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Evaluating EEG complexity and spectral signatures in Alzheimer’s disease and frontotemporal dementia: evidence for rostrocaudal asymmetry
Kassra Ghassemkhani, Kevin S. Saroka, Blake T. Dotta. npj Aging, 2025-06-09
Topic: Amyloid, tau and blood-test diagnosis
Accurate classification of neurodegenerative disorders remains a challenge in neuroscience. Using open-source electroencephalography (EEG) data, we investigated electrophysiological signatures to differentiate frontotemporal dementia (FTD) from Alzheimer's disease (AD) via complexity measures. Traditional relative band power analysis showed consistent increases in lower-frequency activity but did not distinguish the two disorders after correction. In contrast, fractal dimension and long-range temporal correlations (LRTCs) revealed distinct topographical differences: AD exhibited rostral dominance in fractal dimension, whereas FTD showed caudal dominance. Both disorders demonstrated reduced LRTCs, particularly in caudal regions, indicating disrupted large-scale neural dynamics. These findings suggest that complexity-based EEG features may offer a reliable, cost-effective tool for distinguishing neurodegenerative conditions, complementing traditional neuroimaging approaches.
Key findings
- In contrast, fractal dimension and long-range temporal correlations (LRTCs) revealed distinct topographical differences: AD exhibited rostral dominance in fractal dimension, whereas FTD showed caudal dominance.
- Both disorders demonstrated reduced LRTCs, particularly in caudal regions, indicating disrupted large-scale neural dynamics.
- These findings suggest that complexity-based EEG features may offer a reliable, cost-effective tool for distinguishing neurodegenerative conditions, complementing traditional neuroimaging approaches.
Why it matters
Complexity-based EEG features revealed distinct topographical differences between Alzheimer's disease and frontotemporal dementia, with AD exhibiting rostral dominance and FTD showing caudal dominance in fractal dimension. These findings suggest complexity-based EEG features may offer a reliable, cost-effective tool for distinguishing neurodegenerative conditions, complementing traditional neuroimaging.
Study details
- Evidence strengthLow
How this study scored 39/100
Published in a peer-reviewed journal. Scored zero for study design, sample size, effect reported, studied in people and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (npj Aging) |
| Journal's citation record | 0 / 4 | Npj Aging: journal h-index 31 (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 | 4 / 5 | 2025 — within 3 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) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 3 / 7 | Cited 17 times (OpenAlex, 2026-10-10) |
| Citations per year | 2 / 5 | 5.7 citations a year over 3 year(s) since 2025 |
| Impact for its field and year | 4 / 6 | Cited 10.8× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 1 / 6 | Cited by 2 other studies in this library |
| Still being cited | 2 / 4 | Cited 17 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 1 / 4 | Last-listed author Blake T. Dotta: h-index 16 (OpenAlex, whole career) |
| Institution's track record | 0 / 3 | Laurentian University: institution h-index 277 (OpenAlex) |
| Multi-centre collaboration | 0 / 3 | OpenAlex lists 1 institution(s) in 1 country — scores zero (affiliation lists can be incomplete) |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 40490479) |
| Free to read | 2 / 2 | Free to read |
| Total | 39 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
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Cite this study APA, Vancouver, BibTeX · download .bib or .ris
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APA 7th
Ghassemkhani, K., Saroka, K. S., & Dotta, B. T. (2025). Evaluating EEG complexity and spectral signatures in Alzheimer’s disease and frontotemporal dementia: evidence for rostrocaudal asymmetry. npj Aging. https://doi.org/10.1038/s41514-025-00243-y
Vancouver
Ghassemkhani K, Saroka KS, Dotta BT. Evaluating EEG complexity and spectral signatures in Alzheimer’s disease and frontotemporal dementia: evidence for rostrocaudal asymmetry. npj Aging. 2025. doi:10.1038/s41514-025-00243-y. PMID: 40490479.
BibTeX
@article{ghassemkhani2025-40490479,
author = {Ghassemkhani, Kassra and Saroka, Kevin S. and Dotta, Blake T.},
title = {{Evaluating EEG complexity and spectral signatures in Alzheimer’s disease and frontotemporal dementia: evidence for rostrocaudal asymmetry}},
journal = {npj Aging},
year = {2025},
doi = {10.1038/s41514-025-00243-y},
pmid = {40490479},
url = {https://doi.org/10.1038/s41514-025-00243-y}
}
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