{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T10:38:16Z","timestamp":1774435096954,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T00:00:00Z","timestamp":1727308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computers"],"abstract":"<jats:p>Mental workload, visuospatial processes and autonomic nervous system (ANS) activity are highly intertwined phenomena crucial for achieving optimal performance and improved mental health. Virtual reality (VR) serves as an effective tool for creating variety of controlled environments to better probe these features. This study investigates the relationship between mental and visuospatial workload, physiological arousal, and performance during a high-demand task in a VR environment. We utilized a modified version of the popular computer game TETRIS as the task, involving 25 participants, and employed a physiological computing VR headset that simultaneously records multimodal physiological data. Our findings indicate a broadband increase in EEG power just prior to a helper event, followed by a spike of visuospatial engagement (parietal alpha and beta 0-1-3 s) occurring concurrently with a decrease in mental workload (frontal theta 2\u20134 s), and subsequent decreases in visuospatial engagement (parietal theta at 14 s) and physiological arousal (HRV at 20 s). Regression analysis indicated that the subjective relief and helpfulness of the helper intervention was primarily driven by a decrease in physiological arousal and an increase in visuospatial engagement. These findings highlight the importance of multimodal physiological recording in rich environments, such as real world scenarios and VR, to understand the interplay between the various physiological responses involved in mental and visuospatial workload.<\/jats:p>","DOI":"10.3390\/computers13100246","type":"journal-article","created":{"date-parts":[[2024,9,26]],"date-time":"2024-09-26T04:05:46Z","timestamp":1727323546000},"page":"246","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Unraveling the Dynamics of Mental and Visuospatial Workload in Virtual Reality Environments"],"prefix":"10.3390","volume":"13","author":[{"given":"Guillermo","family":"Bernal","sequence":"first","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hahrin","family":"Jung","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7756-5378","authenticated-orcid":false,"given":"\u0130smail Emir","family":"Yass\u0131","sequence":"additional","affiliation":[{"name":"School of Medicine, Bursa Uludag University, 16059 Bursa, Turkey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nelson","family":"Hidalgo","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yodahe","family":"Alemu","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tyler","family":"Barnes-Diana","sequence":"additional","affiliation":[{"name":"Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, RI 02912, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7722-6038","authenticated-orcid":false,"given":"Pattie","family":"Maes","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/S0166-4115(08)62386-9","article-title":"Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research","volume":"Volume 52","author":"Hart","year":"1988","journal-title":"Advances in Psychology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/00140139.2014.956151","article-title":"State of science: Mental workload in ergonomics","volume":"58","author":"Young","year":"2015","journal-title":"Ergonomics"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Hancock, G., Longo, L., Young, M., and Hancock, P. (2021). Mental workload. Handbook of Human Factors and Ergonomics, John Wiley & Sons.","DOI":"10.1002\/9781119636113.ch7"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sweller, J. (2010). Cognitive load theory: Recent theoretical advances. Cognitive Load Theory, Cambridge University Press.","DOI":"10.1007\/978-1-4419-8126-4"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1038\/s41386-021-01132-0","article-title":"The role of prefrontal cortex in cognitive control and executive function","volume":"47","author":"Friedman","year":"2022","journal-title":"Neuropsychopharmacology"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/35036228","article-title":"The prefontral cortex and cognitive control","volume":"1","author":"Miller","year":"2000","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"553","DOI":"10.1038\/nrn873","article-title":"A common reference frame for movement plans in the posterior parietal cortex","volume":"3","author":"Cohen","year":"2002","journal-title":"Nat. Rev. Neurosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.bbr.2009.03.012","article-title":"Parietal cortex and spatial cognition","volume":"202","author":"Sack","year":"2009","journal-title":"Behav. Brain Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1016\/S0959-4388(00)00191-4","article-title":"Neuroimaging of cognitive functions in human parietal cortex","volume":"11","author":"Culham","year":"2001","journal-title":"Curr. Opin. Neurobiol."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Stiles, J., Reilly, J.S., Levine, S.C., Trauner, D.A., and Nass, R. (2012). Spatial Attention, Working Memory, and Executive Function. Neural Plasticity and Cognitive Development: Insights from Children with Perinatal Brain Injury, Oxford University Press.","DOI":"10.1093\/med\/9780195389944.001.0001"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.neubiorev.2008.08.004","article-title":"Claude Bernard and the heart\u2013brain connection: Further elaboration of a model of neurovisceral integration","volume":"33","author":"Thayer","year":"2009","journal-title":"Neurosci. Biobehav. Rev."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.lfs.2008.12.004","article-title":"Central nervous system fatigue alters autonomic nerve activity","volume":"84","author":"Tanaka","year":"2009","journal-title":"Life Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/S0301-0511(96)05223-4","article-title":"Compensatory control in the regulation of human performance under stress and high workload: A cognitive-energetical framework","volume":"45","author":"Hockey","year":"1997","journal-title":"Biol. Psychol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1002\/cne.920180503","article-title":"The relation of strength of stimulus to rapidity of habit-formation","volume":"18","author":"Yerkes","year":"1908","journal-title":"J. Comp. Neurol. Psychol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1007\/s12160-009-9101-z","article-title":"Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health","volume":"37","author":"Thayer","year":"2009","journal-title":"Ann. Behav. Med."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1007\/s10111-020-00641-0","article-title":"Towards measuring cognitive load through multimodal physiological data","volume":"23","author":"Vanneste","year":"2021","journal-title":"Cogn. Technol. Work."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Fernandez Rojas, R., Debie, E., Fidock, J., Barlow, M., Kasmarik, K., Anavatti, S., Garratt, M., and Abbass, H. (2020). Electroencephalographic workload indicators during teleoperation of an unmanned aerial vehicle shepherding a swarm of unmanned ground vehicles in contested environments. Front. Neurosci., 14.","DOI":"10.3389\/fnins.2020.00040"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10648-010-9130-y","article-title":"Using electroencephalography to measure cognitive load","volume":"22","author":"Antonenko","year":"2010","journal-title":"Educ. Psychol. Rev."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1093\/oxfordjournals.eurheartj.a014868","article-title":"Heart rate variability: Standards of measurement, physiological interpretation, and clinical use","volume":"17","author":"Malik","year":"1996","journal-title":"Eur. Heart J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"e14009","DOI":"10.1111\/psyp.14009","article-title":"EEG power spectral measures of cognitive workload: A meta-analysis","volume":"59","author":"Chikhi","year":"2022","journal-title":"Psychophysiology"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"So, W.K.Y., Wong, S.W.H., Mak, J.N., and Chan, R.H.M. (2017). An evaluation of mental workload with frontal EEG. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0174949"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"ENEURO.0170-17.2017","DOI":"10.1523\/ENEURO.0170-17.2017","article-title":"Beyond the Status Quo: A Role for Beta Oscillations in Endogenous Content (Re)Activation","volume":"4","author":"Spitzer","year":"2017","journal-title":"eNeuro"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Mapelli, I., and \u00d6zkurt, T.E. (2019). Brain Oscillatory Correlates of Visual Short-Term Memory Errors. Front. Hum. Neurosci., 13.","DOI":"10.3389\/fnhum.2019.00033"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"016014","DOI":"10.1088\/1741-2552\/ad200d","article-title":"Real-time estimation of EEG-based engagement in different tasks","volume":"21","author":"Natalizio","year":"2024","journal-title":"J. Neural Eng."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhu, Y., Wang, Q., and Zhang, L. (2021). Study of EEG characteristics while solving scientific problems with different mental effort. Sci. Rep., 11.","DOI":"10.1038\/s41598-021-03321-9"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.ijpsycho.2017.10.004","article-title":"Using theta and alpha band power to assess cognitive workload in multitasking environments","volume":"123","author":"Puma","year":"2018","journal-title":"Int. J. Psychophysiol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"137567","DOI":"10.1016\/j.neulet.2023.137567","article-title":"Exploring the effects of different BCI-based attention training games on the brain: A functional near-infrared spectroscopy study","volume":"818","author":"Chen","year":"2024","journal-title":"Neurosci. Lett."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.apergo.2018.08.028","article-title":"Measuring mental workload using physiological measures: A systematic review","volume":"74","author":"Charles","year":"2019","journal-title":"Appl. Ergon."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-50280-3","article-title":"Heart rate and heart rate variability correlate with clinical reasoning performance and self-reported measures of cognitive load","volume":"9","author":"Solhjoo","year":"2019","journal-title":"Sci. Rep."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chen, F., Zhou, J., Wang, Y., Yu, K., Arshad, S.Z., Khawaji, A., and Conway, D. (2016). Robust Multimodal Cognitive Load Measurement, Springer.","DOI":"10.1007\/978-3-319-31700-7"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Kramer, A.F. (2020). Physiological metrics of mental workload: A review of recent progress. Multiple Task Performance, CRC Press.","DOI":"10.1201\/9781003069447-14"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"103778","DOI":"10.1016\/j.compedu.2019.103778","article-title":"A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda","volume":"147","author":"Radianti","year":"2020","journal-title":"Comput. Educ."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Cipresso, P., Giglioli, I.A.C., Raya, M.A., and Riva, G. (2018). The Past, Present, and Future of Virtual and Augmented Reality Research: A Network and Cluster Analysis of the Literature. Front. Psychol., 9.","DOI":"10.3389\/fpsyg.2018.02086"},{"key":"ref_34","unstructured":"Armengol-Urpi, A., and Sarma, S.E. (December, January 28). Sublime: A hands-free virtual reality menu navigation system using a high-frequency SSVEP-based brain-computer interface. Proceedings of the 24th ACM Symposium on Virtual Reality Software and Technology, Tokyo, Japan."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1038\/533153a","article-title":"Low-cost headsets boost virtual reality\u2019s lab appeal","volume":"533","author":"Castelvecchi","year":"2016","journal-title":"Nature"},{"key":"ref_36","unstructured":"Strickland, D. (1997). Virtual reality for the treatment of autism. Virtual Reality in Neuro-Psycho-Physiology, IOS Press."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1145\/257874.257881","article-title":"Overcoming phobias by virtual exposure","volume":"40","author":"Strickland","year":"1997","journal-title":"Commun. ACM"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"026017","DOI":"10.1088\/1741-2552\/aa5a98","article-title":"A multimodal approach to estimating vigilance using EEG and forehead EOG","volume":"14","author":"Zheng","year":"2017","journal-title":"J. Neural Eng."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1111\/j.1469-7610.2010.02328.x","article-title":"A multimodal approach to emotion recognition ability in autism spectrum disorders","volume":"52","author":"Jones","year":"2011","journal-title":"J. Child Psychol. Psychiatry"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Bernal, G., Yang, T., Jain, A., and Maes, P. (2018, January 8\u201312). PhysioHMD: A conformable, modular toolkit for collecting physiological data from head-mounted displays. Proceedings of the 2018 ACM International Symposium on Wearable Computers, Singapore.","DOI":"10.1145\/3267242.3267268"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Gupta, K., Hajika, R., Pai, Y.S., Duenser, A., Lochner, M., and Billinghurst, M. (2020, January 22\u201326). Measuring human trust in a virtual assistant using physiological sensing in virtual reality. Proceedings of the 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Atlanta, GA, USA.","DOI":"10.1109\/VR46266.2020.00099"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1109\/TAFFC.2016.2582490","article-title":"Cognitive load measurement in a virtual reality-based driving system for autism intervention","volume":"8","author":"Zhang","year":"2017","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Dey, A., Chatburn, A., and Billinghurst, M. (2019, January 23\u201327). Exploration of an EEG-based cognitively adaptive training system in virtual reality. Proceedings of the 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan.","DOI":"10.1109\/VR.2019.8797840"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"18399","DOI":"10.1109\/ACCESS.2023.3247133","article-title":"Virtual Reality Cognitive Gaming Based on Brain Computer Interfacing: A Narrative Review","volume":"11","author":"Hadjiaros","year":"2023","journal-title":"IEEE Access"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Bernal, G., Hidalgo, N., Russomanno, C., and Maes, P. (2022, January 12\u201316). Galea: A physiological sensing system for behavioral research in Virtual Environments. Proceedings of the 2022 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Christchurch, New Zealand.","DOI":"10.1109\/VR51125.2022.00024"},{"key":"ref_46","unstructured":"(2024, January 01). Lab Streaming Layer (LSL). Available online: https:\/\/github.com\/sccn\/labstreaminglayer."},{"key":"ref_47","unstructured":"Markello, R., and DuPre, E. (2024, January 01). Physiopy\/Peakdet: A Toolbox for Physiological Peak Detection Analyses. Available online: https:\/\/zenodo.org\/records\/7244954."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Munoz, M.L., van Roon, A., Riese, H., Thio, C., Oostenbroek, E., Westrik, I., de Geus, E.J.C., Gansevoort, R., Lefrandt, J., and Nolte, I.M. (2015). Validity of (Ultra-)Short Recordings for Heart Rate Variability Measurements. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0138921"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Di Dona, G., and Ronconi, L. (2023). Beta oscillations in vision: A (preconscious) neural mechanism for the dorsal visual stream?. Front. Psychol., 14.","DOI":"10.3389\/fpsyg.2023.1296483"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.rehab.2016.01.002","article-title":"Visual perception is dependent on visuospatial working memory and thus on the posterior parietal cortex","volume":"60","author":"Pisella","year":"2017","journal-title":"Ann. Phys. Rehabil. Med."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"8156","DOI":"10.1007\/s12144-021-02081-z","article-title":"The neural basis of Tetris gameplay: Implicating the role of visuospatial processing","volume":"42","author":"Agren","year":"2023","journal-title":"Curr. Psychol."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"438","DOI":"10.1002\/acp.3339","article-title":"Selective Association Between Tetris Game Play and Visuospatial Working Memory: A Preliminary Investigation","volume":"31","author":"Holmes","year":"2017","journal-title":"Appl. Cogn. Psychol."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Hamann, A., and Carstengerdes, N. (2023). Assessing the development of mental fatigue during simulated flights with concurrent EEG-fNIRS measurement. Sci. Rep., 13.","DOI":"10.1038\/s41598-023-31264-w"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Xie, W., and Richards, J. (2022). Cortical Source Localization in EEG Frequency Analysis 2022. The Oxford Handbook of EEG Frequency, Oxford Academic.","DOI":"10.1093\/oxfordhb\/9780192898340.013.16"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"2450024","DOI":"10.1142\/S0129065724500242","article-title":"Spatio-Temporal Image-Based Encoded Atlases for EEG Emotion Recognition","volume":"34","author":"Avola","year":"2024","journal-title":"Int. J. Neural Syst."}],"container-title":["Computers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-431X\/13\/10\/246\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:03:19Z","timestamp":1760112199000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-431X\/13\/10\/246"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,26]]},"references-count":55,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2024,10]]}},"alternative-id":["computers13100246"],"URL":"https:\/\/doi.org\/10.3390\/computers13100246","relation":{},"ISSN":["2073-431X"],"issn-type":[{"value":"2073-431X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,26]]}}}