An overview as seen in the Neuroscience of Virtual Reality: From Virtual Exposure to Embodied Medicine [1]


Why is VR so effective? Here, the following answer is suggested: VR shares with the brain the same basic mechanism—embodied simulations.

An increasingly popular hypothesis—predictive coding [2,3,4]—suggests that the brain actively maintains an internal model (simulation) of the body and the space around it, which provides predictions about the expected sensory input and tries to minimize the amount of prediction errors (or “surprises”). An in-depth discussion of these concepts is not offered here because authoritative and thorough accounts have been provided elsewhere. [2-7] However, herein, the focus is on the concept of simulation introduced by this paradigm to understand better the links between the brain and VR.

One of the main tenets of predictive coding is that to regulate and control the body in the world effectively, the brain creates an embodied simulation of the body in the world. There are two main characteristics of this simulation. First, different from other internal models used in cognitive science—such as Tolman’s cognitive maps or Johhson–Laird’s internal models—they are simulations of sensory motor experiences. In this view, they include visceral/autonomic (interoceptive), motor (proprioceptive), and sensory (e.g., visual, auditory) information. Second, embodied simulations reactivate multimodal neural networks, which have produced the simulated/expected effect before. To regulate and control the body in the world effectively, the brain creates an embodied simulation of the body in the world used to represent and predict actions, concepts, and emotions. Specifically, it is used to predict: (a) upcoming sensory events both inside and outside the body, and (b) the best action to deal with the impending sensory events.[8]

VR works in a similar way: the VR experience tries to predict the sensory consequences of the individual’s movements, providing to him/her the same scene he/she will see in the real world. To achieve this, the VR system, like the brain, maintains a model (simulation) of the body and the space around it. If presence in the body is the outcome of different embodied simulations, and VR is a simulation technology, this suggests the possibility of altering the experience of the body by designing targeted virtual environments.[9] In this view, VR can be defined as an “embodied technology” for its possibility of modifying the embodiment experience of its users.[10,11,12] As noted by Riva et al., “using VR, subjects can experience the synthetic environment as if it was ‘their surrounding world’ (incarnation: the physical body is within a virtual environment) or can experience their synthetic avatars as if they were ‘their own body’ (embodiment: the physical body is replaced by the virtual one).”13(p9) In other words, VR is able to fool the predictive coding mechanisms used by the brain generating the feeling of presence in a virtual body and in the digital space around it.

As underlined by Barrett, in The Theory of Constructed Emotion, “The brain constructs meaning by correctly anticipating (predicting and adjusting to) incoming sensations. Sensations are categorized so that they are (a) actionable in a situated way and therefore (b) meaningful, based on past experience. When past experiences of emotion (e.g., happiness) are used to categorize the predicted sensory array and guide action, then one experiences or perceives that emotion (happiness).”8(p9) In this view, the feeling of presence in a space can be considered as an evolutive tool used to track the difference between the predicted sensations and those that are incoming from the sensory world, both externally and internally. [14-16]

VR works in a similar way: it uses computer technology to create a simulated world that individuals can manipulate and explore as if they were in it. In other words, the VR experience tries to predict the sensory consequences of your movements, showing to you the same scene you will see in the real world. Specifically, VR hardware tracks the motion of the user, while VR software adjusts the images on the user’s display to reflect the changes produced by the motion in the virtual world. To achieve it, like the brain, the VR system maintains a model (simulation) of the body and the space around it. This prediction is then used to provide the expected sensory input using the VR hardware. To be realistic, the VR model tries to mimic the brain model as much as possible: the more the VR model is similar to the brain model, the more the individual feels present in the VR world. [14, 17]

Moseley et al. suggested that these simulations are integrated with sensory data in the “body matrix,” a coarse supramodal multisensory representation of the body and the space around it. [18-20] Specifically, the contents of the body matrix are defined by top-down predictive signals, integrating the multisensory (motor and visceromotor) simulations of the causes of perceived sensory events. [21] The different simulations are then ranked and included in the body matrix according to their relevance for the intentions of the self (selective attention). At the same time, the content and the priority of the different simulations are corrected by bottom-up prediction errors that signal mismatches between predicted and actual contents of sensory events.[22]

At the end of this process, the body matrix defines where the self is present, that is, in the body that our brain considers as the most likely to be its one. [23-25] As underlined by Apps and Tsakiris, “The mental representation of the physical properties of one’s self are, therefore, also probabilistic. That is, one’s own body is the one that has the highest probability of being ‘me,’ since other objects are probabilistically less likely to evoke the same sensory inputs. In short, the notion that there is a ‘self’ is the most parsimonious and accurate explanation for sensory inputs.”23(p88)

According to neuroscience, the body matrix [18,19, 26, 27] serves to maintain the integrity of the body at both the homeostatic and psychological levels by supervising the cognitive and physiological resources necessary to protect the body and the space around it. Specifically, the body matrix plays a critical role in high-end cognitive processes such as motivation, emotion, social cognition, and self-awareness, [28-30] while exerting a top-down modulation over basic physiological mechanisms such as thermoregulatory control [31, 32] and the immune system.[27]

In this view, different authors [10,12, 33, 34] have recently suggested that an altered functioning of the body matrix and/or its related processes might be the cause of different neurological and psychiatric conditions. If this is true, VR can be the core of a new trans-disciplinary research field—embodied medicine [11, 12]—the main goal of which is the use of advanced technology for altering the body matrix, with the goal of improving people’s health and well-being.

VR compares favorably to existing treatments in anxiety disorders, eating and weight disorders, and pain management, with long-term effects that generalize to the real world. The most common use of VR in behavioral health is for exposure therapy (VR exposure [VRE]). VRE is similar to classic exposure therapy [35, 36, 37] — the patient is exposed to a graded exposure hierarchy—with the only difference being that VR is substituted for other exposure techniques (e.g., in vivo or imaginal exposure). In the treatment of complex anxiety disorders, the use of VRE is often combined with other techniques such as breathing or relaxation exercises,[38] attentional and autonomic control training,[39] biofeedback,[40, 41] and/or cognitive restructuring.[42]

Available data show that VR is able to reduce anxiety symptoms significantly in different anxiety disorders: phobias,[43] post-traumatic stress disorders,[44] panic disorder and agoraphobia,[45] social anxiety disorders,[46] psychological stress,[47]and generalized anxiety disorders.[48] Another article specifically explored the use of VR for the assessment of psychiatric disorders, [49] finding that virtual worlds are able to induce and assess psychiatric symptoms simultaneously, with significant correlations between VR measures and traditional diagnostic tools. Moreover, VR is also effective in assessing cue reactivity[50]: its use is able to increase subjective craving in smokers,[51, 52] alcohol drinkers,[53] eaters,[54] and cocaine-dependent individuals.[55]

Body swapping, [is a technique which] replaces the contents of the bodily self-consciousness with synthetic ones (synthetic embodiment). This has been used in eating and weight disorders to improve the experience of the body in both clinical (anorexia and morbid obesity) [56, 57] and non-clinical subjects.[58-60] Nevertheless, the potential of this approach is wider. [61] For example, it may offer a non-pharmacological way to reduce chronic pain. Nevertheless, according to Tsay et al., “available findings present compelling evidence for a novel multisensory and multimodal approach to therapies for chronic pain disorders”62(p249) In this view, the use of VR embodiment may offer new treatment options for pain management. [63-65] Some studies have suggested the possibility of using VR body swapping to improve body perception disturbance in patients with complex regional pain syndrome. [66, 67]

An emerging approach is the use of VR to augment the bodily experience through the awareness of internal (and difficult to sense) bodily information, or the mapping of a sensory channel to a different one—for example vision to touch or to hearing (augmented embodiment).[68, 69] For example, Suzuki et al.[70] implemented an innovative “cardiac rubber hand illusion” that combined computer-generated augmented reality with feedback of interoceptive information. Their results showed that the virtual-hand ownership is enhanced by cardio-visual feedback in time with the actual heartbeat, supporting the use of this technique to improve emotion regulation. The first outcome of an integrated VR platform able to simulate both the external and the inner world is the possibility of structuring, augmenting, and/or replacing all the different experiential aspects of bodily self-consciousness.

The final long-term outcome of this possibility may be the embodied virtual training machine described by the science-fiction thriller The Matrix. In this movie, the heroes, Trinity and Neo, learned how to fight martial-arts battles and drive motorcycles and helicopters by experiencing the bodily processes and concepts related to the skill through an embodied simulation.

The long-term goal of the vision presented in this article is the use of simulative technologies—both simulating the external world and the internal one—to reverse engineer the psychosomatic processes that connect mind and body. If achieved, this perspective will provide a radically new meaning to the classical Juvenal’s Latin dictum “Mens sana in corpore sano” (a healthy mind in a healthy body) by allowing a new trans-disciplinary research field—“Embodied Medicine”[11, 12]—that will use advanced multisensory technologies to alter bodily processes for enhancing homeostasis and well-being.



  1. Riva G, Wiederhold BK, Mantovani F. Neuroscience of Virtual Reality: From Virtual Exposure to Embodied Medicine. Cyberpsychol Behav Soc Netw. 2019;22(1):82-96. [PubMed] [Google Scholar]
  2. Friston K. The free-energy principle: a unified brain theory? Nature Reviews Neuroscience 2010; 11:127–138 [PubMed] [Google Scholar]
  3. Friston K. Embodied inference and spatial cognition. Cognitive Processing 2012; 13:S171–177 [PMC free article] [PubMed] [Google Scholar]
  4. Clark A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral & Brain Sciences 2013; 36:181–204 [PubMed] [Google Scholar]
  5. Talsma D. Predictive coding and multisensory integration: an attentional account of the multisensory mind. Frontiers in Integrative Neuroscience 2015; 9:19. [PMC free article] [PubMed] [Google Scholar]
  6. Hohwy J. (2013) The predictive mind. Oxford: Oxford University Press [Google Scholar]
  7. Clark A. (2016) Surfing uncertainty: prediction, action, and the embodied mind. Oxford: Oxford University Press [Google Scholar]
  8. Barrett LF. The theory of constructed emotion: an active inference account of interoception and categorization. Social Cognitive & Affective Neuroscience 2017; 12:1–23 [PMC free article] [PubMed] [Google Scholar]
  9. Oliveira ECD, Bertrand P, Lesur MER, et al. . Virtual body swap: a new feasible tool to be explored in health and education. In 2016 XVIII Symposium on Virtual and Augmented Reality (SVR 2016). New York: Institute of Electrical and Electronics Engineers, pp. 81–89 [Google Scholar]
  10. Riva G. From virtual to real body: virtual reality as embodied technology. Journal of Cybertherapy & Rehabiliation 2008; 1:7–22 [Google Scholar]
  11. Riva G. (2016) Embodied medicine: what human computer confluence can offer to health care. In Gaggioli A, Ferscha A, Riva G, et al., eds. Human computer confluence: transforming human experience through symbiotic technologies. Warsaw, Poland: De Gruyter Open, pp. 55–79 [Google Scholar]
  12. Riva G, Serino S, Di Lernia D, et al. . Embodied medicine: mens sana in corpore virtuale sano. Frontiers in Human Neuroscience 2017; 11:120. [PMC free article] [PubMed] [Google Scholar]
  13. Riva G, Baños RM, Botella C, et al. . Transforming experience: the potential of augmented reality and virtual reality for enhancing personal and clinical change. Frontiers in Psychiatry 2016; 7:164. [PMC free article] [PubMed] [Google Scholar]
  14. Riva G. The neuroscience of body memory: from the self through the space to the others. Cortex 2017. July 25 [Epub ahead of print]; DOI: 10.1016/j.cortex.2017.07.013 [PubMed] [CrossRef]
  15. Riva G, Waterworth JA, Waterworth EL, et al. . From intention to action: the role of presence. New Ideas in Psychology 2011; 29:24–37 [Google Scholar]
  16. Riva G, Mantovani F. From the body to the tools and back: a general framework for presence in mediated interactions. Interacting with Computers 2012; 24:203–210 [Google Scholar]
  17. Sanchez-Vives MV, Slater M. From presence to consciousness through virtual reality. Nature Reviews Neuroscience 2005; 6:332–339 [PubMed] [Google Scholar]
  18. Moseley GL, Gallace A, Spence C. Bodily illusions in health and disease: physiological and clinical perspectives and the concept of a cortical “body matrix.” Neuroscience & Biobehavioral Reviews 2012; 36:34–46 [PubMed] [Google Scholar]
  19. Gallace A, Spence C. (2014) In touch with the future: the sense of touch from cognitive neuroscience to virtual reality. Oxford: Oxford University Press [Google Scholar]
  20. Sedda A, Tonin D, Salvato G, et al. . Left caloric vestibular stimulation as a tool to reveal implicit and explicit parameters of body representation. Consciousness & Cognition 2016; 41:1–9 [PubMed] [Google Scholar]
  21. Friston K, Daunizeau J, Kilner J, et al. . Action and behavior: a free-energy formulation. Biological Cybernetics 2010; 102:227–260 [PubMed] [Google Scholar]
  22. Friston K. The free-energy principle: a rough guide to the brain? Trends in Cognitive Sciences 2009; 13:293–301 [PubMed] [Google Scholar]
  23. Apps MA, Tsakiris M. The free-energy self: a predictive coding account of self-recognition. Neuroscience & Biobehavioral Reviews 2014; 41:85–97 [PMC free article] [PubMed] [Google Scholar]
  24. Holmes NP, Spence C. The body schema and the multisensory representation(s) of peripersonal space. Cognitive Processing 2004; 5:94–105 [PMC free article] [PubMed] [Google Scholar]
  25. Serino S, Scarpina F, Dakanalis A, et al. . The role of age on multisensory bodily experience: an experimental study with a virtual reality full-body illusion. Cyberpsychology, Behavior, & Social Networking 2018; 21:304–310 [PMC free article] [PubMed] [Google Scholar]
  26. Finotti G, Migliorati D, Costantini M. Multisensory integration, bodily self-consciousness and disorders of the immune system. Brain, Behavior, & Immunity 2015; 49:e31 [Google Scholar]
  27. Finotti G, Costantini M. Multisensory body representation in autoimmune diseases. Scientific Reports 2016; 6:21074. [PMC free article] [PubMed] [Google Scholar]
  28. Tsakiris M. The multisensory basis of the self: from body to identity to others. Quarterly Journal of Experimental Psychology 2017; 70:597–609 [PMC free article] [PubMed] [Google Scholar]
  29. Maister L, Slater M, Sanchez-Vives MV, et al. . Changing bodies changes minds: owning another body affects social cognition. Trends in Cognitive Sciences 2015; 19:6–12 [PubMed] [Google Scholar]
  30. Maister L, Sebanz N, Knoblich G, et al. . Experiencing ownership over a dark-skinned body reduces implicit racial bias. Cognition 2013; 128:170–178 [PMC free article] [PubMed] [Google Scholar]
  31. Macauda G, Bertolini G, Palla A, et al. . Binding body and self in visuo-vestibular conflicts. European Journal of Neuroscience 2015; 41:810–817 [PubMed] [Google Scholar]
  32. Gallace A, Soravia G, Cattaneo Z, et al. . Temporary interference over the posterior parietal cortices disrupts thermoregulatory control in humans. PLoS One 2014; 9:e88209. [PMC free article] [PubMed] [Google Scholar]
  33. Brugger P, Lenggenhager B. The bodily self and its disorders: neurological, psychological and social aspects. Current Opinion in Neurology 2014; 27:644–652 [PubMed] [Google Scholar]
  34. Tsakiris M, Critchley H. Interoception beyond homeostasis: affect, cognition and mental health. Philosophical Transactions of the Royal Society B 2016; 371 [PMC free article] [PubMed] [Google Scholar]
  35. Maples-Keller JL, Yasinski C, Manjin N, et al. . Virtual reality-enhanced extinction of phobias and post-traumatic stress. Neurotherapeutics 2017; 14:554–563 [PMC free article] [PubMed] [Google Scholar]
  36. Arroll B, Wallace HB, Mount V, et al. . A systematic review and meta-analysis of treatments for acrophobia. The Medical Journal of Australia 2017; 206:263–267 [PubMed] [Google Scholar]
  37. Rothbaum BO, Rizzo AS, Difede J. Virtual reality exposure therapy for combat-related posttraumatic stress disorder. Annals of the New York Academy of Sciences 2010; 1208:126–132 [PubMed] [Google Scholar]
  38. Wiederhold BK, Wiederhold MD. Three-year follow-up for virtual reality exposure for fear of flying. CyberPsychology & Behavior 2003; 6:441–445 [PubMed] [Google Scholar]
  39. McLay RN, Wood DP, Webb-Murphy JA, et al. . A randomized, controlled trial of virtual reality-graded exposure therapy for post-traumatic stress disorder in active duty service members with combat-related post-traumatic stress disorder. Cyberpsychology, Behavior, & Social Networking 2011; 14:223–239 [PubMed] [Google Scholar]
  40. Repetto C, Gorini A, Vigna C, et al. . The use of biofeedback in clinical virtual reality: the INTREPID project. Journal of Visualized Experiments 2009. November 12 [Epub ahead of print]; DOI: 10.3791/1554 [PMC free article] [PubMed] [CrossRef]
  41. Wiederhold BK, Wiederhold MD. Clinical observations during virtual reality therapy for specific phobias. CyberPsychology & Behavior 1999; 2:161–168 [PubMed] [Google Scholar]
  42. Rothbaum BO, Hodges L, Smith S, et al. . A controlled study of virtual reality exposure therapy for the fear of flying. Journal of Consulting & Clinical Psychology 2000; 68:1020–1026 [PubMed] [Google Scholar]
  43. Parsons TD, Rizzo AA. Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: a meta-analysis. Journal of Behavior Therapy & Experimental Psychiatry 2008; 39:250–261 [PubMed] [Google Scholar]
  44. Goncalves R, Pedrozo AL, Coutinho ES, et al. . Efficacy of virtual reality exposure therapy in the treatment of PTSD: a systematic review. PLoS One 2012; 7:e48469. [PMC free article] [PubMed] [Google Scholar]
  45. Botella C, Garcìa-Palacios A, Villa H, et al. . Virtual reality exposure in the treatment of panic disorder and agoraphobia: a controlled study. Clinical Psychology & Psychotherapy 2007; 14:164–175 [Google Scholar]
  46. Anderson PL, Price M, Edwards SM, et al. . Virtual reality exposure therapy for social anxiety disorder: a randomized controlled trial. Journal of Consulting & Clinical Psychology 2013; 81:751–760 [PubMed] [Google Scholar]
  47. Gaggioli A, Pallavicini F, Morganti L, et al. . Experiential virtual scenarios with real-time monitoring (interreality) for the management of psychological stress: a block randomized controlled trial. Journal of Medical Internet Research 2014; 16:e167. [PMC free article] [PubMed] [Google Scholar]
  48. Repetto C, Gaggioli A, Pallavicini F, et al. . Virtual reality and mobile phones in the treatment of generalized anxiety disorders: a Phase-2 clinical trial. Personal & Ubiquitous Computing 2013; 17:253–260 [Google Scholar]
  49. Van Bennekom MJ, de Koning PP, Denys D. Virtual reality objectifies the diagnosis of psychiatric disorders: a literature review. Frontiers in Psychiatry 2017; 8:163. [PMC free article] [PubMed] [Google Scholar]
  50. Hone-Blanchet A, Wensing T, Fecteau S. The use of virtual reality in craving assessment and cue-exposure therapy in substance use disorders. Frontiers in Human Neuroscience 2014; 8:844. [PMC free article] [PubMed] [Google Scholar]
  51. Bordnick PS, Graap KM, Copp HL, et al. . Virtual reality cue reactivity assessment in cigarette smokers. CyberPsychology & Behavior 2005; 8:487–492 [PubMed] [Google Scholar]
  52. Lee J, Lim Y, Graham SJ, et al. . Nicotine craving and cue exposure therapy by using virtual environments. CyberPsychology & Behavior 2004; 7:705–713 [PubMed] [Google Scholar]
  53. Bordnick PS, Traylor A, Copp HL, et al. . Assessing reactivity to virtual reality alcohol based cues. Addictive Behaviors 2008; 33:743–756 [PubMed] [Google Scholar]
  54. Ledoux T, Nguyen AS, Bakos-Block C, et al. . Using virtual reality to study food cravings. Appetite 2013; 71:396–402 [PubMed] [Google Scholar]
  55. Saladin ME, Brady KT, Graap K, et al. . A preliminary report on the use of virtual reality technology to elicit craving and cue reactivity in cocaine dependent individuals. Addictive Behaviors 2006; 31:1881–1894 [PubMed] [Google Scholar]
  56. Keizer A, van Elburg A, Helms R, et al. . A virtual reality full body illusion improves body image disturbance in anorexia nervosa. PLoS One 2016; 11:e0163921. [PMC free article] [PubMed] [Google Scholar]
  57. Serino S, Scarpina F, Keizer A, et al. . A novel technique for improving bodily experience in a non-operable super-super obesity case. Frontiers in Psychology 2016; 7:837. [PMC free article] [PubMed] [Google Scholar]
  58. Serino S, Pedroli E, Keizer A, et al. . Virtual reality body swapping: a tool for modifying the allocentric memory of the body. Cyberpsychology, Behavior, & Social Networking 2016; 19:127–133 [PubMed] [Google Scholar]
  59. Preston C, Ehrsson HH. Illusory changes in body size modulate body satisfaction in a way that is related to non-clinical eating disorder psychopathology. Plos One 2014; 9:e85773. [PMC free article] [PubMed] [Google Scholar]
  60. Preston C, Ehrsson HH. Illusory obesity triggers body dissatisfaction responses in the insula and anterior cingulate cortex. Cerebral Cortex 2016; 26:4450–4460 [PMC free article] [PubMed] [Google Scholar]
  61. Serino S, Dakanalis A. Bodily illusions and weight-related disorders: clinical insights from experimental research. Annals of Physical & Rehabilitation Medicine 2017; 60:217–219 [PubMed] [Google Scholar]
  62. Tsay A, Allen TJ, Proske U, et al. . Sensing the body in chronic pain: a review of psychophysical studies implicating altered body representation. Neuroscience & Biobehavioral Reviews 2015; 52:221–232 [PubMed] [Google Scholar]
  63. Romano D, Llobera J, Blanke O. Size and viewpoint of an embodied virtual body impact the processing of painful stimuli. Journal of Pain 2016; 17:350–358 [PubMed] [Google Scholar]
  64. Pazzaglia M, Haggard P, Scivoletto G, et al. . Pain and somatic sensation are transiently normalized by illusory body ownership in a patient with spinal cord injury. Restorative Neurology & Neuroscience 2016; 34:603–613 [PubMed] [Google Scholar]
  65. Sarig Bahat H, Takasaki H, Chen XQ, et al. . Cervical kinematic training with and without interactive VR training for chronic neck pain—a randomized clinical trial. Manual Therapy 2015; 20:68–78 [PubMed] [Google Scholar]
  66. Hwang H, Cho S, Lee JH. The effect of virtual body swapping with mental rehearsal on pain intensity and body perception disturbance in complex regional pain syndrome. International Journal of Rehabilitation Research 2014; 37:167–172 [PubMed] [Google Scholar]
  67. Jeon B, Cho S, Lee JH. Application of virtual body swapping to patients with complex regional pain syndrome: a pilot study. Cyberpsychology, Behavior, & Social Networking 2014; 17:366–370 [PubMed] [Google Scholar]
  68. Waterworth JA, Waterworth EL. (2014) Altered, expanded and distributed embodiment: the three stages of interactive presence. In Riva G, Waterworth JA, Murray D, eds. Interacting with presence: HCI and the sense of presence in computer-mediated environments. Berlin: De Gruyter Open, pp. 36–50 [Google Scholar]
  69. Duquette P. Increasing our insular world view: interoception and psychopathology for psychotherapists. Frontiers in Neuroscience 2017; 11:135. [PMC free article] [PubMed] [Google Scholar]
  70. Suzuki K, Garfinkel SN, Critchley HD, et al. . Multisensory integration across exteroceptive and interoceptive domains modulates self-experience in the rubber-hand illusion. Neuropsychologia 2013; 51:2909–2917 [PubMed] [Google Scholar]