It can be noted that in addition to the remarkable diagnostic value of VEs, a number of findings demonstrate that VR training/exercise can have a positive impact on an individual’s (neuro)physiological, (neuro)psychological and (neuro)rehabilitation outcomes compared to traditional training and exercise [26,27]. Neuroscientists point out that classical neuropsychological tests/tasks have certain limitations in terms of generalizing their results, while the results obtained in VEs can be extrapolated to real (actual) functioning due to the high ecological validity of VEs (while maintaining the laboratory precision of the measurements) [21,22,23,24,25,26,27]. It is indicated that the advantage of VR is a higher degree of objectivity compared to clinical interviews or self-report methods, which are largely dependent on the circumstances, including unreliable memory (as a result, VR can effectively support and even verify classical approaches). Also of interest are researchers’ observations that VR seems to allow for a more realistic simulation of social interactions compared to standard methods of testing personal space, such as the use of photographs or abstract verbal stimuli, as well as traditional methods of assessing emotions based on role-play tests, in which the effect depends on the individual’s imagination and the examining person. Whether the improvement observed in the VE can be generalized to patients’ daily functioning remains an open question. Nevertheless, a number of studies point to this possibility (Table 1). In addition, every participant in the digital world knows that everything depicted in it is not real. At the same time, the mind and body behave as if it were real after all. This makes it easier for people to face difficult situations or test new therapeutic strategies. A feature of exposure therapies in VEs is the therapist’s ability to constantly adjust the parameters of the environment to match the patient’s actions and feelings. This allows the therapist/system to tailor the level of difficulty to the specific patient, thus providing a highly personalized therapeutic program. The Neuroforma environment works in a similar way [28,29,30].

Digital reality is constantly evolving, so its impact on human health is changing and requires the updating of knowledge. On the other hand, there are already many areas of the use of virtual technologies, such as precise (neuro)diagnostics and effective support in the treatment of a wide range of diseases (also those related to the nervous system), including the latest findings in neuroscience, such as the phenomena of (neuro)plasticity or mirror neuron networks [31,32,33].

For example, the Riva, Cavedoni and Kourtesis teams conducted neuroscientific research to propose, develop, test and validate various models of VR technology (e.g., different levels of immersion) for healthy and patient populations [2,9,20,34,35]. Their novel studies and others [5,21,22,23,24,25] illustrate the benefits of using VR and demonstrate new findings on brain structure/function and plasticity. In addition, Bonini and co-workers [36] provide an interesting summary of 30 years of research on mirror neurons (MNs) from the first description by Rizzolatti’s group [37,38,39] as a class of monkey premotor cells discharging during both action execution and observation to current implications and applications in humans. A recent study by Thompson’s team [40] demonstrates that mirror neuron brain areas contribute to action identification, but not intention. Zhou and colleagues [41] suggest that the configuration of an action observation network depends on the observer’s goals. Plata-Bello’s group [42] analyzed patterns of brain activity during the observation of painful expressions and assessed the relationship between this activity and interpersonal reactivity index (IRI) scores. For non-invasive brain stimulation, authors concluded that observing painful expressions triggers activation in sensorimotor MNs, and this activation is influenced by a person’s level of empathy. Studies of the MN system and neural plasticity using VR environments [43] involving data from electroencephalography, neuroimaging and non-invasive brain stimulation [44,45,46,47] present innovative multidisciplinary treatment models based on the mixed methodologies and/or objective (neuro)physiological signals. Recent findings demonstrate novel individualized biomarker-based approaches with a well-targeted patient population in neurotherapy and neurorehabilitation, for example, individuals with schizophrenia and autism spectrum disorders and individuals with neurological or neuromuscular diseases [48,49,50,51,52,53]. Table 1 presents examples of VR use, as well as comparisons of traditional methods with new digital proposals. Additionally, research using VEs can provide recommendations for their specific application, as well as aiding in the validation and standardization of VEs.

Novel VR-based technologies are constantly developing, and their areas of application are expanding and even overlapping, as we see in neuroscience. Table 1 presents and indicates examples of neuroscientific areas of using virtual environments and tools, including pain management [31,56,57,58], improvement of brain injury patients [5,26,59,60,61], post-stroke [10,20,25,33,65,66,67], prevention, and diagnosis and therapy of many serious illnesses. Examples include diseases such as neurodevelopmental disorders (e.g., attention-deficit hyperactivity disorder, ADHD [22,80,81]); schizophrenia spectrum disorders (e.g., schizophrenia [82,83]); autism spectrum disorders (e.g., autism [84,85]); mood (e.g., depressive disorders [86,87]), anxiety (e.g., panic and phobias [74,75,76]), trauma- and stressor-related (e.g., post-traumatic stress disorder, PTSD [73]), neurocognitive (e.g., Parkinson’s or Alzheimer’s and memory cognitive impairment diseases [23,24,47,69,70,71,72,77,78,79]) and neuromuscular disorders (e.g., multiple sclerosis [32,62,63,64]). In addition, VEs are increasingly being incorporated into research and evaluation of natural aging processes or effective support in (neuro)geriatric care (e.g., preventing falls or improving cognitive function in the elderly) [21,70,71]. Model studies with healthy participants are important and interesting in evaluating/testing new technologies [4,28,29,54,55,56].

Overall, it has been observed that current research approaches primarily (a) compare the effects of traditional methods with those based on VEs; (b) combine traditional and innovative approaches/mixed methodology, e.g., searching for (digital) (neural) biomarkers, additionally taking into account data of EEG, neuroimaging and NIBS, as well as EOG, EMG and other biosignals; (c) present different models of VEs; (d) observe the accompanying beneficial and adverse effects and assess potential risks to eliminate them; and (d) predict the next phases of digital reality development.

Although unusual and unexpected challenges are only beginning to be encountered, VR environments make it possible to expand the scope of research on perception, cognitive and motor imagery, and the effects of different learning and teaching pathways. In this context, studies of neuroplasticity phenomena, including the effects of applied virtual (mirror) tasks and training, are of interest in virtual prevention, neurogeriatrics, neurotherapy and neurorehabilitation [5,31,32,33,36,42,58,61].

Virtual environments are offered with different degrees of immersion: non-immersive, partial immersion and full immersion [9,18,23,88,89,90]. The researchers carried out research in the non-immersive virtual environment created by the Neuroforma system [28,29,30]. Such environments are willingly used due to the fact that there are practically no adverse symptoms related to being in them or participating in virtual tests, tasks and training. Above all, however, VEs with full immersion are very attractive. These environments most often use an HMD (head-mounted display) interface. Nowadays, professional HMD sets, in addition to the classic two small high-resolution screens and a headset, increasingly offer additional equipment such as hand-tracking controllers or gloves for the perfect imitation of hand work, as well as an eye-tracking system, shoes mapping leg movement and a system for tracking the user’s location in space. The amount of information available increases even more when additional equipment allows, for example, the measurement of heart rate or galvanic skin response. Such feedback can be recorded by the system and influence what happens in the virtual environment (which, however, can limit the subject’s freedom in VR). An interesting and unusual development of VR technology is a costume worn over all or part of the body. Every movement of the body is monitored and then mapped to the virtual space, which gives excellent visual–motor synchronicity and is used to create a strong illusion of having a virtual body. Moreover, it is pointed out that the use of first-person perspective in visual–motor synchronization gives an even stronger illusion of virtual body possession. Undoubtedly, the ability to virtually represent a subject’s entire body is one of the most important advantages of the latest VR technology over other types of computer user interfaces. Another interesting VE, although already expensive, is the Cave Automatic Virtual Environment (CAVE), in which images are projected via a projector onto the walls and floor of a small cubic room. In this environment, the participant wears glasses that allow stereoscopic vision, and sound is played through loudspeakers in the room [20]. Furthermore, research suggests that the strength of fully immersive virtual environments will be higher than that of non-immersive VEs, which is supported by findings indicating that higher immersion is associated with a stronger sense of presence, and often with more pronounced emotional reactions. Nevertheless, the relationship between immersion and emotional reactions is not clear, nor are the relationships between specific emotions and the sense of presence in VR yet known.

It has already been mentioned that VR can be a non-immersive environment, as well as low-immersive, semi-immersive and fully immersive. The latter may be responsible for the increased incidence of cybersickness (virtual reality sickness). It is a similar, but not identical, term to the concept of motion sickness or simulator sickness. Cybersickness (CS) most likely results from, e.g., the inconsistency between the sense of movement in the virtual environment and stillness in the real world, according to sensory conflict theory [91]. Its main symptoms include (a) disorientation (systemic and non-systemic dizziness), (b) nausea (belching, unpleasant feeling in the stomach, salivation) and (c) oculomotor symptoms (eye fatigue, difficulty focusing, blurred vision, headaches). These symptoms are exacerbated by various factors, and among the important ones are (a) personal factors: age (the younger the person, the more severe the symptoms), female gender, fatigue, posture (sitting is safest); (b) technical inadequacies (devices/interfaces that are inconvenient to use, image lag and flickering, calibration; and (c) the specifics of the virtual task: a sense of lack of control, too long a virtual session (the longer, the greater the risk of adverse symptoms) [90,91]. It is noteworthy that in simulator sickness, oculomotor complaints predominate, while in cybersickness. it is primarily disorientation [92]. It is estimated that CS symptoms affect 60–70% of HMD users, and their severity is about three times that of simulator sickness. The considerations so far show how serious a problem cybersickness symptoms can be. Hence, intensive research is being conducted to reduce the adverse symptoms associated with being in the digital world [54,90,91,92]. Recommendations are being prepared, and interesting neuroscientific studies are being presented to reduce the risk of adverse symptoms. In addition, various questionnaires are proposed to assess this risk in participants of virtual worlds, for example, by the Stanney [91], Kourtesis [92], Laessoe [93] and Kim [94] groups.

Another difficulty worth mentioning is the lack of validation and standardization of VEs, which consequently leads, for example, to difficulties in replicating studies and their results [9,26,69,83]. As a consequence, evaluations of different environments are incomparable and thus less reliable. Furthermore, the very nature of both non-immersive and immersive VR largely depends on the use of vision to navigate and perform virtual tests and tasks. Therefore, the inclusion criteria for participants in many studies include normal or corrected vision [22,23]. Moreover, VR training requires a certain level of cognitive functioning and supports computer interfaces and/or virtual objects [20]. Above all, the final success depends on the motivation of the participants themselves to complete tasks and programs in VEs [25,64,65,67,95]. The difficulties indicated may result in different and/or inconclusive results, especially when, for example, reviewing studies using these modern technologies in different non-clinical and clinical groups. Therefore, when interpreting the results of various VR studies, in addition to methodological diligence, it is necessary to take into account the specifics of the VEs.

Virtual technologies offer new opportunities and perspectives for physical and/or cognitive exercise to improve human health. An interesting summary of current considerations for the future era of virtual/digital neuroscience is a systematic review by Ali’s team [1]. The authors point out that VR has emerged as an innovative, safe and effective tool for the rehabilitation of many childhood and adult diseases. VR-based therapies have the potential to improve both motor and functional skills across a wide range of age groups through cortical reorganization and activation of various neuronal connections [24,71,73,75]. The great potential of using serious VR-based games that combine perceptual learning and dichoptic stimulation in the rehabilitation of ophthalmic and neurological disorders has been demonstrated. Current research on memory retrieval has been inspired by theories of brain plasticity and discoveries about the nervous system’s ability to reconstruct cellular synapses as a result of interaction with enriched environments [32,76]. Therefore, for example, the use of VR training can play an important role in improving cognitive functions and motor disabilities [25,47,59,62,84,86,95]. VR-based training is currently being researched to prevent and control measurements in ocular diseases such as myopia, amblyopia, presbyopia and age-related macular degeneration [1,96]. As indicated by the dynamic development of IT/ITC (which accelerated even further during the COVID-19 pandemic, including futuristic Metaverse concepts), as well as findings in neuroscience, VR technologies will be more accessible and thus widely used in (digital) healthcare in the future [4,8,12,97]. Finally, it is worth mentioning the important issue of the ethical implications of digital technologies [3,98]. This topic, which represents a new challenge for the future, is already being addressed by many researchers, philosophers and computer scientists, pointing out both benefits and serious dangers (cybersecurity, privacy, lack of general recommendations and methods for validation and standardization of virtual environments and tools) and potential threats (cybersickness, addiction to new technologies, currently unknown negative consequences) to future users of virtual worlds [14,97,99].