PUBLICATION
Argus: An open-source and flexible software application for automated quantification of behavior during social interaction in adult zebrafish
- Authors
- Shams, S., Amlani, S., Scicluna, M., Gerlai, R.
- ID
- ZDB-PUB-180816-6
- Date
- 2018
- Source
- Behavior research methods 51(2): 727-746 (Journal)
- Registered Authors
- Gerlai, Robert T.
- Keywords
- Anxiety, Dyads, R programming language, Social behavior, Zebrafish
- MeSH Terms
-
- Animals
- Automation, Laboratory/methods
- Behavior, Animal*
- Behavioral Research/instrumentation*
- Data Analysis*
- Data Collection/instrumentation*
- Interpersonal Relations
- Social Behavior*
- Software*
- Zebrafish
- PubMed
- 30105442 Full text @ Behav. Res. Methods
Citation
Shams, S., Amlani, S., Scicluna, M., Gerlai, R. (2018) Argus: An open-source and flexible software application for automated quantification of behavior during social interaction in adult zebrafish. Behavior research methods. 51(2):727-746.
Abstract
Zebrafish show great potential for behavioral neuroscience. Promising lines of research, however, require the development and validation of software tools that will allow automated and cost-effective behavioral analysis. Building on our previous work with the RealFishTracker (in-house-developed tracking system), we present Argus, a data extraction and analysis tool built in the open-source R language for behavioral researchers without any expertise in R. Argus includes a new, user-friendly, and efficient graphical user interface, instead of a command-line interface, and offers simplicity and flexibility in measuring complex zebrafish behavior through customizable parameters. In this article, we compare Argus with Noldus EthoVision and Noldus The Observer, to validate this new system. All three software applications were originally designed to quantify the behavior of a single subject. We first also performed an analysis of the movement of individual fish and compared the performance of the three software applications. Next we computed and quantified the behavioral variables that characterize dyadic interactions between zebrafish. We found that Argus and EthoVision extract similar absolute values and patterns of changes in these values for several behavioral measures, including speed, freezing, erratic movement, and interindividual distance. In contrast, the manual coding of behavior in The Observer showed weaker correlations with the two tracking methods (EthoVision and Argus). Thus, Argus is a novel, cost-effective, and customizable method for the analysis of adult zebrafish behavior that may be utilized for the behavioral quantification of both single and dyadic interacting subjects, but further sophistication will be needed for the proper identification of complex motor patterns, measures that a human observers can easily detect.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping