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).

<ol>
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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><tbody><tr><td>ImageFZ program</td><td>Developed by Tsuyoshi Miyakawa</td><td></td><td>This program is available through O&#039;Hara &amp;amp; Co., Tokyo, Japan and for free download at http://www.mouse-phenotype.org/. This software runs on 32-bit Windows XP/Vista/7.&amp;nbsp;</td></tr><tr><td>Conditioning chamber</td><td>O&amp;rsquo;Hara &amp;amp; Co., Japan</td><td>CL-3002L</td><td>For mouse.</td></tr><tr><td>Cued test chamber</td><td>O&amp;rsquo;Hara &amp;amp; Co., Japan</td><td>CLT-3002L</td><td>For mouse.</td></tr><tr><td>Interface</td><td>O&amp;rsquo;Hara &amp;amp; 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&amp;rsquo;Hara &amp;amp; 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&amp;rsquo;Hara &amp;amp; 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&amp;rsquo;Hara &amp;amp; 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&amp;nbsp; ( 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 ± SD (g), 31.4±3.55; mean body size ± SD (pixels), 351.6±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="Static equilibrium setup; diagrams show experiments with speaker lights, camera, shock generator in soundproof room; metal grids and walls for sensory isolation." fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig1highres.jpg" src="/files/ftp_upload/50871/50871fig1.jpg" data-altupdatedat="1747911167000" data-alt="Figure 1"> 
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="Contextual and cued fear conditioning diagram; conditioning timeline, CS, US stimuli, test phases." fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig2highres.jpg" src="/files/ftp_upload/50871/50871fig2.jpg" data-altupdatedat="1747911167000" data-alt="Figure 2"> 
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="Image processing workflow; binary conversion, XOR operation; freezing behavior detection diagram." fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig3highres.jpg" src="/files/ftp_upload/50871/50871fig3.jpg" data-altupdatedat="1747911167000" data-alt="Figure 3"> 
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="Graph comparing human observation and ImageFZ in conditioning, context, and cued tests, r-values." fo:content-width="6in" src="/files/ftp_upload/50871/50871fig4highres.jpg" width="500" data-altupdatedat="1747911167000" data-alt="Figure 4"> 
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="Graph chart showing correlation in varied contexts; points for conditioning, context, cued tests." fo:content-width="6in" src="/files/ftp_upload/50871/50871fig5highres.jpg" width="500" data-altupdatedat="1747911167000" data-alt="Figure 5"> 
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="Freezing behavior graph in conditioned vs. unconditioned rats; time course, behavioral experiment." fo:content-width="5in" fo:src="/files/ftp_upload/50871/50871fig6highres.jpg" src="/files/ftp_upload/50871/50871fig6.jpg" data-altupdatedat="1747911167000" data-alt="Figure 6"> 
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&lt;0.05; †, p&lt;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="Correlation and occurrence graphs; human observation vs. ImageFZ and Freeze Monitor data comparison." fo:content-width="4.3in" src="/files/ftp_upload/50871/50871fig7highres.jpg" width="420" data-altupdatedat="1747911167000" data-alt="Figure 7"> 
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&lt;0.0001</td>
			<td>F(7,56)=16.58, p&lt;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&lt;0.0001</td>
			<td>F(7,56)=11.69, p&lt;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&lt;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

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Behavior

51.3K Views.  Fujita Health University. 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.

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

Construction of Microdrive Arrays for Chronic Neural Recordings in Awake Behaving Mice

State-of-the-art electrophysiological recordings from the brains of freely behaving animals allow researchers to simultaneously examine local field potentials (LFPs) from populations of neurons and action potentials from individual cells, as the animal engages in experimentally relevant tasks. Chronically implanted microdrives allow for brain recordings to last over periods of several weeks. Miniaturized drives and lightweight components allow for these long-term recordings to occur in small mammals, such as mice. By using tetrodes, which consist of tightly braided bundles of four electrodes in which each wire has a diameter of 12.5 &mu;m, it is possible to isolate physiologically active neurons in superficial brain regions such as the cerebral cortex, dorsal hippocampus, and subiculum, as well as deeper regions such as the striatum and the amygdala. Moreover, this technique insures stable, high-fidelity neural recordings as the animal is challenged with a variety of behavioral tasks. This manuscript describes several techniques that have been optimized to record from the mouse brain. First, we show how to fabricate tetrodes, load them into driveable tubes, and gold-plate their tips in order to reduce their impedance from M&Omega; to K&Omega; range. Second, we show how to construct a custom microdrive assembly for carrying and moving the tetrodes vertically, with the use of inexpensive materials. Third, we show the steps for assembling a commercially available microdrive (Neuralynx VersaDrive) that is designed to carry independently movable tetrodes. Finally, we present representative results of local field potentials and single-unit signals obtained in the dorsal subiculum of mice. These techniques can be easily modified to accommodate different types of electrode arrays and recording schemes in the mouse brain.

The design and assembly of microdrives for in vivo electrophysiological recordings of brain signals from the mouse is described. By attaching microelectrode bundles to sturdy driveable carriers, these techniques allow for long-term and stable neural recordings. The lightweight design allows for unrestricted behavioral performance by the animal following drive implantation.

State-of-the-art electrophysiological recordings from the brains of freely behaving animals allow researchers to simultaneously examine local field ...

Trace Fear Conditioning in Mice

In this experiment we present a technique to measure learning and memory. In the trace fear conditioning protocol presented here there are five pairings between a neutral stimulus and an unconditioned stimulus. There is a 20 sec trace period that separates each conditioning trial. On the following day freezing is measured during presentation of the conditioned stimulus (CS) and trace period. On the third day there is an 8 min test to measure contextual memory. The representative results are from mice that were presented with the aversive unconditioned stimulus (shock) compared to mice that received the tone presentations without the unconditioned stimulus. Trace fear conditioning has been successfully used to detect subtle learning and memory deficits and enhancements in mice that are not found with other fear conditioning methods. This type of fear conditioning is believed to be dependent upon connections between the medial prefrontal cortex and the hippocampus. One current controversy is whether this method is believed to be amygdala-independent. Therefore, other fear conditioning testing is needed to examine amygdala-dependent learning and memory effects, such as through the delay fear conditioning.

In the following experiment we describe a protocol for trace fear conditioning in mice. This type of associative memory includes a trace period that separates the neutral stimulus and the unconditioned stimulus.

In this experiment we present a technique to measure learning and memory. In the trace fear conditioning protocol presented here there are five pairings ...

Using the Threat Probability Task to Assess Anxiety and Fear During Uncertain and Certain Threat

Fear of certain threat and anxiety about uncertain threat are distinct emotions with unique behavioral, cognitive-attentional, and neuroanatomical components. Both anxiety and fear can be studied in the laboratory by measuring the potentiation of the startle reflex. The startle reflex is a defensive reflex that is potentiated when an organism is threatened and the need for defense is high. The startle reflex is assessed via electromyography (EMG) in the orbicularis oculi muscle elicited by brief, intense, bursts of acoustic white noise (i.e., &#8220;startle probes&#8221;). Startle potentiation is calculated as the increase in startle response magnitude during presentation of sets of visual threat cues that signal delivery of mild electric shock relative to sets of matched cues that signal the absence of shock (no-threat cues). In the Threat Probability Task, fear is measured via startle potentiation to high probability (100% cue-contingent shock; certain) threat cues whereas anxiety is measured via startle potentiation to low probability (20% cue-contingent shock; uncertain) threat cues. Measurement of startle potentiation during the Threat Probability Task provides an objective and easily implemented alternative to assessment of negative affect via self-report or other methods (e.g., neuroimaging) that may be inappropriate or impractical for some researchers. Startle potentiation has been studied rigorously in both animals (e.g., rodents, non-human primates) and humans which facilitates animal-to-human translational research. Startle potentiation during certain and uncertain threat provides an objective measure of negative affective and distinct emotional states (fear, anxiety) to use in research on psychopathology, substance use/abuse and broadly in affective science. As such, it has been used extensively by clinical scientists interested in psychopathology etiology and by affective scientists interested in individual differences in emotion.

Potentiation of the startle reflex is measured via electromyography of the orbicularis oculi muscle during low (uncertain) and high (certain) probability electric shock threat in the Threat Probability Task. This provides an objective measure of distinct negative emotional states (fear/anxiety) for research on psychopathology, substance use/abuse, and broad affective science.

Fear of certain threat and anxiety about uncertain threat are distinct emotions with unique behavioral, cognitive-attentional, and neuroanatomical ...

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 ...

Fear Incubation Using an Extended Fear-Conditioning Protocol for Rats

Emotional memory has been primarily studied with fear-conditioning paradigms. Fear conditioning is a form of learning through which individuals learn the relationships between aversive events and otherwise neutral stimuli. The most-widely utilized procedures for studying emotional memories entail fear conditioning in rats. In these tasks, the unconditioned stimulus (US) is a footshock presented once or several times across single or several sessions, and the conditioned response (CR) is freezing. In a version of these procedures, called cued fear conditioning, a tone (conditioned stimulus, CS) is paired with footshocks (US) during the training phase. During the first test, animals are exposed to the same context in which training took place, and freezing responses are tested in the absence of footshocks and tones (i.e., a context test). During the second test, freezing is measured when the context is changed (e.g., by manipulating the smell and walls of the experimental chamber) and the tone is presented in the absence of footshocks (i.e., a cue test). Most cued fear conditioning procedures entail few tone-shock pairings (e.g., 1-3 trials in a single session). There is a growing interest in less common versions involving an extensive number of pairings (i.e., overtraining) related to the long-lasting effect called fear incubation (i.e., fear responses increase over time without further exposure to aversive events or conditioned stimuli). Extended fear-conditioning tasks have been key to the understanding of fear incubation&#8217;s behavioral and neurobiological aspects, including its relationship with other psychological phenomena (e.g., post-traumatic stress disorder). Here, we describe an extended fear-conditioning protocol that produces overtraining and fear incubation in rats. This protocol entails a single training session with 25 tone-shock pairings (i.e., overtraining) and a comparison of conditioned freezing responses during context and cue tests 48 h (short-term) and 6 weeks (long-term) after training.

We describe an extended fear-conditioning protocol that produces overtraining and fear incubation in rats. This protocol entails a single training session with 25 tone-shock pairings (i.e., overtraining) and a comparison of conditioned freezing responses during context and cue tests 48 h (short-term) and 6 weeks (long-term) after training.

Emotional memory has been primarily studied with fear-conditioning paradigms. Fear conditioning is a form of learning through which individuals learn the ...

A Novel Pavlovian Fear Conditioning Paradigm to Study Freezing and Flight Behavior

Fear- and anxiety-related behaviors significantly contribute to an organism&#8217;s survival. However, exaggerated defensive responses to perceived threat are characteristic of various anxiety disorders, which are the most prevalent form of mental illness in the United States. Discovering the neurobiological mechanisms responsible for defensive behaviors will aid in the development of novel therapeutic interventions. Pavlovian fear conditioning is a widely used laboratory paradigm to study fear-related learning and memory. A major limitation of traditional Pavlovian fear conditioning paradigms is that freezing is the only defensive behavior monitored. We recently developed a modified Pavlovian fear conditioning paradigm that allows us to study both conditioned freezing and flight (also known as escape) behavior within individual subjects. This model employs higher intensity footshocks and a greater number of pairings between the conditioned stimulus and unconditioned stimulus. Additionally, this conditioned flight paradigm utilizes serial presentation of pure tone and white noise auditory stimuli as the conditioned stimulus. Following conditioning in this paradigm, mice exhibit freezing behavior in response to the tone stimulus, and flight responses during the white noise. This conditioning model can be applied to the study of rapid and flexible transitions between behavioral responses necessary for survival.

Defensive behavioral responses are contingent upon threat intensity, proximity, and context of exposure. Based on these factors, we developed a classical conditioning paradigm that elicits clear transitions between conditioned freezing and flight behavior within individual subjects. This model is crucial for the understanding the pathologies involved in anxiety, panic, and post-traumatic stress disorders.

Fear- and anxiety-related behaviors significantly contribute to an organism&#8217;s survival. However, exaggerated defensive responses to perceived threat ...

Studying Active Defensive Behaviors in Mice with Modified Fear Conditioning

Modified Fear Conditioning for Inducing Flight Behaviors in Mice

The appropriate manifestation of defensive behavior in a threatening situation is critical for survival. The prevailing theory suggests that an active defensive behavior, such as jumping or rapid darting, is expressed under high threat imminence or actual threat, whereas passive defensive behavior, such as freezing, is expressed when the threat is predicted, but the threat imminence is relatively low. In classical fear conditioning, subjects typically exhibit freezing as a conditioned defensive response, with little expression of active defensive behavior in most cases. Here, we introduce a modified fear conditioning procedure for mice to observe the transition from freezing to flight and vice versa, involving five repetitive pairings of conditioned stimuli (CS; continuous tone, 8 kHz, 95 dB SPL (sound pressure levels)) and unconditioned stimuli (US; foot shock, 0.9 mA, 1.0 s) over two days. This modified fear conditioning procedure requires a relatively large number of conditioning sessions and conditioning days but does not necessitate a high-intensity foot shock for modest expression of flight behavior. Using the same context for conditioning and salient CS presentations is essential to elicit flight behaviors. This modified fear conditioning procedure is a reliable method for observing active defensive behaviors in mice, providing an opportunity to elucidate the fine mechanisms and characteristics of such behaviors in a fearful context.

Author Spotlight: Exploring Neural Correlates of Defensive Behaviors in Fear Learning and Extinction

To study flight behaviors in a fearful context, we introduce a modified fear conditioning protocol. This protocol ensures that mice consistently exhibit flight behaviors during cue presentation in the fear conditioning.

The appropriate manifestation of defensive behavior in a threatening situation is critical for survival. The prevailing theory suggests that an active ...

Assessing Rodent Empathy: Observational Fear and Vicarious Freezing Method

Observational Fear as a Model of Affective Empathy in Mice

Empathy, characterized by the ability to recognize and share the emotions of others, plays a fundamental role in shaping social interactions. It allows individuals to respond to the emotional states of others, promoting prosocial behaviors and social bonding. Observational fear is a fundamental aspect of affective empathy, where an observer witnesses a demonstrator undergoing aversive experiences and subsequently exhibits fear behaviors. This socially induced vicarious freezing response in observers, known as emotional contagion or affect sharing, is regarded as an indicator of empathy-like traits in rodents. Here, we present a protocol that delineates the assessment of vicarious freezing responses in observers exposed to conspecific demonstrators receiving aversive foot shocks. The utilization of observational fear assays in rodents has become a widely adopted method for studying the neural mechanisms underlying affective empathy. Given the universality of observational fear across mammals, this methodology further contributes to advancing our understanding of the neural substrates of empathy in humans.

The observational fear paradigm assesses vicarious freezing in rodents as a model for affective empathy. This procedure entails exposing observer rodents to conspecific demonstrators receiving aversive foot shocks to elicit empathic freezing responses. By employing observational fear assays, researchers can investigate the neural mechanisms underlying affective empathy.

Empathy, characterized by the ability to recognize and share the emotions of others, plays a fundamental role in shaping social interactions. It allows ...

Pentylenetetrazole-Induced Kindling Mouse Model

Pentylenetetrazole (PTZ) is a GABA-A receptor antagonist. An intraperitoneal injection of PTZ into an animal induces an acute, severe seizure at a high dose, whereas sequential injections of a subconvulsive dose have been used for the development of chemical kindling, an epilepsy model. A single low-dose injection of PTZ induces a mild seizure without convulsion. However, repetitive low-dose injections of PTZ decrease the threshold to evoke a convulsive seizure. Finally, continuous low-dose administration of PTZ induces a severe tonic-clonic seizure. This method is simple and widely applicable to investigate the pathophysiology of epilepsy, which is defined as a chronic disease that involves repetitive seizures. This chemical kindling protocol causes repetitive seizures in animals. With this method, vulnerability to PTZ-mediated seizures or the degree of aggravation of epileptic seizures was estimated. These advantages have led to the use of this method for screening anti-epileptic drugs and epilepsy-related genes. In addition, this method has been used to investigate neuronal damage after epileptic seizures because the histological changes observed in the brains of epileptic patients also appear in the brains of chemical-kindled animals. Thus, this protocol is useful for conveniently producing animal models of epilepsy.

This protocol describes a method of chemical kindling with pentylenetetrazole and provides a mouse model of epilepsy. This protocol can also be used to investigate vulnerability to seizure induction and pathogenesis after epileptic seizures in mice.

Pentylenetetrazole (PTZ) is a GABA-A receptor antagonist. An intraperitoneal injection of PTZ into an animal induces an acute, severe seizure at a high ...

Neuroscience

Fear Conditioning

Fear Conditioning is a type of learning in which an association is established between a negative unpleasant event and a harmless stimulus. This leads to a fear of the harmless stimulus. This process is largely mediated by the amygdala, which is a brain region involved in emotions and stress reactions. Fear conditioning can be utilized in several ways to understand different aspects of learning and memory.
This video presents an overview of the principles behind fear conditioning, discusses the equipment and a generalized procedure used for this type of experiment. Finally, we'll review some real world applications of fear conditioning in behavioral neuroscience research today.

Fear Conditioning- Classical Conditioning: Principle and Procedure

Fear Conditioning is a type of learning in which an association is established between a negative unpleasant event and a harmless stimulus. This leads to ...