Currently submitted to: JMIR Serious Games
Date Submitted: Mar 31, 2026
Open Peer Review Period: Apr 1, 2026 - May 27, 2026
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Title:Graph-Theoretical EEG Analysis Reveals Virtual Reality–Induced Brain Network Modulation in Alzheimer’s Disease
ABSTRACT
Background:
Background:
Alzheimer’s disease (AD) is increasingly recognized as a disorder of large-scale brain network disruption. Immersive virtual reality (VR) has emerged as a promising digital health intervention for cognitive stimulation, but its neurophysiological effects on whole-brain network organizations remain poorly characterized.
Objective:
Objective:
This study aimed to investigate whether immersive VR stimulation modulates functional brain network organization in individuals with AD using electroencephalography (EEG)–based graph-theoretical analysis.
Methods:
Methods:
A total of 60 participants were enrolled, including 20 patients with AD, 20 individuals with mild cognitive impairment (MCI), and 20 healthy controls. EEG recordings were obtained during three experimental states: pre-VR resting, VR stimulation, and post-VR resting. Functional connectivity networks were constructed using phase locking value across multiple frequency bands. Graph-theoretical metrics, including global efficiency, modularity, and nodal strength, were calculated to characterize large-scale brain network topology and its state-dependent modulation.
Results:
Results:
VR stimulation induced measurable reorganization of functional brain networks. In patients with AD, VR reduced abnormal hemispheric asymmetry, enhanced bilateral connectivity, and modulated the balance between network integration and segregation. The strongest effects were observed in the high-frequency band (32–70 Hz), where VR increased distributed long-range connectivity. These network-level changes reduced functional differences between AD and healthy controls and revealed distinct dynamic response patterns across clinical groups.
Conclusions:
Conclusions:
Immersive VR dynamically modulates large-scale brain network organization in Alzheimer’s disease. These findings support the potential of VR as a scalable digital intervention for cognitive rehabilitation and demonstrate the utility of network-based EEG biomarkers for evaluating technology-enabled cognitive therapies.
Citation
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