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

Guoshi Li; Li-Ming Hsu; Ye Wu; Andrea C Bozoki; Yen-Yu Ian Shih; Pew-Thian Yap

doi:10.1038/s43856-025-00736-7

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

Commun Med (Lond). 2025 Jan 15;5(1):17. doi: 10.1038/s43856-025-00736-7.

Authors

Guoshi Li^{1

2}, Li-Ming Hsu^{1

2

3}, Ye Wu^{1

2}, Andrea C Bozoki⁴, Yen-Yu Ian Shih^{2

3

4}, Pew-Thian Yap^{5

6}

Affiliations

¹ Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
² Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
³ Center for Animal MRI, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
⁴ Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
⁵ Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. [email protected].
⁶ Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. [email protected].

PMID: 39814858
DOI: 10.1038/s43856-025-00736-7

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.

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.

Abstract

Plain language summary

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