ArticleBehavior research methods2022
Accuracy and precision of visual and auditory stimulus presentation in virtual reality in Python 2 and 3 environments for human behavior research.
Article in Behavior research methods, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Color discrimination in action: High-throughput measurement in immersive VR.Journal of vision · 2026Article
- Adult age differences in the modulation of peripersonal space after tool use in virtual reality.Scientific reports · 2026Article
- PTVR - A software in Python to make virtual reality experiments easier to build and more reproducible.Journal of vision · 2024Article
- Article
- Perceptual decisions interfere more with eye movements than with reach movements.Communications biology · 2023Article
- Multiple representations of the body schema for the same body part.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
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Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Virtual reality (VR) is a new methodology for behavioral studies. In such studies, the millisecond accuracy and precision of stimulus presentation are critical for data replicability. Recently, Python, which is a widely used programming language for scientific research, has contributed to reliable accuracy and precision in experimental control. However, little is known about whether modern VR environments have millisecond accuracy and precision for stimulus presentation, since most standard methods in laboratory studies are not optimized for VR environments. The purpose of this study was to systematically evaluate the accuracy and precision of visual and auditory stimuli generated in modern VR head-mounted displays (HMDs) from HTC and Oculus using Python 2 and 3. We used the newest Python tools for VR and Black Box Toolkit to measure the actual time lag and jitter. The results showed that there was an 18-ms time lag for visual stimulus in both HMDs. For the auditory stimulus, the time lag varied between 40 and 60 ms, depending on the HMD. The jitters of those time lags were 1 ms for visual stimulus and 4 ms for auditory stimulus, which are sufficiently low for general experiments. These time lags were robustly equal, even when auditory and visual stimuli were presented simultaneously. Interestingly, all results were perfectly consistent in both Python 2 and 3 environments. Thus, the present study will help establish a more reliable stimulus control for psychological and neuroscientific research controlled by Python environments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.