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

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...

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Published inCommunications medicine Vol. 5; no. 1; pp. 17 - 21
Main Authors Li, Guoshi, Hsu, Li-Ming, Wu, Ye, Bozoki, Andrea C., Shih, Yen-Yu Ian, Yap, Pew-Thian
Format Journal Article
LanguageEnglish
Published London Nature Publishing Group UK 15.01.2025
Springer Nature B.V
Nature Portfolio
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ISSN2730-664X
2730-664X
DOI10.1038/s43856-025-00736-7

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Summary: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. Plain language summary The cells within the brain, neurons, communicate using excitatory and inhibitory activity. The Excitation-inhibition (E-I) balance is a measure of the contribution of excitatory and inhibitory communication. Alzheimer’s disease (AD) is a brain disorder in which memory, thinking and reasoning are disrupted. The E-I balance is found to be disrupted in people with AD. We applied a computational model to brain imaging data and found that E-I balance is progressively disrupted during AD progression. E-I balance could potentially be used to identify people with AD. Also, treatments could be developed that improve the E-I balance, possibly improving symptoms for people with AD. Li et al. apply a multiscale modeling approach to identify excitation-inhibition (E-I) imbalance in large scale neuronal circuits in Alzheimer’s disease (AD) based on functional MRI. E-I imbalance concentrates on the limbic and cingulate regions, and both local and long-range E-I balance is progressively disrupted from cognitively normal subjects to mild cognitive impairment, and to AD.
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ISSN:2730-664X
2730-664X
DOI:10.1038/s43856-025-00736-7