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González-Erena, P.V.; Fernández-Guinea, S.; Kourtesis, P. Cognitive Assessment and Training in Extended Reality: Multimodal Systems, Clinical Utility, and Current Challenges. Encyclopedia. Available online: https://encyclopedia.pub/entry/57698 (accessed on 14 February 2025).
González-Erena PV, Fernández-Guinea S, Kourtesis P. Cognitive Assessment and Training in Extended Reality: Multimodal Systems, Clinical Utility, and Current Challenges. Encyclopedia. Available at: https://encyclopedia.pub/entry/57698. Accessed February 14, 2025.
González-Erena, Palmira Victoria, Sara Fernández-Guinea, Panagiotis Kourtesis. "Cognitive Assessment and Training in Extended Reality: Multimodal Systems, Clinical Utility, and Current Challenges" Encyclopedia, https://encyclopedia.pub/entry/57698 (accessed February 14, 2025).
González-Erena, P.V., Fernández-Guinea, S., & Kourtesis, P. (2025, January 15). Cognitive Assessment and Training in Extended Reality: Multimodal Systems, Clinical Utility, and Current Challenges. In Encyclopedia. https://encyclopedia.pub/entry/57698
González-Erena, Palmira Victoria, et al. "Cognitive Assessment and Training in Extended Reality: Multimodal Systems, Clinical Utility, and Current Challenges." Encyclopedia. Web. 15 January, 2025.
Peer Reviewed
Cognitive Assessment and Training in Extended Reality: Multimodal Systems, Clinical Utility, and Current Challenges

Extended reality (XR) technologies—encompassing virtual reality (VR), augmented reality (AR), and mixed reality (MR)—are transforming cognitive assessment and training by offering immersive, interactive environments that simulate real-world tasks. XR enhances ecological validity while enabling real-time, multimodal data collection through tools such as galvanic skin response (GSR), electroencephalography (EEG), eye tracking (ET), hand tracking, and body tracking. This allows for a more comprehensive understanding of cognitive and emotional processes, as well as adaptive, personalized interventions for users. Despite these advancements, current XR applications often underutilize the full potential of multimodal integration, relying primarily on visual and auditory inputs. Challenges such as cybersickness, usability concerns, and accessibility barriers further limit the widespread adoption of XR tools in cognitive science and clinical practice. This review examines XR-based cognitive assessment and training, focusing on its advantages over traditional methods, including ecological validity, engagement, and adaptability. It also explores unresolved challenges such as system usability, cost, and the need for multimodal feedback integration. The review concludes by identifying opportunities for optimizing XR tools to improve cognitive evaluation and rehabilitation outcomes, particularly for diverse populations, including older adults and individuals with cognitive impairments.

extended reality (XR) cognitive assessment cognitive training user experience usability acceptability ecological validity cybersickness clinical utility immersion
Extended reality (XR), encompassing virtual reality (VR), augmented reality (AR), and mixed reality (MR), has transformed cognitive assessment and training by offering immersive, dynamic environments that simulate real-world tasks [1]. Traditional neuropsychological tests—such as paper-and-pencil tasks or static computerized exercises—often isolate cognitive functions under artificial conditions [2]. XR, in contrast, integrates real-world complexity into cognitive assessments and training [3]. For example, while a traditional memory test might involve recalling a list of words, XR can simulate a virtual shopping mall where participants must locate items on a list, recall their positions, and manage realistic distractions [4]. This not only evaluates memory but also incorporates attention, spatial navigation, and decision-making, offering a more ecologically valid reflection of real-world cognitive performance [4][5].
A key innovation of XR is its ability to combine immersive, interactive experiences with multimodal feedback systems such as eye tracking (ET), galvanic skin response (GSR), electroencephalography (EEG), and body tracking [6][7]. These technologies enable the real-time collection of behavioral, physiological, and neural data, providing deeper insights into cognitive and emotional states during task performance [7][8]. For instance, in an XR-based attention task, eye-tracking data can reveal visual attention patterns, while EEG signals can indicate changes in cognitive load or mental fatigue [6][9]. This continuous, multimodal data collection represents a significant advancement over traditional methods, which often capture only static performance snapshots [1].
XR also addresses challenges such as disengagement and the learning effect observed in repetitive cognitive tasks [3]. Immersive XR environments enhance user engagement and motivation, particularly for older adults and individuals with cognitive impairments, where adherence to training programs is often a concern [10][11]. Additionally, XR systems can adapt task difficulty dynamically in real time based on user performance and cognitive load, ensuring personalized assessments and training programs aligned with individual abilities [9][12].
In clinical contexts, XR demonstrates utility in assessing and rehabilitating cognitive impairments associated with neurodegenerative diseases, brain injuries, and neurodevelopmental disorders [13][14]. For example, XR-based neuropsychological batteries can simulate daily activities, such as navigating virtual cities or managing household responsibilities, providing clinicians with ecologically valid insights into cognitive performance [15][16]. XR’s ability to collect longitudinal, personalized data further enhances its role in monitoring progress and tailoring interventions for improved cognitive outcomes [17].
Despite its potential, XR technologies face several challenges, including the underutilization of sensory modalities beyond visual and auditory feedback, issues such as cybersickness, and barriers to accessibility and usability [1][18]. Addressing these limitations is essential for XR to fulfill its promise as a transformative tool in cognitive science.

References

  1. Pons, P.; Navas-Medrano, S.; Soler-Dominguez, J.L. Extended Reality for Mental Health: Current Trends and Future Challenges. Front. Comput. Sci. 2022, 4, 1034307.
  2. Howieson, D. Current Limitations of Neuropsychological Tests and Assessment Procedures. Clin. Neuropsychol. 2019, 33, 200–208.
  3. Pieri, L.; Tosi, G.; Romano, D. Virtual Reality Technology in Neuropsychological Testing: A Systematic Review. J. Neuropsychol. 2023, 17, 382–399.
  4. Kourtesis, P.; Collina, S.; Doumas, L.A.A.; MacPherson, S.E. Validation of the Virtual Reality Everyday Assessment Lab (VR-EAL): An Immersive Virtual Reality Neuropsychological Battery with Enhanced Ecological Validity. J. Int. Neuropsychol. Soc. 2021, 27, 181–196.
  5. Parsons, T.D.; Carlew, A.R.; Magtoto, J.; Stonecipher, K. The Potential of Function-Led Virtual Environments for Ecologically Valid Measures of Executive Function in Experimental and Clinical Neuropsychology. Neuropsychol. Rehabil. 2017, 27, 777–807.
  6. Baceviciute, S.; Lucas, G.; Terkildsen, T.; Makransky, G. Investigating the Redundancy Principle in Immersive Virtual Reality Environments: An Eye-Tracking and EEG Study. J. Comput. Assist. Learn. 2022, 38, 120–136.
  7. Kalantari, S.; Rounds, J.D.; Kan, J.; Tripathi, V.; Cruz-Garza, J.G. Comparing Physiological Responses during Cognitive Tests in Virtual Environments vs. in Identical Real-World Environments. Sci. Rep. 2021, 11, 10227.
  8. Mishra, S.; Kumar, A.; Padmanabhan, P.; Gulyás, B. Neurophysiological Correlates of Cognition as Revealed by Virtual Reality: Delving the Brain with a Synergistic Approach. Brain Sci. 2021, 11, 51.
  9. Souchet, A.D.; Philippe, S.; Lourdeaux, D.; Leroy, L. Measuring Visual Fatigue and Cognitive Load via Eye Tracking While Learning with Virtual Reality Head-Mounted Displays: A Review. Int. J. Hum.–Comput. Interact. 2022, 38, 801–824.
  10. Riva, G.; Mancuso, V.; Cavedoni, S.; Stramba-Badiale, C. Virtual Reality in Neurorehabilitation: A Review of Its Effects on Multiple Cognitive Domains. Expert Rev. Med. Devices 2020, 17, 1035–1061.
  11. Skurla, M.D.; Rahman, A.T.; Salcone, S.; Mathias, L.; Shah, B.; Forester, B.P.; Vahia, I.V. Virtual Reality and Mental Health in Older Adults: A Systematic Review. Int. Psychogeriatr. 2021, 34, 143–145.
  12. Dey, A.; Chatburn, A.; Billinghurst, M. Exploration of an EEG-Based Cognitively Adaptive Training System in Virtual Reality. In Proceedings of the 2019 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), Osaka, Japan, 23–27 March 2019; pp. 220–226.
  13. Clay, F.; Howett, D.; Fitzgerald, J.; Fletcher, P.; Chan, D.; House, D. Use of Immersive Virtual Reality in the Assessment and Treatment of Alzheimer’s Disease: A Systematic Review. J. Alzheimer’s Dis. 2020, 75, 23–43.
  14. Shen, J.; Lundine, J.P.; Koterba, C.; Udaipuria, S.; Busch, T.; Rausch, J.; Yeates, K.O.; Crawfis, R.; Xiang, H.; Taylor, H.G. VR-Based Cognitive Rehabilitation for Children with Traumatic Brain Injuries: Feasibility and Safety. Rehabil. Psychol. 2022, 67, 474–483.
  15. Howard, M.C. A Meta-Analysis and Systematic Literature Review of Virtual Reality Rehabilitation Programs. Comput. Hum. Behav. 2017, 70, 317–327.
  16. Howett, D.; Castegnaro, A.; Krzywicka, K.; Hagman, J.; Marchment, D.; Henson, R.; Rio, M.; King, J.A.; Burgess, N.; Chan, D. Differentiation of Mild Cognitive Impairment Using an Entorhinal Cortex-Based Test of Virtual Reality Navigation. Brain 2019, 142, 1751–1766.
  17. Wen, D.; Li, R.; Jiang, M.; Li, J.; Liu, Y.; Dong, X.; Saripan, M.I.; Song, H.; Han, W.; Zhou, Y. Multi-Dimensional Conditional Mutual Information with Application on the EEG Signal Analysis for Spatial Cognitive Ability Evaluation. Neural Netw. 2022, 148, 23–36.
  18. Kourtesis, P.; Korre, D.; Collina, S.; Doumas, L.A.A.; MacPherson, S.E. Guidelines for the Development of Immersive Virtual Reality Software for Cognitive Neuroscience and Neuropsychology: The Development of Virtual Reality Everyday Assessment Lab (VR-EAL), a Neuropsychological Test Battery in Immersive Virtual Reality. Front. Comput. Sci. 2020, 1, e00012.
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