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), 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.