Share：
Share this content in WeChat
X
[Chinese] [PDF] 36 1
• Clinical Article •
Excitation/inhibition imbalance in the default mode network of Alzheimer's disease based on MRS and rs-fMRI: Association of Glx/GABA ratio with regional brain activity
XIAO Yao  DONG Ke  LI Xinyu  HU Chunhong  DAI Hui 

Cite this article as: XIAO Y, DONG K, LI X Y, et al. Excitation/inhibition imbalance in the default mode network of Alzheimer's disease based on MRS and rs-fMRI: Association of Glx/GABA ratio with regional brain activity[J]. Chin J Magn Reson Imaging, 2026, 17(10): 63-75. DOI:10.12015/issn.1674-8034.2026.10.008.


[Abstract] Objective To investigate the excitation/inhibition (E/I) balance and brain functional alterations in core nodes of the default mode network (DMN) in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) using multimodal MRI, and to explore the coupling relationship between neurochemistry and brain function.Materials and Methods A total of 22 AD patients, 19 MCI patients, and 22 normal control (NC) were prospectively enrolled. Demographic and neuropsychological data were collected, including the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired to calculate the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo). Magnetic resonance spectroscopy (MRS) data were acquired from regions of interest (ROI) in the left medial prefrontal cortex (Lm-PFC) and precuneus (PCu) to calculate the levels of glutamate-glutamine complex (Glx) and gamma-aminobutyric acid (GABA) combined signal relative to creatine (Cr) (GABA+), as well as the Glx/GABA+ ratio. It should be noted that the Glx/GABA+ ratio reflects the steady-state concentrations of excitatory and inhibitory metabolites in local brain regions, rather than a direct measurement of dynamic synaptic E/I balance, and serves as an indirect indicator of regional E/I metabolic status in this study. Two-sample t-tests were used for pairwise comparisons of rs-fMRI metrics (GRF correction, voxel-level P < 0.001, cluster-level P < 0.05). MRS data were analyzed using one-way analysis of variance (ANOVA) followed by Bonferroni post-hoc comparisons, including only measurements with fitting error less than 15%. Pearson correlation analysis was performed to examine the relationships between the Glx/GABA+ ratio and fALFF values, as well as cognitive scale (MMSE, MoCA) scores . A P-value < 0.05 was considered statistically significant.Results Compared with the NC group, the AD group showed a significantly decreased fALFF value in the left angular gyrus (t = -5.533 4, P < 0.05). No significant differences in ReHo were observed among the three groups (P > 0.05). MRS analysis revealed that the Glx/Cr level and Glx/GABA+ ratio in the Lm-PFC and PCu were significantly higher in the AD group than in the NC and MCI groups (P < 0.001), while no significant difference was found between the NC and MCI groups (P > 0.05). Correlation analysis between whole-brain fALFF and the Glx/GABA+ ratio in the ROI showed that, in the NC group, the Glx/GABA+ ratio in the PCu was significantly negatively correlated with fALFF values in the right superior temporal pole (r = -0.947 1, P < 0.001), left gyrus rectus (r = -0.889 5, P < 0.001), and right cerebellar Crus Ⅲ (r = -0.852 5, P < 0.001). No significant correlations were found in the AD group (P > 0.05). Furthermore, in the NC group, the fALFF values in the right superior temporal pole and left gyrus rectus (which were closely related to cognitive function), as well as the Glx/GABA+ ratios in the ROI in both groups, showed no significant correlations with cognitive scale (MMSE, MoCA) scores (P > 0.05).Conclusions Alterations in E/I-related metabolite homeostasis, reduced local neural activity, and a loss of the metabolical–functional association observed under physiological conditions exist in core nodes of the DMN in AD patients. The metabolic imbalance reflected by the Glx/GABA+ ratio may serve as a valuable imaging reference indicator for the clinical stage of AD; however, its correlation with cognitive and functional measures was not established in the current study, warranting caution in its interpretation as a proxy for E/I balance.
[Keywords] Alzheimer's disease；mild cognitive impairment；excitation；inhibition；magnetic resonance imaging；magnetic resonance spectroscopy；resting-state functional magnetic resonance imaging；glutamate-glutamine complex；γ-aminobutyric acid

XIAO Yao   DONG Ke   LI Xinyu   HU Chunhong   DAI Hui*  

Department of Radiology, the First Affiliated Hospital of Soochow University, Suzhou 215000, China

Corresponding author: DAI H, E-mail: huizi198208@126.com

Conflicts of interest   None.

Received  2026-04-30
Accepted  2026-09-23
DOI: 10.12015/issn.1674-8034.2026.10.008
Cite this article as: XIAO Y, DONG K, LI X Y, et al. Excitation/inhibition imbalance in the default mode network of Alzheimer's disease based on MRS and rs-fMRI: Association of Glx/GABA ratio with regional brain activity[J]. Chin J Magn Reson Imaging, 2026, 17(10): 63-75. DOI:10.12015/issn.1674-8034.2026.10.008.

[1]
ZHENG Q, WANG X. Alzheimer's disease: insights into pathology, molecular mechanisms, and therapy[J]. Protein Cell, 2025, 16(2): 83-120. DOI: 10.1093/procel/pwae026.
[2]
LI J, LIU Y, YIN C, et al. Structural and functional remodeling of neural networks in β-amyloid driven hippocampal hyperactivity[J/OL]. Ageing Res Rev, 2024, 101: 102468 [2026-04-30]. https://doi.org/10.1016/j.arr.2024.102468. DOI: 10.1016/j.arr.2024.102468.
[3]
OKECHUKWU N G, ZACCONE C, LA BARBERA L, et al. Excitation-inhibition imbalance as a common thread linking early Alzheimer's disease with temporal lobe epilepsy[J/OL]. Exp Neurol, 2026, 397: 115581 [2026-04-30]. https://doi.org/10.1016/j.expneurol.2025.115581. DOI: 10.1016/j.expneurol.2025.115581.
[4]
VAN NIFTERICK A M, MULDER D, DUINEVELD D J, et al. Resting-state oscillations reveal disturbed excitation-inhibition ratio in Alzheimer's disease patients[J/OL]. Sci Rep, 2023, 13(1): 7419 [2026-04-30]. https://doi.org/10.1038/s41598-023-33973-8 DOI: 10.1038/s41598-023-33973-8.
[5]
ZHANG X, YOU J, QAO Q, et al. Correlation Between the Fractional Amplitude of Low-Frequency Fluctuation and Cognitive Defects in Alzheimer's Disease[J]. J Alzheimers Dis, 2024, 101(2): 577-587. DOI: 10.3233/JAD-240487.
[6]
DUAN H Q, LI L Q, QIU L H. Research progresses of resting-state functional MRI for mild cognitive impairment and Alzheimer's disease[J]. Chinese Journal of Medical Imaging Technology, 2024, 40(8): 1254-1257.
[7]
CHEN R, ZHANG H, HUANG L, et al. MRS Perspectives: Neurotransmitter and Metabolic Alterations in Cognitive Decline and Mental/Neurological Disorders[J]. Curr Neuropharmacol, 2025, 23(5): 524-546. DOI: 10.2174/011570159X402624250926110831.
[8]
HE Y, SWEATMAN H, THOMSON A R, et al. Regional Excitatory-Inhibitory Balance Relates to Self-Reference Effect on Recollection via the Precuneus/Posterior Cingulate Cortex-Medial Prefrontal Cortex Connectivity[J/OL]. J Neurosci, 2025, 45(25) [2026-04-30]. https://doi.org/10.1523/JNEUROSCI.2343-24.2025. DOI: 10.1523/JNEUROSCI.2343-24.2025.
[9]
TANG X, GUO Z, CHEN G, et al. A Multimodal Meta-Analytical Evidence of Functional and Structural Brain Abnormalities Across Alzheimer's Disease Spectrum[J/OL]. Ageing Res Rev, 2024, 95: 102240 [2026-04-30]. https://doi.org/10.1016/j.arr.2024.102240. DOI: 10.1016/j.arr.2024.102240.
[10]
CASULA E P, BORGHI I, MAIELLA M, et al. Regional Precuneus Cortical Hyperexcitability in Alzheimer's Disease Patients[J]. Ann Neurol, 2023, 93(2): 371-383. DOI: 10.1002/ana.26556.
[11]
EDDEN R A, PUTS N A, HARRIS A D, et al. Gannet: A batch-processing tool for the quantitative analysis of gamma-aminobutyric acid-edited MR spectroscopy spectra[J]. J Magn Reson Imaging, 2014, 40(6): 1445-1452. DOI: 10.1002/jmri.24478.
[12]
CRAVEN A R, BHATTACHARYYA P K, CLARKE W T, et al. Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy[J/OL]. NMR Biomed, 2022, 35(7): e4702 [2026-04-30]. https://doi.org/10.1002/nbm.4702. DOI: 10.1002/nbm.4702.
[13]
MURAI S A, MANO T, SANES J N, et al. Atypical intrinsic neural timescale in the left angular gyrus in Alzheimer's disease[J/OL]. Brain Commun, 2024, 6(4): fcae199 [2026-04-30]. https://doi.org/10.1093/braincomms/fcae199. DOI: 10.1093/braincomms/fcae199.
[14]
SEGHIER M L. Multiple functions of the angular gyrus at high temporal resolution[J]. Brain Struct Funct, 2023, 228(1): 7-46. DOI: 10.1007/s00429-022-02512-y.
[15]
CHA W J, CHUMIN E J, YI D, et al. Amyloid-related default mode network hyperconnectivity and longitudinal decline in network distinctiveness in preclinical Alzheimer's disease[J/OL]. Alzheimers Dement, 2026, 22(2): e71025 [2026-04-30]. https://doi.org/10.1002/alz.71025. DOI: 10.1002/alz.71025.
[16]
HRYBOUSKI S, DAS S R, XIE L, et al. BOLD amplitude correlates of preclinical Alzheimer's disease[J]. Neurobiol Aging, 2025, 150: 157-171. DOI: 10.1016/j.neurobiolaging.2025.02.011.
[17]
COSTA T, PREMI E, BORRONI B, et al. Local functional connectivity abnormalities in mild cognitive impairment and Alzheimer's disease: A meta-analytic investigation using minimum Bayes factor activation likelihood estimation[J/OL]. Neuroimage, 2024, 298: 120798 [2026-04-30]. https://doi.org/10.1016/j.neuroimage.2024.120798. DOI: 10.1016/j.neuroimage.2024.120798.
[18]
ZHAO K, CHEN P, WANG D, et al. A Multiform Heterogeneity Framework for Alzheimer's Disease Based on Multimodal Neuroimaging[J]. Biol Psychiatry, 2025, 97(11): 1022-1033. DOI: 10.1016/j.biopsych.2024.11.008.
[19]
VARELA-LÓPEZ B, ZURRÓN M, LINDÍN M, et al. Compensation versus deterioration across functional networks in amnestic mild cognitive impairment subtypes[J]. Geroscience, 2025, 47(2): 1805-1822. DOI: 10.1007/s11357-024-01369-9.
[20]
PASANTA D, HE J L, FORD T, et al. Functional MRS studies of GABA and glutamate/Glx - A systematic review and meta-analysis[J/OL]. Neurosci Biobehav Rev, 2023, 144: 104940 [2026-04-30]. https://doi.org/10.1016/j.neubiorev.2022.104940. DOI: 10.1016/j.neubiorev.2022.104940.
[21]
THOMSON A R, HOLLESTEIN V, GOODWIN A, et al. In Vivo Glx Measurements From GABA-Edited HERMES at 3 T Are Not Consistent With Those From Short-TE PRESS Across Scanners, Brain Regions, Diagnostic and Age Groups[J/OL]. NMR Biomed, 2026, 39(1): e70171 [2026-04-30]. https://doi.org/10.1002/nbm.70171. DOI: 10.1002/nbm.70171.
[22]
KANAGASABAI K, PALANIYAPPAN L, THÉBERGE J. Precision of metabolite-selective MRS measurements of glutamate, GABA and glutathione: A review of human brain studies[J/OL]. NMR Biomed, 2024, 37(3): e5071 [2026-04-30]. https://doi.org/10.1002/nbm.5071. DOI: 10.1002/nbm.5071.
[23]
SRIVASTAVA I, GOIKOLEA J, AYBERK KAYA T, et al. Reactive Astrocytes with Reduced Function of Glutamate Transporters in the App(NL-G-F) Knock-in Mice[J]. ACS Chem Neurosci, 2025, 16(11): 2035-2047. DOI: 10.1021/acschemneuro.4c00714.
[24]
ZHANG X, ZHAO Y, CHEN X, et al. Suppression of Astrocytic PirB Alleviates Aβ-Induced Excitotoxicity and Cognitive Deficits via EAAT Expression[J/OL]. Glia, 2026, 74(2): e70130 [2026-04-30]. https://doi.org/10.1002/glia.70130. DOI: 10.1002/glia.70130.
[25]
EBRAHIMI R, MOHAMMAD SOLTANI S, MASOURI M M, et al. Glutamatergic and GABAergic metabolite levels in Alzheimer's disease: a systematic review and meta-analysis[J/OL]. BMC Neurol, 2025, 25(1): 344 [2026-04-30]. https://doi.org/10.1186/s12883-025-04375-2. DOI: 10.1186/s12883-025-04375-2.
[26]
KOH W, KWAK H, CHEONG E, et al. GABA tone regulation and its cognitive functions in the brain[J]. Nat Rev Neurosci, 2023, 24(9): 523-539. DOI: 10.1038/s41583-023-00724-7.
[27]
ALI A B, ISLAM A, CONSTANTI A. The fate of interneurons, GABA(A) receptor sub-types and perineuronal nets in Alzheimer's disease[J/OL]. Brain Pathol, 2023, 33(1): e13129 [2026-04-30]. https://doi.org/10.1111/bpa.13129. DOI: 10.1111/bpa.13129.
[28]
SALCEDO C, WAGNER A, ANDERSEN J V, et al. Downregulation of GABA Transporter 3 (GAT3) is Associated with Deficient Oxidative GABA Metabolism in Human Induced Pluripotent Stem Cell-Derived Astrocytes in Alzheimer's Disease[J]. Neurochem Res, 2021, 46(10): 2676-2686. DOI: 10.1007/s11064-021-03276-3.
[29]
CRAVEN A R, DWYER G, ERSLAND L, et al. GABA, glutamate dynamics and BOLD observed during cognitive processing in psychosis patients with hallucinatory traits[J/OL]. Sci Rep, 2025, 15(1): 19466 [2026-04-30]. https://doi.org/10.1038/s41598-025-03612-3. DOI: 10.1038/s41598-025-03612-3.
[30]
TRIPATHI V, BATTA I, ZAMANI A, et al. Default Mode Network Functional Connectivity As a Transdiagnostic Biomarker of Cognitive Function[J]. Biol Psychiatry Cogn Neurosci Neuroimaging, 2025, 10(4): 359-368. DOI: 10.1016/j.bpsc.2024.10.006.
[31]
LI Y, YANG L, LI L, et al. The resting-state cerebro-cerebellar function connectivity and associations with verbal working memory performance[J/OL]. Behav Brain Res, 2022, 417: 113586 [2026-04-30]. https://doi.org/10.1016/j.bbr.2021.113586. DOI: 10.1016/j.bbr.2021.113586.
[32]
WANG C, PAN Y, LIU Y, et al. Aberrant default mode network in amnestic mild cognitive impairment: a meta-analysis of independent component analysis studies[J]. Neurol Sci, 2018, 39(5): 919-931. DOI: 10.1007/s10072-018-3386-8.
[33]
SKANDALAKIS G P, LINN W J, YEH F C, et al. Unveiling the axonal connectivity between the precuneus and temporal pole: Structural evidence from the cingulum pathways[J/OL]. Hum Brain Mapp, 2024, 45(9): e26771 [2026-04-30]. https://doi.org/10.1002/hbm.26771. DOI: 10.1002/hbm.26771.
[34]
SHELINE Y I, RAICHLE M E, SNYDER A Z, et al. Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly[J]. Biol Psychiatry, 2010, 67(6): 584-587. DOI: 10.1016/j.biopsych.2009.08.024.
[35]
LI L, LIU Y, SHU Y, et al. Altered functional connectivity of cerebellar subregions in male patients with obstructive sleep apnea: A resting-state fMRI study[J]. Neuroradiology, 2024, 66(6): 999-1012. DOI: 10.1007/s00234-024-03341-8.
[36]
PORGES E C, WOODS A J, EDDEN R A, et al. Frontal Gamma-Aminobutyric Acid Concentrations Are Associated With Cognitive Performance in Older Adults[J]. Biol Psychiatry Cogn Neurosci Neuroimaging, 2017, 2(1): 38-44. DOI: 10.1016/j.bpsc.2016.06.004.
[37]
BRITTON M K, JENSEN G, EDDEN R A, et al. "Surviving and Thriving": evidence for cortical GABA stabilization in cognitively-intact oldest-old adults[J/OL]. Transl Psychiatry, 2025, 15(1): 79 [2026-04-30]. https://doi.org/10.1038/s41398-025-03270-z. DOI: 10.1038/s41398-025-03270-z.
[38]
LIU L, SUN S, KANG W, et al. A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis[J]. Rev Neurosci, 2024, 35(2): 121-139. DOI: 10.1515/revneuro-2023-0033.
[39]
MAESTú F, DE HAAN W, BUSCHE M A, et al. Neuronal excitation/inhibition imbalance: core element of a translational perspective on Alzheimer pathophysiology[J/OL]. Ageing Res Rev, 2021, 69: 101372 [2026-04-30]. https://doi.org/10.1016/j.arr.2021.101372. DOI: 10.1016/j.arr.2021.101372.
[40]
RANASINGHE K G, KUDO K, SYED F, et al. Distinct manifestations of excitatory-inhibitory imbalance associated with amyloid-β and tau in patients with Alzheimer's disease[J/OL]. Nat Commun, 2025, 16(1): 7957 [2026-04-30]. https://doi.org/10.1038/s41467-025-62798-4. DOI: 10.1038/s41467-025-62798-4.
[41]
MAREK S, LAUMANN T O. Replicability and generalizability in population psychiatric neuroimaging[J]. Neuropsychopharmacology, 2024, 50(1): 52-57. DOI: 10.1038/s41386-024-01960-w.
[42]
ANDERSSON P, LI X, PERSSON J. Hippocampal and prefrontal GABA and glutamate concentration contribute to component processes of working memory in aging[J/OL]. Cereb Cortex, 2025, 35(5): bhaf105 [2026-04-30]. https://doi.org/10.1093/cercor/bhaf105. DOI: 10.1093/cercor/bhaf105.
[43]
FORD T C, NIBBS R, CREWTHER D P. Glutamate/GABA+ ratio is associated with the psychosocial domain of autistic and schizotypal traits[J/OL]. PLoS One, 2017, 12(7): e0181961 [2026-04-30]. https://doi.org/10.1371/journal.pone.0181961. DOI: 10.1371/journal.pone.0181961.
[44]
LIANG J, YANG Z, ZHOU C. Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits[J]. Neuroscientist, 2025, 31(1): 31-46. DOI: 10.1177/10738584231221766.
[45]
PATEL S, SHAH R J, COLEMAN P, et al. Potential peripheral biomarkers for the diagnosis of Alzheimer's disease[J/OL]. Int J Alzheimers Dis, 2011, 2011: 572495 [2026-04-30]. https://doi.org/10.4061/2011/572495. DOI: 10.4061/2011/572495.
[46]
VELU L, PELLERIN L, JULIAN A, et al. Early rise of glutamate-glutamine levels in mild cognitive impairment: Evidence for emerging excitotoxicity[J]. J Neuroradiol, 2024, 51(2): 168-175. DOI: 10.1016/j.neurad.2023.09.003.
[47]
BAI X, EDDEN R A, GAO F, et al. Decreased γ-aminobutyric acid levels in the parietal region of patients with Alzheimer's disease[J]. J Magn Reson Imaging, 2015, 41(5): 1326-1331. DOI: 10.1002/jmri.24665.
[48]
REDOLFI A, MANSET D, BARKHOF F, et al. Head-to-head comparison of two popular cortical thickness extraction algorithms: a cross-sectional and longitudinal study[J/OL]. PLoS One, 2015, 10(3): e0117692 [2026-04-30]. https://doi.org/10.1371/journal.pone.0117692. DOI: 10.1371/journal.pone.0117692.

PREV Construction of a nomogram for predicting cerebral small-vessel disease-related cognitive impairment by combining MRI imaging biomarkers and serum biochemical biomarkers
NEXT Research on acute whole-brain microstructural changes in mild traumatic brain injury based on DTI and DKI
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn