Y-maze avoidance: an automated and rapid associative learning paradigm in zebrafish

Ryo Aoki; Takashi Tsuboi; Hitoshi Okamoto

doi:10.1016/j.neures.2014.10.012

Y-maze avoidance: an automated and rapid associative learning paradigm in zebrafish

Neurosci Res. 2015 Feb:91:69-72. doi: 10.1016/j.neures.2014.10.012. Epub 2014 Nov 4.

Authors

Ryo Aoki¹, Takashi Tsuboi², Hitoshi Okamoto³

Affiliations

¹ Laboratory for Developmental Gene Regulation, Neural Growth and Regeneration Research Group, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan; Department of Life Science, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan.
² Department of Life Science, Graduate School of Arts and Sciences, The University of Tokyo, 3-8-1 Komaba, Meguro, Tokyo 153-8902, Japan.
³ Laboratory for Developmental Gene Regulation, Neural Growth and Regeneration Research Group, RIKEN Brain Science Institute, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. Electronic address: hitoshi@brain.riken.jp.

PMID: 25449146
DOI: 10.1016/j.neures.2014.10.012

Abstract

Adult zebrafish are gaining attention in behavioral neuroscience. By combining 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 an electric shock. Within two hours, zebrafish learn to choose the correct arm at an efficiency of 89.0%. In addition, we also developed a graphical user interface to modify the paradigm assessment parameters such as shape of the tank and time schedules.

Keywords: Adult zebrafish; Automated position detection; Aversive learning paradigm; MATLAB.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Association Learning*
Avoidance Learning*
Maze Learning*
Models, Animal*
Zebrafish