Multiscale Fluctuation Dispersion Entropy of EEG as a Physiological Biomarker of Schizotypy

Journal article


Zandbagleh, A., Azami, H., Mirzakuchaki, S., Daliri, M. R., Sanei, S. and Premkumar, P. (2023). Multiscale Fluctuation Dispersion Entropy of EEG as a Physiological Biomarker of Schizotypy. IEEE Access. pp. 110124 - 110135. https://doi.org/10.1109/ACCESS.2023.3321868
AuthorsZandbagleh, A., Azami, H., Mirzakuchaki, S., Daliri, M. R., Sanei, S. and Premkumar, P.
Abstract

Altered electroencephalography (EEG) activity in schizotypal individuals is a powerful indicator of proneness towards psychosis. This alteration is beyond decreased alpha power often measured in resting state EEG. Multiscale fluctuation dispersion entropy (MFDE) measures the non-linear complexity of the fluctuations of EEGs and is a more effective approach compared to the traditional linear power spectral density (PSD) measures of EEG activity in patients with neurodegenerative disorders. In this study, we applied MFDE to EEG signals to distinguish high schizotypy (HS) and low schizotypy (LS) individuals. The study includes several trials from 29 participants psychometrically classified as HS (n=19) and LS (n=10). After preprocessing, MFDE was computed in frontal, parietal, central, temporal and occipital regions for each participant at multiple time scales. Statistical analysis and machine learning algorithms were used to calculate the differences in MFDE measures between the HS and LS groups. Our findings revealed significant differences in MFDE measures between LS and HS individuals in the delta frequency band (at time scale 100 ms). HS individuals exhibited increased complexity and irregularity compared to LS individuals in the delta frequency band particularly in the occipital region. Furthermore, the MFDE measures resulted in high accuracy (96.55%) in discriminating between HS and LS individuals and outperformed the models based on power spectrum, demonstrating the potential of MFDE as a neurophysiological marker for schizotypy traits. The increased non-linear fluctuation in delta frequency band in the occipital region of HS individuals implies the changes in cognitive functions, such as memory and attention, and has significant potential as a biomarker for schizotypy and proneness towards psychosis.

KeywordsElectroencephalography , Complexity theory , Fluctuations , Entropy , Time series analysis , Power measurement , Mental health
Year2023
JournalIEEE Access
Journal citationpp. 110124 - 110135
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN2169-3536
Digital Object Identifier (DOI)https://doi.org/10.1109/ACCESS.2023.3321868
Web address (URL)https://ieeexplore.ieee.org/document/10271309
Publication dates
Print04 Oct 2023
Publication process dates
Accepted01 Oct 2023
Deposited26 Oct 2023
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File Access Level
Open
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