Many of the paradigms used to study learning and memory in rodents have been successfully translated to fish studies. One of the challenges in these studies though, is keeping track of these fast and sometimes erratically moving animals. EthoVision® XT is able to accurately detect and track any fish species and provides you with the dependent variables you need for your research, such as distance moved, velocity, and time spent in the different parts of the maze. Combined with the Multiple Arenas Module, you can track fish in multiple set-ups simultaneously, saving time and effort.
The T-maze is a great example of a standardized paradigm that is successfully translated to zebrafish studies. It can be used to test natural preferences or the effects of genetic disposition, chemical alterations, substances of abuse (such as alcohol), or promising substances in the treatment of specific disorders.
T-maze learning is often based on color or pattern discrimination. In other cases the natural preference for certain types of environments is used by providing a view of conspecifics or a deeper arm. This way, the goal arm is not only discriminated from the other, the environment also serves as a positive stimulus.
Obviously, the different zones of the T-maze are important in your analysis: the start box, the long arm, the left and right goal arm. EthoVision XT allows you to easily define the different zones of the T-maze in your video image. When you are using the experiment template, these are even predefined. When tracking the zebrafish EthoVision XT uses these zones to link behaviors of interest to. Data analysis is then a breeze – EthoVision XT automatically calculates total time spent in the ‘correct’ goal arm or latency to enter the ‘correct arm’, or number of entries into the ‘wrong’ goal arm.
Start your trial automatically
You can set the conditions for EthoVision XT to automatically start and stop tracking, even when you are monitoring multiple set-ups simultaneously. For example: When using a T-maze set-up, EthoVision XT can automatically start t racking as soon as the fish leaves the start box, and stop as soon as it has been in the goal zone for a predetermined amount of time.
Data that makes sense
EthoVision XT measures a wide range of parameters related to swimming behavior, including swimming speed, distance swam, and percentage of time spent moving. In addition, a variety of parameters related to turning behavior can be measured. Mean turn angle indicates the change in direction and angular velocity measures the speed of direction changing. Both parameters can be used to analyze explorative behavior.
Compare manual observations
EthoVision XT has a built-in Manual Event Recorder. This equips you with an easy-to-use tool to score behaviors in addition to automatically recorded tracking data, or to validate and fine-tune automatically scored behaviors such as freezing or zigzagging. All your results are visualized and analyzed synchronously.
Examples of parameters
- Latency to reach the goal arm
- Arm which received first preference
- The entries into the different zones
- Number of correct choices
- Amount of time spent in each zone
- Total distance travelled in each zone
- Mean velocity
- Percentage of time spent immobile (freezing episodes)
Find out more about learning and memory tests in these blog posts .
Here are a few publications that might interest you:
- Champagne, D.L.; Hoefnagels, C.C.M.; de Kloet, R.E.; Richardson, M.K. (2010). Translating rodent behavioral repertoire to zebrafish (Danio rerio): Relevance for stress research. Behavioural Brain Research, 214, 332-342.
- Levin, E.D. (2011). Zebrafish assessment of cognitive improvement and anxiolysis: filling the gap between in vitro and rodent models for drug development. Reviews in the Neurosciences, 22(1), 75-84.
- Levin, E.D.; Cerutti, D.T. (2009). Behavioral Neuroscience of Zebrafish. Chapter 15 from Methods of Behavior Analysis in Neuroscience, second edition. Boca Raton (FL): CRC Press.
- Grella, S.; Kapur, N.; Gerlai, R. (2010). A Y-maze choice task fails to detect alcohol avoindance or alcohol preference in zebrafish. International Journal of Comparative Psychology, 23, 26-42.
- Grossman, L.; Utterback, E.; Stewart, A.; Gaikwad, S.; Chung, K.M.; Suciu, C.; Wong, K.; Elegante, M.; Elkhayat, S.; Tan, J.; Gilder, T.; Wu, N.; DiLeo, J.; Chachat, J.; Kalueff, A.V. (2010). Characterization of behavioral and endocrine effects of LSD on zebrafish. Behavioural Brain Research , 214 , 277-284.
- Ninkovic, J.; Folchert, A.; Makhankov, Y.V.; Neuhauss, S.C.F.; Sillaber, I.; Straehle, U.; Bally-Cuif, L. (2006). Genetic identification of AChE as a positive modulator of addiction to the psychostimulant D-Amphetamine in zebrafish. Journal of Neurobiology, 66(5), 463-475.
- Peitsaro, N.; Kaslin, J.; Anichtchik, O.V.; Panula, P. (2003). Modulation of the histaminergic system and behavior by α-fluoromethylhistidine in zebrafish. Journal of Neurochemistry, 86, 432-441.
- Saili, K.S.; Corvi, M.M.; Weber, D.N.; Patel, A.U.; Das, S.R.; Przybyla, J.; Anderson, K.A.; Tanguay, R.L. (2012). Neurodevelopmental low-dose bisphenol A exposure leads to early life-stage hyperactivity and learning deficits in adult zebrafish. Toxicology, 291, 83-92.