IntelliProfiler: Advancing Behavioral Analysis in Mice

Behavioral analysis using mice is important for studying how the brain works and identifying diseases. Mice are commonly used for these studies because they are easy to handle and can be genetically altered. Researchers study various behaviors in mice, such as walking, exploring, interacting socially, and remembering things. They use tests like the open field test and the elevated plus maze to measure these behaviors. However, traditional methods face challenges.

One major challenge is that traditional methods collect data slowly since they usually involve one mouse at a time. Most tests only record behavior for short periods in an unnatural setting. For example, in the open field test, researchers place one mouse in a large open space and track its movements. There's also a chance for human bias, as handling the mice can make them anxious, which may affect their behavior. Research has shown that the experimenter’s gender and environmental factors can influence the results.

To address these issues, researchers are looking for better ways to observe mouse behavior in more natural conditions. Recently, there have been advances in video tracking systems that use computer vision to monitor mouse movements. One such system is called DeepLabCut, which allows for precise tracking without needing markers on the mice. However, tracking many mice at once can be difficult with this system, especially when they are close together.

Another technique uses contactless RFID tags, which are small chips that can be attached to the mice. One system that uses RFID is called IntelliCage. It can automatically track mice as they explore their environment and interact with one another. Another RFID system, named ECO-HAB, allows researchers to observe mice moving between connected areas. Recent developments include RFID floor arrays that can monitor multiple mice at once. While these systems give valuable insights into group behavior, they often do not provide enough detail about individual movements.

In this study, we present a new RFID-based system called IntelliProfiler. This system can monitor multiple mice in a home cage setting. It can keep track of groups of four to 16 mice and provides better detail regarding timing and locations than previous methods. With IntelliProfiler, we conducted 72-hour continuous behavior monitoring in young and old male and female mice to see how aging affects Social Interactions within groups.

#Setting Up IntelliProfiler

To set up IntelliProfiler, we used an antenna board made of 96 antenna tiles arranged in a grid. This board was placed under a large cage with food and water for the mice. The software we developed for IntelliProfiler performs several tasks, including collecting data, calculating distances between mice, analyzing social interactions, and creating visual representations of the data.

After collecting the data, we converted it into a format that allows us to analyze each mouse's movements over time. The results were recorded for groups of four, eight, and 16 mice over 72 hours.

#Analyzing Activity in Group-Housed Mice

We focused on how group size affects the activity levels of male and female mice. For example, as the number of mice in a group increased, the total distance traveled by male mice often decreased. In the smaller group of four, the male mice showed the most activity right after they were introduced, and their activity declined after that before increasing again when lights were turned off. Female mice, however, displayed stable levels of activity, showing less variation across time and group size.

To compare differences further, we examined the overall trends in activity over longer periods. Male mice again showed the highest levels of movement in the smallest group, while the females maintained more consistent activity across the different group sizes.

#Social Interactions Among Mice

We also looked at how often mice interacted with each other by measuring the distance between pairs of mice. We categorized these distances into four types: “Same” when two mice were in the same grid, “Close” for adjacent grids, “Intermediate” for nearby grids, and “Away” when they were further apart. We found that in smaller groups, the mice spent more time close to each other, while in larger groups, they tended to be further apart.

For instance, in the four-mouse groups, the proportion of mice that were in the same or close distance increased during the light period and decreased during the dark period. Larger groups had a more consistent trend of social distancing, suggesting that larger group sizes might reduce social interactions.

To quantify how close two mice were to each other over time, we introduced a metric called the Close Contact Ratio (CCR). This measurement helps us understand how often two mice were in close proximity. Male mice had the highest CCR when in smaller groups, while female mice showed a lower CCR in larger group settings.

#Analyzing Aging Effects on Behavior

Aging can affect how mice behave, so we compared younger and older male mice in both small and larger groups. We found that older mice tended to be less active overall, especially in the eight-mouse group. However, in smaller groups, both young and old males showed significant movement.

The activity levels of aged male mice were also less distinct compared to younger mice, who exhibited more defined patterns of behavior. The differences in social proximity were notable, with older males spending more time in the “Intermediate” category, suggesting a change in their social dynamics as they aged.

#Characterizing Group Behavior

We also looked at group behavior through a method called principal component analysis (PCA) to understand how different factors like sex, group size, and age influenced activity and social interactions. The behaviors of male mice in the largest groups formed a distinct cluster, while smaller groups saw more mixing of male and female mice.

When we examined aging effects within groups, we found that younger mice generally behaved differently than older mice, with younger males showing more active and diverse social interactions. This shows that aging influences not only how active the mice are but also how they interact socially.

#Network Analysis of Social Interactions

We used network analysis to study how group size influences social interactions. In larger groups, male mice developed more complex networks of interactions, while female mice maintained a more uniform structure. With younger males showing greater social closeness and varied networks compared to older males, we could see how aging impacts social structure in mice.

#Individual Social Interactions

Lastly, we assessed individual mice's social interactions and noticed variability in behaviors, particularly in larger groups. While there were no significant differences based on sex in smaller groups, larger groups often displayed distinct patterns based on individual mouse behavior.

#Summary and Future Directions

The IntelliProfiler system represents a significant step forward in the study of mouse behavior. By allowing continuous, unbiased monitoring in a home-cage environment, it offers insights into how group size, sex, and aging affect behavior. Our findings highlight how important it is to study mice in a more naturalistic setting to understand their social dynamics better.

Despite the advancements IntelliProfiler provides, there are still limitations, such as spatial precision and the need for surgical implantation of RFID tags. Future developments could focus on enhancing spatial resolution and reducing the invasiveness of the system. Overall, IntelliProfiler opens new avenues for behavioral research that can lead to deeper insights into mouse behavior and, by extension, the workings of the brain.