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 participants of the session time and requirements. Let the participants know that they must wear a loose-fitting top (for blood pressure monitoring), refrain from alcohol for 12 h before the experiment, and refrain from several other activities (i.e., caffeine, smoking, eating, and exercise) for 3 h before the experiment.</li>
</ol>
2. Prepare the Experiment and Physiological Devices Using EVE
<ol>
	<li>Before each experimental session, start the computer, the experimenter monitor, and the testing monitor.</li>
	<li>Ensure that the room fan, the thermometer and the humidity monitor are on.</li>
	<li>Switch on the machine measuring the electrodermal activity (EDA) and the electrocardiography (ECG; e.g., PowerLab from ADInstruments). See Table of Materials.</li>
	<li>Open the EDA/ECG software (EVE currently supports Labchart from ADInstruments) and create a new settings file. Select a sampling rate of 1,000 Hz and the appropriate number of channels (e.g., one for EDA and one for ECG). Save this settings file and re-save a version with a different name for each experimental session.</li>
	<li>For the EDA electrodes, perform an open-circuit zero (i.e., without the electrodes attached to anything) to obtain a baseline measure of system conductivity.</li>
	<li>Ensure that the control interface (e.g., joystick) is connected to the computer.</li>
	<li>On the experimenter monitor, open the executable Unity file for the experiment.
	<ol>
		<li>Open the &#34;Experiment Settings&#34; menu in EVE, and enter the experiment parameters (e.g., participant ID number, physiological measurement file, experimental condition, room temperature and humidity).</li>
		<li>Click &#34;Start Experiment&#34;.</li>
	</ol>
	</li>
</ol>
3. Experimental Procedure
<ol>
	<li>Introduction and consent procedure
	<ol>
		<li>Pick up the participant at the agreed meeting location and guide him/her to the laboratory.</li>
		<li>Indicate that the session will take approximately 90 min and ask the participant to store his or her watch and/or mobile phone.</li>
		<li>Ask the participant to sit in the experimental chair and explain the experimental procedure according to the prepared verbal script.</li>
		<li>Ask the participant to read the information sheet and sign the informed consent form.</li>
	</ol>
	</li>
	<li>Connection of EDA and ECG sensors
	<ol>
		<li>Clean the index finger and the ring finger of the non-dominant hand with a wet tissue without soap. Ensure that they are dry and connect the two EDA electrodes to the medial phalanges.</li>
		<li>Clean the skin on the chest where the ECG electrodes will be placed with a wet cloth.</li>
		<li>Place the white, black, and red electrodes on the participant&#39;s body between the ribs according to Figure 2. Place the white electrode on the upper right abdomen (UR), and the black electrode on the upper left abdomen (UL). Place the red electrode on the lower left abdomen (LL). Ensure that the three electrodes are not directly over a rib.</li>
		<li>Connect the three color-coded ECG wires to the corresponding electrodes attached to the participant&#39;s body.</li>
	</ol>
	</li>
	<li>Pre-experiment questionnaires
	<ol>
		<li>Provide the participant with a keyboard and a mouse that will be used to answer the questionnaires (e.g., demographic questions, the first part of the Short Stress State Questionnaire, the Santa Barbara Sense of Direction Scale), and inform him or her that they will be asked a series of questions on the computer.</li>
		<li>Inform the participants that they can ask the experimenter questions regarding the questionnaires at any time.</li>
		<li>Close the two side walls of the cubicle while the participant is completing the questionnaires.</li>
	</ol>
	</li>
	<li>Preparations for physiological measurement. These steps can be conducted while the participant is completing the questionnaires.
	<ol>
		<li>Inform the participant that the experimenter will now prepare the physiological devices.</li>
		<li>Check that the electrodes are attached to the correct locations.</li>
		<li>Attach the blood pressure cuff to the non-dominant arm.</li>
		<li>Provide instructions to the participant regarding the accurate measurement of blood pressure. Tell the participant to minimize arm and body movements, keep the blood pressure cuff at heart level, and maintain an upright posture with his or her feet flat on the floor.</li>
		<li>Connect the two EDA wires to the electrodes on the fingers.</li>
		<li>Turn off the light above the monitor and dim all other overhead lights to the lowest setting.</li>
		<li>Hand the joystick to the participant and ensure that the mouse is off the screen of the testing monitor.</li>
		<li>Zero the EDA channel in order to obtain a measure of an individual&#39;s starting level of skin conductance.</li>
		<li>In the EDA/ECG software, open the &#34;Bio Amp&#34; dialog box. Choose the signal range in which the heart beat signal covers around one third of the preview window (5 mV in most cases).</li>
		<li>Start recording with the EDA/ECG software, and check whether a signal is visible in the EDA/ECG software window on the experimenter monitor.</li>
		<li>Start blood pressure recording by pressing the appropriate button in the blood pressure machine.</li>
		<li>Switch to the open Unity program, and press &#34;Start Measurements&#34;. A fixation cross should appear.</li>
	</ol>
	</li>
	<li>Joystick training and baseline video
	<ol>
		<li>Ask the participant to watch and follow the training video that instructs him or her how to use the joystick.</li>
		<li>Ask the participants to complete the training maze in order to practice using the joystick. In this training maze, participants are instructed to follow the arrows that indicate a route and collect floating gems.</li>
		<li>If the experiment includes sound, place the headphones on the participant&#39;s head.</li>
		<li>Ask the participant to watch the baseline nature video without moving. This video is used to account for a baseline measurement of the participant&#39;s physiological data during the subsequent analysis.</li>
	</ol>
	</li>
	<li>Navigation task
	<ol>
		<li>Ensure that the participants have read the instructions regarding the to-be-completed navigation task. Inquire as to whether the participant has any questions before the navigation task begins. Tell the participant that they should not ask questions during the navigation task.</li>
		<li>Ask the participant to press the trigger on the joystick when he or she is ready to begin the navigation task.</li>
	</ol>
	</li>
	<li>Final physiological measures and detachment of physiological sensors
	<ol>
		<li>Wait until the system has completed the final blood pressure measurement.</li>
		<li>Stop recording EDA and ECG by pressing the stop button in the EDA/ECG software.</li>
		<li>Remove the blood pressure cuff.</li>
		<li>Remove the EDA electrodes from the participant.</li>
		<li>Ask the participants not to remove the ECG electrodes until the end of the experiment.</li>
		<li>Remove the joystick and headphones.</li>
	</ol>
	</li>
	<li>Post-experiment questionnaires
	<ol>
		<li>Provide the participant with a keyboard and a mouse for the post-experiment questionnaires (e.g., the second part of the Short Stress State Questionnaire, the Self-Assessment Manikin, the Simulator Sickness Questionnaire).</li>
		<li>Inform the participants that they will be asked another series of questions on the computer and that he or she can ask questions if necessary.</li>
	</ol>
	</li>
	<li>End of the experimental session
	<ol>
		<li>Inform the participant that the experimental part is now finished. Thank her or him for participating in the experiment.</li>
		<li>Tell the participant that he/she can now remove the ECG electrodes.</li>
		<li>Pay out the participants and ask them to sign the printed receipt.</li>
		<li>Ask if the participant has any questions regarding the purpose of the experiment, and escort him or her outside of the experimental room.</li>
	</ol>
	</li>
</ol>
4. After Each Experimental Session
<ol>
	<li>Open the &#34;Evaluation&#34; menu in EVE in order to conduct experiment diagnostics (e.g., replay trajectories), and save the physiological measurement files in the EDA/ECG software.</li>
	<li>In the &#34;Evaluation&#34; menu in EVE, press the &#34;Add Event Marker&#34; button to mark events in the physiological measurement files. This step is critical for the analysis of the physiological data in terms of particular experimental phases.</li>
	<li>Save the EDA/ECG file in the physiological measurement file in the EDA/ECG software.</li>
	<li>Export the experimental data for backup using the evertools package.</li>
	<li>Switch off the EDA/ECG machine and clean the EDA electrodes with alcohol pads.</li>
	<li>Mark that the participant showed up in the participant recruitment system.</li>
</ol>

<ol><li>Gallistel, C. R. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aGallistel%2C+CR+%22The+Organization+of+Learning%22">The Organization of Learning</a>. , MIT Press. Cambridge, MA. (1990).</li>
<li>Waller, D., Nadel, L. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aWaller%2C+D+%22Handbook+of+Spatial+Cognition%22">Handbook of Spatial Cognition</a>. , American Psychological Association. Washington D.C. (2013).</li>
<li>Denis, M. <a target="_blank" href="http://scholar.google.com/scholar?hl=en&safe=off&q=author%3aDenis%2C+M+%22Space+and+Spatial+Cognition%3A+A+Multidisciplinary+Perspective%22">Space and Spatial Cognition: A Multidisciplinary Perspective</a>. , Routledge. Abingdon, Oxon. (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/pubmed?term=((The+cognitive+map+in+humans%3A+spatial+navigation+and+beyond%5BTitle%5D)+AND+%22Nature+Neuroscience%22%5BJournal%5D)">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://scholar.google.com/scholar?hl=en&safe=off&q=author%3aO%27Keefe%2C+J+%22The+Hippocampus+as+a+Cognitive+Map%22">The Hippocampus as a Cognitive Map</a>. , Clarendon Press. Oxford. (1978).</li>
<li>Kuipers, B. J. <a target="_blank" href="https://ijcai.org/Proceedings/77-1/Papers/046.pdf">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://scholar.google.com/scholar?hl=en&safe=off&q=author%3aHeppenstall%2C+AJ+%22Agent-Based+Models+of+Geographical+Systems%22">Agent-Based Models of Geographical Systems</a>. , Springer. Netherlands. Dordrecht. (2012).</li>
<li>Kuliga, S. F., Thrash, T., Dalton, R. C., Hölscher, C. <a target="_blank" href="https://www.sciencedirect.com/science/article/pii/S019897151530017X">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>Credé, S., Fabrikant, S. I. <a target="_blank" href="https://link.springer.com/chapter/10.1007/978-3-319-63946-8_31">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/pubmed?term=((WeaVR%3A+a+self-contained+and+wearable+immersive+virtual+environment+simulation+system%29%5BTitle%5D)+AND+%22Behavior+Research+Methods%22%5BJournal%5D)">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/pubmed?term=((15+Years+of+Research+on+Redirected+Walking+in+Immersive+Virtual+Environments%5BTitle%5D)+AND+%22IEEE+Computer+Graphics+and+Applications%22%5BJournal%5D)">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.cs.unc.edu/techreports/01-007.pdf">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/pubmed?term=((Comparing+Four+Approaches+to+Generalized+Redirected+Walking%3A+Simulation+and+Live+User+Data%5BTitle%5D)+AND+%22IEEE+Transactions+on+Visualization+and+Computer+Graphics%22%5BJournal%5D)">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="https://ieeexplore.ieee.org/document/6798851/">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="https://dl.acm.org/citation.cfm?id=509729">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/pubmed?term=((Working+Memory+in+Wayfinding-A+Dual+Task+Experiment+in+a+Virtual+City%5BTitle%5D)+AND+%22Cognitive+Science%3A+A+Multidisciplinary+Journal%22%5BJournal%5D)">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>Grübel, J., Thrash, T., Hölscher, C., Schinazi, V. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Evaluation+of+a+conceptual+framework+for+predicting+navigation+performance+in+virtual+reality%5BTitle%5D)+AND+%22PLOS+ONE%22%5BJournal%5D)">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/pubmed?term=((Variations+in+Cognitive+Maps%3A+Understanding+Individual+Differences+in+Navigation%5BTitle%5D)+AND+%22Journal+of+experimental+psychology.+Learning%2C+memory%2C+and+cognition%22%5BJournal%5D)">Variations in Cognitive Maps: Understanding Individual Differences in Navigation.</a> Journal of experimental psychology. Learning, memory, and cognition. , (2014).</li>
<li>Wiener, J. M., Hölscher, C., Büchner, S., Konieczny, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Gaze+behaviour+during+space+perception+and+spatial+decision+making%5BTitle%5D)+AND+%22Psychological+research%22%5BJournal%5D)">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/pubmed?term=((Decoding+Neuronal+Ensembles+in+the+Human+Hippocampus%5BTitle%5D)+AND+%22Current+Biology%22%5BJournal%5D)">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/pubmed?term=((Navigation+around+London+by+a+taxi+driver+with+bilateral+hippocampal+lesions%5BTitle%5D)+AND+%22Brain%22%5BJournal%5D)">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="https://www.ncbi.nlm.nih.gov/pubmed/25282616">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/pubmed?term=((Oscillations+Go+the+Distance%3A+Low-Frequency+Human+Hippocampal+Oscillations+Code+Spatial+Distance+in+the+Absence+of+Sensory+Cues+during+Teleportation%5BTitle%5D)+AND+%22Neuron%22%5BJournal%5D)">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/pubmed?term=((Brain+connectivity+during+encoding+and+retrieval+of+spatial+information%3A+individual+differences+in+navigation+skills%5BTitle%5D)+AND+%22Brain+Informatics%22%5BJournal%5D)">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/pubmed?term=((Influence+of+acute+stress+on+spatial+tasks+in+humans%5BTitle%5D)+AND+%22Physiology+%26+Behavior%22%5BJournal%5D)">Influence of acute stress on spatial tasks in humans.</a> Physiology & 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/pubmed?term=((Acute+exposure+to+stress+improves+performance+in+trace+eyeblink+conditioning+and+spatial+learning+tasks+in+healthy+men%5BTitle%5D)+AND+%22Learning+%26+memory+%28Cold+Spring+Harbor%2C+N.Y.%29%22%5BJournal%5D)">Acute exposure to stress improves performance in trace eyeblink conditioning and spatial learning tasks in healthy men.</a> Learning & 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/pubmed?term=((Acute+social+stress+increases+biochemical+and+self+report+markers+of+stress+without+altering+spatial+learning+in+humans%5BTitle%5D)+AND+%22Neuro+endocrinology+letters%22%5BJournal%5D)">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/pubmed?term=((Sex+differences+in+stress+effects+on+response+and+spatial+memory+formation%5BTitle%5D)+AND+%22Neurobiology+of+Learning+and+Memory%22%5BJournal%5D)">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/pubmed?term=((Acute+stress+switches+spatial+navigation+strategy+from+egocentric+to+allocentric+in+a+virtual+Morris+water+maze%5BTitle%5D)+AND+%22Neurobiology+of+Learning+and+Memory%22%5BJournal%5D)">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>Grübel, J., Weibel, R., Jiang, M. H., Hölscher, C., Hackman, D. A., Schinazi, V. R. <a target="_blank" href="https://link.springer.com/chapter/10.1007/978-3-319-68189-4_10">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="https://www.sciencedirect.com/science/article/pii/S0160289602001162">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="https://www.sciencedirect.com/science/article/pii/B9780125897624500517">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://journals.sagepub.com/doi/abs/10.1177/1541931215591269">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://journals.sagepub.com/doi/10.1177/154193120404801107">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/pubmed?term=((What+determines+our+navigational+abilities%5BTitle%5D)+AND+%22Trends+in+Cognitive+Sciences%22%5BJournal%5D)">What determines our navigational abilities.</a> Trends in Cognitive Sciences. 14 (3), 138-146 (2010).</li>
<li>Moussaïd, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Crowd+behaviour+during+high-stress+evacuations+in+an+immersive+virtual+environment%5BTitle%5D)+AND+%22Journal+of+The+Royal+Society+Interface%22%5BJournal%5D)">Crowd behaviour during high-stress evacuations in an immersive virtual environment.</a> Journal of The Royal Society Interface. 13 (122), (2016).</li>
<li>Cadogan, M. 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/pubmed?term=((The+law+of+initial+value+in+neurology+and+psychiatry%5BTitle%5D)+AND+%22The+Journal+of+Nervous+and+Mental+Disease%22%5BJournal%5D)">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://psycnet.apa.org/record/2003-06908-002">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="https://onlinelibrary.wiley.com/doi/abs/10.1002/acp.1140">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="https://www.jstor.org/stable/40063340?seq=1#page_scan_tab_contents">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="https://www.mitpressjournals.org/doi/abs/10.1162/105474601750216812">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="https://www.mitpressjournals.org/doi/abs/10.1162/PRES_a_00237?journalCode=pres">Evaluation of control interfaces for desktop virtual environments.</a> Presence. 24 (4), (2015).</li>
<li>Kinateder, M., Warren, W. H. <a target="_blank" href="https://www.frontiersin.org/articles/10.3389/frobt.2016.00043/full">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/pubmed?term=((Immersive+virtual+environment+technology+as+basic+research+tool+in+psychology%5BTitle%5D)+AND+%22Behavior+Research+Methods%2C+Instruments+%26+Computers%22%5BJournal%5D)">Immersive virtual environment technology as basic research tool in psychology.</a> Behavior Research Methods, Instruments & 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><tbody><tr><td>Alienware Area 51 Base</td><td>Dell&amp;nbsp;</td><td>210-ADHC</td><td>Computation</td></tr><tr><td>138 cm 4K Ultra-HD LED-TV</td><td>Samsung</td><td>UE55JU6470U</td><td>Display</td></tr><tr><td>SureSigns VS2+</td><td>Philips Healthcare</td><td>863278</td><td>Blood Pressure</td></tr><tr><td>PowerLab 8/35</td><td>AD Instruments</td><td>PL3508</td><td>Skin Conductance</td></tr><tr><td>PowerLab 26T (LTS)</td><td>AD Instruments</td><td>ML4856</td><td>Heart Rate</td></tr><tr><td>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 ...

virtual-reality-experiments-with-physiological-measures

Research

JoVE Journal

Behavior

12.7K Views.  ETH Zürich. 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.

Video: Virtual Reality Experiments with Physiological Measures

Human Fear Conditioning Conducted in Full Immersion 3-Dimensional Virtual Reality 

Fear conditioning is a widely used paradigm in non-human animal research to investigate the neural mechanisms underlying fear and anxiety. A major challenge in conducting conditioning studies in humans is the ability to strongly manipulate or simulate the environmental contexts that are associated with conditioned emotional behaviors. In this regard, virtual reality (VR) technology is a promising tool. Yet, adapting this technology to meet experimental constraints requires special accommodations. Here we address the methodological issues involved when conducting fear conditioning in a fully immersive 6-sided VR environment and present fear conditioning data.
In the real world, traumatic events occur in complex environments that are made up of many cues, engaging all of our sensory modalities. For example, cues that form the environmental configuration include not only visual elements, but aural, olfactory, and even tactile. In rodent studies of fear conditioning animals are fully immersed in a context that is rich with novel visual, tactile and olfactory cues. However, standard laboratory tests of fear conditioning in humans are typically conducted in a nondescript room in front of a flat or 2D computer screen and do not replicate the complexity of real world experiences. On the other hand, a major limitation of clinical studies aimed at reducing (extinguishing) fear and preventing relapse in anxiety disorders is that treatment occurs after participants have acquired a fear in an uncontrolled and largely unknown context. Thus the experimenters are left without information about the duration of exposure, the true nature of the stimulus, and associated background cues in the environment1. In the absence of this information it can be difficult to truly extinguish a fear that is both cue and context-dependent. Virtual reality environments address these issues by providing the complexity of the real world, and at the same time allowing experimenters to constrain fear conditioning and extinction parameters to yield empirical data that can suggest better treatment options and/or analyze mechanistic hypotheses.
In order to test the hypothesis that fear conditioning may be richly encoded and context specific when conducted in a fully immersive environment, we developed distinct virtual reality 3-D contexts in which participants experienced fear conditioning to virtual snakes or spiders. Auditory cues co-occurred with the CS in order to further evoke orienting responses and a feeling of "presence" in subjects 2 . Skin conductance response served as the dependent measure of fear acquisition, memory retention and extinction.

Human Fear Conditioning Conducted in Full Immersion 3-Dimensional Virtual Reality

Classical fear conditioning paradigm was adapted for human participants in a fully immersive virtual reality setting. Using a discrimination paradigm, conditioned fear, cue and context memory retention, and extinction was measured with skin conductance response to dynamic virtual snakes and spiders (the conditioned stimuli) in two distinct virtual contexts.

Fear conditioning is a widely used paradigm in non-human animal research to investigate the neural mechanisms underlying fear and anxiety. A major ...

Neuroscience

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Studies investigating how people represent themselves and their own body often use variants of &#34;ownership illusions&#34;, such as the traditional rubber-hand illusion or the more recently discovered enfacement illusion. However, these examples require rather artificial experimental setups, in which the artificial effector needs to be stroked in synchrony with the participants&#39; real hand or face&#8212;a situation in which participants have no control over the stroking or the movements of their real or artificial effector. Here, we describe a technique to establish ownership illusions in a setup that is more realistic, more intuitive, and of presumably higher ecological validity. It allows creating the virtual-hand illusion by having participants control the movements of a virtual hand presented on a screen or in virtual space in front of them. If the virtual hand moves in synchrony with the participants&#39; own real hand, they tend to perceive the virtual hand as part of their own body. The technique also creates the virtual-face illusion by having participants control the movements of a virtual face in front of them, again with the effect that they tend to perceive the face as their own if it moves in synchrony with their real face. Studying the circumstances that illusions of this sort can be created, increased, or reduced provides important information about how people create and maintain representations of themselves.

Here, we describe virtual-hand and virtual-face illusion paradigms that can be used to study body-related self-perception/-representation. They have already been used in various studies to demonstrate that, under specific conditions, a virtual hand or face can be incorporated into one&#39;s body representation, suggesting that body representations are rather flexible.

Studies investigating how people represent themselves and their own body often use variants of &#34;ownership illusions&#34;, such as the traditional ...

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

People&#39;s responses to products and/or choice environments are crucial to understanding in-store consumer behaviors. Currently, there are various approaches (e.g., surveys or laboratory settings) to study in-store behaviors, but the external validity of these is limited by their poor capability to resemble realistic choice environments. In addition, building a real store to meet experimental conditions while controlling for undesirable effects is costly and highly difficult. A virtual store developed by virtual reality techniques potentially transcends these limitations by offering the simulation of a 3D virtual store environment in a realistic, flexible, and cost-efficient way. In particular, a virtual store interactively allows consumers (participants) to experience and interact with objects in a tightly controlled yet realistic setting. This paper presents the key elements of using a desktop virtual store to study in-store consumer behavior. Descriptions of the protocol steps to: 1) build the experimental store, 2) prepare the data management program, 3) run the virtual store experiment, and 4) organize and export data from the data management program are presented. The virtual store enables participants to navigate through the store, choose a product from alternatives, and select or return products. Moreover, consumer-related shopping behaviors (e.g., shopping time, walking speed, and number and type of products examined and bought) can also be collected. The protocol is illustrated with an example of a store layout experiment showing that shelf length and shelf orientation influence shopping- and movement-related behaviors. This demonstrates that the use of a virtual store facilitates the study of consumer responses. The virtual store can be especially helpful when examining factors that are costly or difficult to change in real life (e.g., overall store layout), products that are not presently available in the market, and routinized behaviors in familiar environments.

This paper describes the use of a desktop virtual store to create virtual shopping environments to investigate in-store consumer behavior. A description of the protocol to build and run experiments, example results from an experiment concerning store layout, and important considerations when conducting virtual store experiments are presented.

People&#39;s responses to products and/or choice environments are crucial to understanding in-store consumer behaviors. Currently, there are various ...

The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project

Generalized anxiety disorder (GAD) is a psychiatric disorder characterized by a constant and unspecific anxiety that interferes with daily-life activities. Its high prevalence in general population and the severe limitations it causes, point out the necessity to find new efficient strategies to treat it. Together with the cognitive-behavioral treatments, relaxation represents a useful approach for the treatment of GAD, but it has the limitation that it is hard to be learned. The INTREPID project is aimed to implement a new instrument to treat anxiety-related disorders and to test its clinical efficacy in reducing anxiety-related symptoms. The innovation of this approach is the combination of virtual reality and biofeedback, so that the first one is directly modified by the output of the second one. In this way, the patient is made aware of his or her reactions through the modification of some features of the VR environment in real time. Using mental exercises the patient learns to control these physiological parameters and using the feedback provided by the virtual environment is able to gauge his or her success. The supplemental use of portable devices, such as PDA or smart-phones, allows the patient to perform at home, individually and autonomously, the same exercises experienced in therapist's office. The goal is to anchor the learned protocol in a real life context, so enhancing the patients' ability to deal with their symptoms. The expected result is a better and faster learning of relaxation techniques, and thus an increased effectiveness of the treatment if compared with traditional clinical protocols.

The Project on Virtual Reality Intelligent Multi-sensor System for the Treatment of Anxiety-related Disorders (INTREPID) is aimed at developing a multi-sensor context-aware virtual reality system for the treatment of anxiety-related disorders.

Generalized anxiety disorder (GAD) is a psychiatric disorder characterized by a constant and unspecific anxiety that interferes with daily-life ...

Biology

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

Efficient and economical performance evaluation of pilots has become critical to the aviation industry. With the development of virtual reality (VR) and the combination of eye-tracking technology, solutions to meet these needs are becoming a reality. Previous studies have explored VR-based flight simulators, focusing mainly on technology validation and flight training. The current study developed a new VR flight simulator to evaluate pilots' flight performance based on eye movement and flight indicators in a 3D immersive scene. During the experiment, 46 participants were recruited: 23 professional pilots and 23 college students without flight experience. The experiment results showed significant differences in flight performance between participants with and without flight experience, the former being higher than the latter. In contrast, those with flight experience showed more structured and efficient eye-movement patterns. These results of the differentiation of flight performance demonstrate the validity of the current VR flight simulator as a flight performance assessment method. The different eye-movement patterns with flight experience provide the basis for future flight selection. However, this VR-based flight simulator has shortcomings like motion feedback compared to traditional flight simulators. This flight simulator platform is highly flexible except for the apparent low cost. It can meet the diverse needs of researchers (e.g., measuring situation awareness, VR sickness, and workload by adding relevant scales).

A new virtual reality flight simulator was built, which enables efficient and low-cost evaluation of flight performance and eye movement patterns. It also provides a high-potential research tool for ergonomics and other research.

Efficient and economical performance evaluation of pilots has become critical to the aviation industry. With the development of virtual reality (VR) and ...

The Immersive Cleveland Clinic Virtual Reality Shopping Platform for the Assessment of Instrumental Activities of Daily Living

A decline in the performance of instrumental activities of daily living (IADLs) has been proposed as a prodromal marker of neurological disease. Existing clinical and performance-based IADL assessments are not feasible for integration into clinical medicine. Virtual reality (VR) is a powerful yet underutilized tool that could advance the diagnosis and treatment of neurological disease. An impediment to the adoption and scaling of VR in clinical neurology is VR-related sickness resulting from sensory inconsistencies between the visual and vestibular systems (i.e., locomotion problem).
The Cleveland Clinic Virtual Reality Shopping (CC-VRS) platform attempts to solve the locomotion problem by coupling an omnidirectional treadmill with high-resolution VR content, enabling the user to physically navigate a virtual grocery store to simulate shopping. The CC-VRS consists of Basic and Complex shopping experiences; both require walking 150 m and retrieving five items. The Complex experience has additional scenarios that increase the cognitive and motor demands of the task to better represent the continuum of activities associated with real-world shopping. The CC-VRS platform provides objective and quantitative biomechanical and cognitive outcomes related to the user&#39;s IADL performance. Initial data indicate that the CC-VRS results in minimal VR-sickness and is feasible and tolerable for older adults and patients with Parkinson&#39;s disease (PD). The considerations underlying the development, design, and hardware and software technology are reviewed, and initial models of integration into primary care and neurology are provided.

Virtual reality (VR) is a powerful yet underutilized approach to advance the diagnosis and treatment of neurological disease. The Cleveland Clinic Virtual Reality Shopping platform combines state-of-the-art VR content with an omnidirectional treadmill to quantify instrumental activities of daily living-a proposed prodromal marker of neurological disease.

A decline in the performance of instrumental activities of daily living (IADLs) has been proposed as a prodromal marker of neurological disease. Existing ...

Engineering

Integrating VR and Biosensors for Quantitative Motion-Muscle Activity Assessment

Setup for the Quantitative Assessment of Motion and Muscle Activity During a Virtual Modified Box and Block Test

The ability to move allows us to interact with the world. When this ability is impaired, it can significantly reduce one's quality of life and independence and may lead to complications. The importance of remote patient evaluation and rehabilitation has recently grown due to limited access to in-person services. For example, the COVID-19 pandemic unexpectedly resulted in strict regulations, reducing access to non-emergent healthcare services. Additionally, remote care offers an opportunity to address healthcare disparities in rural, underserved, and low-income areas where access to services remains limited. 
Improving accessibility through remote care options would limit the number of hospital or specialist visits and render routine care more affordable. Finally, the use of readily available commercial consumer electronics for at-home care can enhance patient outcomes due to improved quantitative observation of symptoms, treatment efficacy, and therapy dosage. While remote care is a promising means to address these issues, there is a crucial need to quantitatively characterize motor impairment for such applications. The following protocol seeks to address this knowledge gap to enable clinicians and researchers to obtain high-resolution data on complex movement and underlying muscle activity. The ultimate goal is to develop a protocol for remote administration of functional clinical tests. 
Here, participants were instructed to perform a medically-inspired Box and Block task (BBT), which is frequently used to assess hand function. This task requires subjects to transport standardized cubes between two compartments separated by a barrier. We implemented a modified BBT in virtual reality to demonstrate the potential of developing remote assessment protocols. Muscle activation was captured for each subject using surface electromyography. This protocol allowed for the acquisition of high-quality data to better characterize movement impairment in a detailed and quantitative manner. Ultimately, these data have the potential to be used to develop protocols for virtual rehabilitation and remote patient monitoring.

Author Spotlight: Enhancing Remote Rehabilitation with Virtual Reality and Electromyography

The protocol described here aims to enhance the quantitative evaluation of upper limb deficits, with the goal of developing additional technology for remote assessment both in the clinic and at home. Virtual reality and biosensor technologies are combined with standard clinical techniques to provide insights into the functioning of the neuromuscular system.

The ability to move allows us to interact with the world. When this ability is impaired, it can significantly reduce one's quality of life and ...

Motor Imagery Using VR Digital Avatars in a Brain-Computer Interface System

Motor Imagery Performance Through Embodied Digital Twins in a Virtual Reality-Enabled Brain-Computer Interface Environment

This study introduces an innovative framework for neurological rehabilitation by integrating brain-computer interfaces (BCI) and virtual reality (VR) technologies with the customization of three-dimensional (3D) avatars. Traditional approaches to rehabilitation often fail to fully engage patients, primarily due to their inability to provide a deeply immersive and interactive experience. This research endeavors to fill this gap by utilizing motor imagery (MI) techniques, where participants visualize physical movements without actual execution. This method capitalizes on the brain's neural mechanisms, activating areas involved in movement execution when imagining movements, thereby facilitating the recovery process. The integration of VR's immersive capabilities with the precision of electroencephalography (EEG) to capture and interpret brain activity associated with imagined movements forms the core of this system. Digital Twins in the form of personalized 3D avatars are employed to significantly enhance the sense of immersion within the virtual environment. This heightened sense of embodiment is crucial for effective rehabilitation, aiming to bolster the connection between the patient and their virtual counterpart. By doing so, the system not only aims to improve motor imagery performance but also seeks to provide a more engaging and efficacious rehabilitation experience. Through the real-time application of BCI, the system allows for the direct translation of imagined movements into virtual actions performed by the 3D avatar, offering immediate feedback to the user. This feedback loop is essential for reinforcing the neural pathways involved in motor control and recovery. The ultimate goal of the developed system is to significantly enhance the effectiveness of motor imagery exercises by making them more interactive and responsive to the user's cognitive processes, thereby paving a new path in the field of neurological rehabilitation.

Author Spotlight: Enhancing Neurorehabilitation Through EEG, Motor Imagery, and Virtual Reality

Motor imagery in a virtual reality environment has wide applications in brain-computer interface systems. This manuscript outlines the use of personalized digital avatars that resemble the participants performing movements imagined by the participant in a virtual reality environment to enhance immersion and a sense of body ownership.

This study introduces an innovative framework for neurological rehabilitation by integrating brain-computer interfaces (BCI) and virtual reality (VR) ...

Bioengineering

Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure

Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that changes the likelihood of neuronal firing through modulation of neural resting membranes. Compared to other techniques, tDCS is relatively safe, cost-effective, and can be administered while individuals are engaged in controlled, specific cognitive processes. This latter point is important as tDCS may predominantly affect intrinsically active neural regions. In an effort to test tDCS as a potential treatment for psychiatric illness, the protocol described here outlines a novel procedure that allows the simultaneous application of tDCS during exposure to trauma-related cues using virtual reality (tDCS+VR) for veterans with posttraumatic stress disorder (NCT03372460). In this double-blind protocol, participants are assigned to either receive 2 mA tDCS, or sham stimulation, for 25 minutes while passively watching three 8-minute standardized virtual reality drives through Iraq or Afghanistan, with virtual reality events increasing in intensity during each drive. Participants undergo six sessions of tDCS+VR over the course of 2-3 weeks, and psychophysiology (skin conductance reactivity) is measured throughout each session. This allows testing for within and between session changes in hyperarousal to virtual reality events and adjunctive effects of tDCS. Stimulation is delivered through a built-in rechargeable battery-driven tDCS device using a 1 (anode) x 1 (cathode) unilateral electrode set-up. Each electrode is placed in a 3 x 3 cm (current density 2.22 A/m2) reusable sponge pocket saturated with 0.9% normal saline. Sponges with electrodes are attached to the participant&#8217;s skull using a rubber headband with the electrodes placed such that they target regions within the ventromedial prefrontal cortex. The virtual reality headset is placed over the tDCS montage in such a way as to avoid electrode interference.

This manuscript outlines a novel protocol to allow the simultaneous application of transcranial direct current stimulation during exposure to warzone trauma-related cues using virtual reality for veterans with posttraumatic stress disorder.

Transcranial direct current stimulation (tDCS) is a form of non-invasive brain stimulation that changes the likelihood of neuronal firing through ...

Virtual Prism Adaptation Therapy: Protocol for Validation in Healthy Adults

Hemispatial neglect is a common impairment after stroke. It is associated with poor functional and social outcomes. Therefore, an adequate intervention is imperative for the successful management of hemispatial neglect. However, the clinical use of various interventions is limited in real clinical practice. Prism adaptation therapy is one of the most evidence-based rehabilitation modalities to treat hemispatial neglect. To overcome any possible shortcoming that may occur with prism therapy, we developed a new system using immersive virtual reality and depth-sensing camera to create a virtual prism adaptation therapy (VPAT). To validate the VPAT system, we designed an experimental protocol investigating the behavioral errors and changes in cortical activation via the VPAT system. Cortical activation was measured by functional near infrared spectroscopy (fNIRS). The experiment consisted of four phases. All four included clicking, pointing or rest applied to right-handed healthy people. Clicking versus pointing was used for investigating the cortical region related with the gross motor task, and pointing with VPAT versus pointing without VPAT was used for investigating the cortical region associated with visuospatial perception. The preliminary results from four healthy participants showed that pointing errors by the VPAT system was similar to the conventional prism adaptation therapy. Further analysis with more participants and fNIRS data, as well as a study in patients with stroke may be required.

This experimental protocol demonstrates the use of virtual prism adaptation therapy (VPAT) in healthy adults and the association between VPAT and functional near infrared spectroscopy to determine the effect of VPAT on cortical activation. Results suggest that VPAT may be feasible and could induce similar behavioral adaptation as conventional prism adaptation therapy.

Hemispatial neglect is a common impairment after stroke. It is associated with poor functional and social outcomes. Therefore, an adequate intervention is ...

Virtual Reality Experiments with Physiological Measures

Summary

Explore More Videos

Human Fear Conditioning Conducted in Full Immersion 3-Dimensional Virtual Reality

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Using a Virtual Store As a Research Tool to Investigate Consumer In-store Behavior

The use of Biofeedback in Clinical Virtual Reality: The INTREPID Project

Evaluating Flight Performance and Eye Movement Patterns Using Virtual Reality Flight Simulator

The Immersive Cleveland Clinic Virtual Reality Shopping Platform for the Assessment of Instrumental Activities of Daily Living

Setup for the Quantitative Assessment of Motion and Muscle Activity During a Virtual Modified Box and Block Test

Motor Imagery Performance Through Embodied Digital Twins in a Virtual Reality-Enabled Brain-Computer Interface Environment

Simultaneous Application of Transcranial Direct Current Stimulation during Virtual Reality Exposure

Virtual Prism Adaptation Therapy: Protocol for Validation in Healthy Adults