Virtual reality was first experienced as the world’s first flight stimulator Link Trainer by Edwin Link (1929) and later as the interactive theatre ‘Sensorama’ invented by Morton Heilig in 1957. Over time virtual reality has metamorphosed from science fiction to science reality. Today, virtual reality can be experienced in many forms that include not only visual and auditory feedback but also other sensory feedback. Primarily hyped in the entertainment sector, virtual reality also enjoys the application in fields such as simulation-based training and healthcare research. In medicine and medical research, virtual reality allows the opportunity to train, and investigate speculations and behaviors with greater experimental control and without endangering subjects and at relatively reduced costs.
Virtual Reality in Behavioral and Biomedical Research
Traditional methods of practice and research require infrastructure, numerous tools, and apparatuses which all add to the cost and tend to be time-consuming. While animal-based experiments can be performed in laboratory set-ups under different environmental settings, the same is not always possible with human subjects. Further, traditional approaches require maintenance of different environmental parameters and the environments used may not always be ethologically or ecologically satisfactory. Ethical concerns also limit the application scope of traditional methods.
Though traditional methods have their own strengths, the use of virtual reality (VR) offers far more benefits that improve the quality of medical research and practice. Virtual reality-based surgery training has been shown to have a significant influence on surgery performances when compared to performances of individuals trained only using conventional methods (Palter & Grantcharov, 2014; Seymour et al., 2002). Modern medical VR training systems in addition to providing rich virtual environments (VE) also combine haptic systems that make the experience more realistic such as by allowing the feel of tissue resistance in a simulation. Further, VR can be tailored to individual needs as well as the specific needs of different medical scenarios. Thus, VR is a promising teaching and training tool in medical practices that expand the possibilities of learning as well as reduces variable parameters of training (Samadbeik et al., 2018).
Human Behavior Analysis
Beyond training applications, virtual reality can be effectively utilized in analyzing human behaviors. Often data collection for human behaviors relies on case studies and estimated responses of the participants to hypothetical scenarios. While case studies can involve real-time data collection using behavioral experiments such as the unannounced evacuation of an office building to estimate behaviors during a fire event (Nilsson, Frantzich, & Saunders, 2008), the reliability of such experiments is not high enough. Consider the experiment performed by Kinateder et al. (2014) to assess the effect of social influence on exit choice behaviors of participants in a simulated tunnel fire. The experiment employed a virtual tunnel environment that was equipped with a virtual agent (VA) whose behaviors were varied to simulate different scenarios. Kinatedar et al. observed that when no VA was present, the participants would quickly make the decision to move towards the exit. However, a passive VA resulted in the participants waiting longer to make a move which was in agreement with the findings of Latané, and Darley’s (1968) laboratory experiment of bystander influence on escape behaviors. When provided with an active VA that moved towards the exit, 85% of the participants also went towards the exit as opposed to the 75% in the no VA condition. However, a VA running away from the exit resulted in only 61% of the participants making it to the exit. These behaviors were comparable to the Sydney Harbor Tunnel field experiment results of Burns et al.’s (2013). As evident from these outcomes, the virtual reality-based experiment was able to provide comparable and reliable results without compromising the participant’s safety.
Animal Model to Human Model Translations
Translation of animal-based models to human models is made easy with virtual reality. Traditional mazes such as the Elevated Plus Maze and the Radial Arm Maze that are often used with animals to assess fear, anxiety, learning, and memory can easily be programmed into VR. Additionally, virtual environments permit the creation of ecologically and ethologically relevant scenarios, such as city, farmland or an apartment, which can quickly be swapped out without interfering with the task performances. Lee et al.’s (2014) were able to successfully assess memory impairments in patients of amnestic mild cognitive impairment (aMCI) and Alzheimer’s disease (AD) using a virtual Radial Arm Maze. The use of the virtual maze also allowed differentiation of working memory and reference memory. The aMCI patients were observed to have significantly impaired spatial reference memory, though not working memory, while the AD group showed impairments in both memories. Further, a five-year follow-up analysis by Lee et al. comparing the virtual maze performances revealed that the aMCI converters had made more spatial reference memory errors in the task than the corresponding nonconverter group. Another study that utilized the virtual Morris Water Maze was able to translate the findings of the differential effect of scopolamine on hippocampal activity from animals to humans (Antonova et al. 2010). Antonova et al.’s combination of fMRI analysis with the virtual task performance revealed a dissociation between hippocampus-based and striatum-based memory system activations f