Observing the Presence of Information-Seeking Behavior In Mice Through Odor Reward-Based Response and Analyzing Results With the Python and MATLAB Languages.

School Name

South Carolina Governor's School for Science & Mathematics

Grade Level

12th Grade

Presentation Topic

Psychology

Presentation Type

Mentored

Abstract

Observing cognitive information-seeking behavior in animals is the forefront of determining an anatomical correlation to curiosity. Previous research with Rhesus Monkey behavior has shown the presence of information-seeking in animals through odor reward-based association. However, the complex anatomy of rhesus monkeys impaired conclusive evidence. Therefore, this research shifted to a less complex cognitive system: mice. Within this experiment, information seeking behavior was observed through stimulation of the olfactory system. Beginning in a single chamber box, trained mice were exposed to three ports releasing pre-associated odors; the introduction of a choice associated odor permitted behavior analysis of the mice. However, human observation revealed that unrecorded behavior outside of Arduino activated ports exposed obscure behavioral associative patterns. Specifically, during information small reward trials mice failed to wait the ten second waiting period within the port. The aim of this research was to develop a software that could track the mice behavior at any point in time within any trial type. Using the Deniz Cai Lab's ezTrack program, and Python and MATLAB languages, a software was developed that could activate a camera recording to track the mouse using a color gradient. This program overlays the mouse's movement over a reference image from the recording, noting any unusual behavior patterns, such as side bias or repetitive response. The efficiency of this program provided tangible evidence that permitted the development of non-reward-based information seeking behavior analysis in mice. The development of this new tri-chamber box has been completed and is currently under analysis.

Location

Furman Hall 207

Start Date

3-28-2020 11:30 AM

Presentation Format

Oral Only

Group Project

No

COinS
 
Mar 28th, 11:30 AM

Observing the Presence of Information-Seeking Behavior In Mice Through Odor Reward-Based Response and Analyzing Results With the Python and MATLAB Languages.

Furman Hall 207

Observing cognitive information-seeking behavior in animals is the forefront of determining an anatomical correlation to curiosity. Previous research with Rhesus Monkey behavior has shown the presence of information-seeking in animals through odor reward-based association. However, the complex anatomy of rhesus monkeys impaired conclusive evidence. Therefore, this research shifted to a less complex cognitive system: mice. Within this experiment, information seeking behavior was observed through stimulation of the olfactory system. Beginning in a single chamber box, trained mice were exposed to three ports releasing pre-associated odors; the introduction of a choice associated odor permitted behavior analysis of the mice. However, human observation revealed that unrecorded behavior outside of Arduino activated ports exposed obscure behavioral associative patterns. Specifically, during information small reward trials mice failed to wait the ten second waiting period within the port. The aim of this research was to develop a software that could track the mice behavior at any point in time within any trial type. Using the Deniz Cai Lab's ezTrack program, and Python and MATLAB languages, a software was developed that could activate a camera recording to track the mouse using a color gradient. This program overlays the mouse's movement over a reference image from the recording, noting any unusual behavior patterns, such as side bias or repetitive response. The efficiency of this program provided tangible evidence that permitted the development of non-reward-based information seeking behavior analysis in mice. The development of this new tri-chamber box has been completed and is currently under analysis.