an animal disappears from view and it was last seen adjacent to a hidden zone, it is inside the hidden zone. Fig. 4. Arenas and zones of a Morris water maze. The arena is the circular area bounding the outside of the water maze, and it is divided up into four zones ( quadrants, see Case Study 3) labeled North, South, East, and West.

7 A.J. Spink et al. / Physiology & Behavior 73 (2001) All the zones can be defined and altered either before of after data acquisition, allowing iterative exploratory data analysis of the effects of changing zone positions and shapes. The arena can be calibrated so that the parameters such as velocity are calculated in meaningful units. If more than one arena is used, they can each be calibrated separately, or one calibration can be used for all arenas. There are two calibration methods; in standard calibration the user measures a series of lines (for example, a meter ruler placed on the floor of a cage). If the camera image is distorted (by a fish-eye lens, or a lens that is not directly overhead) the standard calibration will not be accurate (the standard deviation of the calibration factors is given to enable the user to determine this), and the user can opt for advanced calibration. In that method a grid of points is mapped onto the arena, and a series of coordinate points are entered, giving a calibration that is accurate for the entire image, even when it is distorted Behavior recording In addition to automatically tracking the movement of the animal, EthoVision can automatically detect certain behaviors, such as rearing. EthoVision also allows the researcher to manually record (by keystroke or mouse-click) behaviors that cannot be detected automatically (such as sniffing) Image filtering As in most video tracking systems, EthoVision calculates the mathematical point at the center of the digitized picture of the animals body, including the tail. This means this point is further towards the mouse s posterior than is correct. Furthermore, a tracking system will still detect movement of the mouse when only the tail is moving. In order to prevent this, the tail can be removed from the image, using image filtering. The bars of a cage can also be filtered using a similar technique Track visualization The user can specify data sets at several hierarchical levels for the analysis and visualization of the data. The data can be selected, sorted, and grouped by independent variables. This way a selection of the tracks in an experiment can be plotted on a single screen, by treatment or genetic strain (see Fig. 5). The track plots can be displayed with or without the arena and zones or the background Fig. 5. This figure displays the EthoVision Workspace Explorer on the left panel and in the right panel eight tracks of a water maze experiment are plotted. The tracks are sorted by animal ID and trial number. As well as plotting the complete tracks, the user can also play the plots back in a customized way.

8 738 A.J. Spink et al. / Physiology & Behavior 73 (2001) image of the experimental setup. The plots can be exported as graphic files in a variety of standard formats Data analysis After initially selecting the tracks for analysis (using independent variables), the user can carry out further data selection by nesting over time-windows, zones, and behaviors (either ones automatically detected by the system, or behaviors entered by the researcher manually). The user can also group by the values of independent variables (such as treatment values), and further fine-tune the data using filter settings like minimal distance moved, to eliminate slight apparent movements, and down-sampling steps, to eliminate redundant data if a lower sample rate describes the path better. A wide range of quantitative measures of behavior is available in EthoVision, and these can be described with a full range of descriptive statistics: Distance moved For example, the total path distance followed by a mouse in a water maze until it reached the target. Velocity For example, the mean speed of the mouse whilst swimming in a water maze. In zone For example, the time taken for a mouse to reach the target of a maze. The zones can be completely redefined at any time before or after data acquisition. Distance to zone and Distance to zone border For example, the average distance that a mouse was from the walls of an open field, except when it was near a novel object. Heading For example, the mean direction of a mouse s path in relation to a maze s target. Turn angle A large mean and variance in the turn angle may indicate stereotypical behavior such as circling movements. Angular velocity High values of absolute angular velocity can be used to indicate a variety of behaviors including local searching patterns, stereotypic movements and abnormal behaviors, reaction to toxins, and measures of behavioral asymmetries in animals with unilateral brain lesions [42,43]. Meander The change in direction of movement of an object relative to the distance it moves. Therefore it can be used to compare the amount of turning of objects travelling at different speeds. Sinuosity The amount of random turning in a given path length. This is one value for the entire track and can be used, for instance, to quantify the foraging behavior of an animal [44,45]. Moving Whether or not the mouse is moving, compared to user-defined thresholds. For example, the percentage of the time that the mouse in a water maze was floating or the number of bouts of movement whilst the mouse was in the central zone of an open field. Rearing A useful parameter for assessing exploratory behavior, for example the frequency of rearing in an open field with and without a novel object. EthoVision detects rearing on the basis of the change in surface area of the mouse (as seen from above), using user-defined thresholds. Distance between objects In EthoVision, the user can select as many combinations of actors and receivers as wanted to calculate social interactions, including this parameter and the ones listed below (which are based on the distance between objects). Both other animals and zones can be selected as receivers of social interactions. Relative movement Whether a mouse is moving towards or away from another mouse. This is a good example of providing an objective measure of behavior, which can later be explicitly interpreted as aggression or avoidance [46]. Proximity Whether a mouse is close to or far away from another mouse (in relation to user-defined thresholds). This parameter has been used to study the effect of individual or group housing on social behavior [46] and social isolation as a symptom of schizophrenia [47,48]. Speed of moving to/from The distance-weighted speed at which an object moves towards or away from another object. These parameters can be used to quantify the intensity of avoidance or aggression. Net relative movement A combined measure for the above two parameters, this parameter is also frequently used in studies of social interaction [46,49]. The analysis report is a spreadsheet that can be manipulated for optimal presentation and exported in different file formats (or copied and pasted) to other spreadsheets or statistics packages for further analysis. The parameters can be calculated for every individual sample, and their statistics calculated both per track and across groups of tracks with the same values of user-defined independent variables (for example, all tracks of mice receiving the same dosage of a treatment). 5. Case studies The following case studies are presented in order to illustrate the use of EthoVision for detection and quantification of various behaviors in mice. Therefore, full details of neither the experimental setup nor full conclusions drawn from the data are given; the reader is referred to the researchers or the original publications for that information [55,70]. However, the raw data from some of these case studies have been placed on the web; follow the link from The data can be downloaded and opened in EthoVision for visualization and analysis Effect of genetic composition on open field behavior of mice. Behavioral phenotyping of the effects of disabling the Munc 18-1 gene The following case study is based on unpublished data kindly provided by R.A. Hensbroek and B.M. Spruijt

9 A.J. Spink et al. / Physiology & Behavior 73 (2001) Open field exploration strategies in mice selected for short and long attack latency Fig. 6. The behavior of mice with various genotypes (genetic background and munc18-1 mutation) in an open field expressed as total distance moved and time spent in the central area. Thick shading represents heterozygotes and thin shading wild types. Left-slanting shading represents 129/Sv mice, right-slanting shading represents hybrids. The bars represent ± 1 standard error of the mean. (Rudolf Magnus Institute for Neuroscience, Utrecht University). For further details about the experimental protocol, please contact them at: Mice that lack the gene for munc18-1 have no secretion of neurotransmitters and consequently die at birth [50]. Heterozygotes still have one functional copy of the gene and a 50% reduction in munc18-1 protein levels. Earlier work had indicated that heterozygotes were more active than wild type mice, but it was not clear whether this was due to the munc18-1 deletion, or due to differences in genetic background. Heterozygotes were therefore repeatedly backcrossed with the inbred strain 129/Sv. The resulting mice were also crossed once with C57Bl/6. The effects of the munc18-1 deletion could now be tested both in a purely 129/Sv background and in hybrids of 129/Sv and C57Bl/6. The mice were placed in an empty circular open field for 15 min, firstly when the field was empty, and secondly with a 10 5 cm metallic cylinder in the middle. Heterozygotes were more active than wild types, both for the hybrids and 129/Sv mice (Fig. 6). The genetic background had a clear effect on the behavior of the mice: in 129/Sv, heterozygotes spent more time in the central area of the open field, while such a difference was not seen in hybrids. The following case study is based on unpublished data kindly provided by M.C. de Wilde and J.M. Koolhaas (University of Groningen). For further details about the experimental protocol, please contact them at: or Male wild house mice selected for short and long attack latency (SAL and LAL, respectively) differ in their way of coping with environmental challenges [51,52]. SAL males show an active behavioral response whereas LAL males show a reactive coping strategy. For instance, in the defensive burying test SAL males actively cover the shock prod with bedding material and LAL males freeze in a corner of the cage. Several studies suggest that the coping styles have a differential fitness in nature, depending on environmental conditions such as food availability [53,54]. The current experiment studied the exploratory behavior of SAL and LAL mice in an open field. The LAL mice (white bars in Fig. 7) were more active than the SAL genotype, moving a greater total distance, and exploring the outer zone more than the SAL mice, whereas the distance traveled in the inner zone was the same for the two groups. The SAL animals showed no difference in behavior in the second time period, compared with the first time period, whereas the LAL mice were significantly more active after the first 5-min period was over, moving a greater distance in both the inner zone and outer zone. These data are consistent with other work describing the two strategies. SAL mice continue to exhibit a behavior that they have found to be successful, whereas LAL mice will develop new behaviors with time. In the beginning the SAL and LAL mice explore the open field in a similar way, and after 5 min the SAL mice continue to explore the arena in that way. In contrast, the LAL mice develop a new exploratory strategy, both moving more, and spending more time Fig. 7. Distance moved by short attack latency (n = 16, black bars, ± standard error of the mean [S.E.M.]) and long attack latency (n = 12, white bars, ± S.E.M.) wild male house mice in an open field experiment.

10 740 A.J. Spink et al. / Physiology & Behavior 73 (2001) Table 1 Variables calculated from the animals tracks in the water maze experiment in Case Study 3 Variable WT vs. ad ( P) WT vs. comp ( P) Swim time n.s. <.05 Swim path length n.s. <.01 % time in goal zone n.s. <.05 Mean distance to goal <.05 <.002 Swimming parallel to wall <.05 <.001 Swimming < 22 mm from wall <.05 <.002 Number of wall contacts n.s. n.s. Swimming speed n.s. n.s. Table legend: n.s. = not significant (Scheffe test), WT = wild type, ad = mice with ad isoform disrupted, comp = mice with all CREB isoforms disrupted. in the inner zone as they adapt to the new situation in the second period The effects of CREB gene dosage on the performance of mice in the water maze learning task The following case study was based on data kindly provided by Dr. D. Wolfer and his colleagues (Department of Anatomy, University of Zurich). For details, please see the publication in Learning & Memory [55]. The Morris water maze task is one of the most frequently used experimental paradigms designed to assess cognitive performance [56]. EthoVision is used by several groups to track and analyze water maze experiments (e.g., Refs. [57 60]). A tank is filled with opaque water (chalk or milk powder is added) and the animal swims until it locates a hidden platform just below the surface of the water. Its speed of learning can be assessed by how rapidly the time to locate the platform is reduced when the task is repeated. Most studies have used rats as subjects, whereas mice have been less frequently used [61,62]. Mice have been shown to produce a normal learning curve [62]. The behavior of mice in tasks of learning and memory is less characterized than in rats and in view of the development of transgenic mouse models with predefined deficiencies as new tools to identify putative cognition enhancers, it is important to conduct preliminary tests on wild type strains that are used to produce these transgenic animals, to calibrate the behavioral paradigm before beginning testing of the transgenic or knockout mice. The transcription factor CREB is involved in the formation and retention of long-term memory [63,64]. Although learning in mice is strongly influenced by the genetic background of the mice [65,66], early water maze studies did not take this into account. The current study aimed to validate previous studies using mice with welldefined genetic backgrounds (see the original paper [55] for details), with mice with different dosages of the CREB gene. Several variables were calculated from the animals tracks (the EthoVision data were processed using the WinTrack program [67]), see Table 1. It was found that mice with one hypomorphic CREB allele (ad) and one null CREB allele (CREBcomp, in which all CREB isoforms are disrupted) showed statistically significant (Scheffe test) defects for most measures of the performance in the water maze (compared with wild type mice) whereas mutants with a and D isoforms disrupted and the b isoform up-regulated showed less disruption. Previous Fig. 8. Two typical tracks of wild-type (right) and trkb-mice in the Morris water maze. The control mouse finds the hidden platform (the top-left square), on the basis of previous training, whereas the mutant mouse stays close to the edges of the tank (the gray circle).

11 A.J. Spink et al. / Physiology & Behavior 73 (2001) studies [68,69] reported major deficits for mice with these genetic defects in all paradigms tested. It is likely that the difference is due to the differing genetic background of the mice used in different studies Learning behavior of mice in a water maze with the trkb gene knocked out in the forebrain during prenatal development The following case study was based on data kindly provided by Dr. D. Wolfer (Department of Anatomy, University of Zurich). For details, please see the publication in Neuron [70]. The TrkB receptor for brain-derived neurotrophic factor regulates short-term synaptic functions and long-term potentiation of brain synapses [71]. Mice were studied which had had the trkb gene knocked-out in the forebrain during postnatal development. The mice developed without gross morphological defects (the mice do not survive until adulthood if the gene is knocked-out for the entire brain [72]), and the activity of the trkb-mice in an open field were similar to wild-type mice. However, in a Morris water maze experiment (similar to that of Case study 1), although the control mice learnt the route to the hidden platform (left track in Fig. 8), the mutant mice tended to hug the walls of the maze (thigmotaxis) and therefore did not find the platform (right track in Fig. 8). 6. Discussion and conclusions The four case studies illustrate different aspects of using EthoVision to track mice. The first case study (knock-out of the Munc 18-1 gene) looked at mice in an open field which were hypothesized to be hyperactive as a result of the knocked-out gene. Plots of two simple variables quantifying the mice s behavior demonstrated the experiment s effects. Simple, straightforward parameters such as distance moved or time in center can be powerful measures to quantify differences in behavior between different genotypes. Likewise the case study of SAL and LAL mice (Case study 2) showed clear differences in behavior between the genotypes on the basis of a variable (total distance moved) calculated from the EthoVision tracks, even though the actual differences in behavior were rather complex. The Morris water maze study on mice with differing CREB gene dosage illustrated that there are occasions one or two variables are insufficient to provide a good description of the experimental effects. It was only when a batch of variables was calculated that the interaction between the mice s genetic background and specific effects of the CREB gene became clear. An advantage of measuring behavior using a video tracking system is that once the tracks of the animals have been derived, a large number of dependent variables can easily be calculated from those tracks. Finally, the study of mice with the trkb gene disabled in the forebrain illustrated the fact that although proper statistical analysis is, of course, necessary, much valuable information, especially about exactly what to test, can be gained from viewing the plots of the animals tracks. The case studies demonstrate that video tracking provides an accurate and powerful means to quantify mouse behavior. Because it is repeatable and not subject to observer variance, it is eminently suitable for comparison of different data sets between different research groups. The case studies shown are all examples of relatively straightforward uses of a system like EthoVision. Even with the current system (EthoVision 2), more complex experiments and analyses can be carried out. In the future, EthoVision and other video tracking systems will be able to carry out more complex tasks. An indication of what these might be can be seen from projects that have been carried out in research projects, or customizations of the software. Whether these functions ever become part of the standard commercial package will depend on both how technically feasible the solution is, and how much interest there is in that application. Synchronization of video (behavioral) and physiological data. It is often the case that an experiment involves not only quantifying the behavior of an animal, but also measuring a variety of physiological parameters [73]. In order to carry out a full statistical analysis of the data obtained, it is necessary for the various data streams to be synchronized. At the time of writing (November 2000) there is no straightforward and uniform solution to this problem. However, Noldus Information Technology, together with several partners are carrying out a research project to resolve this issue [74]. Direct extraction of physiological data from video data. A customized version of EthoVision has been developed which uses an infrared thermographic camera both to record an animal s behavior, and simultaneously to measure its body temperature (at several points on the body simultaneously) [75]. The method is noninvasive and thus particularly appropriate for monitoring the effects of stress. Automatic detection of complex behaviors. EthoVision is able to detect whether a mouse is moving, or whether it is rearing, but (in common with other commercial systems) is not able to automatically detect other behaviors (unless, of course, it is possible to define them in terms of the existing parameters). A behavior such as an epileptic seizure (characterized by the animal turning over with the tail in a characteristic position over the body) can be detected by using EthoVision in combination with neural networks [76] and statistical classification [77]. 3-D tracking. If more than one camera is used (or one camera and a mirror [18]), it is in theory possible to obtain information about the movement of animals in all three dimensions. Although tracking in 3-D was already possible with some simple hardware devices [13] and more primitive video-based systems [19], ironically the more sophisticated the tracking system, the more difficult this becomes. However, a special version of EthoVision has

12 742 A.J. Spink et al. / Physiology & Behavior 73 (2001) been used to successfully track objects moving in three dimensions [78]. Identification of large and indeterminate numbers of animals. To track a large and continually varying number of animals, especially if crowded close together, calls for quite different techniques than the object identification methods used by EthoVision. Some progress has been made using techniques such as active modeling and prediction of the animals shapes [79,80] and dynamic imaging with statistical analysis of detected body features [81]. Acknowledgments We are grateful of those who provided us with their data for use in the case studies section of this paper. All members of the EthoVision team at Noldus Information Technology have contributed towards the product since it was initially launched in 1993; their hard work and dedication is acknowledged here. References [1] Noldus LPJJ. The Observer: a software system for collection and analysis of observational data. Behav Res Methods, Instrum Comput 1991;23: [2] Noldus LPJJ, Trienes RJH, Hendriksen AH, Jansen H, Jansen RG. The Observer Video-Pro: new software for the collection, management, and presentation of time-structured data from videotapes and digital media files. Behav Res Methods, Instrum Comput 2000;32: [3] Clarke RL, Smith RF, Justesen DR. An infrared device for detecting locomotor activity. Behav Res Methods, Instrum Comput 1985;17: [4] Robles E. A method to analyze the spatial distribution of behavior. Behav Res Methods, Instrum Comput 1990;22:540. [5] Kirkpatrick T, Schneider CW, Pavloski R. A computerized infrared monitor for following movement in aquatic animals. Behav Res Methods, Instrum Comput 1991;23: [6] Gapenne O, Simon P, Lannou J. A simple method for recording the path of a rat in an open field. Behav Res Methods, Instrum Comput 1990;22: [7] Silverman R, Chang AS, Russell RW. A microcomputer-controlled system for measuring reactivity in small animals. Behav Res Methods, Instrum Comput 1998;20: [8] Szalda-Petree AD, Karkowski AM, Brooks LR, Haddad NF. Monitoring running-wheel movement using a serial mouse and an IBMcompatible system. Behav Res Methods, Instrum Comput 1994;26: [9] Clarke RL, Smith RF, Justesen DR. A programmable proximity-contact sensor to detect location or locomotion of animals. Behav Res Methods, Instrum Comput 1992;24: [10] Tarpy RM, Murcek RJ. An electronic device for detecting activity in caged rodents. Behav Res Methods, Instrum Comput 1984;16: [11] Akaka WH, Houck BA. The use of an ultrasonic monitor for recording locomotor activity. Behav Res Methods, Instrum Comput 1980;12: [12] Martin PH, Unwin DM. A microwave Doppler radar activity monitor. Behav Res Methods, Instrum Comput 1988;20: [13] Brodkin J, Nash JF. A novel apparatus for measuring rat locomotor behavior. J Neurosci Methods 1995;57: [14] Skinner BF. The behavior of organisms. New York: Appelton- Century-Crofts, [15] Morrison SK, Brown MF. The touch-screen system in the pigeon laboratory: an initial evaluation of its utility. Behav Res Methods, Instrum Comput 1990;22: [16] Sahgal A, Steckler T. TouchWindows and operant behaviour in rats. J Neurosci Methods 1994;55: [17] May CH, Sing HC, Cephus R, Vogel S, Shaya EK, Wagner HN. A new method of monitoring motor activity in baboons. Behav Res Methods, Instrum Comput 1996;28:23 6. [18] Pereira P, Oliveira RF. A simple method using a single video camera to determine the three-dimensional position of a fish. Behav Res Methods, Instrum Comput 1994;26: [19] Morrel-Samulels P, Krauss RM. Cartesian analysis: a computer video interface for measuring motion without physical contact. Behav Res Methods, Instrum Comput 1990;22: [20] Santucci AC. An affordable computer-aided method for conducting Morris water maze testing. Behav Res Methods, Instrum Comput 1995;27:60 4. [21] Vorhees CV, Acuff-Smith KD, Minck DR, Butcher RE. A method for measuring locomotor behavior in rodents: contrast-sensitive computer-controlled video tracking activity assessment in rats. Neurotoxicol Teratol 1992;14:43 9. [22] Klapdor K, Dulfer BG, van der Staay FJ. A computer-aided method to analyse foot print patterns of rats, mice and humans. Poster presented at Measuring Behavior 96, International Workshop on Methods and Techniques in Behavioral Research, October 1996, Utrecht, the Netherlands, [23] Olivo RF, Thompson MC. Monitoring animals movements using digitized video images. Behav Res Methods, Instrum Comput 1988;20: [24] Derry JF, Elliott JH. Automated 3-D tracking of a video-captured movement using the example of an aquatic mollusk. Behav Res Methods, Instrum Comput 1997;29: [25] Hartmann MJ, Assad C, Rasnow B, Bower JM. Applications of video mixing and digital overlay to neuroethology. Methods. Companion Methods Enzymol 2000;21: [26] Rasnow B, Assad C, Hartmann MJ, Bower JM. Applications of multimedia computers and video mixing to neuroethology. J Neurosci Methods 1997;76: [27] Martin BR, Prescott WR, Zhu M. Quantification of rodent catalepsy by a computer-imaging technique. Pharmacol, Biochem Behav 1992; 43: [28] Spruijt BM, Gispen WH. Prolonged animal observations by use of digitized videodisplays. Pharmacol, Biochem Behav 1983;19: [29] Buresova O, Bolhuis JJ, Bures J. Differential effects of cholinergic blockade on performance of rats in the water tank navigation task and in a radial water maze. Behav Neurosci 1986;100: [30] Spruijt BM, Pitsikas N, Algeri S, Gispen WH. Org2766 improves performance of rats with unilateral lesions in the fimbria fornix in a spatial learning task. Brain Res 1990;527: [31] Whalsten D. Standardizing tests of mouse behaviour: reasons, recommendations, and reality (submitted for publication). [32] Spruijt BM, Buma MOS, van Lochem PBA, Rousseau JBI. Automatic behavior recognition; what do we want to recognize and how do we measure it? Proceedings of Measuring Behavior 98 (Groningen, August) 1998; [33] Brown RE, Stanford L, Schellinck HM. Developing standardized behavioral tests for knockout and inbred mice. ILAR J 2000;41: [34] Drai D, Elmer G, Benjamion Y, Kafkafi N, Golani I. Phenotyping of mouse exploratory behavior. Proceedings of Measuring Behavior 2000 (Nijmegen, August) 2000;86 8. [35] Buma M, Smit J, Noldus LPJJ. Automation of behavioral tests using digital imaging. Neurobiology 1997;4:277. [36] Endler JA. On the measurement and classification of colour in studies of animal colour patterns. Biol J Linn Soc 1990;41:

13 A.J. Spink et al. / Physiology & Behavior 73 (2001) [37] Hurlbert SH. Pseudoreplication and the design of ecological field experiments. Ecol Monogr 1984;54: [38] Fentrop N, Wotjak CT. Fiat lux! Spotting a common experimental problem. Proceedings of Measuring Behavior 2000 (Nijmegen, August) 2000;108. [39] Evets H, Koolhaas J. Still waters run deep: EthoVision and the Morris water maze. Noldus News 1999;6(1):3 (February). [40] Spink AJ, Buma MOS, Tegelenbosch RAJ. EthoVision color identification: a new method for color tracking using both hue and saturation. Proceedings of Measuring Behavior 2000 (Nijmegen, August) 2000; [41] Šustr P, Špinka M, Newberry RC. Automatic computer analysis of pig play. Proceedings of Measuring Behavior 2000 (Nijmegen, August) 2000; [42] Bjerselius R, Olsen KH. Behavioural and endocrinological responses of mature male goldfish to the sex pheromone 17a,20b-dihydroxy- 4-pregnen-3-one in the water. J Exp Biol 1995;198: [43] Schwarting RKW, Goldenberg R, Steiner H, Fornaguera J, Huston JP. A video image analyzing system for open-field behavior in the rat focusing on behavioral asymmetries. J Neurosci Methods 1993;49: [44] Bovet P, Benhamou S. Spatial analysis of animals movements using a correlated random walk model. J Theor Biol 1988;131: [45] Bovet P, Benhamou S. Optimal sinuosity in central place foraging movements. Anim Behav 1991;42: [46] Spruijt BM, Hol T, Rousseau JBI. Approach, avoidance and contact behavior of individually recognized animals automatically quantified with an imaging technique. Physiol Behav 1992;51: [47] Sams-Dodd F. Automation of the social interaction test by a video tracking system: behavioural effects of repeated phencyclidine treatment. J Neurosci Methods 1995;59: [48] Sams-Dodd F. The effects of dopamine agonists and antagonists on PCP-induced stereotyped behaviour and social isolation in rats. Behav Pharmacol 1996;7(Suppl. 1):99. [49] Hol T, Spruijt BM. The MSH/ACTH(4 9) analog Org2766 counteracts isolation-induced enhanced social behavior via the amygdala. Peptides 1992;13: [50] Verhage M, Maia AS, Plomp JJ, Brussaard AB, Heeroma JH, Vermeer H, Toonen RF, Hammer RE, Van den Berg TK, Missler M, Geuze HJ, Südhof TC. Synaptic assembly of the brain in the absence of neurotransmitter secretion. Science 2000;287:864 9 (Feb. 4). [51] Sluyter F, Bult A, Meeter F, Van Oortmerssenn GA, Lynch CB. A comparison between Fl reciprocal hybrids of house mouse lines bidirectionally selected for attack latency or nest-building behavior: no Y chromosomal effects on alternative behavioral strategies. Behav Genet 1997;27: [52] Sluyter F, Korte SM, Van Baal GCM, De Ruiter AJH, Van Oortmerssen GA. Y chromosomal and sex effects on the behavioral stress response in the defensive burying test in wild house mice. Physiol Behav 1999;67: [53] Monahan EJ, Maxson SC. Y chromosome, urinary chemosignals, and an agonistic behavior (offense) of mice. Behav Physiol 1998;64: [54] Bult A, Lynch CB. Breaking through artificial selection limits of an adaptive behavior in mice and the consequences for correlated responses. Behav Genet 2000;30: [55] Gass P, Wolfer DP, Balschun D, Rudolph D, Frey U, Lipp HP, Schütz G. Deficits in memory tasks of mice with CREB mutations depend on gene dosage. Learning & Memory 1998;5: [56] Morris R. Development of a water-maze procedure for studying spatial learning in the rat. J Neurosci Methods 1984;11: [57] Oitzl MS. Behavioral approaches to study function of corticosteriods in brain. Methods Neurosci 1994;22: [58] Everts HGJ, Koolhaas JM. Differential modulation of lateral septal vasopressin receptor blockade in spatial learning, social recognition, and anxiety-related behaviors in rats. Behav Brain Res 1999;99:7 16. [59] Leggio MG, Neri P, Graziano A, Mandolesi L, Molinari M, Petrosini L. Cerebellar contribution to spatial event processing: characterization of procedural learning. Exp Brain Res 1999;127:1 11. [60] Dere E, Frisch C, De Souza Silva MA, Huston JP. Improvement and deficit in spatial learning of the enos-knockout mouse (enos / ) dependent on motivational demands of the task; water maze versus radial maze. Proceedings of Measuring Behavior 2000 (Nijmegen, August) 2000;79. [61] Paylor R, Baskall L, Wehner JM. Behavioural dissociations between C57/BL6 and DBA/2 mice on learning and memory tasks: a hippocampal-dysfunction hypothesis. Psychobiology 1993;21: [62] Van der Staay FJ, Stollenwerk A, Hovarth E, Schuurman T. Unilateral middle cerebral artery occlusion does not affect water-escape behaviour of CFW1 mice. Neurosci Res Commun 1992;11:11 8. [63] Frank DA, Greenberg ME. CREB: A mediator of long-term memory from mollusks to mammals. Cell 1994;79:5 8. [64] Bailey CH, Bartsch D, Kandel ER. Toward a molecular definition of long-term memory storage. Proc Natl Acad Sci 1996;93: [65] Gerlai R. Gene-targeting studies of mammalian behavior: is it the mutation or the background genotype? Trends Neurosci 1996;19: [66] Owen EH, Logue SF, Rasmussen DL, Wehner JM. Assessment of learning by the Morris water task and fear conditioning in inbred mice strains and F1 hybrids: implications of genetic background for single gene mutations and quantitative trait loci analyses. Neuroscience 1997;80: [67] Wolfer DP, Lipp H-P. A new computer program for detailed off-line analysis of swimming navigation in the Morris water maze. J Neurosci Methods 1992;41: [68] Hummler E, Cole TJ, Blendy JA, Ganss R, Aguzzi A, Schmid F, Beermann F, Schütz G. Targeted mutation of the camp response element binding protein (CREB) gene: compensation within the CREB/ATF family of transcription factors. Proc Natl Acad Sci 1994;91: [69] Bourtchuladze R, Frenguelli B, Blendy J, Cioffi G, Schütz G, Silva AJ. Deficient long-term memory in mice with a targeted mutation of the camp responsive element binding (CREB) protein. Cell 1994;79: [70] Minichiello L, Korte M, Wolfer DP, Kühn R, Unsicker K, Cestari V, Rossi-Arnaud C, Lipp HP, Bonhoeffer T, Klein R. Essential role for TrkB receptors in hippocampus-mediated learning. Neuron 1999;24: [71] McAllister AK, Katz LC, Lo DC. Neurotrophins and synaptic plasticity. Annu Rev Neurosci 1999;22: [72] Minichiello L, Klein R. TrkB and TrkC neurotrophin receptors cooperate in promoting survival of hippocampal and cerebellar granule neurons. Genes Dev 1996;10: [73] Koolhaas JM, de Boer SF, Sgoifo A, Buwalda B, Meerlo P, Kato K. Measuring behavior: integrating behavior and physiology. Proceedings of Measuring Behavior 98, 2nd International Conference on Methods and Techniques in Behavioral Research, August, Groningen, The Netherlands 1998; [74] Hoogeboom PJ. Data synchronisation through post-processing. Proceedings of Measuring Behavior 2000 (Nijmegen, August) 2000; [75] Houx BB, Buma MOS, Spruijt BM. Non-invasive temperature tracking with automated infrared thermography: measuring inside out. Proceedings of Measuring Behavior 2000, 3rd International Conference on Methods and Techniques in Behavioral Research, August, Nijmegen, The Netherlands 2000; [76] Spruijt BM, Buma MOS, van Lochem PBA, Rousseau JBI. Automatic behavior recognition: what do we want to recognize and how do we measure it? Proceedings of Measuring Behavior 98, 2nd International Conference on Methods and Techniques in Behavioral Research, August, Groningen, The Netherlands 1998; [77] van Lochem PBA, Buma MOS, Rousseau JBI, Noldus LPJJ. Auto-

14 744 A.J. Spink et al. / Physiology & Behavior 73 (2001) matic recognition of behavioral patterns of rats using video imaging and statistical classification. Proceedings of Measuring Behavior 98, 2nd International Conference on Methods and Techniques in Behavioral Research, August, Groningen, The Netherlands 1988; [78] Takken W, Huisman PWT, Buma MOS, Noldus LPJJ. Three-dimensional video tracking and analysis of the flight of nocturnal anopheline mosquitoes. Poster presented at Measuring Behavior 96, International Workshop on Methods and Techniques in Behavioral Research, October, Utrecht, [79] Sergeant DM, Boyle RD, Forbes JM. Computer visual tracking of poultry. Comput Electron Agric 1988;21:1 18. [80] Bulpitt AJ, Boyle RD, Forbes JM. Monitoring behavior of individuals in crowded scenes. Proceedings of Measuring Behavior 2000, 3rd International Conference on Methods and Techniques in Behavioral Research, August, Nijmegen, The Netherlands 2000; [81] van Schelt J, Buma MOS, Moskal J, Smit J, van Lenteren JC. EntoTrack: using video imaging to automate the quality control of mass-reared arthropods. Proc IOBC Workshop Quality Control of Mass-Reared Arthropods 1995 (Santa Barbara, 9 12 October).

Video-Based Eye Tracking

Video-Based Eye Tracking Video-Based Eye Tracking Our Experience with Advanced Stimuli Design for Eye Tracking Software A. RUFA, a G.L. MARIOTTINI, b D. PRATTICHIZZO, b D. ALESSANDRINI, b A. VICINO, b AND A. FEDERICO a a Department

More information

juval@post.tau.ac.il University, Tel-Aviv, Israel. efratbl@post.tau.ac.il

juval@post.tau.ac.il University, Tel-Aviv, Israel. efratbl@post.tau.ac.il Application of a Network-Analysis Algorithm for the Definition of Locations in Open Field Behavior: How Rats Establish Behavioral Symmetry in Spatial Asymmetry S. Weiss 1, O. Yaski 1, E. Blumenfeld-Lieberthal

More information

E190Q Lecture 5 Autonomous Robot Navigation

E190Q Lecture 5 Autonomous Robot Navigation E190Q Lecture 5 Autonomous Robot Navigation Instructor: Chris Clark Semester: Spring 2014 1 Figures courtesy of Siegwart & Nourbakhsh Control Structures Planning Based Control Prior Knowledge Operator

More information

Introduction. www.imagesystems.se

Introduction. www.imagesystems.se Product information Image Systems AB Main office: Ågatan 40, SE-582 22 Linköping Phone +46 13 200 100, fax +46 13 200 150 info@imagesystems.se, Introduction TrackEye is the world leading system for motion

More information

The small open field can also serve as a hole board and as a test chamber for the novel

The small open field can also serve as a hole board and as a test chamber for the novel 1 The Open Field Test Revised 9 July 2004 The open field can be of different sizes; small (38 x 38 cm), or large (72 x 72 cm). The small open field can also serve as a hole board and as a test chamber

More information

Fluorescent Array Imaging Reader

Fluorescent Array Imaging Reader Fluorescent Array Imaging Reader Multiplex Enabled For 2-Color Fluorescent Microarrays Extended Dynamic Range Automated Spot Analysis Compact and Affordable Microarray Analysis With FLAIR FLAIR Sensovation

More information

Robot Perception Continued

Robot Perception Continued Robot Perception Continued 1 Visual Perception Visual Odometry Reconstruction Recognition CS 685 11 Range Sensing strategies Active range sensors Ultrasound Laser range sensor Slides adopted from Siegwart

More information

Correcting the Lateral Response Artifact in Radiochromic Film Images from Flatbed Scanners

Correcting the Lateral Response Artifact in Radiochromic Film Images from Flatbed Scanners Correcting the Lateral Response Artifact in Radiochromic Film Images from Flatbed Scanners Background The lateral response artifact (LRA) in radiochromic film images from flatbed scanners was first pointed

More information

C. elegans motility analysis in ImageJ - A practical approach

C. elegans motility analysis in ImageJ - A practical approach C. elegans motility analysis in ImageJ - A practical approach Summary This document describes some of the practical aspects of computer assisted analysis of C. elegans behavior in practice. C. elegans

More information

Basler. Line Scan Cameras

Basler. Line Scan Cameras Basler Line Scan Cameras High-quality line scan technology meets a cost-effective GigE interface Real color support in a compact housing size Shading correction compensates for difficult lighting conditions

More information

Circuits and Resistivity

Circuits and Resistivity Circuits and Resistivity Look for knowledge not in books but in things themselves. W. Gilbert OBJECTIVES To learn the use of several types of electrical measuring instruments in DC circuits. To observe

More information

High Resolution Spatial Electroluminescence Imaging of Photovoltaic Modules

High Resolution Spatial Electroluminescence Imaging of Photovoltaic Modules High Resolution Spatial Electroluminescence Imaging of Photovoltaic Modules Abstract J.L. Crozier, E.E. van Dyk, F.J. Vorster Nelson Mandela Metropolitan University Electroluminescence (EL) is a useful

More information

Introduction. www.imagesystems.se

Introduction. www.imagesystems.se Product information Image Systems AB Main office: Ågatan 40, SE-582 22 Linköping Phone +46 13 200 100, fax +46 13 200 150 info@imagesystems.se, Introduction Motion is the world leading software for advanced

More information

MACHINE VISION MNEMONICS, INC. 102 Gaither Drive, Suite 4 Mount Laurel, NJ 08054 USA 856-234-0970 www.mnemonicsinc.com

MACHINE VISION MNEMONICS, INC. 102 Gaither Drive, Suite 4 Mount Laurel, NJ 08054 USA 856-234-0970 www.mnemonicsinc.com MACHINE VISION by MNEMONICS, INC. 102 Gaither Drive, Suite 4 Mount Laurel, NJ 08054 USA 856-234-0970 www.mnemonicsinc.com Overview A visual information processing company with over 25 years experience

More information

Demo: Real-time Tracking of Round Object

Demo: Real-time Tracking of Round Object Page 1 of 1 Demo: Real-time Tracking of Round Object by: Brianna Bikker and David Price, TAMU Course Instructor: Professor Deepa Kundur Introduction Our project is intended to track the motion of a round

More information

WHITE PAPER. Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception

WHITE PAPER. Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception Methods for Measuring Flat Panel Display Defects and Mura as Correlated to Human Visual Perception Abstract

More information

Cross-beam scanning system to detect slim objects. 100 mm 3.937 in

Cross-beam scanning system to detect slim objects. 100 mm 3.937 in 891 Object Area Sensor General terms and conditions... F-17 Related Information Glossary of terms... P.1359~ Sensor selection guide...p.831~ General precautions... P.1405 PHOTO PHOTO Conforming to EMC

More information

PRODUCT SHEET. info@biopac.com support@biopac.com www.biopac.com

PRODUCT SHEET. info@biopac.com support@biopac.com www.biopac.com EYE TRACKING SYSTEMS BIOPAC offers an array of monocular and binocular eye tracking systems that are easily integrated with stimulus presentations, VR environments and other media. Systems Monocular Part

More information

ALLEN Mouse Brain Atlas

ALLEN Mouse Brain Atlas TECHNICAL WHITE PAPER: QUALITY CONTROL STANDARDS FOR HIGH-THROUGHPUT RNA IN SITU HYBRIDIZATION DATA GENERATION Consistent data quality and internal reproducibility are critical concerns for high-throughput

More information

Processing the Image or Can you Believe what you see? Light and Color for Nonscientists PHYS 1230

Processing the Image or Can you Believe what you see? Light and Color for Nonscientists PHYS 1230 Processing the Image or Can you Believe what you see? Light and Color for Nonscientists PHYS 1230 Optical Illusions http://www.michaelbach.de/ot/mot_mib/index.html Vision We construct images unconsciously

More information

product overview pco.edge family the most versatile scmos camera portfolio on the market pioneer in scmos image sensor technology

product overview pco.edge family the most versatile scmos camera portfolio on the market pioneer in scmos image sensor technology product overview family the most versatile scmos camera portfolio on the market pioneer in scmos image sensor technology scmos knowledge base scmos General Information PCO scmos cameras are a breakthrough

More information

Graphic Design. Background: The part of an artwork that appears to be farthest from the viewer, or in the distance of the scene.

Graphic Design. Background: The part of an artwork that appears to be farthest from the viewer, or in the distance of the scene. Graphic Design Active Layer- When you create multi layers for your images the active layer, or the only one that will be affected by your actions, is the one with a blue background in your layers palette.

More information

Improved predictive modeling of white LEDs with accurate luminescence simulation and practical inputs

Improved predictive modeling of white LEDs with accurate luminescence simulation and practical inputs Improved predictive modeling of white LEDs with accurate luminescence simulation and practical inputs TracePro Opto-Mechanical Design Software s Fluorescence Property Utility TracePro s Fluorescence Property

More information

International Year of Light 2015 Tech-Talks BREGENZ: Mehmet Arik Well-Being in Office Applications Light Measurement & Quality Parameters

International Year of Light 2015 Tech-Talks BREGENZ: Mehmet Arik Well-Being in Office Applications Light Measurement & Quality Parameters www.led-professional.com ISSN 1993-890X Trends & Technologies for Future Lighting Solutions ReviewJan/Feb 2015 Issue LpR 47 International Year of Light 2015 Tech-Talks BREGENZ: Mehmet Arik Well-Being in

More information

Instruction Manual Service Program ULTRA-PROG-IR

Instruction Manual Service Program ULTRA-PROG-IR Instruction Manual Service Program ULTRA-PROG-IR Parameterizing Software for Ultrasonic Sensors with Infrared Interface Contents 1 Installation of the Software ULTRA-PROG-IR... 4 1.1 System Requirements...

More information

A System for Capturing High Resolution Images

A System for Capturing High Resolution Images A System for Capturing High Resolution Images G.Voyatzis, G.Angelopoulos, A.Bors and I.Pitas Department of Informatics University of Thessaloniki BOX 451, 54006 Thessaloniki GREECE e-mail: pitas@zeus.csd.auth.gr

More information

Manual for simulation of EB processing. Software ModeRTL

Manual for simulation of EB processing. Software ModeRTL 1 Manual for simulation of EB processing Software ModeRTL How to get results. Software ModeRTL. Software ModeRTL consists of five thematic modules and service blocks. (See Fig.1). Analytic module is intended

More information

Manual Analysis Software AFD 1201

Manual Analysis Software AFD 1201 AFD 1200 - AcoustiTube Manual Analysis Software AFD 1201 Measurement of Transmission loss acc. to Song and Bolton 1 Table of Contents Introduction - Analysis Software AFD 1201... 3 AFD 1200 - AcoustiTube

More information

Graphical displays are generally of two types: vector displays and raster displays. Vector displays

Graphical displays are generally of two types: vector displays and raster displays. Vector displays Display technology Graphical displays are generally of two types: vector displays and raster displays. Vector displays Vector displays generally display lines, specified by their endpoints. Vector display

More information

MH - Gesellschaft für Hardware/Software mbh

MH - Gesellschaft für Hardware/Software mbh E.d.a.s.VX Data acquisition on board road and track vehicles The E.d.a.s.VX System is designed for portable applications running on 12 Volts DC, and is capable of measuring at selectable rates up to 30,000,000

More information

GelAnalyzer 2010 User s manual. Contents

GelAnalyzer 2010 User s manual. Contents GelAnalyzer 2010 User s manual Contents 1. Starting GelAnalyzer... 2 2. The main window... 2 3. Create a new analysis... 2 4. The image window... 3 5. Lanes... 3 5.1 Detect lanes automatically... 3 5.2

More information

Measuring Length and Area of Objects in Digital Images Using AnalyzingDigitalImages Software. John Pickle, Concord Academy, March 19, 2008

Measuring Length and Area of Objects in Digital Images Using AnalyzingDigitalImages Software. John Pickle, Concord Academy, March 19, 2008 Measuring Length and Area of Objects in Digital Images Using AnalyzingDigitalImages Software John Pickle, Concord Academy, March 19, 2008 The AnalyzingDigitalImages software, available free at the Digital

More information

Thea Omni Light. Thea Spot Light. Light setup & Optimization

Thea Omni Light. Thea Spot Light. Light setup & Optimization Light setup In this tutorial we will learn how to setup lights inside Thea Studio and how to create mesh lights and optimize them for faster rendering with less noise. Let us have a look at the different

More information

Synthetic Sensing: Proximity / Distance Sensors

Synthetic Sensing: Proximity / Distance Sensors Synthetic Sensing: Proximity / Distance Sensors MediaRobotics Lab, February 2010 Proximity detection is dependent on the object of interest. One size does not fit all For non-contact distance measurement,

More information

MSc in Autonomous Robotics Engineering University of York

MSc in Autonomous Robotics Engineering University of York MSc in Autonomous Robotics Engineering University of York Practical Robotics Module 2015 A Mobile Robot Navigation System: Labs 1a, 1b, 2a, 2b. Associated lectures: Lecture 1 and lecture 2, given by Nick

More information

WHITE PAPER. Are More Pixels Better? www.basler-ipcam.com. Resolution Does it Really Matter?

WHITE PAPER. Are More Pixels Better? www.basler-ipcam.com. Resolution Does it Really Matter? WHITE PAPER www.basler-ipcam.com Are More Pixels Better? The most frequently asked question when buying a new digital security camera is, What resolution does the camera provide? The resolution is indeed

More information

Three Channel Optical Incremental Encoder Modules Technical Data

Three Channel Optical Incremental Encoder Modules Technical Data Three Channel Optical Incremental Encoder Modules Technical Data HEDS-9040 HEDS-9140 Features Two Channel Quadrature Output with Index Pulse Resolution Up to 2000 CPR Counts Per Revolution Low Cost Easy

More information

LoliTrack. Video Tracking Software. Operation Manual

LoliTrack. Video Tracking Software. Operation Manual LoliTrack Video Tracking Software Operation Manual TABLE OF CONTENTS INTRODUCTION TO THE VIDEO TRACKING SOFTWARE Tracking Principle 1 Features 2 Included 2 Computer Requirements 2 INSTALL THE VIDEO TRACKING

More information

PHOTOGRAMMETRIC TECHNIQUES FOR MEASUREMENTS IN WOODWORKING INDUSTRY

PHOTOGRAMMETRIC TECHNIQUES FOR MEASUREMENTS IN WOODWORKING INDUSTRY PHOTOGRAMMETRIC TECHNIQUES FOR MEASUREMENTS IN WOODWORKING INDUSTRY V. Knyaz a, *, Yu. Visilter, S. Zheltov a State Research Institute for Aviation System (GosNIIAS), 7, Victorenko str., Moscow, Russia

More information

A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA

A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA A PHOTOGRAMMETRIC APPRAOCH FOR AUTOMATIC TRAFFIC ASSESSMENT USING CONVENTIONAL CCTV CAMERA N. Zarrinpanjeh a, F. Dadrassjavan b, H. Fattahi c * a Islamic Azad University of Qazvin - nzarrin@qiau.ac.ir

More information

Quantitative approaches in behavioral neuroscience. 1st ISBS Summer School St. Petersburg, Russia May 9th -15th,2008

Quantitative approaches in behavioral neuroscience. 1st ISBS Summer School St. Petersburg, Russia May 9th -15th,2008 Quantitative approaches in behavioral neuroscience 1st ISBS Summer School St. Petersburg, Russia May 9th -15th,2008 From neurons to complex behaviors Neurons Biological neural networks Model neural networks

More information

DDX 7000 & 8003. Digital Partial Discharge Detectors FEATURES APPLICATIONS

DDX 7000 & 8003. Digital Partial Discharge Detectors FEATURES APPLICATIONS DDX 7000 & 8003 Digital Partial Discharge Detectors The HAEFELY HIPOTRONICS DDX Digital Partial Discharge Detector offers the high accuracy and flexibility of digital technology, plus the real-time display

More information

Use of pen test (balance beam) to assess motor balance and coordination in mice

Use of pen test (balance beam) to assess motor balance and coordination in mice Please quote this SOP in your Methods. Use of pen test (balance beam) to assess motor balance and coordination in mice SOP (ID) Number SMA_M.2.1.001 Version 1 Issued September 8 th, 2010 Last reviewed

More information

Accurate Measurement of the Mains Electricity Frequency

Accurate Measurement of the Mains Electricity Frequency Accurate Measurement of the Mains Electricity Frequency Dogan Ibrahim Near East University, Faculty of Engineering, Lefkosa, TRNC dogan@neu.edu.tr Abstract The frequency of the mains electricity supply

More information

5-Axis Test-Piece Influence of Machining Position

5-Axis Test-Piece Influence of Machining Position 5-Axis Test-Piece Influence of Machining Position Michael Gebhardt, Wolfgang Knapp, Konrad Wegener Institute of Machine Tools and Manufacturing (IWF), Swiss Federal Institute of Technology (ETH), Zurich,

More information

Automation System TROVIS 6400 TROVIS 6493 Compact Controller

Automation System TROVIS 6400 TROVIS 6493 Compact Controller Automation System TROVIS 6400 TROVIS 6493 Compact Controller For panel mounting (front frame 48 x 96 mm/1.89 x 3.78 inch) Application Digital controller to automate industrial and process plants for general

More information

SE05: Getting Started with Cognex DataMan Bar Code Readers - Hands On Lab Werner Solution Expo April 8 & 9

SE05: Getting Started with Cognex DataMan Bar Code Readers - Hands On Lab Werner Solution Expo April 8 & 9 SE05: Getting Started with Cognex DataMan Bar Code Readers - Hands On Lab Werner Solution Expo April 8 & 9 Learning Goals: At the end of this lab, the student should have basic familiarity with the DataMan

More information

Working With Animation: Introduction to Flash

Working With Animation: Introduction to Flash Working With Animation: Introduction to Flash With Adobe Flash, you can create artwork and animations that add motion and visual interest to your Web pages. Flash movies can be interactive users can click

More information

T-REDSPEED White paper

T-REDSPEED White paper T-REDSPEED White paper Index Index...2 Introduction...3 Specifications...4 Innovation...6 Technology added values...7 Introduction T-REDSPEED is an international patent pending technology for traffic violation

More information

3 hours One paper 70 Marks. Areas of Learning Theory

3 hours One paper 70 Marks. Areas of Learning Theory GRAPHIC DESIGN CODE NO. 071 Class XII DESIGN OF THE QUESTION PAPER 3 hours One paper 70 Marks Section-wise Weightage of the Theory Areas of Learning Theory Section A (Reader) Section B Application of Design

More information

Template-based Eye and Mouth Detection for 3D Video Conferencing

Template-based Eye and Mouth Detection for 3D Video Conferencing Template-based Eye and Mouth Detection for 3D Video Conferencing Jürgen Rurainsky and Peter Eisert Fraunhofer Institute for Telecommunications - Heinrich-Hertz-Institute, Image Processing Department, Einsteinufer

More information

PHYS 222 Spring 2012 Final Exam. Closed books, notes, etc. No electronic device except a calculator.

PHYS 222 Spring 2012 Final Exam. Closed books, notes, etc. No electronic device except a calculator. PHYS 222 Spring 2012 Final Exam Closed books, notes, etc. No electronic device except a calculator. NAME: (all questions with equal weight) 1. If the distance between two point charges is tripled, the

More information

Automatic and Objective Measurement of Residual Stress and Cord in Glass

Automatic and Objective Measurement of Residual Stress and Cord in Glass Automatic and Objective Measurement of Residual Stress and Cord in Glass GlassTrend - ICG TC15/21 Seminar SENSORS AND PROCESS CONTROL 13-14 October 2015, Eindhoven Henning Katte, ilis gmbh copyright ilis

More information

CNC-STEP. "LaserProbe4500" 3D laser scanning system Instruction manual

CNC-STEP. LaserProbe4500 3D laser scanning system Instruction manual LaserProbe4500 CNC-STEP "LaserProbe4500" 3D laser scanning system Instruction manual 2 Hylewicz CNC-Technik Siemensstrasse 13-15 D-47608 Geldern Fon.: +49 (0) 2831 133236 E-Mail: info@cnc-step.com Website:

More information

AS COMPETITION PAPER 2008

AS COMPETITION PAPER 2008 AS COMPETITION PAPER 28 Name School Town & County Total Mark/5 Time Allowed: One hour Attempt as many questions as you can. Write your answers on this question paper. Marks allocated for each question

More information

THE HUMAN BRAIN. observations and foundations

THE HUMAN BRAIN. observations and foundations THE HUMAN BRAIN observations and foundations brains versus computers a typical brain contains something like 100 billion miniscule cells called neurons estimates go from about 50 billion to as many as

More information

K Service Source. Video Conferencing. QuickTime Conferencing Kit, QuickTime Conferencing ISDN Kit

K Service Source. Video Conferencing. QuickTime Conferencing Kit, QuickTime Conferencing ISDN Kit K Service Source Video Conferencing QuickTime Conferencing Kit, QuickTime Conferencing ISDN Kit K Service Source Basics Video Conferencing Basics Introduction - 1 Introduction QuickTime Conferencing (QTC)

More information

Exercise 1: How to Record and Present Your Data Graphically Using Excel Dr. Chris Paradise, edited by Steven J. Price

Exercise 1: How to Record and Present Your Data Graphically Using Excel Dr. Chris Paradise, edited by Steven J. Price Biology 1 Exercise 1: How to Record and Present Your Data Graphically Using Excel Dr. Chris Paradise, edited by Steven J. Price Introduction In this world of high technology and information overload scientists

More information

Bar Code Label Detection. Size and Edge Detection APPLICATIONS

Bar Code Label Detection. Size and Edge Detection APPLICATIONS Bar Code Label Detection The EE-SY169(-A) and EE-SX199 sensors are used for bar code label detection. The EE-SX199 detects the absence or presence of labels (see Bar Code Printer illustration at right).

More information

KB COPY CENTRE. RM 2300 JCMB The King s Buildings West Mains Road Edinburgh EH9 3JZ. Telephone: 0131 6505001

KB COPY CENTRE. RM 2300 JCMB The King s Buildings West Mains Road Edinburgh EH9 3JZ. Telephone: 0131 6505001 KB COPY CENTRE RM 2300 JCMB The King s Buildings West Mains Road Edinburgh EH9 3JZ Telephone: 0131 6505001 Email: kbcopy@ed.ac.uk martin.byrne@ed.ac.uk colin.doherty@ed.ac.uk Step 1. Set up page orientation

More information

Tube Control Measurement, Sorting Modular System for Glass Tube

Tube Control Measurement, Sorting Modular System for Glass Tube Tube Control Measurement, Sorting Modular System for Glass Tube Tube Control is a modular designed system of settled instruments and modules. It comprises measuring instruments for the tube dimensions,

More information

Module PhenoMaster System

Module PhenoMaster System Sophisticated Life Science Research Instrumentation Module PhenoMaster System Treadmill Module for Mice & Rats www.tse-systems.com Info@TSE-Systems.com Specifications subject to change without notice 2

More information

Detection of Leak Holes in Underground Drinking Water Pipelines using Acoustic and Proximity Sensing Systems

Detection of Leak Holes in Underground Drinking Water Pipelines using Acoustic and Proximity Sensing Systems Research Journal of Engineering Sciences ISSN 2278 9472 Detection of Leak Holes in Underground Drinking Water Pipelines using Acoustic and Proximity Sensing Systems Nanda Bikram Adhikari Department of

More information

Blackbody Radiation References INTRODUCTION

Blackbody Radiation References INTRODUCTION Blackbody Radiation References 1) R.A. Serway, R.J. Beichner: Physics for Scientists and Engineers with Modern Physics, 5 th Edition, Vol. 2, Ch.40, Saunders College Publishing (A Division of Harcourt

More information

MetaMorph Software Basic Analysis Guide The use of measurements and journals

MetaMorph Software Basic Analysis Guide The use of measurements and journals MetaMorph Software Basic Analysis Guide The use of measurements and journals Version 1.0.2 1 Section I: How Measure Functions Operate... 3 1. Selected images... 3 2. Thresholding... 3 3. Regions of interest...

More information

SECURITY CAMERA INSTRUCTION MANUAL ENGLISH VERSION 1.0 LBC5451. www.lorextechnology.com

SECURITY CAMERA INSTRUCTION MANUAL ENGLISH VERSION 1.0 LBC5451. www.lorextechnology.com SECURITY CAMERA INSTRUCTION MANUAL ENGLISH VERSION 1.0 LBC5451 www.lorextechnology.com Contents 1x Camera and mounting stand 1x Power adapter 1x Mounting kit 1x Allen key 1x Screw cap 1x 60 ft. (18m)

More information

Framework for colocated synchronous dual eye tracking

Framework for colocated synchronous dual eye tracking Framework for colocated synchronous dual eye tracking Craig Hennessey Department of Electrical and Computer Engineering University of British Columbia Mirametrix Research craigah@ece.ubc.ca Abstract Dual

More information

3D SCANNERTM. 3D Scanning Comes Full Circle. s u n. Your Most Valuable QA and Dosimetry Tools A / B / C. The 3D SCANNER Advantage

3D SCANNERTM. 3D Scanning Comes Full Circle. s u n. Your Most Valuable QA and Dosimetry Tools A / B / C. The 3D SCANNER Advantage 3D SCANNERTM 3D Scanning Comes Full Circle Relative 3D Dosimetry offering the easiest setup, most objectivity, and best consistency available The 3D SCANNER Advantage Advanced Design Ring and diameter

More information

Real-time PCR: Understanding C t

Real-time PCR: Understanding C t APPLICATION NOTE Real-Time PCR Real-time PCR: Understanding C t Real-time PCR, also called quantitative PCR or qpcr, can provide a simple and elegant method for determining the amount of a target sequence

More information

Rodenstock Photo Optics

Rodenstock Photo Optics Rogonar Rogonar-S Rodagon Apo-Rodagon N Rodagon-WA Apo-Rodagon-D Accessories: Modular-Focus Lenses for Enlarging, CCD Photos and Video To reproduce analog photographs as pictures on paper requires two

More information

Laser Gesture Recognition for Human Machine Interaction

Laser Gesture Recognition for Human Machine Interaction International Journal of Computer Sciences and Engineering Open Access Research Paper Volume-04, Issue-04 E-ISSN: 2347-2693 Laser Gesture Recognition for Human Machine Interaction Umang Keniya 1*, Sarthak

More information

26th IBRO/AFRICA school on Advanced Behavioral Neuroscience, ICIPE, Nairobi Kenya 17 th December 2010

26th IBRO/AFRICA school on Advanced Behavioral Neuroscience, ICIPE, Nairobi Kenya 17 th December 2010 26th IBRO/AFRICA school on Advanced Behavioral Neuroscience, ICIPE, Nairobi Kenya 17 th December 2010 Dominic Ochwang'i (Kenya), Moto Fleur (Cameroon), Duncan Matheka (Kenya), Denver Ncube (Zimbabwe),

More information

THE SIMULATION OF MOVING SOUND SOURCES. John M. Chowning

THE SIMULATION OF MOVING SOUND SOURCES. John M. Chowning THE SIMULATION OF MOVING SOUND SOURCES John M. Chowning The Center for Computer Research in Music and Acoustics (CCRMA) Department of Music Stanford University, Stanford, CA 94306 jmc165@home.com (first

More information

Technical Considerations Detecting Transparent Materials in Particle Analysis. Michael Horgan

Technical Considerations Detecting Transparent Materials in Particle Analysis. Michael Horgan Technical Considerations Detecting Transparent Materials in Particle Analysis Michael Horgan Who We Are Fluid Imaging Technology Manufacturers of the FlowCam series of particle analyzers FlowCam HQ location

More information

Video Camera Image Quality in Physical Electronic Security Systems

Video Camera Image Quality in Physical Electronic Security Systems Video Camera Image Quality in Physical Electronic Security Systems Video Camera Image Quality in Physical Electronic Security Systems In the second decade of the 21st century, annual revenue for the global

More information

Technical Information POWER PLANT CONTROLLER

Technical Information POWER PLANT CONTROLLER Technical Information POWER PLANT CONTROLLER Content The Power Plant Controller offers intelligent and flexible solutions for the control of all PV power plants in the megawatt range. It is suitable for

More information

Quick Reference Manual

Quick Reference Manual Quick Reference Manual ii TABLE OF CONTENTS This guide first leads you through the basics of Logger Pro, including software installation procedures. You will learn how to collect data, manually enter data,

More information

Color holographic 3D display unit with aperture field division

Color holographic 3D display unit with aperture field division Color holographic 3D display unit with aperture field division Weronika Zaperty, Tomasz Kozacki, Malgorzata Kujawinska, Grzegorz Finke Photonics Engineering Division, Faculty of Mechatronics Warsaw University

More information

LIST OF CONTENTS CHAPTER CONTENT PAGE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK

LIST OF CONTENTS CHAPTER CONTENT PAGE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK vii LIST OF CONTENTS CHAPTER CONTENT PAGE DECLARATION DEDICATION ACKNOWLEDGEMENTS ABSTRACT ABSTRAK LIST OF CONTENTS LIST OF TABLES LIST OF FIGURES LIST OF NOTATIONS LIST OF ABBREVIATIONS LIST OF APPENDICES

More information

BARE PCB INSPECTION BY MEAN OF ECT TECHNIQUE WITH SPIN-VALVE GMR SENSOR

BARE PCB INSPECTION BY MEAN OF ECT TECHNIQUE WITH SPIN-VALVE GMR SENSOR BARE PCB INSPECTION BY MEAN OF ECT TECHNIQUE WITH SPIN-VALVE GMR SENSOR K. Chomsuwan 1, S. Yamada 1, M. Iwahara 1, H. Wakiwaka 2, T. Taniguchi 3, and S. Shoji 4 1 Kanazawa University, Kanazawa, Japan;

More information

EVIDENCE PHOTOGRAPHY TEST SPECIFICATIONS MODULE 1: CAMERA SYSTEMS & LIGHT THEORY (37)

EVIDENCE PHOTOGRAPHY TEST SPECIFICATIONS MODULE 1: CAMERA SYSTEMS & LIGHT THEORY (37) EVIDENCE PHOTOGRAPHY TEST SPECIFICATIONS The exam will cover evidence photography involving crime scenes, fire scenes, accident scenes, aircraft incident scenes, surveillances and hazardous materials scenes.

More information

Top. Width. Retrace. Trace. Bottom

Top. Width. Retrace. Trace. Bottom 1 INTRODUCTION TO TELEVISION INTRODUCTION The aim of a television system is to extend the sense of sight beyond its natural limits and to transmit sound associated with the scene. The picture signal is

More information

COMPACT GUIDE. Camera-Integrated Motion Analysis

COMPACT GUIDE. Camera-Integrated Motion Analysis EN 05/13 COMPACT GUIDE Camera-Integrated Motion Analysis Detect the movement of people and objects Filter according to directions of movement Fast, simple configuration Reliable results, even in the event

More information

Heat Map Explorer Getting Started Guide

Heat Map Explorer Getting Started Guide You have made a smart decision in choosing Lab Escape s Heat Map Explorer. Over the next 30 minutes this guide will show you how to analyze your data visually. Your investment in learning to leverage heat

More information

AngioSys 2.0 Image Analysis Software Manual

AngioSys 2.0 Image Analysis Software Manual AngioSys 2.0 Image Analysis Software Manual Table of contents Introduction and ordering Activate your software Analyse a new plate Open a previous plate Add well details Delete well details Fill a row/column

More information

Why Use Fiber Optics For Lighting?

Why Use Fiber Optics For Lighting? Why Use Fiber Optics For Lighting? Using fiber for remote lighting has many advantages, some of which are more important for special types of applications than others. Heat Free Lighting: Since the light

More information

Video Tracking Software User s Manual. Version 1.0

Video Tracking Software User s Manual. Version 1.0 Video Tracking Software User s Manual Version 1.0 Triangle BioSystems International 2224 Page Rd. Suite 108 Durham, NC 27703 Phone: (919) 361-2663 Fax: (919) 544-3061 www.trianglebiosystems.com Table of

More information

AN EXPERT SYSTEM TO ANALYZE HOMOGENEITY IN FUEL ELEMENT PLATES FOR RESEARCH REACTORS

AN EXPERT SYSTEM TO ANALYZE HOMOGENEITY IN FUEL ELEMENT PLATES FOR RESEARCH REACTORS AN EXPERT SYSTEM TO ANALYZE HOMOGENEITY IN FUEL ELEMENT PLATES FOR RESEARCH REACTORS Cativa Tolosa, S. and Marajofsky, A. Comisión Nacional de Energía Atómica Abstract In the manufacturing control of Fuel

More information

The best lab standard. 1,4 Megapixels 2/3 inch sensor Giant pixel size 6 times optical zoom Massive 16-bit imaging for enhanced dynamic

The best lab standard. 1,4 Megapixels 2/3 inch sensor Giant pixel size 6 times optical zoom Massive 16-bit imaging for enhanced dynamic 1 AGENDA Product roadmap...3 Computer based system: PLATINUM..5 XPLORER.6 ESSENTIAL..7 Specifications Computer based system..8 Configuration Computer based system... 9 Software Computer based system...10

More information

Universal Simple Control, USC-1

Universal Simple Control, USC-1 Universal Simple Control, USC-1 Data and Event Logging with the USB Flash Drive DATA-PAK The USC-1 universal simple voltage regulator control uses a flash drive to store data. Then a propriety Data and

More information

Explain the role of blood and bloodstain patterns in forensics science. Analyze and identify bloodstain patterns by performing bloodstain analysis

Explain the role of blood and bloodstain patterns in forensics science. Analyze and identify bloodstain patterns by performing bloodstain analysis Lab 4 Blood Learning Objectives Explain the role of blood and bloodstain patterns in forensics science Analyze and identify bloodstain patterns by performing bloodstain analysis Introduction Blood, a

More information

Effects of Cage Stocking Density on Feeding Behaviors of Group-Housed Laying Hens

Effects of Cage Stocking Density on Feeding Behaviors of Group-Housed Laying Hens Animal Industry Report AS 651 ASL R2018 2005 Effects of Cage Stocking Density on Feeding Behaviors of Group-Housed Laying Hens R. N. Cook Iowa State University Hongwei Xin Iowa State University, hxin@iastate.edu

More information

MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification

MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification MultiQuant Software 2.0 for Targeted Protein / Peptide Quantification Gold Standard for Quantitative Data Processing Because of the sensitivity, selectivity, speed and throughput at which MRM assays can

More information

Rotation: Moment of Inertia and Torque

Rotation: Moment of Inertia and Torque Rotation: Moment of Inertia and Torque Every time we push a door open or tighten a bolt using a wrench, we apply a force that results in a rotational motion about a fixed axis. Through experience we learn

More information

Fixplot Instruction Manual. (data plotting program)

Fixplot Instruction Manual. (data plotting program) Fixplot Instruction Manual (data plotting program) MANUAL VERSION2 2004 1 1. Introduction The Fixplot program is a component program of Eyenal that allows the user to plot eye position data collected with

More information

Interactive Voting System. www.ivsystem.nl. IVS-Basic IVS-Professional 4.4

Interactive Voting System. www.ivsystem.nl. IVS-Basic IVS-Professional 4.4 Interactive Voting System www.ivsystem.nl IVS-Basic IVS-Professional 4.4 Manual IVS-Basic 4.4 IVS-Professional 4.4 1213 Interactive Voting System The Interactive Voting System (IVS ) is an interactive

More information

The Olympus stereology system. The Computer Assisted Stereological Toolbox

The Olympus stereology system. The Computer Assisted Stereological Toolbox The Olympus stereology system The Computer Assisted Stereological Toolbox CAST is a Computer Assisted Stereological Toolbox for PCs running Microsoft Windows TM. CAST is an interactive, user-friendly,

More information

Sensors and Cellphones

Sensors and Cellphones Sensors and Cellphones What is a sensor? A converter that measures a physical quantity and converts it into a signal which can be read by an observer or by an instrument What are some sensors we use every

More information

AMS Suite: Machinery Health Manager v5.4

AMS Suite: Machinery Health Manager v5.4 S-NSF033010 October 2010 AMS Suite: Machinery Health Manager v5.4 The AMS Machinery Manager v5.4 release is the result of user input collected during plant visits and documented by our customer support

More information

CSCI 445 Amin Atrash. Ultrasound, Laser and Vision Sensors. Introduction to Robotics L. Itti & M. J. Mataric

CSCI 445 Amin Atrash. Ultrasound, Laser and Vision Sensors. Introduction to Robotics L. Itti & M. J. Mataric Introduction to Robotics CSCI 445 Amin Atrash Ultrasound, Laser and Vision Sensors Today s Lecture Outline Ultrasound (sonar) Laser range-finders (ladar, not lidar) Vision Stereo vision Ultrasound/Sonar

More information