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Personalized brain models link cognitive decline progression to underlying synaptic and connectivity degeneration
Lorenzo Gaetano Amato, Alberto Arturo Vergani, Michael Lassi, Jacopo Carpaneto, Salvatore Mazzeo, Valentina Moschini, Rachele Burali, Giovanni Salvestrini et al.. Alzheimer s Research & Therapy, 2025-04-05
Topic: Brain proteins, microglia and lab models
Cognitive decline is a condition affecting almost one sixth of the elder population and is widely regarded as one of the first manifestations of Alzheimer's disease. Despite the extensive body of knowledge on the condition, there is no clear consensus on the structural defects and neurodegeneration processes determining cognitive decline evolution. Here, we introduce a Brain Network Model (BNM) simulating the effects of neurodegeneration on neural activity during cognitive processing. The model incorporates two key parameters accounting for distinct pathological mechanisms: synaptic degeneration, primarily leading to hyperexcitation, and brain disconnection. Through parameter optimization, we successfully replicated individual electroencephalography (EEG) responses recorded during task execution from 145 participants spanning different stages of cognitive decline. The cohort included healthy controls, patients with subjective cognitive decline (SCD), and those with mild cognitive impairment (MCI) of the Alzheimer type. Through model inversion, we generated personalized BNMs for each participant based on individual EEG recordings. These models revealed distinct network configurations corresponding to the patient's cognitive condition, with virtual neurodegeneration levels directly proportional to the severity of cognitive decline. Strikingly, the model uncovered a neurodegeneration-driven phase transition leading to two distinct regimes of neural activity underlying task execution. On either side of this phase transition, increasing synaptic degeneration induced changes in neural activity that closely mirrored experimental observations across cognitive decline stages. This enabled the model to directly link synaptic degeneration and hyperexcitation to cognitive decline severity. Furthermore, the model pinpointed posterior cingulum fiber degeneration as the structural driver of this phase transition. Our findings highlight the potential of BNMs to account for the evolution of neural activity across stages of cognitive decline while elucidating the underlying neurodegenerative mechanisms. This approach provides a novel framework for understanding how structural and functional brain alterations contribute to cognitive deterioration along the Alzheimer's continuum.
Key findings
- These models revealed distinct network configurations corresponding to the patient's cognitive condition, with virtual neurodegeneration levels directly proportional to the severity of cognitive decline.
- Our findings highlight the potential of BNMs to account for the evolution of neural activity across stages of cognitive decline while elucidating the underlying neurodegenerative mechanisms.
Why it matters
This study used personalized brain network models based on EEG recordings from 145 participants to link cognitive decline progression to synaptic degeneration and brain disconnection. The models revealed distinct network configurations corresponding to each patient's cognitive condition, with virtual neurodegeneration levels proportional to the severity of cognitive decline.
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Study details
- Participants145
- Evidence strengthModerate
How this study scored 43/100
Published in a peer-reviewed journal. Scored zero for study design, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Alzheimer s Research & Therapy) |
| Journal's citation record | 1 / 4 | Alzheimer s Research & Therapy: journal h-index 146 (OpenAlex, 2026-10-29) |
| Study design | 0 / 12 | No study design recorded — scores zero, not guessed (not stated in the record — scored 0) |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 4 / 5 | 2025 — within 3 year(s) of the newest study here |
| Sample size | 2 / 4 | 145 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 4 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.3 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 2 / 6 | Cited 2.5× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 4 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Alberto Mazzoni: h-index 33 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Vita-Salute San Raffaele University: institution h-index 542 (OpenAlex) |
| Multi-centre collaboration | 2 / 3 | OpenAlex lists 5 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40188185) |
| Free to read | 2 / 2 | Free to read |
| Total | 43 / 100 | — |
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Read the original
- DOI: 10.1186/s13195-025-01718-6
- PubMed: 40188185
- Original source →
- Free full text: Alzheimer s Research & Therapy →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Amato, L. G., Vergani, A. A., Lassi, M., Carpaneto, J., Mazzeo, S., Moschini, V., et al. (2025). Personalized brain models link cognitive decline progression to underlying synaptic and connectivity degeneration. Alzheimer s Research & Therapy. https://doi.org/10.1186/s13195-025-01718-6
Vancouver
Amato LG, Vergani AA, Lassi M, Carpaneto J, Mazzeo S, Moschini V, et al. Personalized brain models link cognitive decline progression to underlying synaptic and connectivity degeneration. Alzheimer s Research & Therapy. 2025. doi:10.1186/s13195-025-01718-6. PMID: 40188185.
BibTeX
@article{amato2025-40188185,
author = {Amato, Lorenzo Gaetano and Vergani, Alberto Arturo and Lassi, Michael and Carpaneto, Jacopo and Mazzeo, Salvatore and Moschini, Valentina and Burali, Rachele and Salvestrini, Giovanni and others},
title = {{Personalized brain models link cognitive decline progression to underlying synaptic and connectivity degeneration}},
journal = {Alzheimer s Research \& Therapy},
year = {2025},
doi = {10.1186/s13195-025-01718-6},
pmid = {40188185},
url = {https://doi.org/10.1186/s13195-025-01718-6}
}
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