In particular, in psychological or neuroscientific experiments, stimuli such as visual (e.g., geometric figure, pictures, and animations) and auditory (e.g., tone sound, voice, and music) information should be presented to participants for a set duration and timing with millisecond accuracy and precision. If experiments are performed with low accuracy and precision or untested apparatus, it is difficult to collect replicable data. Indeed, a recent study has indicated that the VR HMD of HTC Vive enables the measurement of visual cognition performance, such as visual attention and working memory capacity, as reliably as a cathode-ray tube (CRT) display (Foerster et al., 2019).Īs the accuracy and precision of stimulus presentation have been critical for psychological and neuroscience research, millisecond stimulus control should be considered in VR studies. In particular, modern VR head-mounted displays (HMDs), such as HTC Vive and Oculus Rift, allow the presentation of complex and dynamic stimuli that can achieve higher ecological validity (close to daily life) and be subject to more experimental control (Loomis et al., 1999 Parsons, 2015). Since researchers can control stimuli and procedures that are not easily controllable in the real world, VR has been applied in studies on rehabilitation, therapy, and social interaction (Pan & de Hamilton, 2018 Parsons, 2015). Such environments have also been referred to as “ultimate Skinner box” environments (Rizzo et al., 2004 Wilson & Soranzo, 2015). These features help establish more natural environments for experiments in three dimensions (3D), where participants can see, hear, and behave as in the real world, enhancing the ecological validity of research (Parsons, 2015). ( 2018), VR technologies immerse us in a virtual environment and enable us to interact with it. Virtual reality (VR) has attracted much attention as a new methodology for scientific research. Thus, the present study will help establish a more reliable stimulus control for psychological and neuroscientific research controlled by Python environments. Interestingly, all results were perfectly consistent in both Python 2 and 3 environments. These time lags were robustly equal, even when auditory and visual stimuli were presented simultaneously. 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. For the auditory stimulus, the time lag varied between 40 and 60 ms, depending on the HMD. The results showed that there was an 18-ms time lag for visual stimulus in both HMDs. We used the newest Python tools for VR and Black Box Toolkit to measure the actual time lag and jitter. 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. 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. Recently, Python, which is a widely used programming language for scientific research, has contributed to reliable accuracy and precision in experimental control. In such studies, the millisecond accuracy and precision of stimulus presentation are critical for data replicability.

Virtual reality (VR) is a new methodology for behavioral studies.

Stimulus duration framen psychopy