Sensitive Estimation of Flavor Preferences in STFP Using Cumulative Time Profiles

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Frontiers in Behavioral Neuroscience
Mar 2017



Social transmission of food preference (STFP) is observed among rodents between a demonstrator and a naïve hungry observer. During social interaction, hungry observer receives information about safety of the food consumed by the demonstrator. This task has been implemented to develop a single trial non-aversive learning task in order to test hippocampus dependent non-spatial memory in rodents. In this protocol, we describe some novel modifications to the conventional STFP protocol and analysis for more sensitive estimation of change in preferences. Using this method, preference trends can be observed for weeks after training, allowing one to probe the role of systems consolidation (SC) in declarative memory that is relatively independent of spatial navigation.

Keywords: Remote memory (遥远记忆), Social transmission of food preference (STFP) (社会性食物偏好传递(STFP)), Mouse behavior (小鼠行为), Sensitivity (敏感性), Performance (表现), Flavor (口味), Innate preference (先天偏好)


Bennet G Galef Jr. developed STFP based behavior paradigm with rats during 1970’s in order to test memory mechanisms and since then, it has been implemented in various studies with both rats and mice (Galef Jr, 1977; Clark et al., 2002; Wrenn et al., 2003; Ross and Eichenbaum 2006; Smith et al., 2007; Choleris et al., 2011; Lesburguères et al., 2011; Clark, 2012). In case of rodents, the basic premise of this paradigm comes from their natural feeding behavior. Demonstrator mice [DemoMice] find the food that is safe for consumption through trial and error, and soon after consumption, the information for palatable food is shared with other observer mice [ObMice] through social interaction. Such interactions happen at a location situated away from the feeding site where ObMice learn about the safety of consumed food, or more specifically consumed flavor, when it is detected along with certain breath components of the DemoMice (Galef et al., 1988; Choleris et al., 2009). After establishing such flavor-safety association in STFP paradigm, ObMice have been observed to preferably consume the demonstrated flavor (demoFlavor), when given a choice between a novel and a familiar flavor.

Traditionally, the experimental design would involve arriving at the flavor pairs where both flavors are equally palatable during a consumption session with close to 50% preference for each flavor (Galef and Whiskin, 1998). Since the relative palatability of flavors is determined with different set of animals, one does not get any direct information reflecting innate preferences (IP) of experimental animals. After determining relative palatability of the flavor pair, one of these flavors is demonstrated through social interaction and increase in its preference beyond the 50% level is estimated after STFP. However, such a design does not consider the fact that even though average preference of a group of mice could be 50%, there could be individuals with varying native preference and this in turn could bias the interpretations of the result. Our novel design measures the STFP mediated change in preference while considering the native preference of individual animals.

Further, conventional preference estimation involves comparing the weight of food containers recorded before and after the sessions to calculate ‘weight of consumed food’ (WC.F). During a typical STFP testing session with mice, each individual consumes ~1 g and spills the food weighing up to ~5 g from containers weighing close to 100 g (typical weight of the container had to be ~100 g to prevent toppling). Correcting for errors associated with spillage limits the accuracy of WC.F. Consequently, it makes it difficult to detect minor changes in the strength and nature of the flavor-safety associations. Alternatively, we propose and utilize the ‘number of food consumption episodes’ obtained through video analysis as a measure of performance. Using this method, we establish an STFP procedure that is easy to implement and more sensitive. Inherently, such analyses are easy to use and less error prone as compared to weight measure. They utilize more data points and hence they convey more information in comparison to single point measurements such as total weight of consumed food or total time spent during consumption. Since mice consume small amounts over extended time windows, food intake data cannot be used directly for observing variations in rates of food consumption.

Materials and Reagents

  1. Identical plastic containers (Figures 1A and 1B): Dimensions 6.5 x 4.5 cm, assembled weight ~100 g (Julia Pet Jar 130 ml) (Princeware, catalog number: 9462 )
  2. Bedding material made from non-uniform corn cobb granules of 3-4 mm average diameter (Spar Cobb, Sagar Industries, Bangalore, India)
  3. Food vessel: A lid for smaller plastic container was used as food vessel (Figure 1) (Julia Pet Jar 60 ml) (Princeware, catalog number: 9461 )
    Note: It is filled with ground flavored food and placed above the bedding material inside the plastic container. The lid of plastic container is closed such that the centers for food vessel and hole in the lid are aligned vertically.
  4. C57/B6 mice (males, 8-12 weeks of age) housed in pairs after weaning until the beginning of habituation sessions. In order to clearly identify observer mice from demonstrators during interaction sessions in our experiments, demonstrator mice are marked with one hole in each ear pinna under general anesthesia after one week of weaning. Animals are separated for individual housing just before first habituation session.12-16 mice per group provide acceptable power during statistical analyses. The mice are reared in 12 h light/dark cycle and all the experiments are conducted during the light-on phase (06:30 AM-18:30 PM). All the procedures involving animals were performed with approval from institute animal ethics committee, IISc Bangalore
    Note: One important consideration is co-housing of observer mouse with demonstrator mouse after weaning. In our method, we do not use a wire mesh/screen during social interaction to separate ObMice and demoMice, in order for the mice interaction to resemble their natural setting. To avoid excessive fighting during social interaction, we randomly select two just-weaned mice and co-house them in the same cage for one month. At the age of ~2 months, these mice are separated to be housed individually for further steps of the protocol and one of them is assigned to become a demonstrator for its cage-mate. Social interaction between two familiar male mice may also help in making it more effective for STFP in comparison to interaction with a stranger male. So, it is crucial to collect a large number of mice in comparable age group at the same time. Either observer or demonstrator mouse can be marked by making a hole in their ear pinna in order to identify them correctly after social interaction session.
  5. Mouse food pellets (Nutrilab Rodent Feed, Provimi)
  6. Powdered condiments as flavoring agents (Cocoa, Cinnamon, Thyme, Basil; SNAPIN herbs and spices, Lotus household product, India)
    Note: Source of all the condiments must be consistent from the beginning to the end of the experiment.
  7. 70% ethanol to clean all the components of food apparatus
    Note: Ethanol cleaning is carried out a day before the experiment session. All clean components are dried in warm air flow overnight to remove any odor trace from ethanol.
  8. Sodium hypochlorite solution (4% NaOCl solution) (Fisher Scientific, catalog number: SS290-1 )
    Note: It is further diluted to make cleaning solution (see Recipes) for removing prevailing odor from the components of food apparatus and animal cages. After each experiment session, all the components of food apparatus are submerged in a cleaning solution for 15-20 min followed by thorough rinsing in tap water. Cleaned components are then air dried and stored in hygienic conditions.
  9. X% ‘Condiment’ flavored food (see Recipes)
  10. Cleaning solution (see Recipes)


  1. Plier for making metal trays
  2. Paint for metal trays: white paint if black coat mice are used and vice versa
  3. Transparent Perspex sheets with holes drilled along short central axis (Figures 1E)
  4. Aluminum/Tin metal sheet (sized to fit in the test cage): 1-2 mm thickness for making spill-proof trays to hold food containers. The vertical walls of these trays are 2 cm high. Length and breadth of these trays can be adjusted for achieving best fit within the test cage. For our setup, the dimensions were 16 x 13 cm
  5. Weighing balance: with sensitivity up to 10 mg
  6. Electronic grinder (Morphy Richards, model: Icon Essentials ) for making powdered food
  7. Full HD webcam (Logitech, model: C920 ) for multiplexed video monitoring
  8. Polarizer filter (RG610, RG series color glass filters, Optica, Optics India; it is optional) to avoid reflections from transparent Perspex sheets covering the test-cages
  9. Webcam mounting assembly: We used a long wooden stick (300 x 10 x 5 cm3) with a hole at the center along its length and an M6 screw to fix the webcam above test-cage assembly
  10. Individually ventilated cages (IVCs)/polycarbonate cages for individual housing of mice (IVC; 36 long x 14 wide x 12.5 cm high) (Citizen Industries, catalog number: 11 )
  11. Portable electronic drill (Robert Bosch, model: Bosch GSB 10 RE Professional ) with drill bits to make holes of 1 cm diameter in the lids of food container


  1. Free, open source media player such as VLC. Any software for position tracking may also be implemented for estimating time spent near food containers
  2. Origin software
  3. Microsoft Excel
  4. ImageJ plugins (such as Analyze particle)


  1. Preliminary requirements
    1. Design of feeding apparatus (Figures 1A and 1B): This includes a cylindrical food container with a hole in its lid, a small food vessel and an aluminum tray for collecting spilled food.
      1. Identical plastic containers must be used. Lids should be sufficiently flat for mouse to sit on top and consume food.
      2. The lid of each plastic container is drilled at the center to make a hole of 1 cm diameter. Holes must be of the same diameter in all the containers.
      3. Bottom container is filled with bedding material leaving ~1 cm at the top.
      4. A small cylindrical food vessel of ~1 cm height is filled with powdered food and kept inside the bottom container.
      5. The lid is tightened on top of the food vessel aligning their centers vertically. Food should be accessible through the hole in the lid.

        Figure 1. Design of food apparatus (A, B) used during food consumption session (C); During food consumption and social interaction session (D), the test cages were covered with a transparent Perspex sheet (E). All observer mice are provided with powdered food in two identical sets of food apparatuses during preference tests. A. Components of food container include a food vessel filled with powdered food (powdered food not shown) that rests within the bottom container. The lid is modified by drilling a hole of 1 cm diameter at its center to provide access to food. B. Bottom container is filled with bedding material leaving just enough space to place the food vessel on top. C. Mice consuming food from one of the food containers during a preference test. Both food containers are identical in every aspect of their design. If spilled food gets mixed with bedding material in the cage, it is extremely hard to account for during estimation of net consumption. To minimize such unaccountable spill during consumption, each feeding apparatus includes a custom-built aluminum tray to hold the food containers. The food containers are softly glued to the center of the metal tray with a small piece of double-sided adhesive tape. D. Social interaction between observer and demonstrator mice. Demonstrator mice are identified by a hole in their ear pinna. E. Side view of a test cage covered with a transparent Perspex sheet to avoid mice from escaping while video monitoring. Two rows of holes meant for air circulation are visible close to the center of transparent Perspex sheet covering the cage.

      6. A small piece of double-sided adhesive tape (1 x 1 cm) is attached to the center of spill collection tray. After weighing the food containers, they are fixed to the spill collection tray. Spill collection tray was made by bending thin metal sheet. Its dimensions can be decided according to the test cage.
        Note: Size and position of feeding hole on all the lids need to be same, in order to make sure that accessibility to food is uniform for all mice. For black coat mice, all the spill collection trays and lids for food containers can be painted white to provide the best contrast for video analyses.
      7. Containers are temporarily labeled at the bottom with their flavor and their weights are noted with respect to their position in each test cage.
    2. Cage assembly and video recording set up
      1. Test cages with bedding material are arranged in a matrix on the floor/low table in the experiment room. Depending on the number of mice, one could use 3 x 3, 3 x 4 or 4 x 4 matrix to arrange test cages.
      2. It is important to place visual block between all the transparent/translucent cages in order to avoid visual distractions across mice. We placed cardboard sheets (15 cm high, 3 mm thick, length as per the cage arrangement) to maintain complete visual block between test cages during the experiment.
      3. Test cages are covered with transparent Perspex sheets (Figure 1E) for multiplexed video recording of all the cages in top-view (Figures 1C and 1D).
      4. Each Perspex sheet has small holes (3-5 mm diameter) drilled along the short central midline for air circulation (Figure 1E).
      5. A webcam is mounted at ~4 ft height using a customized stand such that each test cage is covering an equivalent area in the field of view and all cages are in focus.
        Note: Any reflection from transparent Perspex cover on test-cages can be avoided by using well-directed lighting and/or a polariser.

  2. Steps for the procedure
    Our STFP behavior protocol has been explained in ten steps including 1) Weaning, 2) Random paired co-housing of two mice in single cage, 3) Handling, 4) Segregation of paired mice as observer and demonstrator, 5) Habituation (5-7 days), 6) Pre-STFP preference test (1 day) for Identification of less preferred flavor as to-be-demonstrated flavor, 7) Feeding respective demonstrator mice on to-be-demonstrated flavor, 8) Social interaction (1 day), 9) Post-STFP preference tests (1 day each) at recent time-points, 10) Post-STFP preference tests (1 day each) at remote time-points (Figure 2). Pre-STFP preference, Social interaction and Retrieval tests were all performed in the same room but on different days. All animals were housed in individually ventilated cages to prevent the unwanted transfer of olfactory, auditory or visual cues between demonstrator and observer mice across sessions. If individually ventilated cages are not available, holding and testing rooms must be separate. Clean-air circulator and exhaust outlets were kept open continuously to prevent odor retention of previous sessions. Clean-air inlet was turned off during the experimental sessions for one hour.

    Figure 2. Modified protocol for STFP with mice. Each step is numbered and explained in detail in this procedure section. P–plain powdered food (without added flavor), A, B–flavors used during the experiment, IPF–innately preferred flavor, RFA–restricted food access (mice were provided with 1 g food pellet daily in addition to the consumption during habituation/testing sessions).

    1. Weaning
      3-4 weeks old male mice are separated from the mother based on their size and health.
    2. Randomly paired housing
      In our protocol, paired housing begins with weaning. Randomly paired two animals are co-housed in a cage just after weaning and kept together until the beginning of habituation sessions. Habituation sessions begin after a minimum of four weeks from weaning. A week after weaning, one of the co-housed animals is ear marked to be the demonstrator.
    3. Handling
      Co-housed animals are handled for about a week before separation. Proper handling helps in reducing anxiety in both animals and the experimenter during behavior. Handling protocols followed in different labs are mostly similar with few modifications depending on the cohort. We are listing down handling steps which we followed while considering the anxiety levels of both the novice animals and the experimenter.
      Note: Each animal is handled for ~10 min daily for 3-5 days in the room where the experiment will be conducted.
      1. Day 1
        Gently lift the animal while holding the tail closer to the body. Rest the body on other hand for 20-30 sec while both the hands are within the home cage. Release back in the cage gently. Repeat 3-5 times at an interval of ~30 sec depending on anxiety of the animal.
        Note: Animals within a cage can be handled with same pairs of gloves as they are familiar with each other’s odor. It is important to change gloves while handling animals from a new cage. Gloves should be changed across cages even if there is no/minimal excretion from previous cage animals.
      2. Day 2
        Repeat day 1 procedure while resting the animal for 60-90 sec on palm. Always change gloves for seemingly anxious animals even if they are cage mates of relatively non-anxious animals.
      3. Day 3
        Repeat day 2 procedure while allowing the animal to walk around for ~2-3 min while positioning the palms just above the cage. Try to make sure that animal lands in cage if it jumps. Follow same glove change rule as of day 1 and day 2.
        Note: In case animal jumps and lands out of the cage (on floor/table), gently lift the animals, keep them back in cage and resume handing only the next day for such animals. Prior arrangements should be made to make all the hiding corners inaccessible for the loose mice.
      4. Day 4/5
        Repeat the steps followed on day 3. If animals seem anxious or ‘jumpy’, repeat over following days. Usually, most of the animals get rid of their anxiety within 4-5 days of handling.
    4. Separating Co-housed animals: Co-housed animals are separated and housed individually in different cages just before the beginning of habituation sessions. The same couple needs to be used during all the interaction sessions to avoid fighting and stress. All the individually ventilated cages for holding single animals are kept in the same room.
    5. Habituation
      Habituation allows animals to get adjusted with two main aspects of the paradigm: daily food deprivation of ~15 h and consuming powdered food pellets by climbing on custom-made food apparatus.
      Food Deprivation: Food deprivation involves limiting access to food by providing animals with a 1 g solid food pellet daily, in addition to the one-hour food consumption session every day. Food deprivation begins by leaving animals with just a 1 g solid food pellet 24 h before commencing the first habituation session for one-hour of food consumption. Food deprivation schedule is continued from the beginning of habituation sessions until the post-STFP preference test conducted after 24 h. For 17- and 41-day remote preference tests, ~15 h deprivation is started 3 days in advance before the testing day. Water is provided ad libitum, except for one hour of experimentation/habituation session.
      1. Preparation, distribution and weighing of food: Regular food pellets are ground before each session. Food was prepared in a ventilation hood with minimum air flow settings.
        1. Each food vessel is filled with powdered pellets and enclosed in the food container.
        2. Weight of each container is carefully noted down in accordance with its relative position with respect to the test room as frame of reference.
        3. Each food container is kept in a light metal-tray custom built for collecting any spilled food.
          Note: Weights of food containers are noted before and after the session. Spilled food is weighed indirectly as explained in the ‘weighing procedure’ below.
        4. Demonstrator mice are given feeding-apparatus within their home cage and allowed to consume food for one hour.
        5. Observer mice are first released in the test cage at their respective position. Then two sets of feeding-apparatus are introduced one after another. Some important considerations in order to avoid biased food-distribution are listed in the note below.
          Note: During habituation, each feeding-apparatus is identical in every aspect including flavor of contained food. So, only variable remains the order of delivery. We change the order of delivery across cages within the same session as well as across sessions within the same cage. For example, on day 1 of habituation, if cage 1 first receives food at position A and then at position B, we ensure that on day 2, position B is given food before position A. Also, within the same session, we ensure the order apparatus placement is alternated across cages i.e., if cage 1 receives food first at position A and then at position B, we ensure that cage 2 receives food first at position B and then at position A. This pseudo-randomization doesn’t allow mice to prefer any peculiar end within the test cage based on ‘first come, first eat basis’ and makes it easier for them to learn to eat equally from both containers.
        6. Weighing Procedure: Weights of food containers are noted before and after the session. Spilled food is weighed indirectly. Any cage litter is removed before weighing the tray. The tray containing spilled food is weighed after the session and its weight is noted. Then the tray is wiped thoroughly to remove any sticking powdered food and weighed again. The difference in these two weights of the tray is noted as ‘spilled food’ and subtracted from the difference of ‘before and after’ weights of the food container to obtain ‘net consumption’. Preference for the flavor A is calculated as the ratio of net consumption from container A vs. total food consumed from both the cups during one-hour session.
      2. Day 1
        Demonstrator mice: They are provided powdered food in a container in their home cage for 1 h. DemoMice are given food one hour before ObMice. Water is removed during food consumption.
        Observer mice:
        1. ObMice are individually released in their respective test cage containing bedding material for 1-h long consumption session.
        2. Trays containing food container are then placed in each cage while following aforementioned pseudo-randomization process.
        3. At the end of the session, all mice are removed from test cages without disturbing the feeding apparatus and kept back in their home cages.
        4. All mice are given a solid food pellet weighing ~1 g after the session. This results in daily food deprivation of ~15 h.
        5. Feeding apparatuses are individually removed from each test cage, carefully weighed in aforementioned manner to calculate net consumed food and dismantled for a thorough cleaning that involves cleaning with odorless detergent/bleach, washing with warm water and drying in warm air flow.
      3. Days 2-7
        Same timing is maintained for feeding both DemoMice and ObMice. It is repeated until observer mice begin to consume equal amount of food from both food containers. Position of containers within a test cage is reversed across sessions over multiple days.
    6. Pre-STFP preference test
      1. Preparation, distribution and weighing of Food:
        1. Just before commencing the test session, powdered food pellets are mixed in a required ratio (% w/w) with the commercially acquired flavors. See ‘Recipes’.
        2. During preference tests, freshly prepared food of one flavor is filled in the food vessel which is then kept inside the container. Containers with the same flavor are assembled first.
        3. The place is thoroughly wiped to remove any traces of previous flavor and remaining vessels are filled with the powdered food containing other flavor and remaining containers are assembled.
        4. Steps ‘i to v’ as for observer habituation are followed further.
        5. Weighing is conducted in aforementioned manner.
      2. ObMice are allowed to consume flavored food from two containers in the test cage kept at their respective positions in the assembly. Complete session is video recorded in addition to the weight measurements.
      3. Based on the weight estimation, each observer mouse is identified as preferring flavor A or flavor B. Choice of flavor at this point most likely represents their innate preference for one of the two flavors. It is noted that during social interaction after 24 h of pre-STFP test, each mouse preferring flavor A during pre-STFP test will be demonstrated with flavor B and vice versa. Since preference for either flavor ranges between 0-1, ObMice having more than 0.5 preference for flavor A will be demonstrated with B and vice versa.
      4. There might be some ObMice which consume equal amounts of both the flavors during pre-STFP test. Half of these mice are allotted to flavor A preferring group and the other half to flavor B preferring group.
        Note: In our experiments, steps 7 (DemoMice feeding) and 8 (social interaction) were most often carried out after 24 h of step 6 (Pre-STFP test). We also tested a scenario when steps 7 and 8 were conducted five days after step 6. Animals need to be given 2 g food pellet daily during the intervening days for maintaining a healthy weight.
    7. Demonstrator Feeding: Respective demonstrator mouse from the co-housed pair is fed for 1 h on the flavor which is preferred less during pre-STFP test by the corresponding observer. This feeding takes place in the individually ventilated home cages of demonstrator mice.
    8. Social interaction for demonstration of flavor (STFP)
      1. At the end of feeding session, demonstrator mice are released in the test cage of corresponding, pre-assigned observer mice for one hour long social interaction.
      2. All mice are kept back in their respective home cages at the end of interaction session.
      3. Interaction session is also video monitored.
    9. Recent memory test
      In order to test the change in preference after social interaction, 24 h after social interaction observer mice are provided both the flavors in two cups in their respective test cages (see Video 1). Post-STFP tests follow the same steps as required for pre-STFP preference test.
    10. Remote memory test
      Remote memory for flavor retention can be carried out after 2-4 weeks depending on the requirement.

      Video 1. Food consumption in a typical test-session conducted after 24 h STFP

Data analysis

  1. Preference estimation using weight measurement
    1. In order to quantitatively express the demoFlavor preference w.r.t either weight or time as a measure, we define mean preference as follows:

      where, WDem and WNon-Dem are Consumed weight of demoFlavor and non-demoFlavor, respectively; TDem and TNon-Dem are Time spent near demoFlavor and non-demoFlavor container, respectively.

  2. Preference estimation using time spent near food cup
    1. Video recording
      All the food consumption sessions were video recorded at 30 frames per second. These videos are then manually scored to record the position of each mouse at an interval of every 10th sec (300th frame). Steps for manual scoring are listed below.
    2. Manual scoring
      1. A session starts after both the food containers are placed in the test cage with mouse. Each video is continuously observed with intermittent pause after every ten sec.
      2. As mentioned before, the videos are recorded at 30 fps, all cages are continuously observed and mice positions are noted after every 10 sec i.e., 300 frames. This results in each 1 h long video of 3,600 sec to be scored to give 360 data points for each mouse. Scorer should be blind to the information about flavor in food cups while scoring.
      3. Each cage (C1, C2 etc.) is assigned 2 columns in the manual scoring sheet (Figure 3A, see the sample excel sheet here) for recording position of mice while scoring.
      4. One of the ways to keep track of manual scoring could be as follows: If the animal is in left half of the cage, then ‘a’ is diagonally crossed. If the animal is in right half of the cage, then ‘b’ is crossed. If animal is in center of the cage ‘©’ is written between a and b. To avoid marking mistakes, a and b for consecutive cages are printed in different fonts (Figure 3A). ‘a, b, and ©’ can be replaced with symbols of choice.

        Figure 3. Portions from example sheet for manual scoring (left) and sample excel sheet for processing manual scores (right). A. C1 refers to cage 1; while manual scoring, video is paused after every 10 sec and position of mouse in cage is recorded (see step ‘d’ in manual scoring above). B. After manual scoring is complete, positions of mice are recorded in analysis sheet. For first 10 sec window (first row marked with time ‘0’), if mouse is found to be in right half of the cage, crossed ‘b’ is recorded by entering ‘1’ in the column titled ‘Right half of cage in video’ and so on. After translating all the data to analysis excel sheet, a macro is run for identifying eating episodes. Cumulative eating episodes for subsequent time windows are then plotted to generate cumulative time profiles.

    3. Automated scoring
      We are in the process of developing a fully automated method to estimate individual flavor preferences using ImageJ plugins (such as Analyze particle) to identify the size of the mice. We have generated heat maps of mice to represent their preferences for each location. We are in process of incorporating the algorithm for identifying eating episodes based on heat maps. We will further extend it to generate live cumulative time profiles as the session progresses.

  3. Processing raw data from manual scoring
    1. All mice positions from the scoring sheet are entered in the Excel data sheet for further analyses (Figure 3B). For each cage, excel sheet contains 3 columns representing left, center and right region of the cage and, 360 rows of cells each representing 10 sec of the video. After manual scoring is complete, positions of mice are recorded in analysis sheet.
      Example: For first 10 sec window (first row marked with time ‘0’), if mouse is found to be in right half of the cage, crossed ‘b’ is recorded by entering ‘1’ in the column titled ‘Right half of cage in video’ while other two neighboring cells are left empty. When mouse position cannot be assigned to either left or right half of the cage, 1 is entered in the cell corresponding to the column marked as ‘Centre’. 
    2. Total time in a cage region is 10 times the sum of all ‘1’ in a column (since each ‘1’ represents 10 sec). In our videos, we observed that mouse does not always consume food when they visit a region for short durations. We found that residence time was highly correlated to food consumption if we defined an eating episode to be of 30 sec or longer duration. Simply put, based on the correlation in addition to our observation during video monitoring, we can safely assume that mice were consuming food whenever they spent more than 30 sec at a location. Such durations which are either equal to or longer than 30 sec are now referred to as ‘eating episodes’. So, in order to calculate total consumption time spent near a food cup, using a visual basic macro we counted only those data points which occur as a consecutive bunch of three or more ‘1’ at the same location. In other words, for calculating total time at a location, only those visits are considered to be ‘eating episode’ when a mouse stays at a location continuously for 30 sec (900 frames) or longer. Instances when mouse position is marked to be in the center of the cage are not accounted for calculating preferences.
    3. After translating all the data to analysis excel sheet, a visual basic macro is run for identifying eating episodes. Cumulative eating episodes for subsequent time windows are then plotted to generate cumulative time profiles. Macro identifies and assorts information about time spent near a food container into ‘eating episodes’ (This macro is just an example for selecting 60 sec long episodes; it needs to be modified according to the duration of eating episodes, total duration of consumption session and number of cages):

      Sub DataAnalysis ()
      Dim row As Long
      Dim column As Long
      Dim sum As Integer
      Dim newcol As Long
      newcol = # (enter column # where you need data after running macro)
      For column = # to # (enter column numbers where raw data is entered)
      For row = # to # (enter row numbers where raw data has been entered)
      sum = WorksheetFunction.sum(Sheets(‘Sheet1’).Range(Cells(row, column), Cells(row + 5, column)))
      If sum = 6 then
      Cells (row, newcol).Value = Cells (row, column).Value
      Cells (row + 1, newcol).Value = Cells (row + 1, column).Value
      Cells (row + 2, newcol).Value = Cells (row + 2, column).Value
      Cells (row + 3, newcol).Value = Cells (row + 3, column).Value
      Cells (row + 4, newcol).Value = Cells (row + 4, column).Value
      Cells (row + 5, newcol).Value = Cells (row + 5, column).Value
      Cells (row + 6, newcol).Value = Cells (row + 6, column).Value
      End If
      Next row
      newcol = newcol + 1
      Next column
      End Sub

    4. Time windows
      We then compare the cumulative consumption of mice within eleven time-windows encompassing the one-hour consumption session. First window is 10 min long while subsequent ten windows are 5 min long each.
      Note: After consumption session begins for first cage, it takes ~5 min to arrange things for food consumption in the last cage of the group leading to an additional 5 min delay in start of the session for last mouse. In addition, after initial switching between food cups, it takes a few minutes for mice to begin continuous consumption. Due to such delays, the first consumption window is 10 min long to obtain average food consumed and remaining 50 min of the session is divided into 10 windows of 5 min each. Average cumulative time spent near a food cup is used to generate cumulative time profiles (CTPs) for both demonstrated and non-demonstrated flavor.

  4. Cumulative time profiles (CTP) and Steps to generate CTPs from eating episodes
    Using pattern of consumption as a diagnostic for predicting retention:
    In case of rodents, meal microstructure can be analyzed using the food intake data obtained as a function of time during food consumption (Fox and Byerly, 2004). The food intake rates in such studies have been related to physiological parameters through Weibull function as follows:

    where, consumption profile (y) is obtained by measuring the amount of food consumed as a function of time. Such consumption profile has been found to depend on the three main parameters namely the initial intake rate (A), slope or rate of decline in intake rate (k) and deviation of the curve from the exponential (d) which represents the duration for which initial intake rates are maintained. One of the ways to interpret the Weibull fit parameters could be the following: parameter A may largely reflect how hungry the animal is at the beginning of the session, parameter k and d would mostly depend on innate preference for the flavor. These parameters may also have some contributions from the moisture content and stability of the food.
    We extended this analysis for more effective monitoring of the average consumption profiles of animals during STFP paradigm. We plot cumulative eating episodes as a function of time to obtain the average consumption profile for group of mice. The Cumulative time profile (CTP) represents variation in the total number of eating episodes in successive 5 min-long time windows for an hour-long consumption session (details are explained in ‘Data analysis’ section). Therefore, the corresponding function to fit the CTPs is the integral of Weibull function i.e., Weibull cumulative distribution function (CDF) given by the following integral:
    Parameters and their meaning:

    A–amplitude parameter representing cumulative consumption,
    b–offset parameter representing the starting preference at the beginning of the session,
    d–deviation parameter representing the deviation of fit from exponential,
    k–slope parameter representing the decline in rate of consumption.
    In a similar aforementioned manner, the WeibullCDF parameters could be interpreted as follows: parameter A may largely reflect animals’ hunger throughout the session, parameter k and d would mostly reflect change in preference for the flavors as session progresses.
    1. Amount of time spent in either half of a cage is measured in terms of eating episodes for each mouse.
    2. Eating episodes for each time window are summated for calculating cumulative time spent in food consumption. For each time window, cumulative time near each food cup spent is averaged for all the mice.
    3. Average cumulative counts for each time window are plotted against time in order to get a cumulative time profile for average time spent near both the food cups (Figure 4).
    4. CTPs are fitted to integral of Weibull function which we refer to as Weibull cumulative distribution function (WeibullCDF). One-way ANOVA is then used to compare the CTPs across successive sessions. Details of complete statistical analysis and fitting procedure have been explained in a recent study (Singh et al., 2017).
    5. Steps for fitting CTPs to Weibull Function: Origin software was used for fitting the consumption pattern data using linear and non-linear functions. Linear fit is provided with the package. For non-linear fit using Weibull function, we added the code in the function builder provided within origin package as follows:
      Analysis → Fitting → Non-linear fit → Open Dialog → Create new fitting function → Select Category as ‘Growth/Sigmoidal’ → Name as ‘Weibull CDF’ (i.e., Weibull Cumulative Distribution Function) → Function Model set as ‘Explicit’ → Function type set as ‘Expression’ → Independent variable set as ‘x’ → Dependent variable set as ‘y’ → Parameters set as ‘A, b, d, k’ → Function body written as ‘A·(1 - exp(-(k·x)d)) + b’.
      Note: While fitting CTPs to Weibull cumulative distribution function (WeibullCDF), parameter initialization values required for four parameters are as follows: A = 1,000, b = 100, d = 1, k = 0.01.

      Figure 4. Cumulative time profiles (CTPs) representing consumption patterns for demoFlavor and non-demoFlavor for two preference tests: pre-STFP (left panel) and 24 h post-STFP (right panel). As indicated in the pre-STFP CTPs, flavor with lower preference (open diamonds) was selected for demonstration during social interaction. 24 h later, observer mice were demonstrated with less preferred flavor during social interaction with demonstrator mice that were fed on to-be-demonstrated flavor for one hour. Flavor with higher preference was not demonstrated. 24 h after STFP, CTP fits indicate the increase in preference for demoFlavor only. Both CTPs were fitted to Weibull cumulative distribution function (WeibullCDF). CTP fit for flavor B could also be approximated equally well by a linear fit. Each datapoint represents summation of eating episodes within respective time window. This data is part of the study that was published earlier (Singh et al., 2017). It is plotted here for representative purposes. Weight-based preference estimation data can also be accessed through the same study.

      Note: At this point just after pre-STFP test in the actual experiment, only weight based consumption preferences are known whereas the time-based data is segregated into cumulative eating episodes after manual scoring of videos. Thus, less preferred flavor is identified as the flavor for which average weight of consumption is lower. In order to speed up the analyses, we are working on a heat map based method for cumulative eating episode based preference estimation.

  5. Simulation-based comparison of random vs. selective demonstration during STFP
    Previous studies seldom considered the effect of innate preference during STFP behavior with rodents. In order to accommodate the contribution of animals’ innate preferences for evaluating the change in preference following demonstration, in our protocol we incorporated a pre-STFP test which is followed by ‘selective demonstration’ of flavors (Singh et al., 2017).
    While conducting social demonstration after pre-STFP test, we had choice between two seemingly alternate ways of proceeding forward, i) selective demonstration: use the pre-STFP test data to group animals with similar preferences for demonstrating less preferred flavor or, ii) random demonstration: randomly distribute animals in two groups independent of pre-STFP test data for demonstrating any one of the two flavors. These two seemingly different approaches could result in introducing some artificial variations while estimating the change in preference across pre-STFP to post-STFP tests. To address this concern, we conceptualized virtual STFP where we simulated two preference tests and compared the effects of aforementioned flavor demonstration strategies on the change in preference. We found both demonstration approaches to be considerably similar based on the results of simulation and we proceeded with the first approach of selective demonstration.
    For simulating STFP, we assume that preference estimated during each preference test has two major components, i) starting preference (SP) component for demoFlavor and, ii) random preference (RP) component for demoFlavor. Corresponding sets of SP and RP are assumed to have distributions with same mean (0.5) and standard deviation. Further, the contribution of both components is weighted with the parameter i, which represents the magnitude of contribution from natural bias or innate preference of animal for demoFlavor. Parameter ‘i’ ranges between 0 < i < 1.
    The steps for simulations are as follows:
    1. Generate first set of N random numbers with a mean of 0.5 and a fixed standard deviation (SD1). This set represents the distribution of ‘starting preference (SP)’ for N animals for demoFlavor. Each value represents SP for one virtual animal. 
    2. Generate second set of N random numbers with a mean of 0.5 and fixed standard deviation as of first set (SD1). This set represents distribution of random preference component (RP1) of N animals for demoFlavor during virtual pre-STFP test. 
    3. Generate third set of N random numbers with mean 0.5 and standard deviation SD1. This set represents distribution of random preference component (RP2) of N animals for demoFlavor during virtual post-STFP test.
    4. Evaluate the virtual pre-STFP preference (P1) by incorporating contributions from SP and RP1 weighted by the parameter ‘i’ using following formula:

      P1 = i.SP + (1-i).RP1

    5. Evaluate the virtual post-STFP preference (P2) by incorporating contributions from SP and RP2 weighted by parameter ‘i’ using following formula:

      P2 = i.SP + (1-i).RP2

      Note: Three values of parameter ‘i’ considered are 0.1, 0.6 and 0.9 representing minimal, intermediate and maximal contributions of innate preference, respectively.
    6. Get the change in preference (ΔP) as the difference between P2 and P1.
    7. For estimating the variations arising due to selective and random demonstration, sort corresponding ΔP values according to the ascending order of P1 values. Following this proceed in following two manners:
      1. Select all the values of ΔP corresponding to P1 < 0.5. Plotting this subset of ΔP w.r.t P1 will give the distribution of N/2 preference values arising due to selective demonstration. This case is analogous to the scenario when demoFlavor is selectively chosen based on pre-STFP data.
      2. Select ΔP for every alternate P1 value resulting in total N/2 values with P1 ranging between 0 < P1 < 1. Plotting such ΔP values w.r.t P1 will give a distribution of N/2 preference values arising due to random demonstration. This case is analogous to the scenario when half the animals are randomly chosen for either demoFlavor without considering pre-STFP data.
      3. Compare statistical parameters of both ‘a’ and ‘b’ distributions to evaluate any differences in estimating ΔP.
    8. Repeat 1-7 for different standard deviations (SD2, SD3 etc.) in order to maximally cover the naturally occurring variability in SP and RP distributions for the population (Figure 5).

      Figure 5. Change in preference (P2-P1 i.e., ΔP) plotted w.r.t the standard deviations (SD) for SP and RP distributions. Only for the scenario when contribution from innate preference is almost negligible (i = 0.05), we observe increasingly different ΔP selective demo (open circles) from ΔP random demo (Square) as population accommodates highly diverse preferences (increasing SD). For all other scenarios, specifically w.r.t cases having dominant contributions from innate preference (0.5 < i < 0.95), we observe that there is no difference between ΔP selective demo and ΔP random demo, even for diverse populations with higher SD.


  1. X% ‘Condiment’ flavored food
    X g of ‘condiment’ powder mixed with (100-X) g of freshly ground food pellets
    Note: We have predominantly used two flavor pairs, i) cocoa (2%) and cinnamon (1%) and, ii) thyme (1%) and basil (0.8%). For both mice groups, plain powdered pellets are mixed with respective flavor to make flavored food (for 2.0% cocoa flavored food, 2 g of powdered cocoa is mixed with 98 g of plain powdered pellets). We acquired commercially available condiments as flavoring agents (SNAPIN herbs and spices, Lotus household product, India). We have chosen the flavor concentrations based on previous studies (Holmes et al., 2002; Ross and Eichenbaum 2006; Smith et al., 2007; Lesburguères et al., 2011) and from pilot experiments conducted in our lab.
  2. Cleaning solution
    0.1% sodium hypochlorite solution in filtered tap water


This protocol has been adapted from a recent study published from our lab (Singh et al., 2017). This work was supported by Department of Science and Technology grants DSTO/BCN/BJ/1102 (Ramanujan Fellowship to JB) and DSTO/BCN/BJ/1297, Department of Biotechnology grants DBTO/BCN/BJ/0402 and DBT-IISc Partnership Program, Tata Trust grant JTT/MUM/INST/IIOS/201314/0033 and Council for Scientific and Industrial Research grants CSIR-09/079(2590)/2012-EMR-I (CSIR Fellowship to AS). The authors have no conflicts of interest.


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在示威者和天真饥饿的观察者之间的啮齿动物中观察到食物偏好(STFP)的社交传播。 在社交互动中,饥饿的观察者收到有关示威者消耗食物安全的信息。 为了测试啮齿类动物的海马依赖性非空间记忆,已经实施了这个任务来开发单一试验的非厌恶性学习任务。 在这个协议中,我们描述了对传统STFP协议的一些新的修改,并分析了对偏好变化的更敏感的估计。 使用这种方法,可以在训练后的几个星期观察偏好趋势,使人们可以探索系统整合(SC)在相对独立于空间导航的声明性记忆中的作用。
【背景】Bennet G Galef Jr.在20世纪70年代为了测试记忆机制而开发了基于STFP的大鼠行为模式,并且从那以后,它已经用大鼠和小鼠进行了各种研究(Galef Jr,1977; Clark等人, 2002; Wrenn等人,2003; Ross和Eichenbaum,2006; Smith等人,2007; Choleris等人, ,2011;Lesburguères et al。,2011; Clark,2012)。在啮齿动物的情况下,这种范式的基本前提来自他们的自然摄食行为。示范小鼠[DemoMice]通过反复试验找到安全食用的食物,食用后不久,与其他观察小鼠[ObMice]通过社交互动共享美味食物的信息。这种相互作用发生在远离饲养场所的地方,在那里,当ObMice与DemoMice的某些呼吸成分一起被检测到时,ObMice知道所食用的食物的安全性,或者更具体地说是所消耗的风味(Galef等, 1988; Choleris等人,2009)。在STFP范式中建立这样的风味 - 安全性关联后,已经观察到ObMice优选消耗所示的风味(demoFlavor),当在新颖味道和熟悉味道之间进行选择时。


此外,传统的偏好估计涉及比较在会话之前和之后记录的食物容器的重量,以计算“食物的重量”(W•F•F•)。在一个典型的小鼠STFP测试过程中,每个人消耗约1克重物,并从重达近100克的容器中溢出重达约5克的食物(典型的容器重量必须是〜100克以防止倾倒)。纠正与溢出相关的误差限制了WF的准确性。因此,它使得难以检测风味 - 安全关联的强度和性质的微小变化。或者,我们提出并利用通过视频分析获得的“食物消费事件的数量”来衡量绩效。使用这种方法,我们建立一个易于实施和更灵敏的STFP程序。本质上,与重量测量相比,这样的分析易于使用且不易出错。他们利用更多的数据点,因此他们传达更多的信息相比单点测量,如消耗的食物的总重量或消耗总时间。由于小鼠在延长的时间窗口内消耗少量食物,因此不能直接使用食物摄入数据来观察食物消耗率的变化。

关键字:遥远记忆, 社会性食物偏好传递(STFP), 小鼠行为, 敏感性, 表现, 口味, 先天偏好


  1. 相同的塑料容器(图1A和1B):尺寸6.5×4.5厘米,组装重量〜100克(朱莉娅宠物罐130毫升)(普林斯特,目录号:9462)
  2. 由不均匀的平均直径为3-4mm的玉米芯颗粒(Spar Cobb,Sagar Industries,Bangalore,India)制成的床上用品。
  3. 食物容器:将用于较小塑料容器的盖子用作食物容器(图1)(Julia Pet Jar 60ml)(Princeware,目录号:9461)
  4. C57 / B6小鼠(雄性,8-12周龄)断奶后成对饲养,直到适应阶段开始。为了在我们的实验的相互作用期间清楚地从示威者身上识别观察小鼠,在断奶一周后,在全身麻醉下在每个耳廓中标记一个孔。在第一次习惯性会议之前将动物分开以供个人住房。每组12-16只小鼠在统计分析期间提供可接受的功率。在12小时光照/黑暗循环中饲养小鼠,所有实验在开光阶段(06:30 AM-18:30PM)进行。所有涉及动物的程序均经过动物伦理学委员会IISc Bangalore的批准 注意:一个重要的考虑是断奶后观察员鼠标与示威鼠标的共同住房。在我们的方法中,我们在社交交互过程中不使用Wire Mesh / Screen来分离ObMice和demoMice,以便鼠标交互类似于它们的自然设置。为了避免在社会交往中过度的战斗,我们随机选择两只刚断奶的老鼠,并将它们共同放置在同一个笼子里一个月。在大约2个月的年龄,这些老鼠分开安置进行议定书的进一步步骤,其中一人被指定为其同伴的示威者。两只熟悉的雄性老鼠之间的社交互动可能也有助于使其更有效地与陌生男性相互作用。因此,同时收集大量可比较年龄组的小鼠至关重要。无论是观察者还是演示者鼠标,都可以通过在他们的耳廓上打一个洞来标记,以便在社交互动会话之后正确识别它们。
  5. 小鼠食物颗粒(Nutrilab啮齿动物饲料,Provimi)
  6. 作为调味剂的粉末调味品(可可,肉桂,百里香,罗勒; SNAPIN草药和香料,莲花家用产品,印度)
  7. 70%的乙醇清洗食品设备的所有组件
  8. 次氯酸钠溶液(4%NaOCl溶液)(Fisher Scientific,目录号:SS290-1)
  9. X%'调味品'调味食品(见食谱)
  10. 清洁解决方案(见食谱)


  1. 制作金属托盘的钳子
  2. 用于金属托盘的涂料:如果使用黑色外套小鼠,则使用白色涂料,反之亦然
  3. 透明的有机玻璃板沿中央短轴钻孔(图1E)
  4. 铝/锡金属片(尺寸适合测试笼):1-2毫米的厚度,使防溢托盘容纳食品容器。这些托盘的垂直墙壁高2厘米。这些托盘的长度和宽度可以调整,以达到测试笼内的最佳配合。对于我们的设置,尺寸是16×13厘米
  5. 称重平衡:灵敏度高达10毫克
  6. 电子粉碎机(Morphy Richards,型号:Icon Essentials)用于制作粉状食品
  7. 全高清网络摄像头(罗技,型号:C920)用于多路复用视频监控
  8. 偏光镜滤光片(RG610,RG系列彩色玻璃滤光片,Optica,Optics India;它是可选的),以避免透明有机玻璃覆盖测试笼的反射
  9. 摄像头安装组件:我们使用了一根长的木棒(300×10×5厘米3),沿其长度方向在中心有一个孔,并用一个M6螺丝将摄像头固定在测试笼组件上方/>
  10. (IVC; 36长×14宽×12.5厘米高)(Citizen Industries,目录号:11)
  11. 便携式电钻(罗伯特•博世,型号:博世GSB 10 RE专业版)带有钻头,可在食品容器的盖子上制作1厘米直径的孔


  1. 免费的开源媒体播放器,如VLC。任何用于位置跟踪的软件也可以用于估计在食品容器附近花费的时间
  2. Origin软件
  3. Microsoft Excel
  4. ImageJ插件(如分析粒子)


  1. 初步要求
    1. 饲养设备的设计(图1A和1B):这包括一个圆柱形食物容器,其盖子上有一个孔,一个小食物容器和一个用于收集溢出食物的铝托盘。
      1. 必须使用相同的塑料容器。盖子应该足够平坦,让老鼠坐在上面吃东西。
      2. 每个塑料容器的盖子在中心钻一个1厘米直径的孔。所有容器中的孔必须具有相同的直径。
      3. 在底部的容器中充满床上用品,顶部留下约1厘米。
      4. 1厘米高的小圆柱形食物容器装满粉末食物并保持在底部容器内。
      5. 将食物容器的盖子垂直对准其中心。食物应该可以通过盖子上的孔进入。

        (C);图1.食品消费期间使用的食品设备(A,B)的设计(C);在食物消费和社交互动环节(D)期间,测试笼子被透明的有机玻璃板(E)覆盖。所有观察小鼠在偏好测试期间在两套相同的食物设备中提供粉末食物。 A.食品容器的部件包括装有放置在底部容器内的粉状食物(未示出的粉状食物)的食物容器。通过在其中心钻一个1厘米直径的孔来修改盖子,以提供食物。 B.在底部的容器中充满床上用品,只留下足够的空间放置食物容器。 C.在偏好测试期间从其中一个食物容器中消耗食物的小鼠。两个食品容器在其设计的每个方面都是相同的。如果溢出的食物与笼中的垫料混合在一起,在估计净消耗量时就非常难以计算。为了尽量减少在消费过程中不可避免的溢出,每个饲养设备都包括一个定制的铝托盘来保存食品容器。用一小块双面胶将食品容器轻轻地粘在金属托盘的中心。 D.观察员和示威者小鼠之间的社交互动。示范小鼠是由他们的耳廓耳洞确定。 E.测试笼的侧视图覆盖透明的有机玻璃板,以避免老鼠在视频监控时逃跑。
      6. 一小块双面胶带(1×1厘米)连接到溢出收集盘的中心。称量食品容器后,将其固定在溢出收集盘上。溢出收集盘是通过弯曲薄金属片制成的。它的尺寸可以根据测试笼来决定。

      7. 。容器在底部暂时贴上标签,并标出它们在每个测试笼中的位置
    2. 网箱组装和录像设置
      1. 试验室的地板/矮桌上,将具有被褥材料的试验笼放置在一个矩阵中。根据小鼠的数量,可以使用3 x 3,3 x 4或4 x 4矩阵来安排测试笼。
      2. 在所有透明/半透明的笼子之间放置视觉阻隔物是重要的,以避免小鼠间的视觉干扰。我们在实验过程中放置纸板(高15厘米,厚3毫米,长度根据笼子布置)以保持测试笼之间的完全可视块。
      3. 测试笼用透明的有机玻璃板覆盖(图1E),用于所有笼子的顶视图(图1C和1D)的多路复用视频记录。
      4. 每个有机玻璃板沿短中心中线钻有小孔(直径3-5毫米),用于空气循环(图1E)。
      5. 摄像头安装在4英尺高的地方,使用定制的支架,使得每个测试笼覆盖视场中的等同区域,并且所有的笼子都处于聚焦状态。

  2. 该程序的步骤
    我们的STFP行为方案已经在十个步骤中进行了解释,包括1)断奶,2)单笼中两只小鼠的随机配对共同住房,3)处理,4)配对小鼠作为观察者和示范者的分离,5)习惯性(5- 7天),6)用于鉴别不太优选的风味物作为待展示风味物的STFP前嗜好测试(1天),7)为将要演示的风味物供给各自的演示小鼠,8)社交互动(1天),9)在最近的时间点进行STFP后偏好测试(每个1天),10)在远程时间点(图2)后STFP偏好测试(每个1天)。 STFP之前的偏好,社交互动和检索测试都是在同一个房间里,但在不同的日子里进行的。所有的动物被安置在独立通风的笼子中,以防止演示者和观察者小鼠之间的嗅觉,听觉或视觉线索的不必要的转移。如果没有单独通风的笼子,则保持和测试室必须是分开的。清洁空气循环器和排气口不断打开,以防止以往会议的气味保留。在实验过程中,清洁空气进口关闭了一个小时。


    1. 断奶
    2. 随机配对住房
    3. 处理
      1. 第1天
      2. 第二天
      3. 第3天
        从第1天和第2天开始遵循相同的手套更换规则 注意:如果动物跳跃并落在笼子里(在地板/桌子上),轻轻地抬起动物,把它们放回笼子里,并且只在第二天恢复这种动物。事先做好安排,使松鼠无法进入所有隐藏的角落。
      4. 第4/5天
    4. 分居同居的动物:在适应期开始之前,同居的动物被分开并安置在不同的笼子中。在所有的互动环节中都需要使用同样的情侣来避免战斗和压力。所有的单独通风笼养单只动物的笼子都放在同一个房间里。
    5. 习惯
      1. 食物的准备,分配和称量:在每次会议之前,定期的食物颗粒被磨碎。食物准备在最小空气流量设置的通风罩。
        1. 每个食物容器装满粉末颗粒并封装在食物容器中。
        2. 根据每个容器相对于测试室的相对位置作为参考,仔细记下每个容器的重量。
        3. 每个食物容器都保存在一个轻便的金属托盘内,用于收集溢出的食物。
        4. 示范小鼠在家笼内给予饲喂装置,并允许食物消耗1小时。
        5. 首先将观察小鼠放入测试笼中各自的位置。然后,两套喂食设备被相继引入。下面的注释中列出了为避免有偏见的食物分配而需要考虑的一些重要因素。
        6. 称重程序:在会前和会后记录食物容器的重量。溢出的食物间接称重。在称重托盘之前,任何笼子垃圾都被移除。装满溢出食物的托盘在称重后记录下来并称重。然后将托盘彻底擦干,以除去任何粘着粉末的食物,并重新称重。托盘的这两个重量的差异被称为“溢出的食物”,并且从食物容器的“前后”重量的差异中减去以获得“净消耗量”。风味A的偏好是根据容器A的净消耗量与一小时内从两个杯子消耗的总食物的比率来计算的。
      2. 第1天
        在食物消耗过程中,水被去除 观察小鼠:
        1. Objice单独放入包含床上用品的试验笼中,进行1小时的消耗。
        2. 然后将含有食物容器的托盘置于每个笼子中,同时遵循上述的伪随机化过程。
        3. 在会议结束时,所有的小鼠都从试验笼中取出,而不会打扰饲养设备,并将其放回笼中。
        4. 所有小鼠在会议后给予重约1克的固体食物颗粒。这导致每天食物剥夺〜15小时。
        5. 将进料装置从每个试验笼上单独取出,按前述方式仔细称重以计算净消耗的食物,并拆除彻底的清洁,包括用无味的清洁剂/漂白剂清洁,用温水清洗并在暖空气流中干燥。
      3. 2-7天
    6. STFP之前的偏好测试
      1. 食物的制备,分配和称量:
        1. 在开始测试期间之前,将粉状食物颗粒与商业获得的香料以所需比例(%w / w)混合。见“食谱”。
        2. 在偏好测试中,将一种香料的新鲜制备的食物装入食品容器中,然后将其保存在容器内。首先装配具有相同风味的容器。
        3. 彻底擦去地方以去除任何以前味道的痕迹,剩余的容器装满含有其他香料的粉末食物,剩余的容器被组装。

        4. 对于观察者习惯的步骤'我到v'进行跟进
        5. 称重是以上述方式进行的。
      2. Objice允许从保存在组件中各个位置的测试笼中的两个容器中消费调味食物。完整的会议是视频录制的重量测量。
      3. 基于重量估计,每个观察者小鼠被确定为喜欢风味A或风味B.在这一点上风味的选择最可能代表他们对两种风味之一的先天偏爱。注意到在STFP前测试24小时之后的社交相互作用期间,在STFP前测试期间优选风味物A的每只小鼠将用风味物B证明,反之亦然。由于对任一种香料的偏好范围在0-1之间,所以对于香料A具有超过0.5的偏好的ObMice将用B来证明,反之亦然。
      4. 在STFP测试前,可能会有一些ObMice消耗相同数量的两种口味。将这些小鼠中的一半分配给A偏好组,另一半分配B偏好组。
    7. 示范者喂食:来自共同饲养的对的各个示范小鼠在相应的观察者进行STFP前测试的情况下喂食1小时。这种喂养发生在示范小鼠的独立通风的笼子里。
    8. 风味演示的社交互动(STFP)
      1. 在喂养结束时,将示范小鼠释放到相应的,预先分配的观察小鼠的测试笼中,进行一小时长的社交互动。
      2. 在互动会议结束时,所有的老鼠都被关在各自的笼子里。
      3. 交互会话也是视频监控。
    9. 最近的内存测试
    10. 远程内存测试



  1. 使用重量测量的偏好估计
    1. 为了定量地表示样本偏好w.r.t或者权重或者时间作为度量,我们定义平均偏好如下:

      非Dem 分别是demoFlavor和non-demoFlavor的消费重量; 和 T 非Dem 是在demoFlavor和non-demoFlavor容器附近花费的时间。

  2. 使用食物杯附近的时间进行偏好估计
    1. 录像
    2. 手动评分
      1. 在两个食物容器放入带有鼠标的测试笼中之后,开始一个会话。
      2. 如前所述,以30fps记录视频,连续观察所有笼,并且在每10秒即300帧后记录小鼠位置。这导致每个3小时的每个1小时的视频得分给每个小鼠360个数据点。记分员应该在进球时对食物杯中的风味信息视而不见。
      3. 每个笼(C1,C2 等)在手工记分表中分配2列(图3A,见样本excel表这里)记录小鼠的位置,同时得分。
      4. 跟踪手动记分的方法之一可能如下:如果动物在笼子的左半边,那么'a'斜对角线。如果动物在笼子的右半部分,那么'b'是交叉的。如果动物在笼子的中心,则在A和B之间写入“©”。为避免标记错误,连续笼子的a和b以不同的字体打印(图3A)。 “a,b和©”可以用选择符号代替。

        图3.人工评分的示例表(左)和用于处理人工评分的示例Excel表(右) A. C1表示笼子1;当手动记分时,视频在每10秒钟后暂停,记录鼠标在鼠笼中的位置(参见上面的手动记分步骤'd')。 B.手动评分完成后,将小鼠的位置记录在分析表中。在第一个10秒窗口(第一行标有时间“0”),如果发现鼠标在笼子的右半部分,通过在标题为“笼子的右半部分”栏中输入“1”来记录交叉“b”视频“等。将所有数据翻译成excel表单后,运行一个宏来识别饮食情节。随后的时间窗口的累积饮食情节,然后绘制产生累积时间配置文件。

    3. 自动评分
  3. 处理来自手动评分的原始数据
    1. 所有来自评分表的小鼠位置都输入到 Excel数据表进一步分析(图3B)。对于每个笼子,Excel表格包含表示笼子的左侧,中间和右侧区域的3列,以及360行单元,每个表示10秒的视频。手动评分完成后,将小鼠的位置记录在分析表中。
    2. 一个笼子区域的总时间是一列中全部“1”的总和的10倍(因为每个“1”代表10秒)。在我们的视频中,我们观察到鼠标访问某个地区的时间并不总是很短。我们发现,如果我们将饮食发生时间定义为30秒或更长时间,则停留时间与食物消耗高度相关。简单地说,根据我们在视频监测过程中观察到的相关性,我们可以有把握地认为,老鼠每当他们在一个地方度过了30秒以上,就会消耗食物。现在这种等于或长于30秒的持续时间现在被称为“吃饭事件”。因此,为了计算在食物杯附近花费的总消耗时间,使用视觉基本宏,我们只计算在相同位置连续出现三个或更多“1”的数据点。换句话说,为了计算一个地点的总时间,当鼠标连续停留30秒(900帧)或更长时,只有这些访问被认为是“吃东西”。当鼠标位置被标记在笼子的中心时的实例不计算计算偏好。
    3. 将所有数据翻译成excel表格后,运行一个视觉基本宏来识别饮食情节。然后绘制随后时间窗口的累积饮食情节以产生累积时间概况。宏识别并将有关在食品容器附近花费的时间的信息分类为“吃饭情节”(这个宏只是选择60秒长的情节的一个例子,它需要根据情节的持续时间,总消耗时间和

      Sub DataAnalysis()
      Dim row As Long
      Dim column As Long
      Dim newcol As Long
      newcol =#(在运行宏后需要数据的地方输入栏#)
      对于column =#to#(输入输入原始数据的列号)
      对于row =#to#(输入输入原始数据的行号)
      sum = WorksheetFunction.sum(Sheets('Sheet1')。Range(Cells(row,column),Cells(row + 5,column)))
      如果sum = 6那么
      单元格(row,newcol).Value =单元格(行,列)。值
      单元格(row + 1,newcol).Value =单元格(行+ 1,列).Value
      单元格(row + 2,newcol).Value =单元格(行+ 2,列).Value
      Cells(row + 3,newcol).Value = Cells(row + 3,column).Value
      单元格(row + 4,newcol).Value =单元格(行+ 4,列).Value
      单元格(第5行,newcol).Value =单元格(第5行,列)。值
      单元格(row + 6,newcol).Value =单元格(row + 6,column).Value
      End If
      newcol = newcol + 1
      End Sub

    4. 时间窗口

  4. 累积时间配置文件(CTP)以及从吃饭事件生成CTP的步骤 使用消费模式作为预测保留的诊断:

    这些参数也可能从食物的含水量和稳定性有一些贡献 为了更有效地监测STFP模式中动物的平均消费特征,我们扩展了这一分析。我们绘制累积的饮食情节作为时间的函数来获得小鼠的平均消费情况。累计时间曲线(CTP)表示连续5分钟的时间窗口中进食一小时的消耗时段的总食入次数的变化(细节在“数据分析”部分中解释)。因此,拟合CTP的相应函数是威布尔函数的积分,即由下式给出的威布尔累积分布函数(CDF):

    1. 在笼子的任一半中花费的时间量是以每只小鼠的进食情况来衡量的。
    2. 总计每个时间段的饮食情节,以计算在食物消耗中累积的时间。对于每个时间窗口,每个食物杯附近的累计时间是所有小鼠的平均值。
    3. 每个时间窗的平均累积计数与时间作图,以获得在两个食物杯附近花费的平均时间的累积时间曲线(图4)。
    4. CTP被拟合为Weibull函数的积分,我们称之为Weibull累积分布函数(WeibullCDF)。然后使用单向ANOVA来比较连续会话中的CTP。完整的统计分析和拟合程序的细节已经在最近的一项研究中得到了解释(Singh et al。,2017)。
    5. 将CTP拟合到Weibull的步骤功能:Origin软件用于使用线性和非线性函数拟合消耗模式数据。包装提供线性配合。对于使用威布尔函数的非线性拟合,我们在原始包中提供的函数生成器中添加了代码,如下所示:
      分析→拟合→非线性拟合→打开对话框→创建新的拟合函数→选择类别为“生长/ Sigmoidal”→命名为“Weibull CDF”( ie ,Weibull累积分布函数)→函数模型设置为'Explicit'→函数类型设置为'Expression'→自变量设置为'x'→从属变量设置为'y'→参数设置为'A,b,d,k'→函数体写为'A (1-exp( - (k•x)d))+ b'。
      注意:在将CTP拟合到Weibull累积分布函数(WeibullCDF)时,四个参数所需的参数初始化值如下:A = 1,000,b = 100,d = 1,k = 0.01。

      图4.表示两种偏好测试的demoFlavor和non-demoFlavor的消费模式的累积时间配置文件(CTP):pre-STFP(左侧面板)和STFP后24小时(右侧面板)。 正如在STFP前CTPs中所指出的那样,在社交互动中选择较低偏好的味道(空心钻石)作为示范。 24小时后,观察小鼠在与试验小鼠的社交相互作用期间表现出较不优选的风味,所述示范小鼠被喂食待展示风味一小时。没有证明具有更高偏好的味道。在STFP后24小时,CTP适合性仅表示对demoFlavor的偏好的增加。两个CTP均符合Weibull累积分布函数(WeibullCDF)。适合风味B的CTP也可以通过线性拟合同样地近似。每个数据点表示在各个时间窗内进食情节的总和。这些数据是之前发表的研究的一部分(Singh等人,2017年)。这里是为了代表性的目的而绘制的。


  5. 在STFP期间随机与选择性演示的模拟比较
    以前的研究很少考虑STFP与啮齿类动物行为的先天偏好的影响。为了适应动物天生喜好对示范后偏好改变的贡献,在我们的方案中,我们引入了STFP前测试,随后是味道的“选择性展示”(Singh等人, 2017)。
    为了模拟STFP,我们假设在每个偏好测试期间估计的偏好具有两个主要组成部分,i)对demoFlavor启动偏好(SP)组件,以及ii)对于demoFlavor的随机偏好(RP)组件。假定相应的SP和RP集合具有相同均值(0.5)和标准差的分布。此外,两个组成部分的贡献是用参数i来加权的,这个参数代表了动物对自然偏向或先天偏好的贡献的大小。参数'i'的范围在0&lt;我&lt; 1.
    1. 生成第一组N个随机数,平均值为0.5,固定标准偏差(SD1)。这个集合代表了用于demoFlavor的N个动物的“首选偏好(SP)”的分布。每个值代表一个虚拟动物的SP。&nbsp;
    2. 生成第二组N个随机数,平均值为0.5,固定标准偏差为第一组(SD1)。这个集合表示在虚拟pre-STFP测试期间,用于demoFlavor的N个动物的随机偏好分量(RP1)的分布。&nbsp;
    3. 生成第三组N个随机数,平均值为0.5,标准偏差为SD1。这个集合表示在虚拟post-STFP测试期间,用于demoFlavor的N个动物的随机偏好分量(RP2)的分布。
    4. 通过使用以下公式来加入来自SP和RP1的加权参数“i”的贡献,评估虚拟pre-STFP偏好(P1):

      P1 = i.SP +(1-i).RP1

    5. 通过使用以下公式来加入参数'i'加权的来自SP和RP2的贡献来评估虚拟后STFP偏好(P2):

      P2 = i.SP +(1-i).RP2

    6. 获得偏好的变化(ΔP),作为P2和P1之间的差异。
    7. 为了估计由于选择性和随机演示而引起的变化,根据P1值的升序对相应的ΔP值进行排序。接着按以下两种方式进行:
      1. 选择对应于P1的所有ΔP的值0.5。绘制这个ΔPw.r.t P1的子集将给出由于选择性论证而产生的N / 2偏好值的分布。这种情况类似于基于pre-STFP数据有选择地选择demoFlavor的场景。
      2. 为每个交替的P1值选择ΔP,得到P1范围在0&lt;&lt; P1&lt; 1.绘制这样的ΔP值将会给出由于随机演示而产生的N / 2偏好值的分布。这种情况类似于在没有考虑STFP前数据的情况下随机选择一半动物的场景。
      3. 比较“a”和“b”分布的统计参数,以评估ΔP的任何差异。
    8. 对不同的标准偏差重复1-7(SD2,SD3等),以最大限度地覆盖群体中SP和RP分布的自然发生变化(图5)。

      图5.偏好(P2-P1 即,ΔP)的变化与SP和RP分布的标准偏差(SD)作图。仅适用于先天偏好几乎可以忽略不计(i = 0.05),随着人口适应高度多样化的偏好(增加SD),我们观察到来自ΔP随机试验(Square)的日益不同的ΔP选择性演示(空心圆圈)。对于所有其他情况,特别是具有先天偏好(0.5 )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。


  1. 的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">X%'调味品'调味食品
    X g调味品粉末与(100-X)g现磨食品颗粒混合
    注:我们主要使用两种风味对,一种是可可(2%)和肉桂(1%),二是百里香(1%)和罗勒(0.8%)。对于两个小鼠组,将普通粉末颗粒与各自的风味混合以制成调味食物(对于2.0%可可味食物,将2g粉状可可粉与98g普通粉末颗粒混合)。我们收购了市售调味品作为调味剂(SNAPIN草药和香料,莲花家用产品,印度)。我们根据以前的研究(Holmes等人,2002; Ross和Eichenbaum,2006; Smith等人,2007;Lesburguères等人,2011)和我们实验室进行的试验实验选择了风味浓度。
  2. 的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">清洁解决方案

的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。=""> 致谢

的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。=""> 该协议已经根据我们实验室最近发表的一项研究(Singh等人,2017年)进行了改编。这项工作得到科技部DSTO / BCN / BJ / 1102(Ramanujan Fellowship to JB)和DSTO / BCN / BJ / 1297,生物技术部拨款DBTO / BCN / BJ / 0402和DBT-IISc伙伴计划,塔塔信托基金授予JTT / MUM / INST / IIOS / 201314/0033和科学与工业研究理事会CSIR-09/079(2590)/ 2012-EMR-I(CSIR研究金)。作者没有利益冲突。

的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。=""> 参考

  1. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Choleris,E.,Clipperton-Allen,A.E.,Gray,D.G.,Diaz-Gonzalez,S.and Welsman,R.G。(2011)。 )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">多巴胺受体D1型和D2型拮抗剂的不同作用以及发情周期对社会的影响学习食物的喜好,喂养和社会交往的小鼠。 Neuropsychopharmacology 36(8):1689-1702。
  2. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Choleris,E.,Clipperton-Allen,A.E。,Phan,A。和Kavaliers,M。(2009)。 大鼠和小鼠社会信息处理的神经内分泌学前神经内分泌学30(4):442-459。
  3. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Clark,R。(2012)。 社会传播的食物偏好(STFP)任务协议。 Bio Protoc e224。
  4. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Clark,R.E.,Broadbent,N.J.,Zola,S.M。和Squire,L.R。(2002)。 顺行性遗忘症和暂时性分级逆行性遗忘症,用于海马和下肢损伤后的非空间记忆任务。 a> J Neurosci 22:4663-4669。
  5. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Fox,E.A。和Byerly,M.S。(2004)。 成人发病性肥胖的机制:脑源性神经营养因子突变体的脑吞噬表型的证据。 :R994-1004。
  6. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Galef Jr,B.G。(1977)。 食物偏好的社会传播:适应断奶的老鼠。 J Comp Physiol Psychol 91:1136-1140。
  7. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Galef,B.G.,Jr.,Mason,J.R.,Preti,G。和Bean,N.J。(1988)。 二硫化碳:一种化学信息介导的社会诱导的饮食选择大鼠 Physiol Behav 42(2):119-124。
  8. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Galef,B.G.,Jr.和Whiskin,E.E。(1998)。 挪威大鼠对食物选择的社会影响限制 行为举止< / em> 56(4):1015-1020。
  9. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Holmes,A.,Wrenn,C.C.,Harris,A.P.,Thayer,K.E。和Crawley,J.N。(2002)。 近交系对小鼠嗅觉,空间和情绪测试的参考记忆的行为概况一个基因脑行为 1(1):55-69。
  10. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Lesburguères,E.,Gobbo,O.L.,Alaux-Cantin,S.,Hambucken,A.,Trifilieff,P.和Bontempi,B。(2011)。 为了形成持久的联想记忆,需要及早标记皮层网络。 科学 331(6019):924-928。
  11. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Ross,R.S。和Eichenbaum,H。(2006)。 巩固非空间记忆过程中海马和皮层激活的动力学 J Neurosci 26(18):4852-4859。
  12. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Singh,A.,Kumar,S.,Singh,V.P.,Das,A。和Balaji,J。(2017)。 依赖风味保留偏远的食物偏好记忆 Front Behav Neurosci 11:7。
  13. )的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Smith,C.A.,Countryman,R.A.,Sahuque,L.L。和Colombo,P.J。(2007)。 获得和回忆社会传播的食物偏好后大鼠海马和新皮质中Fos表达的时程。 Neurobiol Learn Mem 88(1):65-74。
  14. 的主要贡献的情况,我们观察到Δp选择性演示和Δp随机演示之间没有差异,即使对于具有更高sd的不同群体也是如此。="">Wrenn,C.C.,Harris,A.P.,Saavedra,M.C。和Crawley,J.N。(2003)。 小鼠食物偏好的社交传播:方法论和应用于甘丙肽过表达的转基因小鼠 Behav Neurosci 117(1):21-31。
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引用:Singh, A. and Balaji, J. (2017). Sensitive Estimation of Flavor Preferences in STFP Using Cumulative Time Profiles. Bio-protocol 7(21): e2601. DOI: 10.21769/BioProtoc.2601.