Both short- and long-term social recognition was assessed in the social discrimination task. Mice were habituated to the experimental room for 30 min. After habituation to the room, the subject mouse was placed in a standard transparent housing cage (Makrolon type 2 L) with bedding for 5 min to habituate to the experimental environment. After habituation, during the learning phase, the subject mouse was exposed to an unfamiliar male stimulus mouse of the same age for 2 min to familiarize itself. Thereafter, the stimulus mouse was removed, followed by an inter-trial interval of 5 min. Subsequently, during the short-term testing phase, the familiar mouse and a novel mouse (novel 1) were put in the cage with the subject mouse for another 2 min to test short-term recognition. The long-term testing phase took place 24 h after the learning phase. The test was carried out with the familiar mouse and a second novel mouse (novel 2). Before the long-term testing phase, the subject mouse habituated for 5 min to the testing environment. The trials were recorded, and social interaction with conspecifics was scored using The Observer XT 14 (Noldus Information Technology BV, Wageningen, the Netherlands).
Observer xt 14
Manufactured by Noldus
Sourced in Netherlands
The Observer XT 14 is a software solution for observational research, data logging, and behavioral analysis. It provides a comprehensive platform for recording, coding, and analyzing behavioral data from various sources.
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Lab products found in correlation
9 protocols using observer xt 14
1
Social Recognition Memory in Mice
2
Buried Food Test for Olfactory Ability
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The buried food test was carried out to assess general olfactory ability (Yang et al. 2012 (link)). Prior to the test, the subject mouse was food-deprived for 18 h. The test was performed in a standard transparent housing cage (Makrolon type 2 L) containing 3 cm of clean bedding material. Mice were allowed to habituate for 5 min; subsequently, the mouse was briefly removed from the cage and a small food pellet (1 cm3) was buried approximately 1 cm underneath the bedding in one of the corners. The subject mouse was placed back into the cage and the latency to dig and uncover the food pellet as well as the latency to eat the food pallet was scored using The Observer XT 14 software (Noldus Information Technology BV, Wageningen, the Netherlands).
3
Oviposition Behavior and Egg Identification
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Films of oviposition behavior were analyzed using The Observer XT 14 (Noldus, Wageningen, Netherlands). Data were subjected to statistical analysis using SPSS 11.0 for Windows (SPSS, Chicago, IL, USA). One-way analysis of variance (ANOVA) was used to compare the time cost of different behaviors and the mean numbers of eggs for different substrates in the oviposition preference tests. MEGA 7.0 software (https://www.megasoftware.net/ ) and Figtree 1.4.3 (http://tree.bio.ed.ac.uk/software/figtree/ ) were used to analyze the gene sequences for the larvae that hatched from unknown eggs and the larvae of E. scrobiculatus and E. brandti.
4
Observational Coding of Childhood Behaviors
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The research associate filmed 15-min videos of each child at each time point of the study. Five undergraduate research assistants and a doctoral graduate student masked to group (intervention vs. waitlist) and time (pretreatment vs. post-treatment vs. follow-up) coded these videos in randomized order using the BASC-3 SOS initially in Noldus The Observer XT 14, a software program to record behavioral observation data (Noldus Information Technology, 2017 ) and subsequently in Excel due to the necessity of working remotely without access to the Noldus software due to COVID-19. Importantly, coding in Excel followed the same procedure and yielded the same data as the original coding approach in Noldus. Coders were trained by reviewing the operational definitions of BASC-3 SOS behaviors and examples of these behaviors, observing a trained coder to learn the coding procedure, and then coding practice videos prior to coding a reliability set of three videos. New coders were required to meet ≥ 80% inter-rater agreement (as measured by coefficient kappa) with a trained BASC-3 SOS coder on each behavior before coding participant videos. A working document of examples of each behavior was maintained throughout the coding process to promote consistent coding of situations that occurred in early childhood classrooms (see supplemental material).
5
Observing Movement Behavior via Video Coding
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Go-Pro video files were imported into the Noldus Observer XT 14 software (Noldus Information Technology, Wageningen, The Netherlands) for continuous direct observation coding. A customized direct observation scheme was implemented in which the participant’s movement behavior was coded as one of the five activity classes predicted by the activity classification models [26 (link)]: sedentary (SED), light activities and games (LIGHT_AG), moderate-vigorous activities and games (MV_AG), walking (WALK), and running (RUN). A description of the activity classes is provided in Table 1 . If a participant was not in view of the camera, movement behavior was coded as “out of view”. The computerized direct observation system generated a vector of date-time stamps corresponding to the start and finish of each movement event, which were used to calculate the event duration and assign the activity codes to the corresponding time segments of the accelerometer data. The inter-observer reliability was assessed by having two researchers independently code five randomly selected videos. Cohen’s unweighted kappa statistic for activity class was 0.86 (95% CI: 0.84–0.88), which, according to the ratings suggested by Landis and Koch [27 (link)], is almost perfect agreement.
6
Direct Observation of Children's Physical Activity
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Video files were imported into the Noldus Observer XT 14 software (Noldus Information Technology, Wageningen, the Netherlands) for continuous direct observation coding ( 21 ). A customized two-stage direct observation scheme was implemented in which the participant's movement behavior was coded as one of the five activity classes predicted by the Trost laboratory-based classifiers and then activity type, using a list of 23 developmentally appropriate physical activities for children. Table 1 provides a complete listing of the codes. If a participant was not in view of the camera, movement behavior was coded as "out of view." The computerized direct observation system generated a vector of date-time stamps corresponding to start and finish of each movement event, which were used to calculate event duration and assign the activity codes to the corresponding time segments of the accelerometer data. Interobserver reliability was assessed by dual coding of five randomly selected videos. The intraclass correlation coefficient for coding activity class was 0.912 (95% conference interval [CI] = 0.866-0.942) and 0.927 (95% CI = 0.889-0.952) for activity type.
7
Assessing Repetitive Behaviors in Mice
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To assess for repetitive behavior mice were first recorded for an hour in a normal housing cage (Makrolon type 2 L) with bedding and subsequently for 10 min in a housing cage without bedding. Four small objects (lego block, pion, dice, and marble) were put in the corners of the cage with bedding to stimulate exploration behavior. In the first 10 min of the recording, the following behavior was scored: rearing, jumping, grooming (in trials without bedding), and digging (in trials with bedding) using the Observer XT 14 software (Noldus Information Technology BV, Wageningen, the Netherlands). In addition, distance moved was tracked using the Ethovision XT 11.5 software (Noldus Information Technology BV, Wageningen, the Netherlands). Lastly, in the hour-long trials, repetitive locomotion patterns were analyzed as previously described (Bonasera et al. 2008 (link); Molenhuis et al. 2018 (link)). In short, the arena was divided into nine areas where the mouse spent an equal amount of time. Subsequently, the Theme software version 5.0 (Noldus Information Technology BV, Wageningen, the Netherlands) was used to detect patterns of locomotor activity and to calculate the total percentage of time a mouse spent in patterns.
8
Social Play Behavior Observation
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To examine social and emotional behavior, subjects were tested in highly familiar dyads similar to previously published protocols50 (link),73 (link) in a large novel social play cage (390 cubic feet). The social play cage was a hexagonal nonhuman primate social cage (Flex-A-Gon; Britz and Company, Wheatland, WY). There were six separate days of 45 min of testing for a total of 4.5 h of behavioral observations. Subjects entered the cage at the same time, but from separate doors that alternated sides of the cage each day. Each test day was videotaped for behavioral coding later using the Observer XT 14 software (Noldus Inc.) and a detailed ethogram (Supplementary Table 4 ). One experimenter coded all of the videotapes with a high degree of intra-rater reliability Cohen’s κ = 0.98; and an average inter-rater reliability of Cohen’s κ = 0.86 with other trained experimenters at YNPRC. Since the experimenter was not blind to the animals’ treatment, videos were coded without identifying information about the subject, which was revealed after coding was complete.
9
Behavioral Observation of Triangle Ringing
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