Cognition, Behavior, and Memory
Author: Vicente Dell’Oro Sansoni | Email: vicentedelloro@gmail.com
Vicente Dell’Oro Sansoni1°2°, Catalina Pilotto1°2°,Emilio Kropff1°, María Cecilia Martínez1°
1° Departamento de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires
2° Physiology and Algorithms of the Brain, Fundación Instituto Leloir, IIBBA-CONICET
In the field of neuroscience, studying rodent activity provides insights into behavioral patterns and responses to stimuli. However, little is known about how different stress levels impact on social interaction. In this project, we developed an automated device to record videos of animal groups with varying stress levels to study their behavior.
A versatile recording system was built using a Raspberry Pi 3 Model B and a Raspberry Pi Camera Module 2 NoIR. Both components are low-cost and easily programmable. The camera was configured to film videos at specific times, with recordings accessible remotely.
Since rodents are most active at night, nighttime recordings provide the most valuable data. Given that rats are not sensitive to infrared light, a circuit with infrared LEDs was assembled to record without interfering with the animals’ behavior.
Data analysis will be performed using machine learning, allowing efficient and precise study of behavioral patterns. The tool employed will be DeepLabCut in its multi-animal function, trained with videos of the animals in the cage.
This work will provide insights into the behavioral patterns and social interactions of rats, expanding our understanding of how stress influences their social relationships. The results obtained may not only advance knowledge in neuroscience but also have broader implications for studying social behavior in other species.