Imaging of brain electric field networks with spatially resolved EEG
We present a method for spatially resolving the electric field potential throughout the entire volume of the human brain from electroencephalography (EEG) data. The method is not a variation of the well-known ‘source reconstruction’ methods, but rather a direct solution to the EEG inverse problem based on our recently developed model for brain waves that demonstrates the inadequacy of the standard ‘quasi-static approximation’ that has fostered the belief that such a reconstruction is not physically possible. The method retains the high temporal/frequency resolution of EEG, yet has spatial resolution comparable to (or better than) functional MRI (fMRI), without its significant inherent limitations. The method is validated using simultaneous EEG/fMRI data in healthy subjects, intracranial EEG data in epilepsy patients, comparison with numerical simulations, and a direct comparison with standard state-of-the-art EEG analysis in a well-established attention paradigm. The method is then demonstrated on a very large cohort of subjects performing a standard gambling task designed to activate the brain’s ‘reward circuit’. The technique uses the output from standard extant EEG systems and thus has potential for immediate benefit to a broad range of important basic scientific and clinical questions concerning brain electrical activity. By offering an inexpensive and portable alternative to fMRI, it provides a realistic methodology to efficiently promote the democratization of medicine.
Authors
- Stephan Bickel (ORCID: https://orcid.org/0000-0001-5265-2447)
- Antı́gona Martı́nez (ORCID: https://orcid.org/0000-0003-4806-5199)
- Olave E. Krigolson (ORCID: https://orcid.org/0000-0002-9053-908X)
- Susan Frances Tapert (ORCID: https://orcid.org/0000-0001-7259-6112)
- V. L. Galinsky (ORCID: https://orcid.org/0000-0003-0420-6834)
- Lawrence R. Frank (ORCID: https://orcid.org/0000-0001-7235-587X)
Institutions
- Nathan Kline Institute for Psychiatric Research (US)
- Feinstein Institute for Medical Research (US)
- University of Victoria (CA)
- University of California San Diego (US)
Publication Details
- Journal
- eLife
- Published
- 2025-05-23
- DOI
- https://doi.org/10.7554/elife.100123.3
- Primary Topic
- Neural dynamics and brain function
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Simons Foundation Autism Research Initiative
- National Institutes of Health
- Natural Sciences and Engineering Research Council of Canada
- National Institute on Deafness and Other Communication Disorders