Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer's disease assessment
Quantitative EEG has been shown to reflect neurodegenerative processes in Alzheimer's disease (AD) and may provide non-invasive and widely available biomarkers to enhance the objectivization of disease assessment. To address EEG's major drawback - its low spatial resolution - many studies have employed 3D source localization. However, none have investigated whether this complex mapping into 3D space actually adds value over standard surface derivation. In fact, we found no prior study - in any disease - that quantitatively compared the results of a 3D source localization method with those achieved by surface derivation. We analyzed data from one of the largest prospective AD EEG studies ever conducted (four study centers, 188 patients, 100 female). Thousands of distinct quantitative EEG markers of slowing, complexity, and functional connectivity were computed and regressed against disease severity, with rigorous control for multiple testing. We found highly significant associations between quantitative EEG markers and disease severity. However, standardized low-resolution electromagnetic tomography (sLORETA), a widely used 3D source localization method, did not improve results. Furthermore, a surface derivation marker (auto-mutual information of the left hemisphere during the eyes-closed condition) was the best performing marker across our entire sample. While our findings strongly support that quantitative EEG markers reflect neurodegenerative processes in AD, they do not demonstrate additional benefit from sLORETA. Importantly, our results are specific to AD and sLORETA. Therefore, they should not be generalized to other neurological or psychiatric disorders or to other 3D source localization methods without further validation. Finally, these findings do not diminish the value of 3D source localization for visual EEG inspection.
Authors
- Wolfgang Frühwirt
- Gerhard Ransmayr (ORCID: https://orcid.org/0000-0001-9982-1420)
- Peter Dal‐Bianco
- Andreas Hahn (ORCID: https://orcid.org/0000-0003-0235-5211)
- Martin Mairhofer
- Dieter Grossegger
- Heinrich Garn
- Reinhold Schmidt (ORCID: https://orcid.org/0000-0002-6406-7584)
- Markus Waser (ORCID: https://orcid.org/0000-0002-8964-4675)
- Thomas Benke (ORCID: https://orcid.org/0000-0001-8052-7758)
- Georg Dorffner (ORCID: https://orcid.org/0000-0002-3181-2576)
- Stephen Roberts (ORCID: https://orcid.org/0000-0002-9305-9268)
Institutions
- AIT Austrian Institute of Technology GmbH (AT)
- Innsbruck Medical University (AT)
- Austrian Research Institute for Artificial Intelligence (AT)
- Universität Innsbruck (AT)
- Medical University of Graz (AT)
- Oxford Research Group (GB)
- University of Oxford (GB)
- Kepler Universitätsklinikum (AT)
- Medical University of Vienna (AT)
Publication Details
- Journal
- NeuroImage
- Published
- 2025-03-14
- DOI
- https://doi.org/10.1016/j.neuroimage.2025.121144
- Citations
- 3
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 2.86
Funders
- Österreichische Forschungsförderungsgesellschaft