Aged rats learn Morris Water maze using non-spatial search strategies evidenced by a parameter-based algorithm

Area of Science:

• Neuroscience
• Behavioral Science
• Animal Models

Background:

• Spatial learning and memory are crucial for navigation.
• The Morris Water Maze (MWM) is a standard tool for assessing these abilities in rodents.
• Existing MWM analysis methods include traditional parameters and complex computerized trajectory analysis.

Purpose of the Study:

• To develop and validate a non-computerized Search Strategy Algorithm (SSA) for classifying spatial learning and memory strategies.
• To compare the effectiveness of SSA with traditional MWM parameters in differentiating learning processes between young and aged rats.

Main Methods:

• A novel, non-computerized Search Strategy Algorithm (SSA) was developed, classifying rat trajectories into 10 categories based on effectiveness, initial direction, and precision.
• The SSA was validated using young and aged rats in the Morris Water Maze (MWM).
• Trained observers classified rat trajectories to assess the SSA's reliability and reproducibility.

Main Results:

• Traditional MWM measurements (latency, distance, platform crossings) failed to show significant learning differences between age groups.
• The SSA identified significant differences, revealing that young rats employed direct search strategies, while aged rats used indirect ones.
• The number of platform crossings was the sole traditional variable indicating differences in an intermediate probe trial.

Conclusions:

• The parameter-based SSA offers a reliable and reproducible alternative to computerized methods for analyzing spatial learning and memory in MWM studies.
• Aged rats can learn spatial memory tasks, utilizing distinct search strategies compared to younger rats.
• SSA effectively detects changes in spatial learning and memory, providing richer insights than traditional MWM parameters.