Neurobiological mechanism in cognitive decline: from synaptic dysfunction to large-scale neural network disruption

Authors

  • Jing Gu

DOI:

https://doi.org/10.61173/akn7v231

Keywords:

Neurodegenerative Disease, Synaptic Dys-function, Default Mode Network

Abstract

Neurodegenerative diseases are characterised by progressive cognitive decline, traditionally attributed to the accumulation of beta-amyloid (Aβ) and tau pathology. However, growing evidence indicates that the diseases are not only caused by synaptic dysfunction but also a syndrome of large-scale network dysconnectivity. This review synthesised current findings on how synaptic dysfunction scales up to disrupt functional connectivity across brain networks. At the microscopic level, impaired long-term potentiation, enhanced long-term depression, and AMPA receptor dysregulation compromise synaptic plasticity. These local defects extend to macroscopic network breakdown, particularly within the default mode network (DMN) and hippocampal-prefrontal circuits. Neuroimaging techniques such as resting-state fMRI and positron emission tomography (PET) reveal consistent patterns of weakened connectivity and altered synchrony that closely correlate with deficits in episodic memory, executive function, and language. Importantly, effective connectivity within DMN has been shown to predict both the incidence and timing of neurrodegenerative diseases, even years before diagnosis, underscoring its value as biomarker. Furthermore, Aβ and tau accumulation preferentially disrupt DMN, linking molecular pathology with network-level dysfunction. Together, these findings support a synapse-network model of neurodegenarative diseases such as Alzheimer’s disease, where local and global disruptions interact to drive cognitive decline. This framework highlights novel diagnostic opportunities and suggests that interventions preserving both synaptic and network integrity may hold promise for delaying disease progression.

References

[1] Elsayed M E H, Ali O A A M, Mohamed Y B E, Elasha O A F, Idris K O A, Sudheer A. Advancing Alzheimer’s disease treatment: a review of novel targets, innovative therapies, and future prospects [J]. Studies in Science of Science, 2025, 43(8): 283–300.

[2] Fonseca C S, Baker S L, Dobyns L, Janabi M, Jagust W J, Harrison T M. Tau accumulation and atrophy predict amyloid independent cognitive decline in aging [J]. Alzheimer’s & Dementia, 2024, 20(4): 2526. DOI:10.1002/alz.13654.

[3] Wu M, Zhang M, Yin X, Chen K, Hu Z, Zhou Q, Cao X, Chen Z, Liu D. The role of pathological tau in synaptic dysfunction in Alzheimer’s diseases [J]. Translational Neurodegeneration, 2021, 10(1). DOI:10.1186/s40035-021- 00270-1.

[4] Ereira S, Waters S, Razi A, Marshall C R. Early detection of dementia with default-mode network effective connectivity [J]. Nature Mental Health, 2024: 787–800. DOI:10.1038/s44220- 024-00259-5.

[5] Kim E J, Park S, Schuessler B P, Boo H, Cho J, Kim J J. Disruption of hippocampal-prefrontal neural dynamics and risky decision-making in a mouse model of Alzheimer’s disease [J]. Cell Reports, 2025, 44(8): 116081. DOI: 10.1016/ j.celrep.2025.116081.

[6] Texidó L, Martín-Satué M, Alberdi E, Solsona C, Matute C. Amyloid β peptide oligomers directly activate NMDA receptors [J]. Cell Calcium, 2011, 49(3): 184–190. DOI: 10.1016/ j.ceca.2011.02.001. Dean&Francis ISSN 2959-409X

[7] Luscher C, Malenka R C. NMDA receptor-dependent longterm potentiation and long-term depression (LTP/LTD) [J]. Cold Spring Harbor Perspectives in Biology, 2012, 4(6): a005710. DOI:10.1101/cshperspect. a005710.

[8] LaFerla F M, Oddo S. Alzheimer’s disease: Aβ, tau and synaptic dysfunction [J]. Trends in Molecular Medicine, 2005, 11(4): 170–176. DOI: 10.1016/j.molmed.2005.02.009.

[9] Cheng Y, Bai F. The association of tau with mitochondrial dysfunction in Alzheimer’s disease [J]. Frontiers in Neuroscience, 2018, 12: 163. DOI:10.3389/fnins.2018.00163.

[10] Rajendran L, Paolicelli R C. Microglia-mediated synapse loss in Alzheimer’s disease [J]. Journal of Neuroscience, 2018, 38(12): 2911–2919. DOI:10.1523/jneurosci.1136-17.2017.

[11] Xu L, He D, Bai Y. Microglia-mediated inflammation and neurodegenerative disease [J]. Molecular Neurobiology, 2016, 53(10): 6709–6715. DOI:10.1007/s12035-015-9593-4.

[12] Megill A, Tran T, Eldred K, Lee N J, Wong P C, Hoe H S, Kirkwood A, Lee H K. Defective age-dependent metaplasticity in a mouse model of Alzheimer’s disease [J]. Journal of Neuroscience, 2015, 35(32): 11346–11357. DOI:10.1523/ jneurosci.5289-14.2015.

[13] Uhlhaas P J, Singer W. Neural synchrony in brain disorders: relevance for cognitive dysfunctions and pathophysiology [J]. Neuron, 2006, 52(1): 155–168. DOI: 10.1016/ j.neuron.2006.09.020.

[14] Palmqvist S, Schöll M, Strandberg O, Mattsson N, Stomrud E, Zetterberg H, Blennow K, Landau S, Jagust W, Hansson O. Earliest accumulation of β-amyloid occurs within the defaultmode network and concurrently affects brain connectivity [J]. Nature Communications, 2017, 8(1): 1214. DOI:10.1038/ s41467-017-01150-x.

[15] Li M, Long C, Yang L. Hippocampal-prefrontal circuit and disrupted functional connectivity in psychiatric and neurodegenerative disorders [J]. BioMed Research International, 2015, 2015: 810548. DOI:10.1155/2015/810548.

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Published

2025-12-19