The code provided is part of a computational model aimed at studying behavioral patterns in the Morris Water Maze (MWM), a commonly used experimental setup in neuroscience research to assess spatial learning and memory in rodents, particularly mice and rats. Let's delve into the biological basis of what this code is modeling: ## Biological Context ### Morris Water Maze (MWM) The MWM is a circular pool filled with opaque water, where rodents are trained to locate a hidden platform just below the water's surface. The MWM test assesses spatial navigation skills and memory, both of which rely heavily on hippocampal function—a critical brain region involved in memory formation and spatial navigation. Key aspects of the MWM include: - **Spatial Learning and Memory:** The task involves training animals over several sessions to find a platform using spatial cues, allowing researchers to quantify learning rates and memory retention. - **Stress and Behavior:** The task can evaluate the effect of stressors on cognitive functions. The code indicates a division of animals into groups such as 'Control' and 'Stress,' suggesting a focus on how stress impacts learning and memory. ### Code Structure and Biological Relevance #### Experiment Design - **Sessions and Trials:** The model specifies multiple sessions with multiple trials per session (`TRIALS_PER_SESSION`), reflecting how biological experiments are structured to measure learning over time. - **Groups:** The presence of different groups (`GROUPS_DESCRIPTION`), including 'Control', 'Stress', and variations involving diet, indicates a comparison across different physiological states or interventions and their effects on behavior. #### Environment Parameters - **Arena Specifications:** The code defines parameters such as the arena's center (`CENTRE_X`, `CENTRE_Y`) and radius (`ARENA_R`). These are crucial for simulating the actual experimental conditions within the MWM. - **Platform Location:** The platform's coordinates (`PLATFORM_X`, `PLATFORM_Y`) and radius (`PLATFORM_R`) replicate the hidden platform's role in guiding rodents' behavior. #### Behavioral Features - **Trajectory Analysis:** The model calculates several trajectory-related features, such as `FEATURE_LONGEST_LOOP` and `FEATURE_PLATFORM_PROXIMITY`, emphasizing how rodents navigate the maze and relate to the platform. These parameters help determine patterns like direct paths versus exploratory behavior. - **Tags for Behavioral Classes:** Terms like 'thigmotaxis' (wall-hugging behavior, indicative of stress or anxiety), 'scanning', and 'direct finding' capture specific behaviors associated with successful or unsuccessful navigation. They are indicators of cognitive states and learning strategies. #### Data Collection and Analysis - **Trajectory Data:** The code segments directories for trajectory data (`TRAJECTORY_DATA_DIRS`) and snapshots, ensuring comprehensive analysis of rodents' movements. - **Clustering:** The application of features for clustering (`CLUSTERING_FEATURE_SET`) suggests analyzing and categorizing different navigational strategies or behaviors exhibited by rodents during the trials. The code provided, therefore, serves as a framework for understanding how stress and possibly diet variations impact spatial learning and memory as evaluated in the Morris Water Maze. The defined parameters, group descriptions, and behavioral metrics align closely with biological objectives to probe neural substrates of learning, typically processing in the hippocampus and associated structures in the brain.