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Moving visual stimuli can elicit the sensation of self-motion in stationary observers, a phenomenon commonly referred to as vection. Despite the long history of vection research, the neuro-cognitive processes underlying vection have only recently gained increasing attention. Various neuropsychological techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have been used to investigate the temporal and spatial characteristics of the neuro-cognitive processing during vection in healthy participants. These neuropsychological studies allow for the identification of different neuro-cognitive correlates of vection, which (a) will help to unravel the neural basis of vection and (b) offer opportunities for applying vection as a tool in other research areas. The purpose of the current review is to evaluate these studies in order to show the advances in neuropsychological vection research and the challenges that lie ahead. The overview of the literature will also demonstrate the large methodological variability within this research domain, limiting the integration of results. Next, we will summarize methodological considerations and suggest helpful recommendations for future vection research, which may help to enhance the comparability across neuropsychological vection studies.
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Adamovich, S. V., Fluet, G. G., Tunik, E. and Merians, A. S. (2009). Sensorimotor training in virtual reality: a review, NeuroRehabilitation 25, 29–44. DOI:10.3233/NRE-2009-0497.
Allison, R. S., Howard, I. P. and Zacher, J. E. (1999). Effect of field size, head motion, and rotational velocity on roll vection and illusory self-tilt in a tumbling room, Perception 28, 299–306. DOI:10.1068/p2891.
Apthorp, D., Nagle, F. and Palmisano, S. (2014). Chaos in balance: non-linear measures of postural control predict individual variations in visual illusions of motion, PLoS ONE 9, e113897. DOI:10.1371/journal.pone.0113897.
Arnoldussen, D. M., Goossens, J. and van den Berg, A. V. (2013). Differential responses in dorsal visual cortex to motion and disparity depth cues, Front. Hum. Neurosci. 7, 815. DOI:10.3389/fnhum.2013.00815.
Becker-Bense, S., Buchholz, H.-G., zu Eulenburg, P., Best, C., Bartenstein, P., Schreckenberger, M. and Dieterich, M. (2012). Ventral and dorsal streams processing visual motion perception (FDG-PET study), BMC Neurosci. 13, 81. DOI:10.1186/1471-2202-13-81.
Berti, S., Haycock, B., Adler, J. and Keshavarz, B. (2019). Early cortical processing of vection-inducing visual stimulation as measured by event-related brain potentials (ERP), Displays 58, 56–65. DOI:10.1016/j.displa.2018.10.002.
Boegle, R., Stephan, T., Ertl, M., Glasauer, S. and Dieterich, M. (2016). Magnetic vestibular stimulation modulates default mode network fluctuations, NeuroImage 127, 409–421. DOI:10.1016/j.neuroimage.2015.11.065.
Braddick, O. J., O’Brien, J. M. D., Wattam-Bell, J., Atkinson, J., Hartley, T. and Turner, R. (2001). Brain areas sensitive to coherent visual motion, Perception 30, 61–72. DOI:10.1068/p3048.
Brandt, T., Dichgans, J. and Koenig, E. (1973). Differential effects of central versus peripheral vision on egocentric and exocentric motion perception, Exp. Brain Res. 16, 476–491. DOI:10.1007/BF00234474.
Brandt, T., Bartenstein, P., Janek, A. and Dieterich, M. (1998). Reciprocal inhibitory visual-vestibular interaction. Visual motion stimulation deactivates the parieto-insular vestibular cortex, Brain 121, 1749–1758. DOI:10.1093/brain/121.9.1749.
Bremmer, F. (2011). Multisensory space: from eye movements to self-motion, J. Physiol. 589, 815–823. DOI:10.1113/jphysiol.2010.195537.
Bremmer, F., Schlack, A., Shah, N. J., Zafiris, O., Kubischik, M., Hoffmann, K.-P., Zilles, K. and Fink, G. R. (2001). Polymodal motion processing in posterior parietal and premotor cortex: a human fMRI study strongly implies equivalencies between humans and monkeys, Neuron 29, 287–296.
Britton, Z. and Arshad, Q. (2019). Vestibular and multi-sensory influences upon self-motion perception and the consequences for human behavior, Front. Neurol. 10, 63. DOI:10.3389/fneur.2019.00063.
Cardin, V. and Smith, A. T. (2010). Sensitivity of human visual and vestibular cortical regions to egomotion-compatible visual stimulation, Cereb. Cortex 20, 1964–1973. DOI:10.1093/cercor/bhp268.
Cardin, V., Hemsworth, L. and Smith, A. T. (2012). Adaptation to heading direction dissociates the roles of human MST and V6 in the processing of optic flow, J. Neurophysiol. 108, 794–801. DOI:10.1152/jn.00002.2012.
Culham, J. C. and Kanwisher, N. G. (2001). Neuroimaging of cognitive functions in human parietal cortex, Curr. Opin. Neurobiol. 11, 157–163. DOI:10.1016/s0959-4388(00)00191-4.
Cuturi, L. F. and MacNeilage, P. R. (2014). Optic flow induces nonvisual self-motion aftereffects, Curr. Biol. 24, 2817–2821. DOI:10.1016/j.cub.2014.10.015.
DeAngelis, G. C. and Angelaki, D. E. (2012). Visual–vestibular integration for self-motion perception, in: The Neural Bases of Multisensory Processes, ch. 31, M. M. Murray and M. T. Wallace (Eds). CRC Press/Taylor & Francis, Boca Raton, FL, USA. http://www.ncbi.nlm.nih.gov/books/NBK92839/.
Deutschländer, A., Bense, S., Stephan, T., Schwaiger, M., Dieterich, M. and Brandt, T. (2004). Rollvection versus linearvection: comparison of brain activations in PET, Hum. Brain Mapp. 21, 143–153. DOI:10.1002/hbm.10155.
Dieterich, M., Bense, S., Stephan, T., Yousry, T. A. and Brandt, T. (2003). FMRI signal increases and decreases in cortical areas during small-field optokinetic stimulation and central fixation, Exp. Brain Res. 148, 117–127. DOI:10.1007/s00221-002-1267-6.
Dowsett, J., Herrmann, C. S., Dieterich, M. and Taylor, P. C. J. (2020). Shift in lateralization during illusory self-motion: EEG responses to visual flicker at 10 Hz and frequency-specific modulation by tACS, Eur. J. Neurosci. 51, 1657–1675. DOI:10.1111/ejn.14543.
Duffy, C. J. (1998). MST neurons respond to optic flow and translational movement, J. Neurophysiol. 80, 1816–1827. DOI:10.1152/jn.1998.80.4.1816.
Dukelow, S. P., DeSouza, J. F. X., Culham, J. C., van den Berg, A. V., Menon, R. S. and Vilis, T. (2001). Distinguishing subregions of the human MT+ complex using visual fields and pursuit eye movements, J. Neurophysiol. 86, 1991–2000. DOI:10.1152/jn.2001.86.4.1991.
Farkhatdinov, I., Ouarti, N. and Hayward, V. (2013). Vibrotactile inputs to the feet can modulate vection, in: World Haptics Conference (WHC), Daejeon, 2013, pp. 677–681. DOI:10.1109/WHC.2013.6548490.
Field, D. T., Inman, L. A. and Li, L. (2015). Visual processing of optic flow and motor control in the human posterior cingulate sulcus, Cortex 71, 377–389. DOI:10.1016/j.cortex.2015.07.014.
Fischer, E., Bulthoff, H. H., Logothetis, N. K. and Bartels, A. (2012). Visual motion responses in the posterior cingulate sulcus: a comparison to V5/MT and MST, Cereb. Cortex 22, 865–876. DOI:10.1093/cercor/bhr154.
Flanagan, M. B., May, J. G. and Dobie, T. G. (2002). Optokinetic nystagmus, vection, and motion sickness, Aviat. Space Environ. Med. 73(11), 1067–1073.
Frank, S. M., Baumann, O., Mattingley, J. B. and Greenlee, M. W. (2014). Vestibular and visual responses in human posterior insular cortex, J. Neurophysiol. 112, 2481–2491. DOI:10.1152/jn.00078.2014.
Frank, S. M., Wirth, A. M. and Greenlee, M. W. (2016). Visual-vestibular processing in the human Sylvian fissure, J. Neurophysiol. 116, 263–271. DOI:10.1152/jn.00009.2016.
Galletti, C., Fattori, P., Gamberini, M. and Kutz, D. F. (1999). The cortical visual area V6: brain location and visual topography, European J. Neurosci. 11, 3922–3936. DOI:10.1046/j.1460-9568.1999.00817.x.
Gibson, J. J. (1961). Ecological optics, Vis. Res. 1, 253–262. DOI:10.1016/0042-6989(61)90005-0.
Gilbert, C. D. and Li, W. (2013). Top-down influences on visual processing, Nat. Rev. Neurosci. 14, 350–363. DOI:10.1038/nrn3476.
Goonetilleke, S. C., Mezey, L. E., Burgess, A. M. and Curthoys, I. S. (2008). On the relation between ocular torsion and visual perception of line orientation, Vis. Res. 48, 1488–1496. DOI:10.1016/j.visres.2008.03.012.
Greenlee, M. W., Frank, S. M., Kaliuzhna, M., Blanke, O., Bremmer, F., Churan, J., Cuturi, L. F., MacNeilage, P. R. and Smith, A. T. (2016). Multisensory integration in self motion perception, Multisens. Res. 29, 525–556. DOI:10.1163/22134808-00002527.
Guldin, W. O. and Grüsser, O. J. (1998). Is there a vestibular cortex?, Trends Neurosci. 21, 254–259. DOI:10.1016/s0166-2236(97)01211-3.
Guterman, P. S., Allison, R. S., Palmisano, S. and Zacher, J. E. (2012). Influence of head orientation and viewpoint oscillation on linear vection, J. Vestib. Res. 22, 105–116. DOI:10.3233/VES-2012-0448.
Harquel, S., Guerraz, M., Barraud, P.-A. and Cian, C. (2020). Modulation of alpha waves in sensorimotor cortical networks during self-motion perception evoked by different visual-vestibular conflicts, J. Neurophysiol. 123, 346–355. DOI:10.1152/jn.00237.2019.
Hettinger, L. J., Schmidt, T., Jones, D. L. and Keshavarz, B. (2014). Illusory self-motion in virtual environments, in: Handbook of Virtual Environments: Design, Implementation, and Applications, 2nd edn., K. S. Hale and K. M. Stanney (Eds), pp. 435–466. CRC Press, Boca Raton, FL, USA.
Hoppes, C. W., Sparto, P. J., Whitney, S. L., Furman, J. M. and Huppert, T. J. (2018). Functional near-infrared spectroscopy during optic flow with and without fixation, PLoS ONE 13, e0193710. DOI:10.1371/journal.pone.0193710.
Hu, S., Davis, M. S., Klose, A. H., Zabinsky, E. M., Meux, S. P., Jacobsen, H. A., Westfall, J. M. and Gruber, M. B. (1997). Effects of spatial frequency of a vertically striped rotating drum on vection-induced motion sickness, Aviat. Space Environ. Med. 68, 306–311.
Ioannides, A. A. (2009). Magnetoencephalography (MEG), in: Dynamic Brain Imaging, F. Hyder (Ed.), Methods in Molecular Biology, Vol. 489, pp. 167–188. Humana Press, Clifton, NJ, USA. DOI:10.1007/978-1-59745-543-5_8.
Ji, J. T. T., So, R. H. Y. and Cheung, R. T. F. (2009). Isolating the effects of vection and optokinetic nystagmus on optokinetic rotation-induced motion sickness, Hum. Factors 51, 739–751. DOI:10.1177/0018720809349708.
Kashyap, S., Ivanov, D., Havlicek, M., Sengupta, S., Poser, B. A. and Uludağ, K. (2018). Resolving laminar activation in human V1 using ultra-high spatial resolution fMRI at 7T, Sci. Rep. 8, 17063. DOI:10.1038/s41598-018-35333-3.
Kennedy, R. S., Hettinger, L. J., Harm, D. L., Ordy, J. M. and Dunlap, W. P. (1996). Psychophysical scaling of circular vection (CV) produced by optokinetic (OKN) motion: individual differences and effects of practice, J. Vestib. Res. 6, 331–341. DOI:10.3233/VES-1996-6502.
Keshavarz, B. and Berti, S. (2014). Integration of sensory information precedes the sensation of vection: a combined behavioral and event-related brain potential (ERP) study, Behav. Brain Res. 259, 131–136. DOI:10.1016/j.bbr.2013.10.045.
Keshavarz, B., Hettinger, L. J., Vena, D. and Campos, J. L. (2014). Combined effects of auditory and visual cues on the perception of vection, Exp. Brain Res. 232, 827–836. DOI:10.1007/s00221-013-3793-9.
Keshavarz, B., Campos, J. L. and Berti, S. (2015a). Vection lies in the brain of the beholder: EEG parameters as an objective measurement of vection, Front. Psychol. 6, 1581. DOI:10.3389/fpsyg.2015.01581.
Keshavarz, B., Riecke, B. E., Hettinger, L. J. and Campos, J. L. (2015b). Vection and visually induced motion sickness: how are they related?, Front. Psychol. 6, 472. DOI:10.3389/fpsyg.2015.00472.
Keshavarz, B., Speck, M., Haycock, B. and Berti, S. (2017). Effect of different display types on vection and its interaction with motion direction and field dependence, i-Perception 8. DOI:10.1177/2041669517707768.
Keshavarz, B., Philipp-Muller, A. E., Hemmerich, W., Riecke, B. E. and Campos, J. L. (2019). The effect of visual motion stimulus characteristics on vection and visually induced motion sickness, Displays 58, 71–81. DOI:10.1016/j.displa.2018.07.005.
Kikuchi, M., Naito, Y., Senda, M., Okada, T., Shinohara, S., Fujiwara, K., Hori, S.-Y., Tona, Y. and Yamazaki, H. (2009). Cortical activation during optokinetic stimulation — an fMRI study, Acta Oto-Laryngol. 129, 440–443. DOI:10.1080/00016480802610226.
Kim, J. and Khuu, S. (2014). A new spin on vection in depth, J. Vis. 14, 5. DOI:10.1167/14.5.5.
Kim, J. and Palmisano, S. (2008). Effects of active and passive viewpoint jitter on vection in depth, Brain Res. Bull. 77, 335–342. DOI:10.1016/j.brainresbull.2008.09.011.
Kim, J., Palmisano, S. and Bonato, F. (2012). Simulated angular head oscillation enhances vection in depth, Perception 41, 402–414. DOI:10.1068/p6919.
Kirollos, R., Allison, R. S. and Palmisano, S. (2017). Cortical correlates of the simulated viewpoint oscillation advantage for vection, Multisens. Res. 30, 739–761. DOI:10.1163/22134808-00002593.
Kleinschmidt, A., Thilo, K. V., Büchel, C., Gresty, M. A., Bronstein, A. M. and Frackowiak, R. S. J. (2002). Neural correlates of visual-motion perception as object- or self-motion, NeuroImage 16, 873–882. DOI:10.1006/nimg.2002.1181.
Kovács, G., Raabe, M. and Greenlee, M. W. (2008). Neural correlates of visually induced self-motion illusion in depth, Cereb. Cortex 18, 1779–1787. DOI:10.1093/cercor/bhm203.
Kravitz, D. J., Saleem, K. S., Baker, C. I. and Mishkin, M. (2011). A new neural framework for visuospatial processing, Nat. Rev. Neurosci. 12, 217–230. DOI:10.1038/nrn3008.
Kropotov, J. D. (2009). Quantitative EEG, Event-Related Potentials and Neurotherapy. Academic Press, San Diego, CA, USA.
Lubeck, A. J. A., Bos, J. E. and Stins, J. F. (2015). Interaction between depth order and density affects vection and postural sway, PLoS ONE 10, e0144034. DOI:10.1371/journal.pone.0144034.
Luppino, G., Ben Hamed, S., Gamberini, M., Matelli, M. and Galletti, C. (2005). Occipital (V6) and parietal (V6A) areas in the anterior wall of the parieto-occipital sulcus of the macaque: a cytoarchitectonic study, Eur. J. Neurosci. 21, 3056–3076. DOI:10.1111/j.1460-9568.2005.04149.x.
Marquez-Chin, C., Bolivar-Tellería, I. and Popovic, M. R. (2018). Brain–computer interfaces for neurorehabilitation: enhancing functional electrical stimulation, in: Smart Wheelchairs and Brain–Computer Interfaces, P. Diez (Ed.), pp. 425–451. Academic Press. DOI:10.1016/B978-0-12-812892-3.00018-2.
McAssey, M., Dowsett, J., Kirsch, V., Brandt, T. and Dieterich, M. (in press). Different EEG brain activity in right and left handers during visually induced self-motion perception, J. Neurol. DOI:10.1007/s00415-020-09915-z.
Montana, J. I., Tuena, C., Serino, S., Cipresso, P. and Riva, G. (2019). Neurorehabilitation of spatial memory using virtual environments: a systematic review, J. Clin. Med. 8, 1516. DOI:10.3390/jcm8101516.
Morrone, M. C., Tosetti, M., Montanaro, D., Fiorentini, A., Cioni, G. and Burr, D. C. (2000). A cortical area that responds specifically to optic flow, revealed by fMRI, Nat. Neurosci. 3, 1322–1328. DOI:10.1038/81860.
Mursic, R. A., Riecke, B. E., Apthorp, D. and Palmisano, S. (2017). The Shepard–Risset glissando: music that moves you, Exp. Brain Res. 235, 3111–3127. DOI:10.1007/s00221-017-5033-1.
Nakamura, S. (2006). Depth separation between foreground and background on visually induced perception of self-motion, Percept. Mot. Skills 102, 871–877. DOI:10.2466/pms.102.3.871-877.
Nakamura, S. (2010). Additional oscillation can facilitate visually induced self-motion perception: the effects of its coherence and amplitude gradient, Perception 39, 320–329. DOI:10.1068/p6534.
Nakamura, S. (2013). Effects of additional visual oscillation on vection under voluntary eye movement conditions — retinal image motion is critical in vection facilitation, Perception 42, 529–536. DOI:10.1068/p7486.
Nishiike, S., Nakagawa, S., Nakagawa, A., Uno, A., Tonoike, M., Takeda, N. and Kubo, T. (2002). Magnetic cortical responses evoked by visual linear forward acceleration, NeuroReport 13, 1805–1808. DOI:10.1097/00001756-200210070-00023.
Nooij, S. A. E., Pretto, P., Oberfeld, D., Hecht, H. and Bülthoff, H. H. (2017). Vection is the main contributor to motion sickness induced by visual yaw rotation: implications for conflict and eye movement theories, PloS ONE 12, e0175305. DOI:10.1371/journal.pone.0175305.
Palmisano, S. and Kim, J. (2009). Effects of gaze on vection from jittering, oscillating, and purely radial optic flow, Atten. Percept. Psychophys. 71, 1842–1853. DOI:10.3758/APP.71.8.1842.
Palmisano, S., Gillam, B. J. and Blackburn, S. G. (2000). Global-perspective jitter improves vection in central vision, Perception 29, 57–67. DOI:10.1068/p2990.
Palmisano, S., Apthorp, D., Seno, T. and Stapley, P. J. (2014). Spontaneous postural sway predicts the strength of smooth vection, Exp. Brain Res. 232, 1185–1191. DOI:10.1007/s00221-014-3835-y.
Palmisano, S., Allison, R. S., Schira, M. M. and Barry, R. J. (2015). Future challenges for vection research: definitions, functional significance, measures, and neural bases, Percept. Sci. 6, 193. DOI:10.3389/fpsyg.2015.00193.
Palmisano, S., Barry, R. J., De Blasio, F. M. and Fogarty, J. S. (2016a). Identifying objective EEG based markers of linear vection in depth, Front. Psychol. 7, 1205. DOI:10.3389/fpsyg.2016.01205.
Palmisano, S., Summersby, S., Davies, R. G. and Kim, J. (2016b). Stereoscopic advantages for vection induced by radial, circular, and spiral optic flows, J. Vis. 16, 7. DOI:10.1167/16.14.7.
Perez-Marcos, D., Bieler-Aeschlimann, M. and Serino, A. (2018). Virtual reality as a vehicle to empower motor-cognitive neurorehabilitation, Front. Psychol. 9, 2120. DOI:10.3389/fpsyg.2018.02120.
Peuskens, H., Sunaert, S., Dupont, P., Van Hecke, P. and Orban, G. A. (2001). Human brain regions involved in heading estimation, J. Neurosci. 21, 2451–2461. DOI:10.1523/JNEUROSCI.21-07-02451.2001.
Pineda, J. A. (2005). The functional significance of mu rhythms: translating “seeing” and “hearing” into “doing”, Brain Res. Rev. 50, 57–68.
Pitzalis, S., Sdoia, S., Bultrini, A., Committeri, G., Di Russo, F., Fattori, P., Galletti, C. and Galati, G. (2013a). Selectivity to translational egomotion in human brain motion areas, PLoS ONE 8, e60241. DOI:10.1371/journal.pone.0060241.
Pitzalis, S., Fattori, P. and Galletti, C. (2013b). The functional role of the medial motion area V6, Front. Behav. Neurosci. 6, 91. DOI:10.3389/fnbeh.2012.00091.
Pitzalis, S., Fattori, P. and Galletti, C. (2015). The human cortical areas V6 and V6A, Vis. Neurosci. 32, E007. DOI:10.1017/S0952523815000048.
Pitzalis, S., Serra, C., Sulpizio, V., Committeri, G., de Pasquale, F., Fattori, P., Galletti, C., Sepe, R. and Galati, G. (2020). Neural bases of self- and object-motion in a naturalistic vision, Hum. Brain Mapp. 41, 1084–1111. DOI:10.1002/hbm.24862.
Previc, F. H., Liotti, M., Blakemore, C., Beer, J. and Fox, P. (2000). Functional imaging of brain areas involved in the processing of coherent and incoherent wide field-of-view visual motion, Exp. Brain Res. 131, 393–405. DOI:10.1007/s002219900298.
Putcha, D., Ross, R. S., Rosen, M. L., Norton, D. J., Cronin-Golomb, A., Somers, D. C. and Stern, C. E. (2014). Functional correlates of optic flow motion processing in Parkinson’s disease, Front. Integr. Neurosci. 8, 57. DOI:10.3389/fnint.2014.00057.
Riecke, B. E., Schulte-Pelkum, J., Avraamides, M. N., Von Der Heyde, M. and Bülthoff, H. H. (2006). Cognitive factors can influence self-motion perception (vection) in virtual reality, ACM Trans. Appl. Percept. 3, 194–216. DOI:10.1145/1166087.1166091.
Riecke, B. E., Feuereissen, D. and Rieser, J. J. (2009). Auditory self-motion simulation is facilitated by haptic and vibrational cues suggesting the possibility of actual motion, ACM Trans. Appl. Percept. 6, 20. http://doi.acm.org/10.1145/1577755.1577763.
Riecke, B. E., Feuereissen, D., Rieser, J. J. and McNamara, T. P. (2012). Self-motion illusions (vection) in VR — are they good for anything?, in: 2012 IEEE Virtual Reality Workshops (VRW), Costa Mesa, CA, pp. 35–38. DOI:10.1109/VR.2012.6180875.
Schulte-Pelkum, J., Riecke, B., Caniard, F. and Bülthoff, H. (2005). Can auditory cues influence the visually induced self-motion illusion?, in: European Conference on Visual Perception (ECVP 2005). A Coruña, Spain. http://eprints.iat.sfu.ca/484/.
Seno, T., Palmisano, S. and Ito, H. (2011). Independent modulation of motion and vection aftereffects revealed by using coherent oscillation and random jitter in optic flow, Vis. Res. 51, 2499–2508. DOI:10.1016/j.visres.2011.10.007.
Seno, T., Murata, K., Fujii, Y., Kanaya, H., Ogawa, M., Tokunaga, K. and Palmisano, S. (2018). Vection is enhanced by increased exposure to optic flow, i-Perception 9, 1–16. DOI:10.1177/2041669518774069.
Slobounov, S., Wu, T., Hallett, M., Shibasaki, H., Slobounov, E. and Newell, K. (2006). Neural underpinning of postural responses to visual field motion, Biol. Psychol. 72, 188–197. DOI:10.1016/j.biopsycho.2005.10.005.
Smith, A. T., Wall, M. B., Williams, A. L. and Singh, K. D. (2006). Sensitivity to optic flow in human cortical areas MT and MST, Eur. J. Neurosci. 23, 561–569. DOI:10.1111/j.1460-9568.2005.04526.x.
Smith, A. T., Beer, A. L., Furlan, M. and Mars, R. B. (2017). Connectivity of the cingulate sulcus visual area (CSv) in the human cerebral cortex, Cereb. Cortex 28, 713–725. DOI:10.1093/cercor/bhx002.
So, R. H. Y., Lo, W. T. and Ho, A. T. K. (2001). Effects of navigation speed on motion sickness caused by an immersive virtual environment, Hum. Factors 43(3), 452–461. DOI:10.1518/001872001775898223.
Stern, R. M., Hu, S., Anderson, R. B., Leibowitz, H. W. and Koch, K. L. (1990). The effects of fixation and restricted visual field on vection-induced motion sickness, Aviat. Space Environ. Med. 61, 712–715.
Stróżak, P., Francuz, P., Augustynowicz, P., Ratomska, M., Fudali-Czyż, A. and Bałaj, B. (2016). ERPs in an oddball task under vection-inducing visual stimulation, Exp. Brain Res. 234, 3473–3482. DOI:10.1007/s00221-016-4748-8.
Stróżak, P., Augustynowicz, P., Ratomska, M., Francuz, P. and Fudali-Czyż, A. (2019). Vection attenuates N400 event-related potentials in a change-detection task, Perception 48, 702–730. DOI:10.1177/0301006619861882.
Tarita-Nistor, L., González, E. G., Spigelman, A. J. and Steinbach, M. J. (2006). Linear vection as a function of stimulus eccentricity, visual angle, and fixation, J. Vestib. Res. 16, 265–272.
Thilo, K. V., Kleinschmidt, A. and Gresty, M. A. (2003). Perception of self-motion from peripheral optokinetic stimulation suppresses visual evoked responses to central stimuli, J. Neurophysiol. 90, 723–730. DOI:10.1152/jn.00880.2002.
Tokumaru, O., Kaida, K., Ashida, H., Yoneda, I. and Tatsuno, J. (1999). EEG topographical analysis of spatial disorientation, Aviat. Space Environ. Med. 70, 256–263.
Tootell, R. B., Reppas, J. B., Kwong, K. K., Malach, R., Born, R. T., Brady, T. J., Rosen, B. R. and Belliveau, J. W. (1995). Functional analysis of human MT and related visual cortical areas using magnetic resonance imaging, J. Neurosci. 15, 3215–3230.
Tootell, R. B. H., Mendola, J. D., Hadjikhani, N. K., Ledden, P. J., Liu, A. K., Reppas, J. B., Sereno, M. I. and Dale, A. M. (1997). Functional analysis of V3A and related areas in human visual cortex, J. Neurosci. 17, 7060–7078. DOI:10.1523/JNEUROSCI.17-18-07060.1997.
Townsend, B., Legere, J. K., O’Malley, S., Mohrenschildt, M. v. and Shedden, J. M. (2019). Attention modulates event-related spectral power in multisensory self-motion perception, NeuroImage 191, 68–80. DOI:10.1016/j.neuroimage.2019.02.015.
Uesaki, M. and Ashida, H. (2015). Optic-flow selective cortical sensory regions associated with self-reported states of vection, Front. Psychol. 6, 775. DOI:10.3389/fpsyg.2015.00775.
Väljamäe, A. (2009). Auditorily-induced illusory self-motion: a review, Brain Res. Rev. 61(2), 240–255. DOI:10.1016/j.brainresrev.2009.07.001.
Väljamäe, A., Larsson, P., Västfjäll, D. and Kleiner, M. (2009). Auditory landmarks enhance circular vection in multimodal virtual reality, J. Audio Eng. Soc. 57, 111–120.
Van der Hoorn, A., Beudel, M. and de Jong, B. M. (2010). Interruption of visually perceived forward motion in depth evokes a cortical activation shift from spatial to intentional motor regions, Brain Res. 1358, 160–171. DOI:10.1016/j.brainres.2010.08.050.
Vilhelmsen, K., van der Weel, F. R. and van der Meer, A. L. H. (2015). A high-density EEG study of differences between three high speeds of simulated forward motion from optic flow in adult participants, Front. Systems Neurosci. 9, 146. DOI:10.3389/fnsys.2015.00146.
Wada, A., Sakano, Y. and Ando, H. (2016). Differential responses to a visual self-motion signal in human medial cortical regions revealed by wide-view stimulation, Front. Psychol. 7, 309. DOI:10.3389/fpsyg.2016.00309.
Wall, M. B. and Smith, A. T. (2008). The representation of egomotion in the human brain, Curr. Biol. 18, 191–194. DOI:10.1016/j.cub.2007.12.053.
Ward, B. K., Roberts, D. C., Otero-Millan, J. and Zee, D. S. (2019). A decade of magnetic vestibular stimulation: from serendipity to physics to the clinic, J. Neurophysiol. 121, 2013–2019. DOI:10.1152/jn.00873.2018.
Warren, P. A. and Rushton, S. K. (2009). Optic flow processing for the assessment of object movement during ego movement, Curr. Biol. 19, 1555–1560. DOI:10.1016/j.cub.2009.07.057.
Weech, S., Kenny, S., Calderon, C. M. and Barnett-Cowan, M. (in press). Limits of subjective and objective vection for ultra-high frame rate visual displays, Displays 64, 101961. DOI:10.1016/j.displa.2020.101961.
Wei, Y., Okazaki, Y. O., So, R. H. Y., Chu, W. C. W. and Kitajo, K. (2019). Motion sickness-susceptible participants exposed to coherent rotating dot patterns show excessive N2 amplitudes and impaired theta-band phase synchronization, NeuroImage 202, 116028. DOI:10.1016/j.neuroimage.2019.116028.
Wiest, G., Amorim, M. A., Mayer, D., Schick, S., Deecke, L. and Lang, W. (2001). Cortical responses to object-motion and visually-induced self-motion perception, Cogn. Brain Res. 12, 167–170. DOI:10.1016/S0006-8993(01)02457-X.
Woodman, G. F. (2010). A brief introduction to the use of event-related potentials in studies of perception and attention, Atten. Percept. Psychophys. 72, 2031–2046. DOI:10.3758/APP.72.8.2031.
Zeki, S., Watson, J. D., Lueck, C. J., Friston, K. J., Kennard, C. and Frackowiak, R. S. (1991). A direct demonstration of functional specialization in human visual cortex, J. Neurosci. 11, 641–649. DOI:10.1523/JNEUROSCI.11-03-00641.1991.
Zeki, S. (2015). Area V5 — a microcosm of the visual brain, Front. Integr. Neurosci. 9, 21. DOI:10.3389/fnint.2015.00021.
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Moving visual stimuli can elicit the sensation of self-motion in stationary observers, a phenomenon commonly referred to as vection. Despite the long history of vection research, the neuro-cognitive processes underlying vection have only recently gained increasing attention. Various neuropsychological techniques such as functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) have been used to investigate the temporal and spatial characteristics of the neuro-cognitive processing during vection in healthy participants. These neuropsychological studies allow for the identification of different neuro-cognitive correlates of vection, which (a) will help to unravel the neural basis of vection and (b) offer opportunities for applying vection as a tool in other research areas. The purpose of the current review is to evaluate these studies in order to show the advances in neuropsychological vection research and the challenges that lie ahead. The overview of the literature will also demonstrate the large methodological variability within this research domain, limiting the integration of results. Next, we will summarize methodological considerations and suggest helpful recommendations for future vection research, which may help to enhance the comparability across neuropsychological vection studies.
All Time | Past Year | Past 30 Days | |
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Abstract Views | 837 | 271 | 18 |
Full Text Views | 54 | 29 | 1 |
PDF Views & Downloads | 97 | 53 | 3 |