Related Experiment Video
Updated: May 29, 2026

12:59
Barnes Maze Testing Strategies with Small and Large Rodent Models
Published on: February 26, 2014
41.9K
Rodent maze studies: from following simple rules to complex map learning
Kjell Wijnen1, Lisa Genzel2, Jacqueline van der Meij3
1Donders Institute for Brain, Cognition and Behaviour, Radboud University, Postbus 9010, 6500 GL, Nijmegen, The Netherlands.
Brain Structure & Function
|March 15, 2024
Summary
Rodent mazes have evolved over 100 years, but optimal designs and training for learning and memory research are still debated. This review explores maze history, strategies, learning phases, and training impacts.
Area of Science:
- Neuroscience
- Animal Behavior
- Cognitive Science
Background:
- The use of mazes in rodent research dates back over a century.
- Numerous maze designs exist, with ongoing modifications and new introductions for specific research questions.
- Optimal maze selection and training paradigms for rodent learning and memory studies remain subjects of debate.
Purpose of the Study:
- To provide a historical overview of maze designs and their application in rodent learning and memory research.
- To discuss potential navigational strategies employed by rodents in various mazes.
- To summarize learning phases within maze tasks and analyze the influence of training and design on spatial learning.
Main Methods:
- Literature review of historical and contemporary maze designs.
- Analysis of rodent navigational strategies.
- Synthesis of learning phases and training effects in spatial tasks.
Main Results:
- A historical perspective on the evolution of rodent mazes.
- Identification of diverse navigational strategies used by rodents.
- Summary of learning processes and the impact of experimental parameters.
Conclusions:
- Maze design and training protocols significantly influence the spatial learning outcomes in rodents.
- Understanding these factors is crucial for effective experimental design in learning and memory research.
- Further research may clarify optimal maze and training configurations for specific cognitive functions.

