Some of the data shown here were obtained in the laboratory of Dr. Jacqueline N. Crawley in the U.S. National Institute of Mental Health and we would like to thank her for allowing us to show the data in the paper. We also thank Kazuo Nakanishi for his help in developing ImageFZ program for behavioral analysis. This research was supported by Grant-in-Aid for Scientific Research (B) (21300121), Grant-in-Aid for Scientific Research on Innovative Areas (Comprehensive Brain Science Network) from the Ministry of Education, Science, Sports and Culture of Japan, grant from Neuroinformatics Japan Center (NIJC), and grants from CREST of Japan Science and Technology Agency (JST).

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We confirm that there are no known conflicts of interest associated with this publication and there has been no significant financial support for this work that could have influenced its outcome.

The contextual and cued fear conditioning test is one of the most widely used paradigms to assess learning and memory. This test is a form of Pavlovian conditioning in which an association is made between a context and/or a conditioned stimulus (auditory cue) and an aversive stimulus (electric footshock). After even a single pairing of the context/auditory cue and footshock, mice exhibit long-lasting freezing when faced with either the context or the cue. In this test, freezing behavior is used as an index of fear memory. Pharmacological and lesion studies have revealed that memory formation, consolidation, and retrieval are regulated by several brain regions, such as the amygdala, hippocampus, and prefrontal cortex3,33-35. In addition, molecular genetics studies have demonstrated the role of specific genes and molecules involved in learning and memory in these brain regions using genetically engineered mice36. Therefore, this test is simple and useful for exploring the neurobiological basis underlying fear learning and memory. In this movie article, we introduced our protocol to provide experimenters with detailed information to understand and easily perform the test.
Freezing behavior was quantified through direct observation by human experimenters. A well-trained experimenter is expected to produce reliable, stable results across observations. However, this method involves potential problems, such as differences in the observational method, observer biases, and simple quantification mistakes, making it difficult to directly compare the results from independent experimenters and different laboratories. An automated photobeam-based computer measurement system has also been used26,30-32. However, this system also presents potential problems in measuring freezing behaviors. Because of the sensor arrangement, this system might be unable to detect small head movements that would typically be scored as &#8216;active&#8217; through human observation. In addition, trembling during freezing might be considered as nonfreezing because when an animal freezes, intermittent interruptions in the photobeam are observed as a consequence of trembling. As an alternative method, automated image- and video-analyzing systems have been developed17-20,37,38. Anagnostaras et al.37&#160;described a few systems with image analysis software programs that have good validity and score freezing well17,20,37-38. However, most of these systems and analysis programs have to be obtained from commercial suppliers and are typically costly. We developed the ImageFZ software program for the analysis of freezing behavior, and this program is distributed as a free software program. ImageFZ detects the mouse as a body of pixels (a particle) and discriminates subtle mouse movement as &#8216;freezing&#8217; or &#8216;non-freezing&#8217; depending on the amount of area of nonoverlapping regions between particles of each pair of consecutive images. As shown in the representative results, measurements using the ImageFZ program are consistent with or more accurate than obtained using other methods. Thus, the ImageFZ program automatically measures the behavior that human observers judge as freezing using defined criteria. In addition, the ImageFZ program calculates the distance traveled (cm) before, during, and after footshock exposure, facilitating an assessment of the shock sensitivity and analysis of the freezing behavior.
Methodological differences exist between laboratories. These differences may result in difficulty in comparing data among laboratories and in replicating results in different laboratories. To obtain more stable and comparable data, it is necessary to standardize the test protocol as much as possible. The analysis system with ImageFZ leads to the automation of test procedures, which can contribute to the standardization of protocols used across laboratories.
Several behavioral responses must be considered when analyzing freezing behavior. First, when animals face a fearful situation, they may flee instead of freezing39. Fleeing is one of the fear responses, and its occurrence will lead to underestimating fear memory. Second, freezing may depend on a general activity level, and the activity level in experimental and control mice needs to be examined. For example, although mice lacking the M1 muscarinic acetylcholine receptor showed reduced levels of freezing compared to wild-type mice, various behavioral tests indicated that the results may be attributed to their hyperactivity phenotype instead of their memory impairment18. ImageFZ calculates the distance (cm) traveled by the subjects. The data are available to examine whether or not differences exist in the general activity levels between subjects. If there is a group difference in the distance traveled, one possible approach to the problem is to consider the distance traveled during the first 2 min of training as the baseline activity and to use a suppression ratio (suppression ratio = (activity during testing)/(activity during baseline + activity during testing)) as a secondary index of fear17,40. Finally, a difference in pain sensitivity, inducing the changes in reactivity to an electric footshock, if any, may result in variations in freezing behavior. ImageFZ also calculates the distance traveled (cm) in detail from 2 sec before an exposure of a 2&#160;sec footshock to 2 sec after its exposure (for 6 sec), which can be used as an index of footshock sensitivity.
Video-analyzing systems have been developed to measure the freezing behavior of albino, black, agouti, and dilute brown mice. ImageFZ uses a black floor tray and black grids to examine white mice (see Figure 1B). The black grids are made of specially processed metals with coated black paint and have an electrical conductivity similar to that of the noncoated metal grids, which are typically used for black mice. ImageFZ also analyzes the freezing behavior in rats and other rodents through adjustments of the program parameters. In the current version of ImageFZ, the behavior of the subject is recorded using a video camera from the top wall to analyze freezing. ImageFZ could also be used in a set-up where the images are captured from the side of the chamber. In addition, the ImageFZ controls a maximum of 4 apparatuses. This feature allows the researcher to simultaneously examine 4 mice, saving time and reducing the potential influences from differences in the execution time of each subject and the testing order on behavior. Thus, ImageFZ simplifies the testing procedure and analysis of freezing behavior, and this program facilitates testing with less labor and without any training for the behavioral experiments.
In the Miyakawa lab, we have assessed more than 110 strains of genetically engineered mice and wild-type control mice in the contextual and cued fear conditioning test using the video analyzing system to elucidate the effects of a given gene on learning and memory41-42. We have obtained a large set of raw data for more than 5,000 mice. The raw data that was used for published research articles4-16 are included in the &#39;Mouse Phenotype Database&#39; as a public database (URL: http://www.mouse-phenotype.org/). The present movie article provides detailed information regarding the details of our experimental procedure and promotes the understanding of the testing situation.

The contextual and cued fear conditioning test is the behavioral paradigm used to assess associative fear learning and memory in rodents1-3. This test has been widely used to understand the neurobiological mechanisms of fear learning and memory in transgenic and knockout mice1,4-16. Freezing behavior, which is defined as complete immobility with the exception of breathing, is a common response to fearful situations. In this behavioral paradigm, after animals are exposed to a pairing of an auditory cue with an electric footshock, they respond to the fear-producing stimulus by displaying freezing behavior, which is measured as an index of associative fear learning and memory. This test requires less elaborate equipment, less physical exertion by the investigator, and much less training time for mice than other learning and memory tasks; it generally requires approximately 5-10 min/day per mouse for 2 days. Although the testing procedure is simple and requires little time to perform, the investigator must carefully observe and measure mouse behavior; therefore, several automated measurement systems have been developed to conduct the behavioral analysis17-20. Our video-analyzing system, which we developed with the ImageFZ software program, allows us to easily analyze freezing behavior and produce highly reliable results. This article provides detailed information on our testing procedure and describes how to use the ImageFZ software program.

<table border="0" cellpadding="0" cellspacing="0" width="701">
	<tbody>
		<tr>
			<td>&#160;ImageFZ&#160; program</td>
			<td>Developed by Tsuyoshi Miyakawa</td>
			<td></td>
			<td>&#160;This program is available through O&#39;Hara &#38; Co., Tokyo, Japan and for free download at http://www.mouse-phenotype.org/. This software runs on 32-bit Windows XP/Vista/7.&#160;</td>
		</tr>
		<tr>
			<td>Conditioning chamber</td>
			<td>O&#39;Hara &#38; co., Japan</td>
			<td>CL-3002L</td>
			<td>For mouse.</td>
		</tr>
		<tr>
			<td>Cued test chamber</td>
			<td>O&#39;Hara &#38; co., Japan</td>
			<td>CLT-3002L</td>
			<td>For mouse.</td>
		</tr>
		<tr>
			<td>Interface</td>
			<td>O&#39;Hara &#38; co., Japan</td>
			<td>CL-1040</td>
			<td>The interface includes a white noise/tone generator, which can be controlled by ImageFZ program.</td>
		</tr>
		<tr>
			<td>Scrambled shock generator</td>
			<td>O&#39;Hara &#38; co., Japan</td>
			<td>SGA-2040</td>
			<td>The shock generator can be controlled by ImageFZ program.</td>
		</tr>
		<tr>
			<td>Shock grid tester (ammeter)</td>
			<td>O&#39;Hara &#38; co., Japan</td>
			<td>SG-T</td>
			<td></td>
		</tr>
		<tr>
			<td>USB video capture device</td>
			<td>XLR8</td>
			<td>USB2IVOSX</td>
			<td></td>
		</tr>
		<tr>
			<td>Quad image splitter</td>
			<td>Wireless Tsukamoto Co., Ltd., Japan</td>
			<td>400AS</td>
			<td></td>
		</tr>
		<tr>
			<td>Soundproof room</td>
			<td>O&#39;Hara &#38; co., Japan</td>
			<td>CL-4210</td>
			<td></td>
		</tr>
		<tr>
			<td>Freeze Monitor</td>
			<td>San Diego Instruments, Inc., CA, USA</td>
			<td></td>
			<td>16 x 16 photbeam array&#160; ( 2.5 cm spacing)</td>
		</tr>
	</tbody>
</table>

contextual and cued fear conditioning test using a video analyzing system in mice

The contextual and cued fear conditioning test is one of the behavioral tests that assesses the ability of mice to learn and remember an association between environmental cues and aversive experiences. In this test, mice are placed into a conditioning chamber and are given parings of a conditioned stimulus (an auditory cue) and an aversive unconditioned stimulus (an electric footshock). After a delay time, the mice are exposed to the same conditioning chamber and a differently shaped chamber with presentation of the auditory cue. Freezing behavior during the test is measured as an index of fear memory. To analyze the behavior automatically, we have developed a video analyzing system using the ImageFZ application software program, which is available as a free download at http://www.mouse-phenotype.org/. Here, to show the details of our protocol, we demonstrate our procedure for the contextual and cued fear conditioning test in C57BL/6J mice using the ImageFZ system. In addition, we validated our protocol and the video analyzing system performance by comparing freezing time measured by the ImageFZ system or a photobeam-based computer measurement system with that scored by a human observer. As shown in our representative results, the data obtained by ImageFZ were similar to those analyzed by a human observer, indicating that the behavioral analysis using the ImageFZ system is highly reliable. The present movie article provides detailed information regarding the test procedures and will promote understanding of the experimental situation.

In the fear conditioning test, human experimenters used to quantify the freezing behavior through labor-intensive direct observation26-29, but recently photobeam-based computer measurement (e.g. the 'Freeze Monitor' system) and image-analyzing systems have been used to automatically measure the freezing behavior26,30-32. ImageFZ is an automated image-analyzing system, which produces results comparable to those obtained through human observation, as described below. Here, we compared the outcomes of human observation with those of ImageFZ analysis under varying parameters: 'Rate (frame/sec)' and 'Freezing criterion (pixels).' In this experiment, five male C57BL/6J mice (mean body weight &#177; SD (g), 31.4&#177;3.55; mean body size &#177; SD (pixels), 351.6&#177;62.2) were used at 15-27 weeks of age. The human observation was made using an event-recording program (a Macintosh OS9 software program); a key-pressing event that continued for 2 sec or more when a mouse displayed a bout of no movement was considered 'freezing'. The percentage of freezing was calculated every 60 sec in each test and used for correlation analyses. The percent of freezing scored by the 2 observers (interobserver reliability, for conditioning, r=0.879; for context test, r=0.957; for cued test, r=0.866, for all cases, r=0.888) was averaged to generate a human score. Correlations between the freezing percentages measured through ImageFZ with each frame rate (i.e. 1, 2, and 4 fps) and those obtained through human observations were examined. As illustrated in Figure 4, the freezing percentages calculated through ImageFZ (1, 2, and 4 fps) were highly correlated with the average value obtained from the measurements of the 2 observers. Notably, capturing images at a higher frame rate does not always produce the best correlation. Image analysis at 1 fps generated results similar to those obtained from human observers in each test. Correlations between the freezing percentages measured through human observations and using ImageFZ under each condition of the 'Freezing criterion (pixels)' (i.e. 20, 30, and 40 pixels) were examined. The freezing percentages calculated using ImageFZ at the 'Freezing criterion (pixels)' of 20, 30, and 40 pixels were, in all cases, highly correlated with those obtained through human observations (Figure 5). As shown in Figure 5D, when the freezing criterion is set to a low value, the subtle movement of a mouse, considered to be 'freezing' by human observers, would be considered 'non-freezing' using ImageFZ. Conversely, if the criterion is set to a high value, the movement of a mouse, scored as 'non-freezing' by human observers, would be considered 'freezing' using ImageFZ (Figures 5C, 5F, and 5I). Thus, to obtain the most reliable results, each parameter of the ImageFZ program should be calibrated using the data scored through human observations in each testing environment.
In addition, we compared the results generated by a human observer, using a photobeam-based computer measurement system (the Freeze Monitor system), to those obtained using ImageFZ (see Figure 6). The human observer was blinded to the treatment group and the results of ImageFZ scoring. For the parameter settings of the Freeze Monitor system, we used 3 measures of the percentage of freezing from a previously validated system30. Briefly, the number of 10-sec intervals in which the animals required more than 1 or 2 sec to cross the first new beam of the interval (1sec 10sec and 2sec 10sec, respectively) and the latency between the beginning of each 5 sec interval and the third new beam interruption within this interval (Latency3) were measured. The percentages of the intervals during which the mouse was freezing or the percentage of the total amount of time required to break the third photobeam were calculated.
The percentages of freezing measured in each system are illustrated in Figure 6. The groups were compared using two-way repeated measures ANOVA followed by t-tests (see Table 1). The freezing percentages measured using ImageFZ (Figure 6B) were more similar to those scored through human observation (Figure 6A) than the data obtained using a photobeam-based system (Figures 6C-E). The freezing percentages measured using the ImageFZ program in each test were highly correlated with those scored through human observation (conditioning, r=0.947; context test, r=0.970; cued test, r=0.934), whereas the correlations between the freezing percentages measured using the photobeam-based computer measurement system (1sec 10sec, 2sec 10sec, or Latency3) and the human observer were lower (conditioning, r=0.503, 0.593, and 0.761; context test, r=0.772, 0.819, and 0.912) compared to the correlations between the freezing percentages measured using ImageFZ and human observation (Figures 7A and 7B). In addition, Figure 7 reveals that the differences between the freezing percentages obtained through human observation and using ImageFZ in each mouse were the smallest differences. These results indicated that the freezing percentages measured using ImageFZ were similar to those obtained through human observation and that ImageFZ is highly accurate when measuring the amount of freezing.
<img alt="Figure 1" fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig1highres.jpg" src="/files/ftp_upload/50871/50871fig1.jpg" /> 
Figure 1. Apparatuses for the contextual and cued fear conditioning test. (A) An acrylic square chamber for the conditioning and context test, (B) metal grids on a white plastic floor for black, agouti, or dilute brown mice (top) and electrifiable black metal grids on a black plastic floor for white mice (bottom); enlarged images of the grids are shown in the right panel, (C) a white noise/tone generator and a shock generator, (D) a soundproof room, and (E) an acrylic triangular chamber with a flat floor for the cued test. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig1highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 2" fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig2highres.jpg" src="/files/ftp_upload/50871/50871fig2.jpg" /> 
Figure 2. Schematic representation of the protocol. (A) Overview of the contextual and cued fear conditioning test, (B) conditioning, (C) context test, and (D) cued test. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig2highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 3" fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig3highres.jpg" src="/files/ftp_upload/50871/50871fig3.jpg" /> 
Figure 3. Image analysis by the ImageFZ software program. For each pair of successive images, the amount of area (pixels) through which the mouse moved is calculated by ImageFZ. When this area is below a certain threshold (e.g. 30 pixels), the behavior is judged to be 'freezing'. When the amount of area equals or exceeds the threshold, the behavior is considered to be 'non-freezing'. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig3highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 4" fo:content-width="6in" src="/files/ftp_upload/50871/50871fig4highres.jpg" width="500" /> 
Figure 4. Comparisons of the freezing percentages calculated from images at different frame rates using ImageFZ with those measured through human observation. The fear conditioning tests were conducted using male C57BL/6J mice (n=5). During the tests, two observers scored the freezing behavior. Simultaneously, live images were captured at 4 fps using the ImageFZ program. The files captured at 4 fps were downsized after extracting the frames to correspond to images captured at 1 fps or 2 fps . The parameter values of 'Rate (frame/sec)' were set to 1, 2, or 4 fps , and freezing percentages in each 60-sec bin were calculated from image files using ImageFZ offline analysis. Each dot represents a freezing percentage of each 60-sec bin. Pearson's correlation coefficients between the data obtained from human observation and ImageFZ analysis were calculated. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig4highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 5" fo:content-width="6in" src="/files/ftp_upload/50871/50871fig5highres.jpg" width="500" /> 
Figure 5. The freezing percentages calculated from the images at different freezing criterion values using ImageFZ and those measured through human observations were compared. The fear conditioning tests were conducted using male C57BL/6J mice (n=5). During the tests, two observers recorded the freezing behavior, and the live images were captured using the ImageFZ program. The freezing percentages in each 60 sec bin were calculated from the images (1 frame/sec) through ImageFZ offline analysis, setting the parameter values of 'Freezing criterion (pixels)' to 20, 30, or 40 pixels. Each dot represents a freezing percentage of each 60-sec bin. Pearson's correlation coefficients between the data obtained from human observation and the ImageFZ analysis were calculated in each test. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig5highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 6" fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig6highres.jpg" src="/files/ftp_upload/50871/50871fig6.jpg" /> 
Figure 6. The percentages of freezing were measured using automated systems and human observation in unconditioned and conditioned groups of male C57BL/6J mice (n=5, each group). (A) Human observation, (B) ImageFZ, (C) Freeze Monitor system 1 (1sec 10sec), (D) Freeze Monitor system 2 (2sec 10sec), and (E) Freeze Monitor system 3 (Latency3). Group comparisons were performed using two-way repeated measures ANOVA followed by t-tests (unconditioned group vs. conditioned group, *, P&#60;0.05; &#8224;, p&#60;0.01). The data obtained using ImageFZ were similar to those scored through human observation. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig6highres.jpg" target="_blank">Click here to view larger image.</a>
<img alt="Figure 7" fo:content-width="4.3in" src="/files/ftp_upload/50871/50871fig7highres.jpg" width="420" /> 
Figure 7. Correlation and frequency distribution of the differences between the freezing percentages, measured using automated systems and human observation. (A-B) Scatter plots and Pearson's correlation coefficients between freezing percentages scored through automated systems and human observation are shown. The freezing percentages, calculated using ImageFZ, were highly correlated with those obtained through human observation. (C-F) Occurrences of less than a 10% difference between the freezing percentages obtained from automated systems vs. human observation were highest when the data analyzed using ImageFZ were compared with those analyzed through human observation. <a href="https://www.jove.com/files/ftp_upload/50871/50871fig7highres.jpg" target="_blank">Click here to view larger image.</a>
<table border="0" cellpadding="0" cellspacing="0">
	<tbody>
		<tr>
			<td></td>
			<td>ANOVAs</td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td></td>
			<td>Condition</td>
			<td>Time</td>
			<td>Condition x Time</td>
		</tr>
		<tr>
			<td>Day 1 (conditioning)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Human</td>
			<td>F(1,8)=28.53, p=0.0007</td>
			<td>F(7,56)=20.79, p&#60;0.0001</td>
			<td>F(7,56)=16.58, p&#60;0.0001</td>
		</tr>
		<tr>
			<td>ImageFZ</td>
			<td>F(1,8)=13.97, p=0.0057</td>
			<td>F(7,56)=21.40, p&#60;0.0001</td>
			<td>F(7,56)=11.69, p&#60;0.0001</td>
		</tr>
		<tr>
			<td>Freeze Monitor (1sec10sec)</td>
			<td>F(1,8)=5.16, p=0.0528</td>
			<td>F(7,56)=2.39, p=0.0329</td>
			<td>F(7,56)=0.72, p=0.6572</td>
		</tr>
		<tr>
			<td>Freeze Monitor (2sec10sec)</td>
			<td>F(1,8)=4.07, p=0.0782</td>
			<td>F(7,56)=3.44, p=0.0039</td>
			<td>F(7,56)=1.52, p=0.1803</td>
		</tr>
		<tr>
			<td>Freeze Monitor (Latency3)</td>
			<td>F(1,8)=4.44, p=0.0682</td>
			<td>F(7,56)=9.94, p&#60;0.0001</td>
			<td>F(7,56)=4.33, p=0.0007</td>
		</tr>
		<tr>
			<td>Day 2 (context)</td>
			<td></td>
			<td></td>
			<td></td>
		</tr>
		<tr>
			<td>Human</td>
			<td>F(1,8)=42.94, p=0.0002</td>
			<td>F(4,32)=1.91, p=0.1336</td>
			<td>F(4,32)=1.48, p=0.2302</td>
		</tr>
		<tr>
			<td>ImageFZ</td>
			<td>F(1,8)=49.61, p=0.0001</td>
			<td>F(4,32)=2.06, p=0.1087</td>
			<td>F(4,32)=0.83, p=0.5174</td>
		</tr>
		<tr>
			<td>Freeze Monitor (1sec10sec)</td>
			<td>F(1,8)=20.28, p=0.002</td>
			<td>F(4,32)=1.63, p=0.1918</td>
			<td>F(4,32)=0.55, p=0.6997</td>
		</tr>
		<tr>
			<td>Freeze Monitor (2sec10sec)</td>
			<td>F(1,8)=40.20, p=0.0002</td>
			<td>F(4,32)=2.66, p=0.0504</td>
			<td>F(4,32)=1.20, p=0.3306</td>
		</tr>
		<tr>
			<td>Freeze Monitor (Latency3)</td>
			<td>F(1,8)=35.30, p=0.0003</td>
			<td>F(4,32)=2.49, p=0.0626</td>
			<td>F(4,32)=1.09, p=0.3793</td>
		</tr>
	</tbody>
</table>
Table 1. Comparisons of statistics.

Watch this Scientific Journal Video about Contextual and Cued Fear Conditioning Test Using a Video Analyzing System in Mice at JoVE.com

Contextual and Cued Fear Conditioning Test Using a Video Analyzing System in Mice

This article presents a protocol for a contextual and cued fear conditioning test using a video analyzing system to assess fear learning and memory in mice.

The contextual and cued fear conditioning test is one of the behavioral tests that assesses the ability of mice to learn and remember an association ...

contextual-cued-fear-conditioning-test-using-video-analyzing-system

Research

JoVE Journal

Behavior

50.7K 조회수.  Fujita Health University.  이 문서에서는 마우스에서 학습 공포와 메모리를 평가하기 위해 비디오 분석 시스템을 사용하여 상황과 큐 공포 조건화 시험을위한 프로토콜을 제시한다. 