## 4 Discussion
### Limitations and Directions of Further Studies
The successful integration of brain-computer interfaces and virtual reality faces inherent technical hurdles. Electroencephalography, a non-invasive and relatively affordable approach, is susceptible to noise and artifacts, such as muscle activity and eye movements, which can obscure brain signals and impede accurate control. Additionally, the movement of electrodes in some commercially available BCI devices further exacerbates this issue, introducing another layer of variability to the already noisy EEG signal. Furthermore, while VR technology is rapidly advancing, it still falls short of perfectly replicating the complexity and fidelity of real-world environments. This discrepancy can limit the ecological validity of BCI-VR applications, particularly those intended for training or rehabilitation purposes, where the transfer of skills to real-world scenarios is crucial. To address these challenges, researchers are exploring innovative solutions to enhance the integration of BCIs and virtual reality. One promising approach involves the incorporation of multimodal sensing, where brain activity is combined with other physiological data, such as eye tracking and motion capture, to provide a more comprehensive and robust assessment of user interactions within the virtual environment. This synergistic integration of multiple data streams can help mitigate the impact of noise and artifacts, leading to more accurate decoding of user intent and improved overall system performance [57]. A crucial aspect demanding careful consideration in BCI-VR integration is the safeguarding of neural data and mitigation of potential cognitive risks. The sensitive nature of brainwave data necessitates robust cybersecurity measures to prevent unauthorized access, breaches, or malicious use. Furthermore, the long-term effects of prolonged BCI use on cognitive function remain an active area of investigation. Further research is essential to establish comprehensive neurosecurity standards, develop privacy-preserving data encryption methods, and investigate the potential for unintended cognitive or neural impacts arising from extended or improper BCI-VR interaction. Specifically, researchers should explore effective techniques for anonymizing and encrypting neural data to protect user privacy. Additionally, studies should examine the cumulative impact of repeated BCI-VR sessions on cognitive performance, attention, and neural plasticity over extended periods. Establishing clear guidelines and protocols for safe, ethically-sound BCI-VR usage will be crucial in ensuring the responsible advancement and widespread adoption of these transformative technologies. Addressing these concerns proactively will be paramount in ensuring the ethical and responsible advancement of BCI-VR technology [81, 82, 83, 84, 85]. VR-BCI systems raise several ethical concerns, particularly around data privacy, as they collect sensitive neurological data that can reveal personal thoughts, emotions, or cognitive states, posing significant risks if mishandled or accessed without permission. Ensuring informed consent is challenging, especially given the complexity of VR-BCI technology, as users may not fully understand how their data will be used or what the potential long-term implications may be. The potential for the technology to influence cognitive states or perceptions raises concerns about unintended psychological effects,including the possibility of changing the user's thought patterns or emotional states over time. There is also a risk of addiction or overreliance, as long-term use of VR-BCI systems can blur the lines between virtual and real experiences for users, potentially affecting their mental health and decision-making. Equitable access and potential biases in system design are additional concerns, as VR-BCI systems may reinforce existing inequalities if not made available to diverse populations.