Background/Objectives: HANS (human papillomavirus vaccination-associated neuroimmunopathic syndrome) is a type of adverse reaction to HPV vaccination that causes cognitive dysfunction. Human brain function can be represented by functional connectivity and the Brain Functional Connectivity Network (BFCN), which are constructed by scalp-recorded electroencephalograms (EEGs). Functional connectivity and BFCN are used to estimate functional efficiency. The effects of cognitive dysfunction on network properties have been reported. However, network properties in HANS patients are incompletely understood. In this study, we examined (1) identifiability between HANS patients and young controls and (2) the impact of cognitive dysfunction due to HANS on BFCN for five frequency bands. Methods: 16-ch EEGs were recorded in a resting state with eyes closed for 14 HANS patients and 12 young controls. We used Synchronization Likelihood (SL) as measured functional connectivity, which is used for classification by machine learning and for the construction of BFCN for five frequency bands. In (1), SL values were used as features for classification. Accuracies were calculated by leave-one-out cross-validation. Accuracies for five frequency bands were compared to that of random prediction. In (2), clustering coefficient, characteristic path length, and small-worldness of BFCN were compared between HANS patients and young controls. Results: Our study revealed (1) high accuracies were illustrated for lower alpha and theta bands and (2) a significant decrease compared to controls in small-worldness in HANS patients for the gamma band. Conclusion: Our study shows identifiability between HANS patients and young controls. In addition, changes in network characteristics based on functional connectivity are relevant to cognitive dysfunction in HANS.
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