PUBLICATION
Y-maze avoidance: An automated and rapid associative learning paradigm in zebrafish
- Authors
- Aoki, R., Tsuboi, T., Okamoto, H.
- ID
- ZDB-PUB-141203-52
- Date
- 2015
- Source
- Neuroscience research 91: 69-72 (Other)
- Registered Authors
- Okamoto, Hitoshi
- Keywords
- Adult zebrafish, Automated position detection, Aversive learning paradigm, MATLAB
- MeSH Terms
-
- Animals
- Association Learning*
- Avoidance Learning*
- Maze Learning*
- Models, Animal*
- Zebrafish
- PubMed
- 25449146 Full text @ Neurosci. Res.
Citation
Aoki, R., Tsuboi, T., Okamoto, H. (2015) Y-maze avoidance: An automated and rapid associative learning paradigm in zebrafish. Neuroscience research. 91:69-72.
Abstract
Recent genetic and neuroanatomical studies have demonstrated the suitability of adult zebrafish as a model animal in behavioral neuroscience. To evaluate their ability for adaptive learning, it is beneficial to develop a more efficient, more precise, and less laborious behavioral paradigm. By combining real-time video tracking and computer-controlled visual cue presentations on a liquid crystal display screen under the tank, we have developed a new method by which zebrafish can be trained to avoid one arm of a Y-shaped tank by presenting a specific color on the floor paired with a noxious electric shock. The whole procedure takes less than 2hours, and zebrafish learn to choose the correct arm of the tank at an efficiency rate of 89.0%, which is high compared with other associative learning paradigms. In addition, the acquired memory lasted for 24hours. We also developed a graphical user interface by which users can modify the paradigm assessment parameters such as shape of the tank and time schedules. Our assay system enables the rapid and reliable evaluation of cognitive ability in adult zebrafish, with high reproducibility, minimal experimenters' bias, and ease of customization.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping