This review aims to improve the effectiveness and accuracy of learning-memory tests used in animal models. It highlights several
criteria that may influence the data and results obtained from these tests. Furthermore, it seeks to showcase both classical and
modern methods. PubMed, Google Scholar, and Web of Science databases were used for searches on learning and memory tests.
Keywords included were neuroscience, cognitive function, learning, memory, and rat. Both recent articles and older studies still
considered relevant were included. Most invasive procedures required to investigate the neural mechanisms of learning and memory
cannot be performed in humans. Therefore, animal models have become a valuable alternative for learning and memory research.
Rodents are widely used in neurodegenerative disease research. Many behavioural tests have been developed to investigate different
types of cognition in rodents. The most commonly used tests are the open field habituation test, which assesses spatial memory; the
Y-maze test, which assesses short-term memory; the passive avoidance test, which assesses fear memory; the active avoidance test,
which assesses conceptual memory; the Morris water maze test, which assesses long-term spatial memory; and the radial arm maze
test, which assesses reference-related memory. It is important to consider the advantages and disadvantages of each of these tests.
Data obtained through learning-memory tests may indicate learning memory deficits in various nervous system diseases. With
advancing technology, rodent research is shifting from traditional methods to increasingly complex automated systems. Systems
including radio frequency identification, touchscreen-based systems, virtual reality, and artificial intelligence are now available for
learning-memory tests.
| Primary Language | English |
|---|---|
| Subjects | Central Nervous System |
| Journal Section | Review |
| Authors | |
| Submission Date | December 1, 2025 |
| Acceptance Date | January 3, 2026 |
| Publication Date | January 30, 2026 |
| Published in Issue | Year 2026 Volume: 2 Issue: 1 |