Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2508.18712 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866918280451588096 |
|---|---|
| author | Yaser, Samin Ali, Mahad Jiang, Yang Nguyen, Phuc Xiang, Jing Brattain, Laura J. |
| author_facet | Yaser, Samin Ali, Mahad Jiang, Yang Nguyen, Phuc Xiang, Jing Brattain, Laura J. |
| contents | High Frequency Oscillations (HFOs), rapid bursts of brain activity above 80 Hz, have emerged as a highly specific biomarker for epileptogenic tissue. Recent evidence suggests that HFOs are also present in Alzheimer's Disease (AD), reflecting underlying network hyperexcitability and offering a promising, noninvasive tool for early diagnosis and disease tracking. This synoptic review provides a comprehensive analysis of publicly available electroencephalography (EEG) datasets relevant to HFO research in neurodegenerative disorders. We conducted a bibliometric analysis of 1,222 articles, revealing a significant and growing research interest in HFOs, particularly within the last ten years. We then systematically profile and compare key public datasets, evaluating their participant cohorts, data acquisition parameters, and accessibility, with a specific focus on their technical suitability for HFO analysis. Our comparative synthesis highlights critical methodological heterogeneity across datasets, particularly in sampling frequency and recording paradigms, which poses challenges for cross-study validation, but also offers opportunities for robustness testing. By consolidating disparate information, clarifying nomenclature, and providing a detailed methodological framework, this review serves as a guide for researchers aiming to leverage public data to advance the role of HFOs as a cross-disease biomarker for AD and related conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_18712 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Synoptic Review of High-Frequency Oscillations as a Biomarker in Neurodegenerative Disease Yaser, Samin Ali, Mahad Jiang, Yang Nguyen, Phuc Xiang, Jing Brattain, Laura J. Signal Processing High Frequency Oscillations (HFOs), rapid bursts of brain activity above 80 Hz, have emerged as a highly specific biomarker for epileptogenic tissue. Recent evidence suggests that HFOs are also present in Alzheimer's Disease (AD), reflecting underlying network hyperexcitability and offering a promising, noninvasive tool for early diagnosis and disease tracking. This synoptic review provides a comprehensive analysis of publicly available electroencephalography (EEG) datasets relevant to HFO research in neurodegenerative disorders. We conducted a bibliometric analysis of 1,222 articles, revealing a significant and growing research interest in HFOs, particularly within the last ten years. We then systematically profile and compare key public datasets, evaluating their participant cohorts, data acquisition parameters, and accessibility, with a specific focus on their technical suitability for HFO analysis. Our comparative synthesis highlights critical methodological heterogeneity across datasets, particularly in sampling frequency and recording paradigms, which poses challenges for cross-study validation, but also offers opportunities for robustness testing. By consolidating disparate information, clarifying nomenclature, and providing a detailed methodological framework, this review serves as a guide for researchers aiming to leverage public data to advance the role of HFOs as a cross-disease biomarker for AD and related conditions. |
| title | A Synoptic Review of High-Frequency Oscillations as a Biomarker in Neurodegenerative Disease |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2508.18712 |