Why you shouldn’t use a black box to measure animal behavior
When studying animal behavior, as a researcher we want to rely on using video tracking tools that are reliable, insightful, easy to use, and most crucially to avoid using a research software tool that is a black box. Below we layed out a clear explanation of the potential risks and limitations of using a black box tool in behavioral research, along with questions you can ask your software supplier to make sure this isn’t the case!
Why you shouldn’t use a black box to measure animal behavior
Lack of transparency in data processing algorithms
Blackbox tools often lack transparency in their algorithms, making it difficult for researchers to understand how the software processes specific readouts. But what does this mean?
For example, if a blackbox software tool is used to measure anxiety in an elevated plus maze, the researcher might not have access to the specific algorithms (or settings) that the software uses to track and interpret the animal's movements, but more importantly in this example: what it classifies as anxiety-like behavior.
As a researcher it remains your responsibility to determine what readouts are linked to specific behavioral outcomes. We thus don’t want the software to measure anxiety, but we want it to measure (and show us) the time the animal spent in the open arms versus the closed arms of the maze (and head dips for example).
Without visibility into the underlying algorithms, researchers cannot assess the accuracy and reliability of the results. We want to have full insight into the data and into its acquisition, because a lack of transparency can undermine the scientific rigor of the study and raise concerns about the validity and replicability of the findings.
Limitations in customization and adaptability
Blackbox tools also often lack flexibility in customization to fit specific research requirements. Studying animal behavior does have a lot of standardized setups, but there are also many situations that need unique experimental setups or specific parameters. A blackbox tool restricts your ability to adapt the software to your specific needs, limiting the exploration of novel research questions or refinement of experimental designs.
To quickly summarize, using a blackbox research software tool to study animal behavior can introduce considerable risks and limitations. The lack of transparency, inability to validate results, potential biases and errors, and limited customization capabilities can compromise the accuracy, reliability, and scientific rigor of research findings.
Researchers should prioritize using software tools that provide transparency, customization options, and opportunities for independent validation to ensure the integrity of their studies.
So how do we choose the right research tool? What questions should every researcher ask their software supplier?
What algorithms and methodologies are employed in the software?
Transparency is paramount in scientific research. Request detailed information about the algorithms and methodologies utilized in the software. Understanding how the software processes data and generates insights will allow you to evaluate the reliability and validity of the results. This knowledge empowers you to identify potential biases, errors, or limitations that could impact the accuracy of your findings.
How does the software ensure data quality control?
Data integrity is crucial for obtaining reliable research outcomes. Inquire about the measures taken by the software to ensure data quality control. Does it have features to detect and correct errors, filter noise, or handle confounding factors? Robust data quality control mechanisms will enable you to eliminate inaccuracies and ensure the validity of your research.
Can the software provide comprehensive reports and visualizations?
Effective communication of research findings relies on clear and visually appealing reports and visualizations. Ask the software supplier if their tool offers features for generating comprehensive reports and visual representations of the data. This capability allows you to present your results in a compelling manner, facilitating understanding and enhancing the impact of your research.
Can the software be customized to suit specific experimental requirements?
Each research project has unique requirements. Inquire about the customization capabilities of the software. Can it be tailored to fit different experimental setups, specific animal species, or behavioral parameters? The ability to customize the software ensures that it aligns with your research needs, allowing you to explore novel research questions and refine your experimental designs.
Does the software support data export and integration with other tools?
Seamless data analysis and collaboration are vital in scientific research. Ensure that the software allows for easy data export and integration with other analysis tools or statistical software. Compatibility with commonly used data analysis platforms enables you to integrate data from multiple sources and enhances the overall efficiency of your research process.
Is there a supportive and responsive user community?
A vibrant user community can greatly enhance your research experience. Inquire about the availability of user forums, online communities, or support channels where you can seek guidance or share experiences with fellow users. Engaging with such communities provides valuable insights, troubleshooting assistance, and fosters collaboration among researchers in the field of animal learning and memory behavior.
It is crucial to select the software tool for your research that provides transparency, accuracy, and reliability in data analysis. Choosing the right tool for your research will be key to your success, because measuring animal behavior can be a fickle thing. By having insight in the way your data is acquired you can be confident in the conclusions you draw from your data, and make sure your study is replicable. By seeking clarity from your software supplier on these aspects you can make an informed decision and make confident claims.