Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI

Abstract Background Alzheimer’s disease (AD) is a serious neurodegenerative disorder without a clear understanding of pathophysiology. Recent experimental data have suggested neuronal excitation-inhibition (E-I) imbalance as an essential element of AD pathology, but E-I imbalance has not been system...

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Main Authors: Guoshi Li, Li-Ming Hsu, Ye Wu, Andrea C. Bozoki, Yen-Yu Ian Shih, Pew-Thian Yap
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Communications Medicine
Online Access:https://doi.org/10.1038/s43856-025-00736-7
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author Guoshi Li
Li-Ming Hsu
Ye Wu
Andrea C. Bozoki
Yen-Yu Ian Shih
Pew-Thian Yap
author_facet Guoshi Li
Li-Ming Hsu
Ye Wu
Andrea C. Bozoki
Yen-Yu Ian Shih
Pew-Thian Yap
author_sort Guoshi Li
collection DOAJ
description Abstract Background Alzheimer’s disease (AD) is a serious neurodegenerative disorder without a clear understanding of pathophysiology. Recent experimental data have suggested neuronal excitation-inhibition (E-I) imbalance as an essential element of AD pathology, but E-I imbalance has not been systematically mapped out for either local or large-scale neuronal circuits in AD, precluding precise targeting of E-I imbalance in AD treatment. Method In this work, we apply a Multiscale Neural Model Inversion (MNMI) framework to the resting-state functional MRI data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to identify brain regions with disrupted E-I balance in a large network during AD progression. Results We observe that both intra-regional and inter-regional E-I balance is progressively disrupted from cognitively normal individuals, to mild cognitive impairment (MCI) and to AD. Also, we find that local inhibitory connections are more significantly impaired than excitatory ones and the strengths of most connections are reduced in MCI and AD, leading to gradual decoupling of neural populations. Moreover, we reveal a core AD network comprised mainly of limbic and cingulate regions. These brain regions exhibit consistent E-I alterations across MCI and AD, and thus may represent important AD biomarkers and therapeutic targets. Lastly, the E-I balance of multiple brain regions in the core AD network is found to be significantly correlated with the cognitive test score. Conclusions Our study constitutes an important attempt to delineate E-I imbalance in large-scale neuronal circuits during AD progression, which may facilitate the development of new treatment paradigms to restore physiological E-I balance in AD.
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spelling doaj-art-18c429112ff543fc911e51e7a5702e352025-01-19T12:36:56ZengNature PortfolioCommunications Medicine2730-664X2025-01-015112110.1038/s43856-025-00736-7Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRIGuoshi Li0Li-Ming Hsu1Ye Wu2Andrea C. Bozoki3Yen-Yu Ian Shih4Pew-Thian Yap5Department of Radiology, University of North Carolina at Chapel HillDepartment of Radiology, University of North Carolina at Chapel HillDepartment of Radiology, University of North Carolina at Chapel HillDepartment of Neurology, University of North Carolina at Chapel HillBiomedical Research Imaging Center, University of North Carolina at Chapel HillDepartment of Radiology, University of North Carolina at Chapel HillAbstract Background Alzheimer’s disease (AD) is a serious neurodegenerative disorder without a clear understanding of pathophysiology. Recent experimental data have suggested neuronal excitation-inhibition (E-I) imbalance as an essential element of AD pathology, but E-I imbalance has not been systematically mapped out for either local or large-scale neuronal circuits in AD, precluding precise targeting of E-I imbalance in AD treatment. Method In this work, we apply a Multiscale Neural Model Inversion (MNMI) framework to the resting-state functional MRI data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to identify brain regions with disrupted E-I balance in a large network during AD progression. Results We observe that both intra-regional and inter-regional E-I balance is progressively disrupted from cognitively normal individuals, to mild cognitive impairment (MCI) and to AD. Also, we find that local inhibitory connections are more significantly impaired than excitatory ones and the strengths of most connections are reduced in MCI and AD, leading to gradual decoupling of neural populations. Moreover, we reveal a core AD network comprised mainly of limbic and cingulate regions. These brain regions exhibit consistent E-I alterations across MCI and AD, and thus may represent important AD biomarkers and therapeutic targets. Lastly, the E-I balance of multiple brain regions in the core AD network is found to be significantly correlated with the cognitive test score. Conclusions Our study constitutes an important attempt to delineate E-I imbalance in large-scale neuronal circuits during AD progression, which may facilitate the development of new treatment paradigms to restore physiological E-I balance in AD.https://doi.org/10.1038/s43856-025-00736-7
spellingShingle Guoshi Li
Li-Ming Hsu
Ye Wu
Andrea C. Bozoki
Yen-Yu Ian Shih
Pew-Thian Yap
Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI
Communications Medicine
title Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI
title_full Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI
title_fullStr Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI
title_full_unstemmed Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI
title_short Revealing excitation-inhibition imbalance in Alzheimer’s disease using multiscale neural model inversion of resting-state functional MRI
title_sort revealing excitation inhibition imbalance in alzheimer s disease using multiscale neural model inversion of resting state functional mri
url https://doi.org/10.1038/s43856-025-00736-7
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