The creation of this system was supported by 5RO1MH77027.

The three fully automated protocols in the TSsystem (matching, appetitive instrumental and classical conditioning) and the switch protocol have been approved by the Animal Care and Facilities Committee at Rutgers New Brunswick.
1. Setting Up the Physical System
<ol>
	<li>Set up the test environments in the cabinets (see Figure 1).</li>
	<li>Install the experiment-control software provided with the test environments on the protocol-control computers. 
	Note: Do not use these computers for any other purpose!</li>
</ol>
2. Setting Up the Software System
<ol>
	<li>Set up the LAN (local area network) so that the server on which data-analysis software is installed can access the hard disks of the computer(s) controlling the test environments (see Figure 1).</li>
	<li>Establish a file-synchronizing account for data storage in the &#34;cloud&#34;.</li>
	<li>Put the TSsystem folder and its subfolders on the search path of the commercial programming language in a cloud-synchronized folder. 
	Note: The TSsystem is a software toolbox, that is, a library of over 30 high-level functions that facilitate the creation of complex data-analysis and data-graphing code that automatically processes the data whenever it is harvested from the output files generated by the experiment-control program. All of the commands operate on data in fields of the Experiment structure and put the results in other fields in the same structure (see Figure 2). These open-source commands are written in one of the most widely used commercial scientific programming and graphing languages. It has many other &#34;toolboxes&#34;, including most usefully a statistics toolbox.</li>
</ol>
3. Starting an Experiment
<ol>
	<li>Call TSbegin (see Figure 3). 
	Note: TSbegin is an interactive GUI (Graphic User Interface) in the TSsystem toolbox. It leads the user through the process of creating the hierarchical data structure into which the raw data and all results derived from it will be placed by the other functions in the TSsystem toolbox.</li>
	<li>Call TSaddprotocol (see Figure 4). 
	Note: TSaddprotocol is a GUI in the TSsystem toolbox. It leads the user through the process of specifying control parameters for an experimental protocol, specifying decision code that will automate the decision to terminate the protocol and go on to the next one, and specifying the decision criteria to be used.</li>
	<li>Place mice in the 24/7 live-in test environments, one mouse per environment. 
	Notes: Take care to note the ID number of the mouse that goes into each of the numbered experimental environments (Box 1, Box 2, etc.). Also, note the letter that identifies the experiment-control computer on the Local Area Network (LAN) and its IP address.</li>
	<li>Call TSstartsession (Figure 5). 
	Note: TSstartsession is a GUI in the TSsystem toolbox . It leads the user through the process of starting an experimental session. Experimental sessions last one or two weeks, during which several different behavioral testing protocols are run. TSstartsession stores the information that goes into the macro that the protocol-control software reads when a session is started. Included is the path to and name of the code file that the protocol-control software reads. TSsystem&#39;s analytic software reads this code into the hierarchical data structure, so there is never doubt as to the exact protocol in force at any time.</li>
	<li>Go to the control computers and call the macros written to the MedPC folder, in order to start the session&#160;for the boxes controlled by that&#160;computer.</li>
</ol>
4. Data Analysis
<ol>
	<li>If you have created a new protocol, write appropriate data-analysis and graphing code using the commands in the TSsystem toolbox, which greatly simplify the creation of complex data analyses. 
	Note: Data-analysis and graphing code for the three protocols whose results are described below are included in the TSsystem toolbox. Because, they are open source, they may be modified at will. The code for these analyses is extensively commented, which makes it easier to create code for analyzing the results from user-specified protocols.</li>
	<li>For the duration of the experiment (24 hr&#160;to many weeks), monitor email for alerts from the server indicating possible equipment malfunctions (power failures, spontaneous, control-computer reboots, pellet feeder malfunctions, etc.), which the TSsystem data-analyzing program detects.</li>
	<li>Study the plots of performance that the data-analyzing code written in TSsystem produces every time it is called by the analysis timer (typically 2-4 times/day). 
	Note: The analysis timer calls the data-analysis and graphing program at user-specified intervals. The called program is written with functions in TSsystem. It reads into the hierarchical data structure the raw data harvested from the file to which the protocol-control software writes. Then, it analyzes the data and graphs the results of the analyses. The file containing the hierarchical data structure is stored in a file-synchronization folder in the cloud. This provides automatic off-site backup. The automatic file-synchronization stores copies of the structure file on the computers of all the personnel and collaborators who have been granted access. Specified graphs are automatically emailed to specified personnel and collaborators. A principal investigator can monitor the progress of the testing from anywhere in the world at any time, and, if necessary, revise the experimental protocol, on line, remote from the site where the mice are being tested.</li>
	<li>Use TSbrowser to study the data and summary statistics in the hierarchical data structure as they become available, in quasi real time (see Figure 2).</li>
</ol>

<ol>
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F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+genetics+of+quantitative+traits:+challenges+and+prospects.">The genetics of quantitative traits: challenges and prospects.</a> 10, 565-577 (2009).</li><li>Weber, J. N., Peterson, B. K., Hoekstra, H. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Discrete+genetic+modules+are+responsible+for+complex+burrow+evolution+in+Peromyscus+mice.">Discrete genetic modules are responsible for complex burrow evolution in Peromyscus mice.</a> Nature. 493, 402-405 (2013).</li><li>Balsam, P. D., Drew, M. R., Gallistel, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Time+and+Associative+Learning.">Time and Associative Learning.</a> Compar. Cogn. Behav. 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J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Derivatives+of+matching.">Derivatives of matching.</a> Psychol. Rev. 86, 486-495 (1979).</li><li>Mark, T. A., Gallistel, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinetics+of+matching.">Kinetics of matching.</a> J. Exp. Psychol. Animal Behav. Process. 20, 79-95 (1994).</li><li>Brandeis, R., Brandys, Y., Yehuda, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+use+of+the+Morris+water+maze+in+the+study+of+memory+and+learning.">The use of the Morris water maze in the study of memory and learning.</a> Int. J. Neurosci. 48, 29-69 (1989).</li><li>Foucaud, J., Burns, J. G., Mery, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Use+of+spatial+information+and+search+strategies+in+a+water+maze+analog+in+Drosophila+melanogaster.">Use of spatial information and search strategies in a water maze analog in Drosophila melanogaster.</a> PLoS ONE. 5, (2010).</li><li>Logue, S. F., Paylor, R., Wehner, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hippocampal+lesions+cause+learning+deficits+in+inbred+mice+in+the+Morris+water+maze+and+conditioned-fear+task.">Hippocampal lesions cause learning deficits in inbred mice in the Morris water maze and conditioned-fear task.</a> Behav. Neurosci. 111, 104-113 (1997).</li><li>Upchurch, M., Wehner, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differences+between+inbred+strains+of+mice+in+Morris+water+maze+performance.">Differences between inbred strains of mice in Morris water maze performance.</a> Behav. Genet. 18, 55-68 (1988).</li><li>Zilles, K., Wu, J., Crusio, W. E., Schwegler, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Water+maze+and+radial+maze+learning+and+the+density+of+binding+sites+of+glutamate,+GABA,+and+serotonin+receptors+in+the+hippocampus+of+inbred+mouse+strains.">Water maze and radial maze learning and the density of binding sites of glutamate, GABA, and serotonin receptors in the hippocampus of inbred mouse strains.</a> Hippocampus. 10, 213-225 (2000).</li><li>Chen, G., King, J. A., Burgess, N., O'Keefe, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+vision+and+movement+combine+in+the+hippocampal+place+code.">How vision and movement combine in the hippocampal place code.</a> Proc. Natl. Acad. Sci. U.S.A. 110, 378-383 (2013).</li><li>Gallistel, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The organization of learning. , (1990).</li><li>Wittlinger, M., Wehner, R., Wolf, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+desert+ant+odometer:+a+stride+integrator+that+accounts+for+stride+length+and+walking+speed.">The desert ant odometer: a stride integrator that accounts for stride length and walking speed.</a> J. Exp. Biol. 210, (2007).</li><li>Challet, E., Mendoza, J., Dardente, H., Pevet, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neurogenetics+of+food+anticipation.">Neurogenetics of food anticipation.</a> Eur. J. Neurosci. 30, 1676-1687 (2009).</li><li>Arcediano, F., Miller, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Some+constraints+for+models+of+timing:+A+temporal+coding+hypothesis+perspective.">Some constraints for models of timing: A temporal coding hypothesis perspective.</a> Learn. Mot. 33, 105-123 (2002).</li><li>Denniston, J. C., Blaisdell, A. P., Miller, R. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Temporal+Coding+in+Conditioned+Inhibition:+Analysis+of+Associative+Structure+of+Inhibition.">Temporal Coding in Conditioned Inhibition: Analysis of Associative Structure of Inhibition.</a> J. Exp. Psychol. Animal Behav. Process. 30, 190-202 (2004).</li><li>Balci, F., Freestone, D., Gallistel, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Risk+assessment+in+man+and+mouse.">Risk assessment in man and mouse.</a> Proc. Natl. Acad. Sci. U.S.A. 106, 2459-2463 (2009).</li><li>Kheifets, A., Gallistel, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mice+take+calculated+risks.">Mice take calculated risks.</a> Proc. Natl. Acad. Sci. U.S.A. 109, 8776-8779 (2012).</li><li>Fetterman, J. G., Killeen, P. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Categorical+scaling+of+time:+Implications+for+clock-counter+models.">Categorical scaling of time: Implications for clock-counter models.</a> J. Exp. Psychol. Animal Behav. Process. 21, 43-63 (1995).</li><li>Luby, M., 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=Food+anticipatory+activity+behavior+of+mice+across+a+wide+range+of+circadian+and+non-circadian+intervals.">Food anticipatory activity behavior of mice across a wide range of circadian and non-circadian intervals.</a> PLoS One. 7, (2012).</li><li>Lee, S. A., Vallortigara, G., Ruga, V., Sovrano, V. 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The authors have nothing to disclose.

Our method yields a wide range of physiological meaningful, quantitative results on the functioning of several different mechanisms of cognition, learning and memory, for many mice at once, in a minimum amount of time, with a minimum of human labor, and with no handling of the experimental subjects during days, weeks, or months of testing. These attributes suit it for genetic and pharmacological screening programs. It uses minimally modified off-the-shelf hardware (test boxes and nest tubs). It produces more data from mo...

To bring the powerful techniques of genetics, molecular genetics, molecular biology, and neuropharmacology to bear on elucidating the cellular and molecular mechanisms that mediate basic mechanisms of cognition, we need high-volume, high-through-put psychophysical screening methods that quantify physiologically meaningful properties of cognitive mechanisms. A psychophysically measurable, physiological meaningful quantitative property of a mechanism is a property that can be measured by behavioral means and also by electrophysiological or biochemical means. Examples are the absorption spectrum of rhodopsin, the free-running period of the circadian clock, and the refractory period of reward axons in the medial forebrain bundle1,2. Psychophysical measurements that can be compared to cellular and molecular measurements lay a foundation for linking cellular and molecular mechanisms to psychological mechanisms through quantitative correspondence. For example, the fact that the in situ absorption spectrum of the rhodopsin in the outer segments of rods superimposes on the human scotopic spectral sensitivity function is strong evidence that the photon-triggered isomerization of rhodopsin is the first step in scotopic vision. The quantitative aspects of complex behavior patterns are also central to the use of QTL methods in behavioral genetics3,4.
The performance of mice (and rats) on well-established instrumental and Pavlovian learning protocols depends on brain mechanisms that measure abstract quantities like time, number, duration, rate, probability, risk, and spatial location. For example, the speed of acquisition of Pavlovian conditioned responses depends on the ratio between the average interval between the reinforcing events (typically, food deliveries) and the average latency to reinforcement following the onset of the signal for impending reinforcement5-7. For a second example, the ratio of the average duration of the visits to two feeding hoppers in a matching protocol approximately equals the ratio of the rates of reinforcement at those two hoppers8-10.
The behavioral testing methods currently in wide use by neuroscientists interested in underlying mechanisms are, for the most part, low volume, low through-put, and labor intensive26. Moreover, they do not measure quantities that can be compared with quantities measured by electrophysiological and biochemical methods, as, for example, the behaviorally measured periods and phases of circadian oscillators may be compared to electrophysiological and biochemical measures of circadian period and phase. Current behavioral testing methods focus on categories of learning, such as spatial learning, temporal learning, or fear learning, rather than on underlying mechanisms. The widely used water maze test of spatial learning11-15 is an example of these shortcomings. Spatial learning is a category. Learning in that category depends on many mechanisms, one of which is the mechanism of dead reckoning16,17. Dead reckoning depends in turn on the odometer, the mechanism that measures distance run18. Similarly, temporal learning is a category. A circadian clock is among the mechanisms on which learning in that category depends, because an oscillator with an approximately 24&#160;hr period is required for animals to learn the time of day at which events occur17,19. The clock that enables food anticipation has yet to be discovered19.
A clock is a time-measuring mechanism. Endogenous oscillators with a wide range of periods allow the brain to locate events in time by recording the phases of those clocks16,17. The ability to record locations in time enables the measurement of durations, that is, distances between locations in time. Associative learning depends on the brain&#39;s measurements of durations5,6,20,21. Counters are number-measuring mechanisms. Number measuring enables probability estimation, because a probability is the proportion between the numerosity of a subset and the numerosity of the superset. Number measuring and duration measuring enable rate estimation, because a rate is the number of events divided by the duration of the interval over which that number was measured. Measurements of duration, number, rate, and probability enable behavioral adjustments to changing risks.22,23 Our method focuses on measuring the accuracy and precision of these foundational mechanisms. Accuracy is the extent to which the brain&#39;s measure corresponds to an objective measure. Precision is the variation or uncertainty in the brain&#39;s measure of a fixed objective value, for example, a fixed duration. Weber&#39;s Law is the oldest and most securely established result in psychophysics. It asserts that the precision of the brain&#39;s measure of a quantity is a fixed fraction of that quantity. The Weber Fraction, which is the statistician&#39;s coefficient of variation in a distribution (&#963;/&#956;), measures precision. The ratio of the psychophysical mean (e.g.&#160;mean judged duration) to the objective mean (mean objective duration) is the measure of accuracy.
The method presented here maximizes volume (number of animals being screened at any one time in a given amount of lab space) and throughput (amount of information obtained divided by the average duration of the screening of a single animal) while minimizing the amount of human labor required to make the measurements and maximizing the immediacy with which the results of the screening become known.
The data-analysis software architecture presented here automatically puts the raw data and all the summary results and statistics derived from the data together in a single data structure, with field headings that render intelligible the vast seas of numbers therein contained. The analytic software only operates on data in that structure, and always stores the results of its operations in fields within that same structure. This insures an intact trail from raw data to published summaries and graphs.
The software automatically writes into the structure the experiment-control programs that governed the fully automated testing, and it automatically indicates which raw data came from which program. Thus, it preserves an impeccable data trail, with no doubt as to which experimental conditions were in force for each animal at each point in the testing and no doubt about how the summary statistics were derived from the raw data. This method of data preservation greatly facilitates the development of standardized behavioral screening data bases, making it possible for other laboratories to further analyze these rich data sets.
This method minimizes the risk of loss of support for the firmware and software on which it depends. The testing apparatus is trivially modified from a long-established commercial source. The programming languages are the custom language provided by the hardware manufacturer, for protocol control, and, for data analysis and graphing, a purpose-built, noncommercial, open-source toolbox (TSsystem) written in a very widely supported commercial scientific programming, data analysis and graphing language. The toolbox contains high-level commands for extracting structural information and summary statistics from lengthy time-stamped event records. The protocol-implementing programs and the data-analyzing programs are open source and thoroughly documented.
The screening system is schematized in Figure 1. Ten cabinets, each containing 8 test environments may be set up in a 10 ft&#160;x 15 ft&#160;laboratory room, enabling 80 mice to be run at one time. Cables passing through a port in a party wall should connect the environments to the electronic/electrical interface cards and PCs in another room. The PCs run the protocol-control programs. One computer is required for every 2 cabinets (16 test environments). The PCs must be connected via a Local Area Network to a server running the data-analysis and graphing software.

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		<tr height="21">
			<td height="21" style="height:21px;width:213px;">SmartCtrl Connection Panel</td>
			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;">SG-716B (115)</td>
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			<td>smart card for each chamber</td>
			<td>8</td>
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			<td height="21" style="height:21px;width:213px;">Universal Cable</td>
			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;">SG-210CB (115)</td>
			<td>cable from smart card to control panel</td>
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			<td>28 volt power</td>
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			<td>test chamber</td>
			<td>8</td>
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			<td style="width:136px;">ENV-307W-FP (32)</td>
			<td>various-size panels for test chamber</td>
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			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;">ENV-307W-GF (31)</td>
			<td>test chamber floor grid</td>
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			<td style="width:127px;">Med Associates</td>
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			<td>hopper light</td>
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			<td height="21" style="height:21px;width:213px;">House Light</td>
			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;">ENV-315W (43)</td>
			<td>house light</td>
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		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">IR Controller</td>
			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;">ENV-253B (77)</td>
			<td>entry detector for tube between nest and test</td>
			<td>16</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">Fan</td>
			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;">ENV-025F28 (42)</td>
			<td>exhaust fan for each chamber</td>
			<td>8</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Polypropylene Nest Tub</td>
			<td></td>
			<td></td>
			<td>nest box</td>
			<td>8</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Acrylic Connection Tube</td>
			<td></td>
			<td></td>
			<td>connection between nest and test areas</td>
			<td>8</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">Steel Cabinet</td>
			<td></td>
			<td></td>
			<td>cabinet to hold test chambers (78&#34;H, 48&#34;W, 24&#34;D)</td>
			<td>1</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">Windows computer</td>
			<td style="width:127px;"> </td>
			<td style="width:136px;"> </td>
			<td>running MedPC experiment-control software</td>
			<td>1</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">Server</td>
			<td style="width:127px;"> </td>
			<td style="width:136px;"> </td>
			<td>running Matlab, linked to exper-control computer by LAN</td>
			<td>1</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;"> </td>
			<td style="width:127px;"> </td>
			<td style="width:136px;"> </td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">Software</td>
			<td style="width:127px;"> </td>
			<td style="width:136px;"> </td>
			<td></td>
			<td></td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">MedPC software</td>
			<td style="width:127px;">Med Associates</td>
			<td style="width:136px;"> </td>
			<td>proprietary process-control programming language</td>
			<td>1</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:213px;">Matlab w Statistics Toolbox</td>
			<td style="width:127px;">Matlab</td>
			<td style="width:136px;"> </td>
			<td>proprietary data analysis and graphing programing system</td>
			<td>1</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:213px;">TSsystem</td>
			<td></td>
			<td style="width:136px;">in Supplementary Material w updates from senior author</td>
			<td>Open-source Matlab Toolbox</td>
			<td>1</td>
		</tr>
		<tr height="189">
			<td height="189" style="height:189px;width:213px;">Note: This is the euipment needed for one cabinet, containing 8 test environments. Hardware must be replicated for each such cabinet. However one computer can control 2 cabinets (16 test environments)</td>
			<td style="width:127px;"> </td>
			<td style="width:136px;"> </td>
			<td></td>
			<td></td>
		</tr>
	</tbody>
</table>

automated, quantitative cognitive/behavioral screening of mice: for genetics, pharmacology, animal cognition and undergraduate instruction

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and pharmacological manipulations on basic mechanisms of cognition and learning in mice. A standard polypropylene mouse housing tub is connected through an acrylic tube to a standard commercial mouse test box. The test box has 3 hoppers, 2 of which are connected to pellet feeders. All are internally illuminable with an LED and monitored for head entries by infrared (IR) beams. Mice live in the environment, which eliminates handling during screening. They obtain their food during two or more daily feeding periods by performing in operant (instrumental) and Pavlovian (classical) protocols, for which we have written protocol-control software and quasi-real-time data analysis and graphing software. The data analysis and graphing routines are written in a MATLAB-based language created to simplify greatly the analysis of large time-stamped behavioral and physiological event records and to preserve a full data trail from raw data through all intermediate analyses to the published graphs and statistics within a single data structure. The data-analysis code harvests the data several times a day and subjects it to statistical and graphical analyses, which are automatically stored in the &#34;cloud&#34; and on in-lab computers. Thus, the progress of individual mice is visualized and quantified daily. The data-analysis code talks to the protocol-control code, permitting the automated advance from protocol to protocol of individual subjects. The behavioral protocols implemented are matching, autoshaping, timed hopper-switching, risk assessment in timed hopper-switching, impulsivity measurement, and the circadian anticipation of food availability. Open-source protocol-control and data-analysis code makes the addition of new protocols simple. Eight test environments fit in a 48 in x 24 in x 78 in&#160;cabinet; two such cabinets (16 environments) may be controlled by one computer.

The system can and should be used to run protocols tailored to the aims of the individual investigator or classroom teacher. However, we have developed a suite of 3 protocols that should prove useful in large-scale screening of genetically manipulated mice and large-scale pharmacological testing: the matching protocol, the 2-hopper autoshaping protocol, and the switch protocol. The matching protocol measures the mouse&#39;s capacity to estimate incomes (food pellets per unit time) at two different locations, to remember ...

Watch this Scientific Journal Video about Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction at JoVE.com

Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Fully automated system for measuring physiologically meaningful properties of the mechanisms mediating spatial localization, temporal localization, duration, rate&#160;and probability estimation, risk assessment, impulsivity, and the accuracy and precision of memory, in order to assess the effects of genetic and pharmacological manipulations on foundational mechanisms of cognition in mice.

We describe a high-throughput, high-volume, fully automated, live-in 24/7 behavioral testing system for assessing the effects of genetic and ...

automated-quantitative-cognitivebehavioral-screening-mice-for

Research

JoVE Journal

Behavior

14.2K Views.  Rutgers University. Fully automated system for measuring physiologically meaningful properties of the mechanisms mediating spatial localization, temporal localization, duration, rate and probability estimation, risk assessment, impulsivity, and the accuracy and precision of memory, in order to assess the effects of genetic and pharmacological manipulations on foundational mechanisms of cognition in mice.

Video: Automated, Quantitative Cognitive/Behavioral Screening of Mice: For Genetics, Pharmacology, Animal Cognition and Undergraduate Instruction

Modulating Cognition Using Transcranial Direct Current Stimulation of the Cerebellum

Numerous studies have emerged recently that demonstrate the possibility of modulating, and in some cases enhancing, cognitive processes by exciting brain regions involved in working memory and attention using transcranial electrical brain stimulation. Some researchers now believe the cerebellum supports cognition, possibly via a remote neuromodulatory effect on the prefrontal cortex. This paper describes a procedure for investigating a role for the cerebellum in cognition using transcranial direct current stimulation (tDCS), and a selection of information-processing tasks of varying task difficulty, which have previously been shown to involve working memory, attention and cerebellar functioning. One task is called the Paced Auditory Serial Addition Task (PASAT) and the other a novel variant of this task called the Paced Auditory Serial Subtraction Task (PASST). A verb generation task and its two controls (noun and verb reading) were also investigated. All five tasks were performed by three separate groups of participants, before and after the modulation of cortico-cerebellar connectivity using anodal, cathodal or sham tDCS over the right cerebellar cortex. The procedure demonstrates how performance (accuracy, verbal response latency and variability) could be selectively improved after cathodal stimulation, but only during tasks that the participants rated as difficult, and not easy. Performance was unchanged by anodal or sham stimulation. These findings demonstrate a role for the cerebellum in cognition, whereby activity in the left prefrontal cortex is likely dis-inhibited by cathodal tDCS over the right cerebellar cortex. Transcranial brain stimulation is growing in popularity in various labs and clinics. However, the after-effects of tDCS are inconsistent between individuals and not always polarity-specific, and may even be task- or load-specific, all of which requires further study. Future efforts might also be guided towards neuro-enhancement in cerebellar patients presenting with cognitive impairment once a better understanding of brain stimulation mechanisms has emerged.

Transcranial direct current stimulation (tDCS) over the cerebellum exerts a remote effect on the prefrontal cortex, which can modulate cognition and performance. This was demonstrated using two information-processing tasks of varying complexity, whereby only cathodal tDCS improved performance when the task was difficult, but not easy.

Numerous studies have emerged recently that demonstrate the possibility of modulating, and in some cases enhancing, cognitive processes by exciting brain ...

The Modified Hole Board - Measuring Behavior, Cognition and Social Interaction in Mice and Rats

This protocol describes the modified hole board (mHB), which combines features from a traditional hole board and open field and is designed to measure multiple dimensions of unconditioned behavior in small laboratory mammals (e.g., mice, rats, tree shrews and small primates). This paradigm is a valuable alternative for the use of a behavioral test battery, since a broad behavioral spectrum of an animal&#8217;s behavioral profile can be investigated in one single test.
The apparatus consists of a box, representing the &#8216;protected&#8217; area, separated from a group compartment. A board, on which small cylinders are staggered in three lines, is placed in the center of the box, representing the &#8216;unprotected&#8217; area of the set-up. The cognitive abilities of the animals can be measured by baiting some cylinders on the board and measuring the working and reference memory. Other unconditioned behavior, such as activity-related-, anxiety-related- and social behavior, can be observed using this paradigm. Behavioral flexibility and the ability to habituate to a novel environment can additionally be observed by subjecting the animals to multiple trials in the mHB, revealing insight into the animals&#8217; adaptive capacities.
Due to testing order effects in a behavioral test battery, na&#239;ve animals should be used for each individual experiment. By testing multiple behavioral dimensions in a single paradigm and thereby circumventing this issue, the number of experimental animals used is reduced. Furthermore, by avoiding social isolation during testing and without the need to food deprive the animals, the mHB represents a behavioral test system, inducing if any, very low amount of stress.

This protocol describes the modified hole board, which is a behavioral test set-up that comprises the characteristics of an open field and a traditional hole board. This set-up enables the differential analysis of unconditioned behavior of small laboratory mammals as well as the analysis of cognitive abilities.

This protocol describes the modified hole board (mHB), which combines features from a traditional hole board and open field and is designed to measure ...

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device (ALDM) Test Systems

Fagot &#38; Paleressompoulle1 and Fagot &#38; Bonte2 have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys maintained in semi-free ranging conditions. Data accumulated during the last five years have consistently demonstrated the efficiency of this protocol to investigate individual/physical cognition in monkeys, and have further shown that this procedure reduces stress level during animal testing3. This paper demonstrates that networks of ALDM can also be used to investigate different facets of social cognition and in-group expressed behaviors in monkeys, and describes three illustrative protocols developed for that purpose. The first study demonstrates how ethological assessments of social behavior and computerized assessments of cognitive performance could be integrated to investigate the effects of socially exhibited moods on the cognitive performance of individuals. The second study shows that batteries of ALDM running in parallel can provide unique information on the influence of the presence of others on task performance. Finally, the last study shows that networks of ALDM test units can also be used to study issues related to social transmission and cultural evolution. Combined together, these three studies demonstrate clearly that ALDM testing is a highly promising experimental tool for bridging the gap in the animal literature between research on individual cognition and research on social cognition.

Assessment of Social Cognition in Non-human Primates Using a Network of Computerized Automated Learning Device ALDM Test Systems

Fagot &#38; Paleressompoulle1 have published an automated learning device (ALDM) aimed at testing individual cognitive abilities in semi-free ranging monkeys. The main goal of our protocol is to use a network of ALDM test units to study social cognition in non-human primates.

Fagot &#38; Paleressompoulle1 and Fagot &#38; Bonte2 have published an automated learning device (ALDM) for the study of cognitive abilities of monkeys ...

A Protocol for Housing Mice in an Enriched Environment

Environmental enrichment (EE) is a housing environment for mice that boosts mental and physical health compared to standard laboratory housing. Our recent studies demonstrate that environmental enrichment decreases adiposity, increases energy expenditure, resists diet induced obesity, and causes cancer remission and inhibition in mice. EE typically consists of larger living space, a variety of &#8216;toys&#8217; to interact with, running wheels, and can include a number of other novel environmental changes. All of this fosters a more complex social engagement, cognitive and physical stimulations. Importantly, the toy location and type of toy is changed regularly, which encourages the mice to adapt to a frequently changing and novel environment. Many variables can be manipulated in EE to promote health effects in mice. Thus these approaches are difficult to control and must be properly managed to successfully replicate the associated phenotypes. Therefore, the goal of this video is to demonstrate how EE is properly set up and maintained to assure a complex, challenging, and controlled environment so that other researchers can easily reproduce the protective effects of EE against obesity and cancer.

Environmental enrichment for mice requires a complex and challenging setup, as well as comprehensive husbandry and handling techniques to assure robust metabolic and anti-cancer effects in the mice. This protocol provides detailed procedures to reproduce the above mentioned effects in mice.

Environmental enrichment (EE) is a housing environment for mice that boosts mental and physical health compared to standard laboratory housing. Our recent ...

Rodent Brain Microinjection to Study Molecular Substrates of Motivated Behavior

Brain microinjection can aid elucidation of the molecular substrates of complex behaviors, such as motivation. For this purpose rodents can serve as appropriate models, partly because the response to behaviorally relevant stimuli and the circuitry parsing stimulus-action outcomes is astonishingly similar between humans and rodents. In studying molecular substrates of complex behaviors, the microinjection of reagents that modify, augment, or silence specific systems is an invaluable technique. However, it is crucial that the microinjection site is precisely targeted in order to aid interpretation of the results. We present a method for the manufacture of surgical implements and microinjection needles that enables accurate microinjection and unlimited customizability with minimal cost. Importantly, this technique can be successfully completed in awake rodents if conducted in conjunction with other JoVE articles that covered requisite surgical procedures. Additionally, there are many behavioral paradigms that are well suited for measuring motivation. The progressive ratio is a commonly used method that quantifies the efficacy of a reinforcer to maintain responding despite an (often exponentially) increasing work requirement. This assay is sensitive to reinforcer magnitude and pharmacological manipulations, which allows reinforcing efficacy and/ or motivation to be determined. We also present a straightforward approach to program operant software to accommodate a progressive ratio reinforcement schedule.

Rodents are an appropriate model to investigate the molecular substrates of behavior and complex psychiatric disorders. Brain microinjection in awake rodents can be used to elucidate disease substrates. An efficient and customizable brain microinjection method as well as the execution of an operant paradigm that quantifies motivation is presented.

Brain microinjection can aid elucidation of the molecular substrates of complex behaviors, such as motivation. For this purpose rodents can serve as ...

Introducing Clicker Training as a Cognitive Enrichment for Laboratory Mice

Establishing new refinement strategies in laboratory animal science is a central goal in fulfilling the requirements of Directive 2010/63/EU. Previous research determined a profound impact of gentle handling protocols on the well-being of laboratory mice. By introducing clicker training to the keeping of mice, not only do we promote the amicable treatment of mice, but we also enable them to experience cognitive enrichment. Clicker training is a form of positive reinforcement training using a conditioned secondary reinforcer, the "click" sound of a clicker, which serves as a time bridge between the strengthened behavior and an upcoming reward. The effective implementation of the clicker training protocol with a cohort of 12 BALB/c inbred mice of each sex proved to be uncomplicated. The mice learned rather quickly when challenged with tasks of the clicker training protocol, and almost all trained mice overcame the challenges they were given (100% of female mice and 83% of male mice). This study has identified that clicker training for mice strongly correlates with reduced fear in the mice during human-mice interactions, as shown by reduced anxiety-related behaviors (e.g., defecation, vocalization, and urination) and fewer depression-like behaviors (e.g., floating). By developing a reliable protocol that can be easily integrated into the daily routine of the keeping of laboratory mice, the lifetime experience of welfare in the mice can be improved substantially.

The development of new refinement strategies for laboratory mice is a challenging task that contributes towards fulfilling the 3R principle. This protocol introduces clicker training as a cognitive enrichment program for laboratory mice.

Establishing new refinement strategies in laboratory animal science is a central goal in fulfilling the requirements of Directive 2010/63/EU. Previous ...

Battery of Behavioral Tests Assessing General Locomotion, Muscular Strength, and Coordination in Mice

Behavioral testing is used in pre-clinical trials to assess the phenotypic effects and outcomes that a particular disease or treatment has on the animal&#39;s wellbeing and health. There are numerous behavioral tests that may be applied. We selected a test for general locomotion, the open field test (OFT); a test for muscular strength, the mesh test (MT); and a test for coordination, the rotarod test (RR). Testing can be accomplished on a weekly or monthly basis. As a test for general locomotion, the OFT works by objectively monitoring movement parameters while the mouse is in an open field apparatus. The field is generally a 2&#39; x 2&#39; box, and the movements are recorded through laser sensing or through video capture. The mouse is placed in the center of the open field and allowed to move freely for the test. The MT uses the latency for a mouse to fall off an inverted screen as a measure of muscular strength. A mouse is placed on a screen, which is inverted over a clear box, and is timed for their latency to fall. Three trials are performed, with the best of the three trials scored for that day. A score of 60 s is the maximum time a mouse is left inverted. Mice are given a 5-min rest period between mesh test trials. Lastly, an accelerated protocol on the RR assesses motor coordination and endurance. During a trial, a mouse walks on a rotating rod as it increases in speed from 4 rpm to 40 rpm over 5 min. The trial ends when the mouse touches the magnetized pressure sensor upon falling. Each mouse undergoes three trials, and the best trial is scored for that day. This combined behavioral data allows for the global assessment of mobility, coordination, strength, and movement of the test animals. At least two out of the three behavioral testing measures must show improvement for an animal to qualify as having overall improved motor function.

Behavioral testing is used in pre-clinical trials to assess the phenotypic effects of a disease or treatment on an animal's wellbeing. In order to globally assess motor functioning, we selected tests for general locomotion, muscular strength, and coordination: the open field test, the mesh test, and the rotarod test, respectively.

Behavioral testing is used in pre-clinical trials to assess the phenotypic effects and outcomes that a particular disease or treatment has on the ...

Systematic Assessment of Well-Being in Mice for Procedures Using General Anesthesia

In keeping with the 3R Principle (Replacement, Reduction, Refinement) developed by Russel and Burch, scientific research should use alternatives to animal experimentation whenever possible. When there is no alternative to animal experimentation, the total number of laboratory animals used should be the minimum needed to obtain valuable data. Moreover, appropriate refinement measures should be applied to minimize pain, suffering, and distress accompanying the experimental procedure. The categories used to classify the degree of pain, suffering, and distress are non-recovery, mild, moderate, or severe (EU Directive 2010/63). To determine which categories apply in individual cases, it is crucial to use scientifically sound tools.
The well-being-assessment protocol presented here is designed for procedures during which general anesthesia is used. The protocol focuses on home cage activity, the Mouse Grimace Scale, and luxury behaviors such as burrowing and nest building behavior as indicators of well-being. It also uses the free exploratory paradigm for trait anxiety-related behavior. Fecal corticosterone metabolites as indicators of acute stress are measured over the 24-h post-anesthetic period.
The protocol provides scientifically solid information on the well-being of mice following general anesthesia. Due to its simplicity, the protocol can easily be adapted and integrated in a planned study. Although it does not provide a scale to classify distress in categories according to the EU Directive 2010/63, it can help researchers estimate the degree of severity of a procedure using scientifically sound data. It provides a way to improve the assessment of well-being in a scientific, animal-centered manner.

We developed a protocol to assess well-being in mice during procedures using general anesthesia. A series of behavioral parameters indicating levels of well-being as well as glucocorticoid metabolites were analyzed. The protocol can serve as a general aid to estimate the degree of severity in a scientific, animal-centered manner.

In keeping with the 3R Principle (Replacement, Reduction, Refinement) developed by Russel and Burch, scientific research should use alternatives to animal ...

An Automated T-maze Based Apparatus and Protocol for Analyzing Delay- and Effort-based Decision Making in  Free Moving Rodents

Many neurological and psychiatric patients demonstrate difficulties and/or deficits in decision making. Rodent models are helpful to produce a deeper understanding of the neurobiological causes underlying the decision-making problems. A cost-benefit based T-maze task is used for measuring decision making in which rodents choose between a high reward arm (HRA) and a low reward arm (LRA). There are two paradigms of the T-maze decision-making task, one in which the cost is a time delay and the other in which it is physical effort. Both paradigms require a tedious and labor-intensive management of experimental animals, multiple doors, pellet reward, and arm choice recordings. In the current work, we invented an apparatus based on traditional T-maze with full automation for pellet delivery, door management and choice recordings. This automated setup can be used for the evaluation of both delay- and effort-based decision making in rodents. With the protocol described here, our lab investigated the decision-making phenotypes of multiple genetically modified mice. In the representative data, we showed that the mice with ablated medial habenular showed aversions of both delay and effort and tended to choose the immediate and effortless reward. This protocol helps to decrease the variability caused by experimenter intervention and to enhance experiment efficiency. In addition, chronic silicon probe or microelectrode recording, fiber-optic imaging and/or manipulation of neural activity can be easily applied during the decision-making task using the setup described here.

This article introduces an automated T-maze apparatus that we invented, and a protocol based on this apparatus for analyzing delay-based decision making and effort-based decision making in free moving rodents.

Many neurological and psychiatric patients demonstrate difficulties and/or deficits in decision making. Rodent models are helpful to produce a deeper ...

Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer's Disease, Using IntelliCage

Multiple factors&#8212;such as aging and genes&#8212;are frequently associated with cognitive decline. Genetically modified mouse models of cognitive decline, such as Alzheimer&#39;s disease (AD), have become a promising tool to elucidate the underlying mechanisms and promote the therapeutic advances. An important step is the validation and characterization of expected behavioral abnormality in the models, in the case of AD, cognitive decline. The long-term behavioral investigations of laboratory animals to study the effect of aging demand substantial efforts from researchers. The IntelliCage system is a high-throughput and cost-effective test battery for mice that eliminates the need for daily human handling. Here, we describe how the system is utilized in the long-term phenotyping of a genetic Alzheimer&#39;s disease model, specifically focusing on the cognitive functions. The experiment employs repeated battery of tests that assess spatial learning and executive functions. This cost-effective age-dependent phenotyping allows us to identify the transient and/or permanent effects of genes on various cognitive aspects.

Automated, Long-term Behavioral Assay for Cognitive Functions in Multiple Genetic Models of Alzheimer&#039;s Disease, Using IntelliCage

This paper describes a protocol for cognitive assessments for genetic models of the Alzheimer&#39;s disease using the IntelliCage system, which is a high throughput automated behavioral monitoring system with operant conditioning.

Multiple factors&#8212;such as aging and genes&#8212;are frequently associated with cognitive decline. Genetically modified mouse models of cognitive ...