Toward objective biomarkers in psychiatric rehabilitation: detecting the “Berger Effect” with a sheet-type EEG device

For individuals undergoing psychiatric rehabilitation, there is an urgent need to establish an objective biomarker of brain activity without invasive or behavioral restrictions. To investigate an objective index for potential psychiatric rehabilitation assessment and intervention strategies in the future, we tried to detect the "Berger effect", the alpha EEG reactivity to eyes opening, and to verify the suitability of a sheet-type electroencephalography (EEG) device, HARU-1. We measured EEG of 20 healthy young to middle-aged subjects using HARU-1 from the forehead area during resting closed-eye and open-eye conditions. Fast Fourier transform and time-frequency analysis were then performed on the data from all subjects in the resting closed-eye and resting open-eye conditions. Statistical analysis found that the reference electrode derivation method showed a significant increase in alpha waves and a significant decrease in beta and gamma waves in the three forehead channels of Fp1, Fp2 and AFz during the resting closed eye condition compared to the resting open eye condition. In the bipolar derivation method, all Fp1-AFz, Fp2-Fp1 and AFz-Fp2 showed a significant decrease in the β and γ bands at approximately 13-50 Hz. These results demonstrated that HARU-1 accurately measured the "Berger effect" in the forehead region, suggesting that HARU-1 may be useful in detecting objective biomarkers of brain activity during psychiatric rehabilitation.

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Publication Details

Journal
Frontiers in Psychiatry
Published
2025-05-06
DOI
https://doi.org/10.3389/fpsyt.2025.1503715
Citations
1
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
1.43
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article

Toward objective biomarkers in psychiatric rehabilitation: detecting the “Berger Effect” with a sheet-type EEG device

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Frontiers in Psychiatry
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article

Toward objective biomarkers in psychiatric rehabilitation: detecting the “Berger Effect” with a sheet-type EEG device

Ryouhei Ishii, Masahiro Hata, Masaya Ueda, China Shiroma, Shun Takahashi, Yasuo Naito, Keigo Shiraiwa, Keita Ueno, Junya Orui, Fumie Tazaki, Takao Inoue
article en
1 citations

Abstract

For individuals undergoing psychiatric rehabilitation, there is an urgent need to establish an objective biomarker of brain activity without invasive or behavioral restrictions. To investigate an objective index for potential psychiatric rehabilitation assessment and intervention strategies in the future, we tried to detect the "Berger effect", the alpha EEG reactivity to eyes opening, and to verify the suitability of a sheet-type electroencephalography (EEG) device, HARU-1. We measured EEG of 20 healthy young to middle-aged subjects using HARU-1 from the forehead area during resting closed-eye and open-eye conditions. Fast Fourier transform and time-frequency analysis were then performed on the data from all subjects in the resting closed-eye and resting open-eye conditions. Statistical analysis found that the reference electrode derivation method showed a significant increase in alpha waves and a significant decrease in beta and gamma waves in the three forehead channels of Fp1, Fp2 and AFz during the resting closed eye condition compared to the resting open eye condition. In the bipolar derivation method, all Fp1-AFz, Fp2-Fp1 and AFz-Fp2 showed a significant decrease in the β and γ bands at approximately 13-50 Hz. These results demonstrated that HARU-1 accurately measured the "Berger effect" in the forehead region, suggesting that HARU-1 may be useful in detecting objective biomarkers of brain activity during psychiatric rehabilitation.

Frontiers in PsychiatryVol. 16
Morinomiya University of Medical Sciences (JP), University of Hyogo (JP), Wakayama Medical University (JP), Osaka Kawasaki Rehabilitation University (JP), Showa General Hospital (JP), Osaka Health Science University (JP), Osaka Metropolitan University (JP), Hyogo University (JP), The University of Osaka (JP)
Openalex Percentile: Top 20%
EEG and Brain-Computer Interfaces
1.43
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