Abstract
Virtual Reality (VR) not only offers great opportunities in terms of entertainment, it is also widely applicable in the field of attention guidance, medicine and psychology. The distinction between VR and ordinary media is the 360\(^\circ \) - also known as omnidirectional - environment. When applying the option of an omnidirectional platform with auditory as well as visual actions, the focus on the right story line within VR is crucial. In order to analyze whether attention guidance in VR activates the same brain regions as in the real world, data of both topographical brain views must be compared. To do so, functional near-infrared spectroscopy (fNIRS), a brain imaging technology, is being utilized. fNIRS is a non-invasive neuroimaging technique, which measures brain oxygenation and by that identifies brain activity. The fNIRS method offers a fast and convenient application and is easily adaptable to the field of VR. In this experiment, the brain activity of 23 participants was examined under two scenarios. The first scenario required the location of click noises when being present in the real world, while the second scenario demanded the same in the virtual reality. The environment of both settings - in the real world as well as in the virtual world - were identical. Each brain picture was analyzed on the basis of a within-subject design. Therefore, all participants were required to experience both settings while wearing fNIRS in order to compare similarities and differences of the recordings. Once all 46 recordings were allocated and broken down by milliseconds, a cortex view through Oxysoft - a software that analyzes and evaluates NIRS recordings - was generated. Despite fNIRS limited recording depth, increased brain activity was detected during the subject’s click orientation. The greatest disparity between the resting phase and the stimulation was visible in the temporal as well as the parietal lobe. Findings also showed that in spite of the stimulated brain regions, the hemoglobin level remained the same in both environments, the real world and the virtual world.
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References
Bucher, J.: Storytelling for Virtual Reality: Methods and Principles for Crafting Immersive Narratives. Taylor & Francis Group, New York (2017)
Smith, W.S., Tadmor, Y.: Nonblurred regions show priority for gaze directon over spatical blur. Q. J. Exp. Psychol. (2013). https://doi.org/10.1080/17440218.2012722659
Hata, H., Koike, H., Sato, Y.: Visual guidance with unnoticed blur effect. In: Proceedings of the International Working Conference on Advanced Visual Interfaces - AVI 2016. ACM Press, New York (2016)
Cole, F., DeCarlo, D., Finkelstein, A., Kin, K., Morley, K., Santella, A.: Directing gaze in 3D models with stylized focus. In: Proceedings of the 17th Europgraphics Conference on Rendering Techniques (2006). https://doi.org/10.2312/egwr/egsr06/377-387
Rothe, S., Buschek, D., Hussmann, H.: Guidance in cinematic virtual reality-taxonomy, research status and challenges. Multimodal Technol. Interact. 3, 19 (2019). https://doi.org/10.3390/mti3010019
Subramanian, R., Shankar, D., Sebe, N., Melcher, D.: Emotion modulates eye movement patterns and subsequent memory for the gist and details of movie scenes. J. Vis. 14, 31 (2014). https://doi.org/10.1167/14.3.31
Dorr, M., Vig, E., Barth, E.: Eye movement prediction and variability on natural video data sets. Vis. Cogn. 20 (2012). https://doi.org/10.1080/13506285.2012.667456
Tse, A., Jennet, C., Moore, J., Watson, Z., Rigby, J., Cox, A.L.: Was i there? In: Proceedings of the 2017 CHI Conference Extended Abstracts on Human Factors in Computing Systems. ACM Press, New York (2017)
MacQuarrie, A., Steed, A.: Cinematic virtual reality: evaluating the effect of display type on the viewing experience for panoramic video. In: Proceedings of the 2017 IEEE Virtual Reality (VR), Los Angeles, CA, USA (2017)
Sheikh, A., Brown, A., Watson, Z., Evans, M.: Directing attention in 360-degree video. In: IBC 2016 Conference (2016)
Rothe, S., Hussmann, H., Allary, M.: Diegetic cues for guiding the viewer in cinematic virtual reality. In: Proceedings of the 23rd ACM Symposium (2017). https://doi.org/10.1145/3139131.3143421
Bohil, C., Alicea, B., Biocca, F.: Virtual reality in neuroscience research and therapy. Nat. Rev. Neurosci. 12, 752–62 (2011). https://doi.org/10.1038/nrn3122
Seraglia, B., Gamberini, L., Priftis, K., Scatturin, P., Martinelli, M., Cutini, S.: An exploratory fNIRS study with immersive virtual reality: a new method for technical implementation. Front. Hum. Neurosci. 5, 176 (2011). https://doi.org/10.3389/fnhum.2011.00176
Peck, E.M., Afergan, D., Yuksel, B.F., Lalooses, F., Jacob, R.J.K.: Using fNIRS to measure mental workload in the real world. In: Fairclough, S.H., Gilleade, K. (eds.) Advances in Physiological Computing. HIS, pp. 117–139. Springer, London (2014). https://doi.org/10.1007/978-1-4471-6392-3_6
Cansiz, Y., Tokel, S.T.: Effects of way finding affordances on usability of virtual world environments in terms of users’ satisfaction, performance, and mental workload: examination by eye-tracking and fNIR. In: Amiel, T., Wilson, B. (eds.) Proceedings of EdMedia + Innovate Learning 2012, pp. 1073–1079. Association for the Advancement of Computing in Education (AACE), Waynesville (2012)
Campbell, Z., Zakzanis, K., Jovanovski, D., Joordens, S., Mraz, R., Graham, S.J.: Utilizing virtual reality to improve the ecological validity of clinical neuropsychology: an fMRI case study elucidating the neural basis of planning by comparing the Tower of London with a three-dimensional navigation task. Appl. Neuropsychol. 16, 295–306 (2009)
Perani, D., et al.: Different brain correlates for watching real and virtual hand actions. Neuroimage 14, 749–758 (2001)
Ulsamer, P., Pfeffel, K., Müller, N.H.: Indoor navigation through storytelling in virtual reality. In: Zaphiris, P., Ioannou, A. (eds.) HCII 2019. LNCS, vol. 11591, pp. 230–239. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21817-1_18
Boecker, M., Schroeter, M.L.: Signal-und bildgebende Verfahren: Nahinfrarot-Spektroskopie. In: Gauggel, S., Hermann, M. (eds.) Handbuch der Neuro-und Biopsychologie, pp. 211–219. Hogrefe, Goettingen (2008)
Kober, S., Wood, G., Neuper, C.: Measuring brain activation during spatial navigation in virtual reality: a combined EEG-NIRS study. In: Virtual Environments: Developments, Applications and Challenges, pp. 1–24 (2013)
Siegel, A.W., White, S.H.: The development of spatial representations of large-scale environments. Adv. Child Dev. Behav. 10, 9–55 (1975). https://doi.org/10.1016/s0065-2407(08)60007-5. PMID: 1101663
Janzen, G., van Turennout, M.: Selective neural representation of objects relevant for navigation. Nat. Neurosci. 7, 673–677 (2004). https://doi.org/10.1038/nn1257
Maguire, E.A., Burgess, N., Donnett, J.G., Frackowiak, R.S., Frith, C.D., O’Keefe, J.: Knowing where and getting there: a human navigation network. Science 280(5365), 921–4 (1998)
Molholm, S., Martinez, A., Ritter, W., Javitt, D.C., Foxe, J.J.: The neural circuitry of pre-attentive auditory change-detection: an fMRI study of pitch and duration mismatch negativity generators. Cereb. Cortex 15, 545–551 (2005)
Wolbers, T., et al.: Neural foundations of emerging route knowledge in complex spatial environments. Cogn. Brain. Res. 21(3), 401–411 (2004)
Grön, G., Wunderlich, A., Spitzer, M., et al.: Brain activation during human navigation: gender-different neural networks as substrate of performance. Nat. Neurosci. 3, 404–408 (2000). https://doi.org/10.1038/73980
Scholkmann, F., Kleiser, S., Metz, A.J., Zimmermann, R., Pavia, J.M., Wolf, U., et al.: A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage 85, 6–27 (2014). https://doi.org/10.1016/j.neuroimage.2013.05.004
Siegel, A.M., Marota, J.J.A., Boas, D.A.: Design and evaluation of a continuous-wave diffuse optical tomography system. Opt. Express 4, 287–298 (1999). https://doi.org/10.1364/OE.4.000287
Weiskopf, N.: Real-time fMRI and its application to neurofeedback. NeuroImage 62, 682–692 (2012)
Kamran, M.A., Mannann, M.M.N., Jeong, M.Y.: Differential path-length factor’s effect on the characterization of brain’s hemodynamic response function: a functional near-infrared study. Front. Neuroinform. 12, 37 (2018). https://doi.org/10.3389/fninf.2018.00037
Duncan, A., Meek, J., Clemence, M., et al.: Measurement of cranial optical path length as a function of age using phase resolved near infrared spectroscopy. Pediatr. Res. 39, 889–894 (1996). https://doi.org/10.1203/00006450-199605000-00025
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Ulsamer, P., Pfeffel, K., Müller, N.H. (2020). Brain Activation in Virtual Reality for Attention Guidance. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Human and Technology Ecosystems. HCII 2020. Lecture Notes in Computer Science(), vol 12206. Springer, Cham. https://doi.org/10.1007/978-3-030-50506-6_14
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