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Mouse Short- and Long-term Locomotor Activity Analyzed by Video Tracking Software
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Open-source software for mouse-tracking in Qualtrics to measure category competition
Maya B Mathur1,2, David B Reichling3
1Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA. mmathur@stanford.edu.
Behavior Research Methods
|June 15, 2019
Summary
This study introduces user-friendly, open-source software for online mouse-tracking experiments. The tool simplifies the measurement of cognitive processes and category competition, making advanced research accessible.
Area of Science:
- Cognitive Psychology
- Human-Computer Interaction
- Computational Neuroscience
Background:
- Mouse-tracking measures rapid cognitive processes during decision-making.
- Investigating competition between perceptual or cognitive categories is crucial.
- Existing methods for online mouse-tracking can be complex to implement.
Purpose of the Study:
- To provide accessible, open-source software for online mouse-tracking experiments.
- To simplify the design and analysis of cognitive category competition studies.
- To enable researchers without advanced programming skills to utilize mouse-tracking.
Main Methods:
- Developed user-friendly, open-source software using Qualtrics, JavaScript, CSS, and R.
- Integrated software for seamless experiment design and data analysis.
- Validated software performance using established stimuli (android robot faces) and crowdsourced data.
Main Results:
- The software effectively facilitates online mouse-tracking experiments.
- Empirical validation confirmed the software's reliable performance.
- The system demonstrated accurate data collection and analysis for category competition.
Conclusions:
- The developed software lowers the barrier to entry for online mouse-tracking research.
- This tool democratizes the study of dynamic cognitive processes.
- The open-source nature allows for adaptation to other online survey platforms.
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