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Wavelet coherence model for diagnosis of Alzheimer disease
Sankari Z, Adeli H, Adeli A.. Clinical EEG and neuroscience, 2012-05-10
Topic: Amyloid, tau and blood-test diagnosis
This article presents a wavelet coherence investigation of electroencephalograph (EEG) readings acquired from patients with Alzheimer disease (AD) and healthy controls. Pairwise electrode wavelet coherence is calculated over each frequency band (delta, theta, alpha, and beta). For comparing the synchronization fraction of 2 EEG signals, a wavelet coherence fraction is proposed which is defined as the fraction of the signal time during which the wavelet coherence value is above a certain threshold. A one-way analysis of variance test shows a set of statistically significant differences in wavelet coherence between AD and controls. The wavelet coherence method is effective for studying cortical connectivity at a high temporal resolution. Compared with other conventional AD coherence studies, this study takes into account the time-frequency changes in coherence of EEG signals and thus provides more correlational details. A set of statistically significant differences was found in the wavelet coherence among AD and controls. In particular, temporocentral regions show a significant decrease in wavelet coherence in AD in the delta band, and the parietal and central regions show significant declines in cortical connectivity with most of their neighbors in the theta and alpha bands. This research shows that wavelet coherence can be used as a powerful tool to differentiate between healthy elderly individuals and probable AD patients.
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
APA 7th
Sankari, Z., Adeli, H., & Adeli, A. (2012). Wavelet coherence model for diagnosis of Alzheimer disease. Clinical EEG and neuroscience. https://doi.org/10.1177/1550059412444970
Vancouver
Sankari Z, Adeli H, Adeli A. Wavelet coherence model for diagnosis of Alzheimer disease. Clinical EEG and neuroscience. 2012. doi:10.1177/1550059412444970. PMID: 22715491.
BibTeX
@article{sankari2012-22715491,
author = {Sankari, Z. and Adeli, H. and Adeli, A.},
title = {{Wavelet coherence model for diagnosis of Alzheimer disease}},
journal = {Clinical EEG and neuroscience},
year = {2012},
doi = {10.1177/1550059412444970},
pmid = {22715491},
url = {https://doi.org/10.1177/1550059412444970}
}
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Key findings
- A one-way analysis of variance test shows a set of statistically significant differences in wavelet coherence between AD and controls.
- Compared with other conventional AD coherence studies, this study takes into account the time-frequency changes in coherence of EEG signals and thus provides more correlational details.
- A set of statistically significant differences was found in the wavelet coherence among AD and controls.
- In particular, temporocentral regions show a significant decrease in wavelet coherence in AD in the delta band, and the parietal and central regions show significant declines in cortical connectivity with most of their neighbors in the theta and alpha bands.
Why it matters
Wavelet coherence analysis of EEG signals showed statistically significant differences between Alzheimer's disease patients and controls, with decreased coherence in temporocentral regions in the delta band and in parietal and central regions in the theta and alpha bands. This method can differentiate between healthy controls and Alzheimer's disease patients by studying cortical connectivity.
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Study details
- Evidence strengthLow
How this study scored 42/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Clinical EEG and neuroscience) |
| Journal's citation record | 0 / 4 | Clinical EEG and Neuroscience: journal h-index 68 (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 | 3 / 3 | Studied in people (pubmed indexes it as a clinical or observational study) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 5 / 7 | Cited 134 times (OpenAlex, 2026-10-10) |
| Citations per year | 3 / 5 | 8.4 citations a year over 16 year(s) since 2012 |
| Impact for its field and year | 3 / 6 | Cited 7.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 1 other studies in this library |
| Still being cited | 1 / 4 | Cited 14 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Anahita Adeli: h-index 38 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Mayo Clinic: institution h-index 1,606 (OpenAlex) |
| Multi-centre collaboration | 1 / 3 | OpenAlex lists 2 institution(s) in 1 country |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 22715491) |
| Free to read | 0 / 2 | Behind a paywall — scores zero |
| Total | 42 / 100 | — |
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