This work was supported by The Human Frontier Science Program (HFSP grant RGP0019/2015), the Israel Science Foundation (ISF grants #1350/12, 1361/17), by the Milgrom Foundation and by the Ministry of Science, Technology and Space of Israel (Grant #3-12068).

All methods described have been approved by the Institutional Animal Care and Use Committee (IACUC) of the University of Haifa.
1. Experimental Set-up
<ol>
	<li>Arena
	<ol>
		<li>Construct the experimental arena for mice (Figure 1A,D) by placing a white or black (depending on the animal&#39;s color) plexiglass box (37 cm x 22 cm x 35 cm) in the middle of an acoustic chamber (60 cm x 65 cm x 80 cm, made of 2 cm thick wood coated on the inside with 2 cm thick foam). For the light, remove a strip (2 cm wide, 10 cm below the ceiling of the chamber) of the foam around the acoustic chamber (besides the door), and attach an LED strip with either red or white light bulbs. Make sure the light is as uniform as possible around the arena to prevent reflections.</li>
		<li>Construct the arena for rats similarly to the one described above for mice, with different dimensions that appropriately fit the size of Sprague-Dawley (SD) rats (Figure 1G). Place a black plexiglass box (50 cm x 50 cm x 40 cm) in the middle of an acoustic chamber (90 cm x 60 cm x 85 cm, made of 2 cm thick wood coated on the inside with 2 cm thick foam).</li>
	</ol>
	</li>
	<li>Chambers
	<ol>
		<li>For mice, create two black or white (depending on the fur color) triangular chambers (12 cm isosceles, 35 cm height, with the floors closed) from 6 mm thick plexiglass. Locate them in two randomly selected opposite corners of the arena (Figure 1B,E). Stick a metal mesh (18 mm x 6 cm; 1 cm x 1 cm holes) in the lower part of each chamber using epoxy glue to allow direct interactions with the stimulus through the mesh (Figure 1C,F). Mark each chamber in a manner that allows discrimination from the others in a video without giving clues to the subjects (see Figure 1B,E for examples). 
		NOTE: Each chamber will eventually contain a social stimulus (mouse) or object (plastic toy, 5 cm x 5 cm x 5 cm, with a distinct shape and color; Figure 1C,I insets).&#160;Let the epoxy glue smell evaporate for at least a week before usage.</li>
		<li>For rats, create two black triangular chambers (20.5 cm isosceles, 40 cm height, made of 6 mm thick plexiglass, with the floors closed) and place them in two randomly selected opposite corners of the arena (Figure 1H), each with a metal mesh (25 cm x 7 cm; 2.5 cm x 1 cm holes) covering its lower portion (Figure 1I).</li>
	</ol>
	</li>
	<li>Place a high quality monochromatic camera, equipped with a wide-angle lens, at the top of the acoustic chamber and connect it to a computer to enable clear viewing and recording of the subject&#39;s behavior using commercial software (see Table of Materials for suggestions).</li>
</ol>
2. Behavioral Paradigm
NOTE: Steps 2.1-2.7 describe the behavioral paradigm for mice. See section 2.8 for specific instructions involving rats.
<ol>
	<li>Make sure that the cages of all animals (subjects: 2-4 month-old male mice; stimuli: 21-30 day-old juvenile mice) remain in the experimental room for at least 1 h before beginning the behavioral experiment.</li>
	<li>Following the acclimation period, insert two empty chambers into the arena randomly at two opposite corners. Place the subject in the middle of the arena for 15 min of habituation. During that time, place the two social stimuli, each in a different chamber located out of the arena for habituation. Place an object (a plastic toy, 5 cm x 5 cm x 5 cm, with a distinct shape and color) in another chamber.</li>
	<li>To perform the social preference (SP) test, start video recording and keep recording until the end of the test.</li>
	<li>Remove the two empty chambers and immediately insert the object and one of the social stimuli, each in a distinct chamber. Locate these chambers randomly in the opposite corners of the arena that were empty during habituation. Allow the subject to interact with the stimuli for the 5 min of the SP test. At the end of the test, stop recording.</li>
	<li>Following the SP test, remove the stimuli-containing chambers from the arena and leave the subject in the empty arena for 15 min.&#160;Clean the chambers from outside with 10% ethanol wipes.</li>
	<li>To perform the social novelty preference (SNP) test, start video recording and insert two chambers into the arena: one containing the same social stimulus used for the SP test (familiar stimulus), and the other containing the novel social stimulus. Place these chambers randomly in two opposite corners of the arena, making sure these&#160;locations&#160;were not used for the SP test. Allow the subject to interact with the stimuli for the 5 min of the SNP test.</li>
	<li>At the end of the SNP test, stop video recording, remove the subject and chambers from the arena, and place the subject back in its home cage. Leave the stimuli in the chambers for the next experiment (with another subject) or return them to their home cages. Clean the arena and chambers with running water followed by 10% ethanol and let dry.</li>
	<li>Behavioral paradigm for rats
	<ol>
		<li>For rats, repeat the behavioral paradigm described in steps 2.1-2.7, with two modifications: 1) handle the rat subjects and habituate the social stimuli to the chambers for 2 days (10 min every day) prior to the experiment; and 2) extend the SP test for 15 min to give the rats a longer period of exposure to social stimuli. Later, restrict the analysis of the SP test to the initial 5 min. 
		NOTE: At least one arena and five chambers are needed in order to run a single session.</li>
	</ol>
	</li>
</ol>
3. Using the TrackRodent GUI for Behavioral Analysis
NOTE: See the upper panel of Figure 2A for the TrackRodent GUI.
<ol>
	<li>Open MATLAB (tested with 2014a-2019a) and choose the TrackRodent folder.</li>
	<li>Add all subfolders to the working path by right-clicking on each folder and selecting Add to Path | Selected Folders and Subfolders.</li>
	<li>Type TrackRodent in the command window and press Enter.</li>
	<li>Upload a single file or multiple video files (AVI or MP4 format) by selecting Load session file (AVI).</li>
	<li>A movie inspector, allowing the inspection of the video clip frame-by-frame, will immediately be opened for the first file in the list (Figure 2A). Use it to examine the video clip and define the first and last frames of the segment to be analyzed. Record the numbers of these frames, which will be required later. Close the window when done.</li>
	<li>For inspecting additional video files, open the video inspector at any time by pressing Inspect movie and selecting a specific video file.</li>
	<li>Select the species tested (mouse or rat; mouse is the default).</li>
	<li>Exclude all the areas that may interrupt the tracking, in accordance with the colors of the subject and arena (black or white).
	<ol>
		<li>To exclude a given area, press Exclude area, and after the cursor changes to a cross shape, mark all corners of the area for exclusion. When done, right-click on the mouse, then double left-click the center of the marked area. The excluded area will become a shade of red on the screen. Repeat this procedure to exclude as many areas as needed.</li>
	</ol>
	</li>
	<li>To remove an area from exclusion, press Remove excluded area, then (using the crossed cursor) click on the area to be removed from exclusion.</li>
	<li>To define each chamber as a &#39;stimulus&#39; area, for automatic detection of its investigation by the subject, choose the shape of the &#39;stimulus&#39; area to be either polygon or elliptical by checking the appropriate box, then pressing Stimulus X (where &#34;X&#34; represents 1, 2, or 3). Mark the &#39;stimulus&#39; areas similarly to the excluded areas, which will then become yellow in color. For changing the location of a specific &#39;stimulus&#39; area, press Stimulus X again and mark the new area location (this will automatically update the location). 
	NOTE: Choose the different stimuli number in a consistent manner for all files (i.e. object as stimulus 1 for all the SP test files).</li>
	<li>To track the presence of the subject in a specific virtual compartment inside the arena, choose the shape of the &#39;compartment&#39; area (polygon or elliptical), then press Compartment X (where &#34;X&#34; represents 1, 2, 3, 4, or 5). Mark the &#39;compartment&#39; areas similarly to the excluded or stimuli areas, which will then become blue in color. For changing the location of a specific &#39;compartment&#39; area, press Compartment X again and mark the new area location (this will automatically update the location).</li>
	<li>Choose the desired algorithm (BlackMouseBodyBased was used for the video) from the list (see available algorithms in Figure 2B).</li>
	<li>Write the numbers of starting and ending frames for the analysis in the corresponding edit boxes of the GUI.</li>
	<li>Choose a threshold for detecting the subject body. 
	NOTE: Most algorithms use the &#34;Low&#34; threshold only, while the head directionality-based algorithms use the &#34;High&#34; threshold, as well. For the &#34;Low&#34; threshold, choose a level that includes the mouse/rat body without the tail (as much as possible), while the &#34;High&#34; threshold should also include the tail. In the case of using head directionality-based algorithms, the software will determine the head location as being opposite to the tail location. 
	NOTE: The software will later on ignores small objects detected using the chosen threshold.</li>
	<li>To evaluate automatic detection of the subject borders for a given threshold, insert a value to the relevant threshold field and press Enter on the keyboard.</li>
	<li>When choosing multiple files, move to the next file (using the Next button at the top) and select the appropriate definitions for each file. When finished, verify the parameters and area locations for all files by moving between each, using the Previous and Next buttons at the top of the GUI. 
	NOTE: The definitions of all areas and parameters are specific to a given file.</li>
	<li>For starting behavioral analysis of all selected files, move to the first file and press Start.</li>
	<li>At the end of the analysis, a results file (.mat file) is saved for each movie in the same directory of the movie files. 
	NOTE: If the slow (non-fast) version of the algorithm is used, it will also save a version of the movie with a white cross of the center of body mass, which changes its color every frame that is detected as investigatory, unless the Save analyzed movie toggle button of the GUI is unchecked. This version of the movie (saved in the same directory, with the same name as the original movie, with the suffix &#39;analyzed movie&#39;) can be used offline to evaluate the quality of the automatic detection performed by the system.</li>
</ol>
4. Using the TrackRodent GUI for Results Presentation
NOTE: See the lower panel of Figure 2A for results presentation.
<ol>
	<li>To inspect the results of each movie file, press Load results file and choose the .mat files generated by the behavioral analysis.</li>
	<li>Move between the toggle buttons to examine onscreen any of the following analyses: Mouse location trace (Figure 2A); Compartments occupation along session (if &#39;compartments&#39; were defined, not shown); Stimuli exploration along session (Figure 2C); Total time in compartments (if &#39;compartments&#39; were defined, not shown); and Total stimuli exploration time (Figure 2D). 
	NOTE: &#39;Stimulus&#39; areas are areas in which the software evaluates subject interaction, while &#39;Compartment&#39; areas are areas in which the software tracks the presence of the subject. Stopping the analysis using the Stop analysis button will automatically save the results generated up to the last analyzed frame. For most computers, it should be possible to upload and analyze as many as 20 movies at once (depending on computer performance).</li>
</ol>
5. Using the TrackRodentPopulationSummary GUI for Population Analysis (Figure 2E)
<ol>
	<li>Open MATLAB (tested with 2014a-2019a) and choose the TrackRodent folder.</li>
	<li>Type TrackRodentPopulationSummary in the command window and press Enter.</li>
	<li>Upload multiple TrackRodent results files (.mat format) by pressing Choose results files.</li>
	<li>Fill in the numbers of Last frame for analysis, Test name, Stimulus 1 name, and Stimulus 2 name.</li>
	<li>Choose the desired analyses from the list of optional analyses by checking all appropriate boxes.</li>
	<li>Choose the Export results to a speadsheet by checking the appropriate box to extract all the results of the checked analyses as a single spreadsheet file.</li>
	<li>Press Start and wait until analysis complete. 
	NOTE: This concludes the analysis. The software can be used to analyze the results of as many movie files as desired, given that they were all behaviorally analyzed using the TrackRodent software. The analysis performed by the software assumes video recording at a frame rate of 30 Hz. In the case that a different frame rate was used, multiply the time by 30 and divide by the frame rate used for recording to convert it to the correct value (s).</li>
</ol>

<ol>
	<li>Insel, T. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+challenge+of+translation+in+social+neuroscience:+a+review+of+oxytocin,+vasopressin,+and+affiliative+behavior.">The challenge of translation in social neuroscience: a review of oxytocin, vasopressin, and affiliative behavior.</a> Neuron. 65 (6), 768-779 (2010).</li><li>Moy, S. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sociability+and+preference+for+social+novelty+in+five+inbred+strains:+an+approach+to+assess+autistic-like+behavior+in+mice.">Sociability and preference for social novelty in five inbred strains: an approach to assess autistic-like behavior in mice.</a> Genes, Brain and Behavior. 3 (5), 287-302 (2004).</li><li>Carr, W. J., Yee, L., Gable, D., Marasco, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Olfactory+recognition+of+conspecifics+by+domestic+Norway+rats.">Olfactory recognition of conspecifics by domestic Norway rats.</a> Journal of Comparative and Physiological Psychoogyl. 90 (9), 821-828 (1976).</li><li>Ferguson, J. N., Aldag, J. M., Insel, T. R., Young, L. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oxytocin+in+the+medial+amygdala+is+essential+for+social+recognition+in+the+mouse.">Oxytocin in the medial amygdala is essential for social recognition in the mouse.</a> Journal of Neuroscience. 21 (20), 8278-8285 (2001).</li><li>Nadler, J. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+apparatus+for+quantitation+of+social+approach+behaviors+in+mice.">Automated apparatus for quantitation of social approach behaviors in mice.</a> Genes, Brain and Behavior. 3 (5), 303-314 (2004).</li><li>Page, D. T., Kuti, O. J., Sur, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Computerized+assessment+of+social+approach+behavior+in+mouse.">Computerized assessment of social approach behavior in mouse.</a> Frontiers in Behavioral Neuroscience. 3, 48 (2009).</li><li>Sankoorikal, G. M., Kaercher, K. A., Boon, C. J., Lee, J. K., Brodkin, E. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+mouse+model+system+for+genetic+analysis+of+sociability:+C57BL/6J+versus+BALB/cJ+inbred+mouse+strains.">A mouse model system for genetic analysis of sociability: C57BL/6J versus BALB/cJ inbred mouse strains.</a> Biological Psychiatry. 59 (5), 415-423 (2006).</li><li>Martin, L., Sample, H., Gregg, M., Wood, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validation+of+operant+social+motivation+paradigms+using+BTBR+T+tf/J+and+C57BL/6J+inbred+mouse+strains.">Validation of operant social motivation paradigms using BTBR T+tf/J and C57BL/6J inbred mouse strains.</a> Brain and Behavior. 4 (5), 754-764 (2014).</li><li>Noldus, L. P. J. J., Spink, A. J., Tegelenbosch, R. A. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EthoVision:+A+versatile+video+tracking+system+for+automation+of+behavioral+experiments.">EthoVision: A versatile video tracking system for automation of behavioral experiments.</a> Behavior Research Methods Instruments &amp; Computers. 33 (3), 398-414 (2001).</li><li>Sams-Dodd, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automation+of+the+social+interaction+test+by+a+video-tracking+system:+behavioural+effects+of+repeated+phencyclidine+treatment.">Automation of the social interaction test by a video-tracking system: behavioural effects of repeated phencyclidine treatment.</a> Journal of Neuroscience Methods. 59 (2), 157-167 (1995).</li><li>Netser, S., Haskal, S., Magalnik, H., Wagner, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+novel+system+for+tracking+social+preference+dynamics+in+mice+reveals+sex-+and+strain-specific+characteristics.">A novel system for tracking social preference dynamics in mice reveals sex- and strain-specific characteristics.</a> Molecular Autism. 8, 53 (2017).</li></ol>

The authors have nothing to disclose.

The experimental system described here, which was designed as an alternative to the three-chamber apparatus2,5, allows performance of the same tests while solving some of its limitations. The use of triangular chambers, which are located in two opposite corners of the rectangular arena limits the subject-stimulus interaction area to a well-defined plane, thus enabling precise automated analysis of investigation behavior. One advantage is the use of the analysis software (TrackRodent) to calculate multiple behavioral parameters for each test. It also allows repositioning of the chambers in random opposite corners of the arena during the various stages of the paradigm, neutralizing any effects of spatial navigation skills.
Furthermore, the two corners of the arena, which are left empty during each stage, offer the subject a convenient place for resting and grooming and draw it away from the chambers, minimizing false-positive results. Thus, the system allows direct assessment of the subject&#39;s motivation to investigate each stimulus during the SP and SNP tests. Furthermore, as behavioral analysis of the videos is done in an automated manner by the TrackRodent software, an experimenter may load multiple movies for analysis, define the correct parameters for each, and let the software process overnight, which saves precious time. Notably, the system may be used for any type of social discrimination test, such as discrimination between male and female social stimuli or stimuli of distinct strains. Moreover, there are no limits (upper/lower) to the size of subjects that can be tracked using this system; thus, it may be used with juveniles or obese animals. This experimental system is inexpensive and simple to produce, and the computer codes used for analysis are publicly available as an open-source codes, allowing any laboratory to easily adopt the method.
The automated detection of investigation behavior in the system is based on detection of physical contact between the body contours of a subject and each of the areas defined by the experimenter as &#39;stimuli&#39;. Thus, if the subject touches the &#39;stimuli&#39; area with its body rather than head, this event is considered investigatory (i.e., a false positive). For this purpose, the head-directionality based algorithm was generated, which identifies the head of the subject and takes into account only contact between the head and &#39;stimuli&#39;. However, this algorithm runs significantly slower than the body-based algorithms; hence, it is not recommended for analysis of a large number of movies, unless experimental conditions require it.
Similar results were observed (1.1% difference, n = 11 experiments, 5 min each, data not shown) between the two algorithms; therefore, the body-based algorithms were most often used. It should be noted that although analyses of large groups of animals are presented here, a much smaller group size is needed for observing a statistically significant difference between two stimuli, based on the total investigation time measured by the system. For example, power calculations revealed that sample sizes of only five and eight animals are required for the SP and SNP tests of mice, respectively (&#945; = 0.05, power = 0.8). Yet, significantly larger groups of animals were used here to ensure observation of all the dynamics of social behavior.
The system requires that the experimenter manually defines the threshold for detection of the subject&#39;s body contours. Finding the right threshold to be use may require some experience; hence, most algorithms used in this system have regular, slower versions. These versions present the analyzed movie and detect investigation events online, while their fast versions do not enable online presentation. It is recommended that new users use the regular versions and monitor analyses online to ensure that it works properly, and that they use the &#34;fast&#34; algorithms only after gathering experience with the analysis procedure.
One advantage of this system over the three-chamber test is that it measures multiple parameters of investigation behavior, thus supporting more detailed analyses. This advantage is two-fold. First, the experimenter does not have to rely solely on the total investigation time to determine the preference. It was found that the long investigation bouts and long intervals are more sensitive than the total investigation time when detecting a preference of one stimulus over another. Regarding these parameters, it should be noted that their values during the last minute of the test are biased downwards, as the long investigation bouts and intervals are prematurely terminated at the end of the 5-min session.
Second, the multiple parameters allow detecting of subtle changes in the dynamics of social investigation following various manipulations. For example, it was found that C57BL/6J male mice lost their social preference following whisker-trimming. In contrast, SD male rats retained their social preference but changed social behavior dynamics as shown by shorter investigation bouts and higher level of transitions in the early phase of the test. Overall, these data suggest a reduction in the tendency of rats and mice for social interactions following whisker trimming. Thus, this system supports a rigorous analysis of the dynamics of social behavior, which may be highly sensitive to various manipulations.
In summary, we presented here a novel, simple, and affordable experimental system that supports automated analysis of social investigation behavior dynamics. This system will facilitate detailed analyses of social behavioral deficits in various strains and genetically modified lines of small rodents. Furthermore, the precise detection of investigation bouts demonstrated here, combined with the capability of this system to analyze behavior while subjects are connected to electrical cables or optical fibers, allows its use in experiments involving recording of brain activity associated with social behavior.

Revealing the biological mechanisms underlying neurodevelopmental disorders (NDDs) is one of the main challenges in the field of neuroscience1. Addressing this challenge requires behavioral paradigms and experimental systems that typify the behavior of rodents in a standard and unbiased manner. An influential study published more than a decade ago by Moy and colleagues2 presented the three-chamber test. Since then, this test has been widely used to investigate social behavior in rodent models of NDDs. This test evaluates two innate tendencies of rodents: 1) to stay in the proximity of a social stimulus over an object (sociability, also termed social preference [SP]), and 2) to prefer the proximity of a novel social stimulus over a familiar one (social novelty preference [SNP])3,4. Several subsequent studies suggested methods of automated analysis of the three-chamber test using computerized methods5,6.
This test still suffers from several caveats. First, it principally examines social place preference rather than the motivation of the subject to directly interact with a social stimulus, although some groups also measure olfactory investigation (sniffing) time, either manually7 or using commercial computerized systems8,9,10. Second, the three-chamber test is mostly used to measure the total time spent by the subject in each chamber, and it neglects behavioral dynamics. Finally, it relies on only one aspect of the social behavior, which is the time spent by the subject in each chamber (or sniffing time, if measured).
Here we present a novel and affordable experimental system that is an alternative to the three-chamber apparatus. It also allows performance of the same behavioral tests while solving the abovementioned caveats. The presented behavioral system automatically and directly measures the investigative behavior of a rodent towards two stimuli. Additionally, it analyzes the behavioral dynamics in an observer-independent manner. Moreover, this system measures multiple behavioral parameters and analyzes these at both individual and population levels; thus, it supports a rigorous analysis of social behavior and its dynamics during each test. Furthermore, random repositioning of the chambers in opposite corners of the arena during the various test stages neutralizes any effects of spatial memory or preference. This system may also be used for other discrimination tests, such as sex discrimination. The custom apparatus is easy to produce, and the analysis system is publicly accessible as an open-source code, thereby allowing its use in any laboratory. We demonstrate the ability of this system to measure multiple parameters of social behavior in rodent strains with distinct fur colors during the social preference and social novelty preference tests. We also validate the ability of the system to reveal modified dynamics of social behavior in rodents following manipulations, such as whisker trimming.
TrackRodent software: three algorithms were written in MATLAB (2014a-2019a) to track the experimental subject and its interactions with the stimuli. All algorithms were deposited in GitHub, found at &#60;https://github.com/shainetser/TrackRodent&#62;. The main aim of all four algorithms is to track the contours of the subject&#39;s body to detect any direct contact with the stimuli areas.
Body-based algorithm: this algorithm has three versions that track the contours of an unwired dark mouse on a white background (BlackMouseBodyBased), a white mouse on a dark background (WhiteMouseBodyBased), or a white rat on a dark background (WhiteRatBodyBased). The graphical user interface (GUI) of the software requires that the experimenter chooses an experiment using either mice or rats and then selects the correct code. For each version of the algorithm, there are two optional codes: one that presents the tracking process on the screen while it performs the analysis, and one that does not (hence, it runs faster and is termed &#34;fast&#34;). For example, the names of the relevant codes for the BlackMouseBodyBased algorithm are: &#34;BlackMouseBodyBased23_7_14&#34; and &#34;BlackMouseBodyBased23_7_14_Fast&#34;. All algorithms ending with &#34;fast&#34; do not show the tracking online, and users must directly save the data to the results file (.mat file). All body-based algorithms require setting a single threshold (&#34;low threshold&#34; in the software&#39;s GUI) to detect the body of the subject.
Head-directionality based algorithm: the second algorithm, which is available only for black mice, is based on the body-based algorithm, in addition to determining head directionality. This algorithm detects the interactions of subject&#39;s head with the &#34;stimuli&#34; areas, thus avoiding false positives that can arise from random contacts of the subject&#39; with these areas. For this algorithm, two detection thresholds of mouse body contours are defined: high threshold, which includes the brighter tail of black mice, and low threshold, which includes the body without tail. Thereafter, the algorithm fits an ellipsoid to the detected boundaries using the lower threshold and defines the location of the mouse head and tail (with no distinction between the two). The final discrimination between the tail and head is based on the boundaries defined by the higher threshold.
Wired animal algorithm: the third algorithm aims to minimize artifacts resulting from cables (i.e., electrical wire or optical fiber) connected to the animal, allowing analysis of the animal&#39;s behavior while connected to a cable. This algorithm has codes only for black mice and white rats. The code for rats requires the experimenter to define both low and high thresholds, while the mouse code requires only a low threshold.

<table><tbody><tr><td>Flea3 1.3 MP Mono USB3 Vision</td><td>FLIR (formerly PointGrey)</td><td>FL3-U3-13Y3M-C</td><td>Monochromatic Camera</td></tr><tr><td>FlyCap 2.0</td><td>FLIR (formerly PointGrey)</td><td>FlyCapture 2.13.3.61X64</td><td>Video recording software</td></tr><tr><td>Home 5 minute Epoxy glue</td><td>Devocon</td><td>20845</td><td>For gluing the metal mesh to the Plexiglas stimuli chambers</td></tr><tr><td>Matlab 2014-2019</td><td>MathWorks</td><td>R2014a - R2019a</td><td>Programming environment</td></tr><tr><td>Plexiglas boards (6 mm thickBlack or white)</td><td>Melina (1990) LTD, Israel</td><td>NaN</td><td>For arena and stimuli chambers construction</td></tr><tr><td>Red led strips (60 leds per meter) connected to a 12 V power supply</td><td>2012topdeal eBay supplier</td><td>NaN</td><td>For illumination of the acoustic chamber</td></tr></tbody></table>

a system for tracking the dynamics of social preference behavior in small rodents

Exploring the neurobiological mechanisms of social behavior requires behavioral tests that can be applied to animal models in an unbiased and observer-independent manner. Since the beginning of the millennium, the three-chamber test has been widely used as a standard paradigm to evaluate sociability (social preference) and social novelty preference in small rodents. However, this test suffers from multiple limitations, including its dependence on spatial navigation and negligence of behavioral dynamics. Presented and validated here is a novel experimental system that offers an alternative to the three-chamber test, while also solving some of its caveats. The system requires a simple and affordable experimental apparatus and publicly available open-source analysis system, which automatically measures and analyzes multiple behavioral parameters at individual and population levels. It allows detailed analysis of the behavioral dynamics of small rodents during any social discrimination test. We demonstrate the efficiency of the system in analyzing the dynamics of social behavior during the social preference and social novelty preference tests as performed by adult male mice and rats. Moreover, we validate the ability of the system to reveal modified dynamics of social behavior in rodents following manipulations such as whisker trimming. Thus, the system allows for rigorous investigation of social behavior and dynamics in small rodent models and supports more accurate comparisons between strains, conditions, and treatments.

Watch this Scientific Journal Video about A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents at JoVE.com

A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

Described here is a novel automated experimental system that offers an alternative to the three-chamber test and also solves several caveats. This system supplies multiple behavioral parameters that enable rigorous analysis of small rodent behavioral dynamics during the social preference and social novelty preference tests.

Exploring the neurobiological mechanisms of social behavior requires behavioral tests that can be applied to animal models in an unbiased and ...

a-system-for-tracking-dynamics-social-preference-behavior-small

Nanyang Technological University

Research

JoVE Journal

Behavior

7.5K Views.  University of Haifa. Described here is a novel automated experimental system that offers an alternative to the three-chamber test and also solves several caveats. This system supplies multiple behavioral parameters that enable rigorous analysis of small rodent behavioral dynamics during the social preference and social novelty preference tests.

Video: A System for Tracking the Dynamics of Social Preference Behavior in Small Rodents

Experimental Assessment of Mouse Sociability Using an Automated Image Processing Approach

Mouse is the preferred model organism for testing drugs designed to increase sociability. We present a method to quantify mouse sociability in which the test mouse is placed in a standardized apparatus and relevant behaviors are assessed in three different sessions (called session I, II, and III).
The apparatus has three compartments (see Figure 1), the left and right compartments contain an inverted cup which can house a mouse (called &#34;stimulus mouse&#34;).
In session I, the test mouse is placed in the cage and its mobility is characterized by the number of transitions made between compartments. In session II, a stimulus mouse is placed under one of the inverted cups and the sociability of the test mouse is quantified by the amounts of time it spends near the cup containing the enclosed stimulus mouse vs. the empty inverted cup. In session III, the inverted cups are removed and both mice interact freely. The sociability of the test mouse in session III is quantified by the number of social approaches it makes toward the stimulus mouse and by the number of times it avoids a social approach by the stimulus mouse.
The automated evaluation of the movie detects the nose of the test mouse, which allows the determination of all described sociability measures in session I and II (in session III, approaches are identified automatically but classified manually). To find the nose, the image of an empty cage is digitally subtracted from each frame of the movie and the resulting image is binarized to identify the mouse pixels. The mouse tail is automatically removed and the two most distant points of the remaining mouse are determined; these are close to nose and base of tail. By analyzing the motion of the mouse and using continuity arguments, the nose is identified.
<img alt="Figure 1" src="/files/ftp_upload/52508/52508fig1.jpg" /> 
Figure 1. Assessment of Sociability During 3 sessions. Session I (top): Acclimation of test mouse to the cage. Session II (middle): Test mouse moving freely in the cage while the stimulus mouse is enclosed in an inverted cup. Session III (bottom): Both test mouse and stimulus mouse are allowed to move freely and interact with each other.

This protocol describes a method to quantify mouse sociability. Mice are videotaped as they move and interact in a special cage. Movie processing allows for the automated quantification of sociability with excellent accuracy and reliability.

Mouse is the preferred model organism for testing drugs designed to increase sociability. We present a method to quantify mouse sociability in which the ...

Assessment of Social Interaction Behaviors

Social interactions are a fundamental and adaptive component of the biology of numerous species. Social recognition is critical for the structure and stability of the networks and relationships that define societies. For animals, such as mice, recognition of conspecifics may be important for maintaining social hierarchy and for mate choice 1.
A variety of neuropsychiatric disorders are characterized by disruptions in social behavior and social recognition, including depression, autism spectrum disorders, bipolar disorders, obsessive-compulsive disorders, and schizophrenia. Studies of humans as well as animal models (e.g., Drosophila melanogaster, Caenorhabditis elegans, Mus musculus, Rattus norvegicus) have identified genes involved in the regulation of social behavior 2. To assess sociability in animal models, several behavioral tests have been developed (reviewed in 3). Integrative research using animal models and appropriate tests for social behavior may lead to the development of improved treatments for social psychopathologies.
The three-chamber paradigm test known as Crawley's sociability and preference for social novelty protocol has been successfully employed to study social affiliation and social memory in several inbred and mutant mouse lines (e.g. 4-7). The main principle of this test is based on the free choice by a subject mouse to spend time in any of three box's compartments during two experimental sessions, including indirect contact with one or two mice with which it is unfamiliar. To quantitate social tendencies of the experimental mouse, the main tasks are to measure a) the time spent with a novel conspecific and b) preference for a novel vs. a familiar conspecific. Thus, the experimental design of this test allows evaluation of two critical but distinguishable aspects of social behavior, such as social affiliation/motivation, as well as social memory and novelty. "Sociability" in this case is defined as propensity to spend time with another mouse, as compared to time spent alone in an identical but empty chamber 7. "Preference for social novelty" is defined as propensity to spend time with a previously unencountered mouse rather than with a familiar mouse 7. This test provides robust results, which then must be carefully analyzed, interpreted and supported/confirmed by alternative sociability tests. In addition to specific applications, Crawley's sociability test can be included as an important component of general behavioral screen of mutant mice.

Here we describe a detailed protocol for examination of sociability in mice by using Crawley's sociability and preference for social novelty test. We describe the advantages and possible applications for this procedure, including critical details important for correct interpretation of the results.

Social interactions are a fundamental and adaptive component of the biology of numerous species. Social recognition is critical for the structure and ...

Neuroscience

Quantifying Social Motivation in Mice Using Operant Conditioning

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered shuttle boxes were equipped with two operant levers (left and right) and a food receptacle in one chamber, which was then divided from the second chamber by an automated guillotine door covered by a wire grid. Different stimulus mice, rotated across testing days, served as a social stimulus behind the wire grid, and were only visible following the opening of the guillotine door. Test mice were trained to lever press in order to open the door and gain access to the stimulus partner for 15 sec. The number of lever presses required to obtain the social reward progressively increased on a fixed schedule of 3. Testing sessions ended after test mice stopped lever pressing for 5 consecutive minutes. The last reinforced ratio or breakpoint can be used as a quantitative measure of social motivation. For the second paradigm, test mice were trained to discriminate between left and right lever presses in order to obtain either a food reward or the social reward. Mice were rewarded for every 3 presses of each respective lever. The number of food and social rewards can be compared as a measurement of the value placed upon each reward. The ratio of each reward type can also be compared between mouse strains and the change in this ratio can be monitored within testing sessions to measure satiation with a given reward type. Both of these operant conditioning paradigms are highly useful for the quantification of social motivation in mouse models of autism and other disorders of social behavior.

This article describes a new protocol for the quantitative measurement of social motivation in mice using operant conditioning for a social reward. The protocol is useful for the measurement of social motivation in mouse models of autism and other disorders of social behavior.

In this protocol, social motivation is measured in mice through a pair of operant conditioning paradigms. To conduct the experiments, two-chambered ...

Novel Object Exploration as a Potential Assay for Higher Order Repetitive Behaviors in Mice

Restricted, repetitive behaviors (RRBs) are a core feature of autism spectrum disorder (ASD) and disrupt the lives of affected individuals. RRBs are commonly split into lower-order and higher-order components, with lower order RRBs consisting of motor stereotypies and higher order RRBs consisting of perseverative and sequencing behaviors. Higher order RRBs are challenging to model in mice. Current assays for RRBs in mice focus primarily on the lower order components, making basic biomedical research into potential treatments or interventions for higher-order RRBs difficult. Here we describe a new assay, novel object exploration. This assay uses a basic open-field arena with four novel objects placed around the perimeter. The test mouse is allowed to freely explore the arena and the order in which the mouse investigates the novel objects is recorded. From these data, patterned sequences of exploration can be identified, as can the most preferred object for each mouse. The representative data shared here and past results using the novel object exploration assay illustrate that inbred mouse strains do demonstrate different behavior in this assay and that strains with elevated lower order RRBs also show elevated patterned behavior. As such, the novel object exploration assay appears to possess good face validity for higher order RRBs in humans and may be a valuable assay for future studies investigating novel therapeutics for ASD.

Higher order restricted, repetitive behaviors (RRBs) disrupt the lives of affected individuals. These behaviors are challenging to model in rodents, making basic biomedical research into potential treatments or interventions for RRBs difficult. Here we describe novel object exploration as a potential assay for higher order RRBs in mice.

Restricted, repetitive behaviors (RRBs) are a core feature of autism spectrum disorder (ASD) and disrupt the lives of affected individuals.  RRBs are ...

Assessment of Social Transmission of Food Preferences Behaviors

Olfactory recognition deficits are suggested to be able to serve as clinical marker to differentiate Alzheimer&#39;s disease (AD) subjects from healthy aging groups. For example, olfactory dysfunction in AD can present as impairment in olfactory recognition, emerging during early stages of the disease and worsening while the disease progresses. The social transmission of food preferences (STFP) task is based on a rudimentary form of communication between rodents concerning distant foods dependent on the transmission of olfactory cues. Healthy wild-type mice would prefer to eat a novel, flavored food that was previously cued by a conspecific, and this food preference would be hampered in transgenic AD mice, such as the APP/PS1 model. Indeed, a strong preference for the cued food in C57Bl6/J mice of 3 months of age was found, and this was reduced in 3 months old transgenic APP/PS1 mice. In summary, STFP task could be a powerful measure to be integrated in present subclinical detection assays of AD.

This paper presents a protocol for the investigation of social transmission of food preference in mice. The advantages and possible applications for this procedure, for instance, in detecting early changes in AD mouse models, are highlighted. To conclude, interpretation of the results in light of critical details are discussed.

Olfactory recognition deficits are suggested to be able to serve as clinical marker to differentiate Alzheimer&#39;s disease (AD) subjects from healthy ...

Analyzing Spatial Learning and Prosocial Behavior in Mice Using the Barnes Maze and Damsel-in-Distress Paradigms

The Barnes maze is a reliable measure of spatial learning and memory that does not require food restriction or exposure to extremely stressful stimuli. The Barnes maze can also assess other mouse behaviors, such as general motivation to escape from the maze platform and exploratory behavior. The Barnes maze can measure whether a genetic mutation or environmental variable can impact the acquisition and retention of spatial memories, as well as provide information about the search strategy employed by the mice. Here we use the Barnes maze to detect a memory deficit in adult mice following a single developmental ethanol exposure event. The newly described Damsel-in-Distress paradigm exposes a male mouse to a female mouse trapped in a chamber in the open center field of the arena. It provides an opportunity for the mouse to socially respond to the trapped female and exhibit prosocial behavior. The Damsel-in-Distress paradigm can also be used to examine mouse behavior in a novel arena and measure locomotor activity. Both the Barnes Maze and the Damsel-in-Distress protocols require minimal financial investment and most aspects of the tests can be constructed from common lab supplies. These flexible and accessible tools can also be used to detect behavioral changes over the course of development.

This protocol measures spatial learning and memory using the Barnes maze. A novel Damsel-in-Distress paradigm is used to assess locomotor activity and prosocial behavior in mice.

The Barnes maze is a reliable measure of spatial learning and memory that does not require food restriction or exposure to extremely stressful stimuli. ...

Peering into the Dynamics of Social Interactions: Measuring Play Fighting in Rats

Play fighting in the rat involves attack and defense of the nape of the neck, which if contacted, is gently nuzzled with the snout. Because the movements of one animal are countered by the actions of its partner, play fighting is a complex, dynamic interaction. This dynamic complexity raises methodological problems about what to score for experimental studies. We present a scoring schema that is sensitive to the correlated nature of the actions performed. The frequency of play fighting can be measured by counting the number of playful nape attacks occurring per unit time. However, playful defense, as it can only occur in response to attack, is necessarily a contingent measure that is best measured as a percentage (#attacks defended/total # attacks X 100%). How a particular attack is defended against can involve one of several tactics, and these are contingent on defense having taken place; consequently, the type of defense is also best expressed contingently as a percentage. Two experiments illustrate how these measurements can be used to detect the effect of brain damage on play fighting even when there is no effect on overall playfulness. That is, the schema presented here is designed to detect and evaluate changes in the content of play following an experimental treatment.

Play fighting in the rat involves attack and defense of the nape of the neck, which if contacted, is gently nuzzled with the snout. Because the movements of one animal are countered by the actions of its partner, play fighting is a complex, dynamic interaction. This dynamic complexity raises methodological problems about what to score for experimental studies. We present a scoring schema that is sensitive to the correlated nature of the actions performed. Two experiments illustrate how these measurements can be used to detect the effect of brain damage on play fighting even when there is no effect on overall playfulness. That is, the schema presented here is designed to detect and evaluate changes in the content of play following an experimental treatment.

Play fighting in the rat involves attack and defense of the nape of the neck, which if contacted, is gently nuzzled with the snout. Because the movements ...

A Complex Diving-For-Food Task to Investigate Social Organization and Interactions in Rats

For many species, where status is a vital motivator that can affect health, social hierarchies influence behavior. Social hierarchies that include dominant-submissive relationships are common in both animal and human societies. These relationships can be affected by interactions with others and with their environment, making them difficult to analyze in a controlled study. Rather than a simple dominance hierarchy, this formation has a complicated presentation that allows rats to avoid aggression. Status can be stagnant or mutable, and results in complex societal stratifications. Here we describe a complex diving-for-food task to investigate rodent social hierarchy and behavioral interactions. This animal model may allow us to assess the relationship between a wide range of mental illnesses and social organization, as well as to study the effectiveness of therapy on social dysfunction.

This protocol describes a method of examining social hierarchy in a rat model. Rats perform a complex diving-for-food task in which they form a distinct hierarchy according to their willingness to dive underwater and swim to obtain a food pellet. This method is used to understand decision making and social relationships among highly social animals in small groups.

For many species, where status is a vital motivator that can affect health, social hierarchies influence behavior. Social hierarchies that include ...

Behavioral Assays for Autism Spectrum Disorder in Mouse Models

Strategies for Assessing Autistic-Like Behaviors in Mice

Autism spectrum disorder (ASD) is a neurobiologically complex condition with a heterogeneous genetic etiology. Clinically, ASD is diagnosed by social communication impairments and restrictive or repetitive behaviors, such as hand flapping or lining up objects. These behavioral patterns can be reliably observed in mouse models with ASD-linked genetic mutations, making them highly useful tools for studying the underlying cellular and molecular mechanisms in ASD. Understanding how genetic changes affect the neurobiology and behaviors observed in ASD will facilitate the development of novel targeted therapeutic compounds to ameliorate core behavioral impairments. Our lab has employed several protocols encompassing well-described training and testing procedures that reflect a wide range of behavioral deficits related to ASD. Here, we detail two assays to study the core features of ASD in mouse models: self-grooming (a measure of repetitive behavior) and the three-chamber social interaction test (a measure of social interaction approach and preference for social novelty).

Rodent models are valuable tools for studying core behaviors related to autism spectrum disorder (ASD). In this article, we expound on two behavioral tests for modeling the core features of ASD in mice: self-grooming, which assesses repetitive behavior, and the three-chamber social interaction test, which documents social impairments.

Autism spectrum disorder (ASD) is a neurobiologically complex condition with a heterogeneous genetic etiology. Clinically, ASD is diagnosed by social ...

A Real-Time Interactive System for Studying Confrontational Pursuit Behavior in Rodents

Predatory pursuit behavior involves a series of important physiological processes, such as locomotion, learning, and decision-making that are critical to the success of an animal in capturing prey. However, there are few methods and systems for studying predatory pursuit behavior in the laboratory, especially in mice, a commonly used mammalian model. The main factors limiting this research are the uncontrollability of live prey (e.g., crickets) and the challenge of harmonizing experimental standards. The goal of this study was to develop an interactive platform to detect and quantify predatory pursuit behaviors in mice on a robotic bait. The platform uses computer vision to monitor the relative positions of the mouse and robotic bait in real time to program the motion patterns of the robotic bait, and the interactive two-dimensional sliders magnetically control the movement of the robotic bait to achieve a closed-loop system. The robotic bait is able to evade approaching hungry mice in real-time, and its escape speed and direction can be adjusted to mimic the predatory pursuit process in different contexts. After a short period of unsupervised training (less than two weeks), the mice were able to perform the predation task with a relatively high efficiency (less than 15 s). By recording kinematic parameters such as speed and trajectories of the robotic bait and the mice, we were able to quantify the pursuit process under different conditions. In conclusion, this method provides a new paradigm for the study of predatory behavior and can be used to further investigate the dynamics and neural mechanisms of predatory pursuit behavior.

Here, we present a protocol to detect and quantify predatory pursuit behavior in a mouse model. This platform provides a new research paradigm for studying the dynamics and neural mechanisms of predatory pursuit behavior in mice and will provide a standardized platform for studying pursuit behavior.

Predatory pursuit behavior involves a series of important physiological processes, such as locomotion, learning, and decision-making that are critical to ...