Spatiotemporal survival analysis for movement trajectory tracking in virtual reality

We present a novel method for analyzing response trajectory tracking data. Limiting behavioral experiments to discrete, key-press response measures, such as reaction times and accuracy, is unsatisfactory for observing the ongoing dynamics of cognition. We assessed the utility of continuous response tracking in Virtual Reality (VR) by comparing it to key-press responses in a classical N-back matching task. For elucidatory purposes, in both classical and VR versions of the task we first worked through analyses of discrete measures, before drawing information from the continuous trajectory tracking data in VR. Classical ANOVAs reproduced effects of visual working memory load in an N-back task. Violations of ANOVA assumptions suggested effects were buried in the noise; some of these were revealed in subsequent survival analyses, namely frequency neglect (a strong preference for match responses despite the infrequency of this response category) in the fast responses and category frequency-tuned response in the slow responses. Spatiotemporal survival analysis (StSA), our newly proposed method of analyzing response trajectories, revealed that all these effects also occur in the VR conditions. In addition, initial divergences towards the wrong responses were corrected later in the course of trajectories in the non-Match trials. While the StSA method is theory-free and can be used for exploratory purposes, we present examples of hypothesis testing in StSA.

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Publication Details

Journal
Scientific Reports
Published
2025-03-01
DOI
https://doi.org/10.1038/s41598-025-91471-5
Citations
2
Primary Topic
Visual perception and processing mechanisms
Type
article
Field-Weighted Citation Impact
2.86
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article

Spatiotemporal survival analysis for movement trajectory tracking in virtual reality

Vera Eymann, Cees van Leeuwen, Nicole Burkard, Omar Fahmi Jubran et al.
2 citations
Scientific Reports
Visual perception and processing mechanisms
2.86
article

Spatiotemporal survival analysis for movement trajectory tracking in virtual reality

Vera Eymann, Cees van Leeuwen, Nicole Burkard, Omar Fahmi Jubran, Daniela Czernochowski, Thomas Lachmann, Marc Herrlich, Maximillian Philipp Wolkersdorfer
article en
2 citations

Abstract

We present a novel method for analyzing response trajectory tracking data. Limiting behavioral experiments to discrete, key-press response measures, such as reaction times and accuracy, is unsatisfactory for observing the ongoing dynamics of cognition. We assessed the utility of continuous response tracking in Virtual Reality (VR) by comparing it to key-press responses in a classical N-back matching task. For elucidatory purposes, in both classical and VR versions of the task we first worked through analyses of discrete measures, before drawing information from the continuous trajectory tracking data in VR. Classical ANOVAs reproduced effects of visual working memory load in an N-back task. Violations of ANOVA assumptions suggested effects were buried in the noise; some of these were revealed in subsequent survival analyses, namely frequency neglect (a strong preference for match responses despite the infrequency of this response category) in the fast responses and category frequency-tuned response in the slow responses. Spatiotemporal survival analysis (StSA), our newly proposed method of analyzing response trajectories, revealed that all these effects also occur in the VR conditions. In addition, initial divergences towards the wrong responses were corrected later in the course of trajectories in the non-Match trials. While the StSA method is theory-free and can be used for exploratory purposes, we present examples of hypothesis testing in StSA.

Scientific ReportsVol. 15(1)
University of Kaiserslautern (DE), Universidad Nebrija (ES), German Research Centre for Artificial Intelligence (DE), KU Leuven (BE)
Openalex Percentile: Top 12%
Visual perception and processing mechanisms
2.86
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