The virtual environment was kindly provided by VIS Games (http://www.vis-games.de) to conduct research in virtual reality.

The following protocol was conducted in accordance with guidelines approved by the Ethics Commission of ETH Z&#252;rich as part of the proposal EK 2013-N-73.
1. Recruit and Prepare Participants
<ol>
	<li>Select participants with particular demographics (e.g., age, gender, educational background) using a participant recruitment system or mailing list (e.g., UAST; http://www.uast.uzh.ch/).</li>
	<li>Contact selected participants by e-mail. In this e-mail, remind the participa...

<ol>
	<li>Gallistel, C. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Organization of Learning. , (1990).</li><li>Waller, D., Nadel, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Handbook of Spatial Cognition. , (2013).</li><li>Denis, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Space and Spatial Cognition: A Multidisciplinary Perspective. , (2017).</li><li>Epstein, R. A., Patai, E. Z., Julian, J. B., Spiers, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+cognitive+map+in+humans:+spatial+navigation+and+beyond.">The cognitive map in humans: spatial navigation and beyond.</a> Nature Neuroscience. 20, 1504 (2017).</li><li>O'Keefe, J., Nadel, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> The Hippocampus as a Cognitive Map. , (1978).</li><li>Kuipers, B. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modelling+spatial+knowledge.">Modelling spatial knowledge.</a> Cognitive Science. 2, 129-153 (1978).</li><li>Heppenstall, A. J., Crooks, A. T., See, L. M., Batty, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Agent-Based Models of Geographical Systems. , (2012).</li><li>Kuliga, S. F., Thrash, T., Dalton, R. C., H&#246;lscher, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Virtual+reality+as+an+empirical+research+tool+-+Exploring+user+experience+in+a+real+building+and+a+corresponding+virtual+model.">Virtual reality as an empirical research tool - Exploring user experience in a real building and a corresponding virtual model.</a> Computers, Environment and Urban Systems. 54, 363-375 (2015).</li><li>Cred&#233;, S., Fabrikant, S. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Let's+Put+the+Skyscrapers+on+the+Display-Decoupling+Spatial+Learning+from+Working+Memory.">Let's Put the Skyscrapers on the Display-Decoupling Spatial Learning from Working Memory.</a> Proceedings of Workshops and Posters at the 13th International Conference on Spatial Information Theory (COSIT 2017). , 163-170 (2018).</li><li>Hodgson, E., Bachmann, E. R., Vincent, D., Zmuda, M., Waller, D., Calusdian, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=WeaVR:+a+self-contained+and+wearable+immersive+virtual+environment+simulation+system).">WeaVR: a self-contained and wearable immersive virtual environment simulation system).</a> Behavior Research Methods. 47 (1), 296-307 (2015).</li><li>Nilsson, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=15+Years+of+Research+on+Redirected+Walking+in+Immersive+Virtual+Environments.">15 Years of Research on Redirected Walking in Immersive Virtual Environments.</a> IEEE Computer Graphics and Applications. , 1-19 (2018).</li><li>Razzaque, S., Kohn, Z., Whitton, M. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Redirected+walking.">Redirected walking.</a> Proceedings of EUROGRAPHICS. , 105-106 (2001).</li><li>Hodgson, E., Bachmann, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+Four+Approaches+to+Generalized+Redirected+Walking:+Simulation+and+Live+User+Data.">Comparing Four Approaches to Generalized Redirected Walking: Simulation and Live User Data.</a> IEEE Transactions on Visualization and Computer Graphics. 19 (4), 634-643 (2013).</li><li>Nescher, T., Huang, Y. -. Y., Kunz, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Planning+redirection+techniques+for+optimal+free+walking+experience+using+model+predictive+control.">Planning redirection techniques for optimal free walking experience using model predictive control.</a> 2014 IEEE Symposium on 3D User Interfaces (3DUI). , 111-118 (2014).</li><li>Razzaque, S., Swapp, D., Slater, M., Whitton, M. C., Steed, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Redirected+walking+in+place.">Redirected walking in place.</a> Eurographics workshop on virtual environments. , 123-130 (2002).</li><li>Meilinger, T., Knauff, M., Bulthoff, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Working+Memory+in+Wayfinding-A+Dual+Task+Experiment+in+a+Virtual+City.">Working Memory in Wayfinding-A Dual Task Experiment in a Virtual City.</a> Cognitive Science: A Multidisciplinary Journal. 32 (4), 755-770 (2008).</li><li>Gr&#252;bel, J., Thrash, T., H&#246;lscher, C., Schinazi, V. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+a+conceptual+framework+for+predicting+navigation+performance+in+virtual+reality.">Evaluation of a conceptual framework for predicting navigation performance in virtual reality.</a> PLOS ONE. 12 (9), 0184682 (2017).</li><li>Weisberg, S. M., Schinazi, V. R., Newcombe, N. S., Shipley, T. F., Epstein, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Variations+in+Cognitive+Maps:+Understanding+Individual+Differences+in+Navigation.">Variations in Cognitive Maps: Understanding Individual Differences in Navigation.</a> Journal of experimental psychology. Learning, memory, and cognition. , (2014).</li><li>Wiener, J. M., H&#246;lscher, C., B&#252;chner, S., Konieczny, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Gaze+behaviour+during+space+perception+and+spatial+decision+making.">Gaze behaviour during space perception and spatial decision making.</a> Psychological research. 76 (6), 713-729 (2012).</li><li>Hassabis, D., Chu, C., Rees, G., Weiskopf, N., Molyneux, P. D., Maguire, E. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Decoding+Neuronal+Ensembles+in+the+Human+Hippocampus.">Decoding Neuronal Ensembles in the Human Hippocampus.</a> Current Biology. 19 (7), 546-554 (2009).</li><li>Maguire, E. A., Nannery, R., Spiers, H. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Navigation+around+London+by+a+taxi+driver+with+bilateral+hippocampal+lesions.">Navigation around London by a taxi driver with bilateral hippocampal lesions.</a> Brain. 129, 2894-2907 (2006).</li><li>Marchette, S. A., Vass, L. K., Ryan, J., Epstein, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Anchoring+the+neural+compass:+coding+of+local+spatial+reference+frames+in+human+medial+parietal+lobe.">Anchoring the neural compass: coding of local spatial reference frames in human medial parietal lobe.</a> Nature neuroscience. 17 (11), 1598-1606 (2014).</li><li>Vass, L. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Oscillations+Go+the+Distance:+Low-Frequency+Human+Hippocampal+Oscillations+Code+Spatial+Distance+in+the+Absence+of+Sensory+Cues+during+Teleportation.">Oscillations Go the Distance: Low-Frequency Human Hippocampal Oscillations Code Spatial Distance in the Absence of Sensory Cues during Teleportation.</a> Neuron. 89 (6), 1180-1186 (2016).</li><li>Sharma, G., Gramann, K., Chandra, S., Singh, V., Mittal, A. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Brain+connectivity+during+encoding+and+retrieval+of+spatial+information:+individual+differences+in+navigation+skills.">Brain connectivity during encoding and retrieval of spatial information: individual differences in navigation skills.</a> Brain Informatics. 4 (3), (2017).</li><li>Richardson, A. E., VanderKaay Tomasulo, M. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+acute+stress+on+spatial+tasks+in+humans.">Influence of acute stress on spatial tasks in humans.</a> Physiology &amp; Behavior. 103 (5), 459-466 (2011).</li><li>Duncko, R., Cornwell, B., Cui, L., Merikangas, K. R., Grillon, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acute+exposure+to+stress+improves+performance+in+trace+eyeblink+conditioning+and+spatial+learning+tasks+in+healthy+men.">Acute exposure to stress improves performance in trace eyeblink conditioning and spatial learning tasks in healthy men.</a> Learning &amp; memory (Cold Spring Harbor, N.Y.). 14 (5), 329-335 (2007).</li><li>Klopp, C., Garcia, C., Schulman, A. H., Ward, C. P., Tartar, J. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acute+social+stress+increases+biochemical+and+self+report+markers+of+stress+without+altering+spatial+learning+in+humans.">Acute social stress increases biochemical and self report markers of stress without altering spatial learning in humans.</a> Neuro endocrinology letters. 33 (4), 425-430 (2012).</li><li>Guenzel, F. M., Wolf, O. T., Schwabe, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sex+differences+in+stress+effects+on+response+and+spatial+memory+formation.">Sex differences in stress effects on response and spatial memory formation.</a> Neurobiology of Learning and Memory. 109, 46-55 (2014).</li><li>van Gerven, D. J. H., Ferguson, T., Skelton, R. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Acute+stress+switches+spatial+navigation+strategy+from+egocentric+to+allocentric+in+a+virtual+Morris+water+maze.">Acute stress switches spatial navigation strategy from egocentric to allocentric in a virtual Morris water maze.</a> Neurobiology of Learning and Memory. 132, 29-39 (2016).</li><li>Gr&#252;bel, J., Weibel, R., Jiang, M. H., H&#246;lscher, C., Hackman, D. A., Schinazi, V. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=EVE:+A+Framework+for+Experiments+in+Virtual+Environments.">EVE: A Framework for Experiments in Virtual Environments.</a> Spatial Cognition X: Lecture Notes in Artificial Intelligence. , 159-176 (2017).</li><li>Hegarty, M., Richardson, A. E., Montello, D. R., Lovelace, K., Subbiah, I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+self-report+measure+of+environmental+spatial+ability.">Development of a self-report measure of environmental spatial ability.</a> Intelligence. 30, 425-447 (2002).</li><li>Ziegler, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Psychological+Stress+and+the+Autonomic+Nervous+System.">Psychological Stress and the Autonomic Nervous System.</a> Primer on the Autonomic Nervous System. , 189-190 (2004).</li><li>Michaelis, J. R., Rupp, M. A., Montalvo, F., McConnell, D. S., Smither, J. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Effect+of+Vigil+Length+on+Stress+and+Cognitive+Fatigue.">The Effect of Vigil Length on Stress and Cognitive Fatigue.</a> Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 59 (1), 916-920 (2015).</li><li>Helton, W. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validation+of+a+Short+Stress+State+Questionnaire.">Validation of a Short Stress State Questionnaire.</a> Proceedings of the Human Factors and Ergonomics Society Annual Meeting. 48 (11), 1238-1242 (2004).</li><li>Wolbers, T., Hegarty, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=What+determines+our+navigational+abilities.">What determines our navigational abilities.</a> Trends in Cognitive Sciences. 14 (3), 138-146 (2010).</li><li>Moussa&#239;d, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Crowd+behaviour+during+high-stress+evacuations+in+an+immersive+virtual+environment.">Crowd behaviour during high-stress evacuations in an immersive virtual environment.</a> Journal of The Royal Society Interface. 13 (122), (2016).</li><li>. Lead positioning Available from: <a target="_blank" href="https://lifeinthefastlane.com/ecg-library/basics/lead-positioning/">https://lifeinthefastlane.com/ecg-library/basics/lead-positioning/</a> (2017)</li><li>Wilder, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+law+of+initial+value+in+neurology+and+psychiatry.">The law of initial value in neurology and psychiatry.</a> The Journal of Nervous and Mental Disease. 125 (1), 73-86 (1957).</li><li>Loomis, J., Knapp, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visual+Perception+of+Egocentric+Distance+in+Real+and+Virtual+Environments.">Visual Perception of Egocentric Distance in Real and Virtual Environments.</a> Virtual and Adaptive Environments. , 21-46 (2003).</li><li>Richardson, A. R., Waller, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effect+of+feedback+training+on+distance+estimation+in+virtual+environments.">The effect of feedback training on distance estimation in virtual environments.</a> Applied Cognitive Psychology. 19 (8), 1089-1108 (2005).</li><li>Klatzky, R. L., Loomis, J. M., Beall, A. C., Chance, S. S., Golledge, R. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatial+updating+of+self-position+and+orientation+during+real,+imagined,+and+virtual+locomotion.">Spatial updating of self-position and orientation during real, imagined, and virtual locomotion.</a> Psychological Science. 9, 293-298 (1998).</li><li>Bakker, N. H., Werkhoven, P. J., Passenier, P. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Calibrating+Visual+Path+Integration+in+VEs.">Calibrating Visual Path Integration in VEs.</a> Presence: Teleoperators and Virtual Environments. 10 (2), 216-224 (2001).</li><li>Thrash, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+control+interfaces+for+desktop+virtual+environments.">Evaluation of control interfaces for desktop virtual environments.</a> Presence. 24 (4), (2015).</li><li>Kinateder, M., Warren, W. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Social+Influence+on+Evacuation+Behavior+in+Real+and+Virtual+Environments.">Social Influence on Evacuation Behavior in Real and Virtual Environments.</a> Frontiers in Robotics and AI. 3, 43 (2016).</li><li>Loomis, J. M., Blascovich, J. J., Beall, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Immersive+virtual+environment+technology+as+basic+research+tool+in+psychology.">Immersive virtual environment technology as basic research tool in psychology.</a> Behavior Research Methods, Instruments &amp; Computers. 31 (4), 557-564 (1999).</li></ol>

The authors have nothing to disclose.

In the present paper, we described a protocol for conducting experiments in VR with physiological devices using the EVE framework. These types of experiments are unique because of additional hardware considerations (e.g., physiological devices and other peripherals), the preparatory steps for collecting physiological data using VR, and data management requirements. The present protocol provides the necessary steps for experimenters that intend to collect data from multiple peripherals simultaneously. For example...

Understanding how individuals navigate has important implications for several fields, including cognitive science1,2,3, neuroscience4,5, and computer science6,7. Navigation has been investigated in both real and virtual environments. One advantage of real-world experiments is that navigation does not require the mediation of a control interface and thus may produce more realistic spatial behavior. In contrast, virtual reality (VR) experiments allow for more precise measurement of behavioral (e.g., walking trajectories) and physiological (e.g., heart rate) data, as well as more experimental control (i.e., internal validity). In turn, this approach can result in simpler interpretations of the data and thus more robust theories of navigation. In addition, neuroscience can benefit from VR because researchers can investigate the neural correlates of navigation while participants are engaged in the virtual environment but cannot physically move. For computer scientists, navigation in VR requires unique developments in processing power, memory, and computer graphics in order to ensure an immersive experience. Findings from VR experiments can also be applied in architecture and cartography by informing the design of the building layouts8 and map features9 to facilitate real-world navigation. Recently, advances in VR technology combined with a dramatic decrease in its cost have led to an increase in the number of laboratories employing VR for their experimental designs. Because of this growing popularity, researchers need to consider how to streamline the implementation of VR applications and standardize the experiment workflow. This approach will help shift resources from implementation to the development of theory and extend the existing capabilities of VR.
VR setups can range from more to less realistic in terms of displays and controls. More realistic VR setups tend to require additional infrastructure such as large tracking spaces and high-resolution displays10. These systems often employ redirected walking algorithms in order to inject imperceptible rotations and translations into the visual feedback provided to users and effectively enlarge the virtual environment through which participants can move11,12. These algorithms can be generalized in that they do not require the knowledge of environmental structure13 or predictive in that they assume particular paths for the user14. Although most research on redirected walking has used head-mounted displays (HMDs), some researchers employ a version of this technique with walking-in-place as part of a large projection system (e.g., CAVEs)15. While HMDs can be carried on the head of the participant, CAVE displays tend to provide a wider horizontal field of view16,17. However, less infrastructure is needed for VR systems using desktop displays18,19. Neuroscientific research has also employed VR systems in combination with functional magnetic resonance imaging (fMRI) during scanning20, in combination with fMRI after scanning21,22, and in combination with electroencephalography (EEG) during recording23,24. Software frameworks are needed in order to coordinate the variety of displays and controls that are used for navigation research.
Research that incorporates VR and physiological data poses additional challenges such as data acquisition and synchronization. However, physiological data allows for the investigations of implicit processes that may mediate the relationship between navigation potential and spatial behavior. Indeed, the relationship between stress and navigation has been studied using desktop VR and a combination of different physiological sensors (i.e., heart rate, blood pressure, skin conductance, salivary cortisol, and alpha-amylase)25,26,27,28. For example, van Gerven and colleagues29 investigated the impact of stress on navigation strategy and performance using a virtual reality version of a Morris water maze task and several physiological measures (e.g., skin conductance, heart rate, blood pressure). Their results revealed that stress predicted navigation strategy in terms of landmark use (i.e., egocentric versus allocentric) but was not related to navigation performance. In general, findings from previous studies are somewhat inconsistent regarding the effect of stress on navigation performance and spatial memory. This pattern may be attributable to the separation of the stressor (e.g., the cold pressor procedure26, the Star Mirror Tracing Task25) from the actual navigation task, the use of simple maze-like virtual environments (e.g., virtual Morris water maze26, virtual radial arm maze28), and differences in methodological details (e.g., type of stressor, type of physiological data). Differences in the format of collected physiological data can also be problematic for the implementation and analysis of such studies.
The Experiments in Virtual Experiments (EVE) framework facilitates the design, implementation, and analysis of VR experiments, especially those with additional peripheral devices (e.g., eye trackers, physiological devices)30. The EVE framework is freely available as an open-source project on GitHub (https://cog-ethz.github.io/EVE/). This framework is based on the popular Unity 3D game engine (https://unity3d.com/) and the MySQL database management system (https://www.mysql.com/). Researchers can use the EVE framework in order to prepare the various stages of a VR experiment, including pre- and post-study questionnaires, baseline measurements for any physiological data, training with the control interface, the main navigation task, and tests for spatial memory of the navigated environment&#160;(e.g., judgments of relative direction). Experimenters can also control the synchronization of data from different sources and at different levels of aggregation (e.g., across trials, blocks, or sessions). Data sources may be physical (i.e., connected to the user; see Table of Materials) or virtual (i.e., dependent on interactions between the participant&#39;s avatar and the virtual environment). For example, an experiment may require recording heart rate and position/orientation from the participant when that participant&#39;s avatar moves through a particular area of the virtual environment. All of this data is automatically stored in a MySQL database and evaluated with replay functions and the R package evertools (https://github.com/cog-ethz/evertools/). Evertools provides exporting functions, basic descriptive statistics, and diagnostic tools for distributions of data.
The EVE framework may be deployed with a variety of physical infrastructures and VR systems. In the present protocol, we describe one particular implementation at the NeuroLab at ETH Z&#252;rich (Figure 1). The NeuroLab is a 12 m by 6 m room containing an isolated chamber for conducting EEG experiments, a cubicle containing the VR system (2.6 m x 2.0 m), and a curtained area for attaching physiological sensors. The VR system includes a 55&#34; ultra-high definition television display, a high-end gaming computer, a joystick control interface, and several physiological sensors (see Table of Materials). In the following sections, we describe the protocol for conducting a navigation experiment in the NeuroLab using the EVE framework and physiological sensors, present representative results from one study on stress and navigation, and discuss the opportunities and challenges associated with this system.

<table border="0" cellpadding="0" cellspacing="0" style="width:732px;" width="731">
	<tbody>
		<tr height="21">
			<td height="21" style="height:21px;width:253px;">Alienware Area 51 Base</td>
			<td style="width:143px;">Dell&#160;</td>
			<td style="width:113px;">210-ADHC</td>
			<td style="width:223px;">Computation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">138cm 4K Ultra-HD LED-TV</td>
			<td>Samsung</td>
			<td>UE55JU6470U</td>
			<td>Display</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">SureSigns VS2+</td>
			<td>Philips Healthcare</td>
			<td>863278</td>
			<td>Blood Pressure</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PowerLab 8/35</td>
			<td>AD Instruments</td>
			<td>PL3508</td>
			<td>Skin Conductance</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">PowerLab 26T (LTS)</td>
			<td>AD Instruments</td>
			<td>ML4856</td>
			<td>Heart Rate</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;">Extreme 3D Pro Joystick</td>
			<td>Logitech</td>
			<td>963290-0403</td>
			<td>HID</td>
		</tr>
	</tbody>
</table>

virtual reality experiments with physiological measures

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and laboratory experiments, respectively. VR is especially useful for geographic visualizations and investigations of spatial behavior. In spatial behavior research, VR provides a platform for studying the relationship between navigation and physiological measures (e.g., skin conductance, heart rate, blood pressure). Specifically, physiological measures allow researchers to address novel questions and constrain previous theories of spatial abilities, strategies, and performance. For example, individual differences in navigation performance may be explained by the extent to which changes in arousal mediate the effects of task difficulty. However, the complexities in the design and implementation of VR experiments can distract experimenters from their primary research goals and introduce irregularities in data collection and analysis. To address these challenges, the Experiments in Virtual Environments (EVE) framework includes standardized modules such as participant training with the control interface, data collection using questionnaires, the synchronization of physiological measurements, and data storage. EVE also provides the necessary infrastructure for data management, visualization, and evaluation. The present paper describes a protocol that employs the EVE framework to conduct navigation experiments in VR with physiological sensors. The protocol lists the steps necessary for recruiting participants, attaching the physiological sensors, administering the experiment using EVE, and assessing the collected data with EVE evaluation tools. Overall, this protocol will facilitate future research by streamlining the design and implementation of VR experiments with physiological sensors.

From each participant in the NeuroLab, we typically collect physiological data (e.g., ECG), questionnaire data (e.g., the Santa Barbara Sense of Direction Scale or SBSOD31), and navigation data (e.g., paths through the virtual environment). For example, changes in heart rate (derived from ECG data) have been associated with changes in stress states in combination with other physiological32 and self-report measures<...

Watch this Scientific Journal Video about Virtual Reality Experiments with Physiological Measures at JoVE.com

Virtual Reality Experiments with Physiological Measures

Virtual reality (VR) experiments can be difficult to implement and require meticulous planning. This protocol describes a method for the design and implementation of VR experiments that collect physiological data from human participants. The Experiments in Virtual Environments (EVE) framework is employed to accelerate this process.

Virtual reality (VR) experiments are increasingly employed because of their internal and external validity compared to real-world observation and ...

This method allows for the design and implementation of virtual reality experiments that collect physiological data from human participants. The experiments in virtual environment framework is implied to facilitate this process. The main advantage of this technique is the control of extraneous variables while collecting data from various sources, including physiological devices.The implications of this technique extend toward cognitive science in general because of the potential for studying the relationship between cognition and emotion in a controlled environment. Though this method can provide insight into navigation behavior specifically, it can also be applied to other fields, such as environmental perception, behavioral geography, and decision making. Generally, individuals new to this method will struggle because the knowledge required to collect and analyze physiological measures is sometimes beyond that provided by a cognitive science curriculum.Visual demonstration of this method is important because it provides other researchers with a step-by-step guide for collecting physiological data that includes the placement of electrodes. To begin, open the EDA-ECG software and create a new settings file. Set the sampling rate to 1, 000 hertz and select the appropriate number of channels.Then, save the settings file and re-save a version of this file with a new name for the experimental session. Next, perform an open circuit zero on the EDA electrodes to obtain a baseline measurement of system conductivity. Open the experiment settings menu in the software and enter the experiment parameters.Then, click start experiment. First, ask the participant to read the information sheet and sign an informed consent form. Then, use a wet tissue to clean the index and ring fingers of the participant's non-dominant hand.After ensuring the participant's fingers are dry, connect the two EDA electrodes to the medial phalanges. Place the white, black, and red electrodes on the participant's body between the ribs according to the text protocol. Then, connect the three color-coded ECG wires to their corresponding electrodes.While the participant completes the questionnaires, close the two side walls of the cubicle and prepare for the physiological measurement. Attach the blood pressure cuff to the non-dominant arm. Connect the two EDA wires to the electrodes on the participant's fingers.Ensure the electrodes are attached to the correct locations. Then, turn off the light above the monitor and dim the overhead lights to the lowest setting. Next, zero the EDA channel to obtain a measure of the participant's starting level of skin conductants.In the EDA-ECG software, open the Bio Amp dialog box. Then, choose the signal range in which the heart beat signal covers around one-third of the preview window. Start the recording with the software and ensure the signal is visible in the software window on the experimenter's monitor.Then, start the blood pressure recording by pressing the appropriate button on the blood pressure machine. In the open unity software, click start measurements. Ask the participant to watch the baseline nature video.Ask the participant to complete the training maze in order to practice using the joystick. In the training maze game, the participant will follow the arrows and collect floating gems. After this, instruct the participant to complete the navigation task.Let the participant run through the navigation task. After the participant completes the navigation task, stop the EDA and ECG recording. Then, remove the blood pressure cuff, disconnect the cables to the ECG electrodes, and remove the EDA electrodes from the participant's fingers.Inform the participant that they will be asked another series of questions on the computer, and that they may ask questions if necessary. In the evaluation menu in the eve software, press the add event marker button to mark the events in the physiological measurement files. Then, save the EDA-ECG file in the physiological measurement file in the EDA-ECG software.Next, use the evertools package to export the experimental data for backup. Finally, tidy up the equipment and clean the electrodes with alcohol pads. Using this protocol, 60 participants were studied to investigate the effective stress on the acquisition of spatial knowledge during navigation.As predicted, the physiological data indicated higher arousal for the stress group than the no stress group in terms of heart rate, but not in terms of EDA. In general, there was also a negative relationship between self-reported navigation ability and time required to learn the virtual environment. According to the visualized trajectories, the participants from the stress group also appeared to be more efficient in the virtual environment.This indicates that higher arousal and spatial ability may be related to more efficient navigation behavior. This technique can pave the way for researchers in the field of cognitive science to explore the relationship between stress and human navigation behavior using virtual reality and physiological measures.

virtual-reality-experiments-with-physiological-measures

Research

JoVE Journal

Behavior

12.6K vistas.  ETH Zürich. This method allows for the design and implementation of virtual reality experiments that collect physiological data from human participants. The experiments in virtual environment framework is implied to facilitate this process. The main advantage of this technique is the control of extraneous variables while collecting data from various sources, including physiological devices.The implications of this technique extend toward cognitive science in general because of the potential for st...