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Disruption of functional brain networks in Alzheimer's disease: what can we learn from graph spectral analysis of resting-state magnetoencephalography?
de Haan W, van der Flier WM, Wang H, Van Mieghem PF, Scheltens P, Stam CJ.. Brain connectivity, 2012-06-11
Topic: Amyloid, tau and blood-test diagnosis
In Alzheimer's disease (AD), structural and functional brain network organization is disturbed. However, many of the present network analysis measures require a priori assumptions and methodological choices that influence outcomes and interpretations. Graph spectral analysis (GSA) is a more direct algebraic method that describes network properties, which might lead to more reliable results. In this study, GSA was applied to magnetoencephalography (MEG) data to explore functional network integrity in AD. Sensor-level resting-state MEG was performed in 18 Alzheimer patients (age 67 ± 9, 6 women) and 18 healthy controls (age 66 ± 9, 11 women). Weighted, undirected graphs were constructed based on functional connectivity analysis using the Synchronization likelihood, and GSA was performed with a focus on network connectivity, synchronizability, and node centrality. The main outcomes were a global loss of network connectivity and altered synchronizability in most frequency bands. Eigenvector centrality mapping confirmed the hub status of the parietal areas, and demonstrated a low centrality of the left temporal region in the theta band in AD patients that was strongly related to the mini mental state examination (global cognitive function test) score (r=0.67, p=0.001). Summarizing, GSA is a theoretically solid approach that is able to detect the disruption of functional network topology in AD. In addition to the previously reported overall connectivity losses and parietal area hub status, impaired network synchronizability and a clinically relevant left temporal centrality loss were found in AD patients. Our findings imply that GSA is valuable for the purpose of studying altered brain network topology and dynamics in AD.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
de Haan, W., van der Flier, W. M., Wang, H., Van Mieghem, P. F., Scheltens, P., & Stam, C. J. (2012). Disruption of functional brain networks in Alzheimer's disease: what can we learn from graph spectral analysis of resting-state magnetoencephalography? Brain connectivity. https://doi.org/10.1089/brain.2011.0043
Vancouver
de Haan W, van der Flier WM, Wang H, Van Mieghem PF, Scheltens P, Stam CJ. Disruption of functional brain networks in Alzheimer's disease: what can we learn from graph spectral analysis of resting-state magnetoencephalography? Brain connectivity. 2012. doi:10.1089/brain.2011.0043. PMID: 22480296.
BibTeX
@article{dehaan2012-22480296,
author = {de Haan, W. and van der Flier, W. M. and Wang, H. and Van Mieghem, P. F. and Scheltens, P. and Stam, C. J.},
title = {{Disruption of functional brain networks in Alzheimer's disease: what can we learn from graph spectral analysis of resting-state magnetoencephalography?}},
journal = {Brain connectivity},
year = {2012},
doi = {10.1089/brain.2011.0043},
pmid = {22480296},
url = {https://doi.org/10.1089/brain.2011.0043}
}
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. Check the citation against the original before you use it.
Key findings
- Graph spectral analysis (GSA) is a more direct algebraic method that describes network properties, which might lead to more reliable results.
- Eigenvector centrality mapping confirmed the hub status of the parietal areas, and demonstrated a low centrality of the left temporal region in the theta band in AD patients that was strongly related to the mini mental state examination (global cognitive function test) score (r=0.67, p=0.001).
- In addition to the previously reported overall connectivity losses and parietal area hub status, impaired network synchronizability and a clinically relevant left temporal centrality loss were found in AD patients.
- Our findings imply that GSA is valuable for the purpose of studying altered brain network topology and dynamics in AD.
Why it matters
This small study used magnetoencephalography and graph spectral analysis to detect disrupted functional brain networks in people who already had Alzheimer's disease. It is a technical method for measuring network changes, not a treatment, cure, or prevention for Alzheimer's disease.
New to this subject? Start with our plain-English guide: Brain scans & tests →
Study details
- Evidence strengthLow
How this study scored 40/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomized / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Brain connectivity) |
| Journal's citation record | 1 / 4 | Brain Connectivity: journal h-index 83 (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 | 1 / 5 | Rated “low” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 1 / 5 | 2012 — within 20 year(s) of the newest study here |
| Sample size | 0 / 4 | Participant count not stated — scores zero (not stated in the record — scored 0) |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 0 / 3 | Not stated whether this was studied in people — scores zero (not stated in the record — scored 0) |
| Randomized / blinded | 0 / 2 | No randomization or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 4 / 7 | Cited 95 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 5.9 citations a year over 16 year(s) since 2012 |
| Impact for its field and year | 3 / 6 | Cited 3.7× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 2 / 6 | Cited by 3 other studies in this library |
| Still being cited | 1 / 4 | Cited 9 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 4 / 4 | Last-listed author Cornelis J. Stam: h-index 108 (OpenAlex, whole career) |
| Institution's track record | 1 / 3 | Amsterdam UMC Location Vrije Universiteit Amsterdam: institution h-index 938 (OpenAlex) |
| Multicenter collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 22480296) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 40 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1089/brain.2011.0043
- PubMed: 22480296
- Original source →
- Free full text: Pure Amsterdam UMC →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
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