On the Relationship of Synaptic Activity to Macroscopic Measurements: Does Co-Registration of EEG with fMRI Make Sense?
Abstract
A two-scale theoretical description outlines relationships between brain current sources and the resulting extracranial electric field, recorded as EEG. Finding unknown sources of EEG, the so-called "inverse problem", is discussed in general terms, with emphasis on the fundamental non-uniqueness of inverse solutions. Hemodynamic signatures, measured with fMRI, are expressed as voxel integrals to facilitate comparisons with EEG. Two generally distinct cell groups (1 and 2), generating EEG and fMRI signals respectively, are embedded within the much broader class of synaptic action fields. Cell groups 1 and 2 may or may not overlap in specific experiments. Implications of this incomplete overlap for co-registration studies are considered. Each experimental measure of brain function is generally sensitive to a different kind of source activity and to different spatial and temporal scales. Failure to appreciate such distinctions can exacerbate conflicting views of brain function that emphasize either global integration or functional localization.
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fMRI and EEG signals largely share a common origin in cortical synaptic activity, but reflect its distribution and dynamics at different spatial and temporal scales with distinct sensitivity, resolution, and specificity.
“Given these findings, it is reasonable to state that fMRI and EEG signals, to a large extent, share a common origin of cortical synaptic activity, but reflect its distribution and dynamics in highly different spatial and temporal scales with distinctive sensitivity, resolution, and specificity (141).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [141]
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- Authors
- Nunez, P. L., & Silberstein, R. B.
- Affiliations
- Tulane University (US)
- Corresponding author
- Nunez, Paul L.
- ORCID
- Nunez, Paul L.
- Venue
- Brain Topography
- Published
- 2000-12
- Volume
- 13
- Issue
- 2
- Pages
- 79-96
- ISSN
- 0896-0267 (ISSN-L)
- 1573-6792
- OpenAlex
- W2146533369
- Cited by
- 307
- References
- 62
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 5 · 2023: 3 · 2022: 6 · 2021: 8 · 2020: 8 · 2019: 4 · 2018: 12 · 2017: 10 · 2016: 12 · 2015: 9 · 2014: 14 · 2013: 17 · 2012: 18
- FWCI
- 4.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Brain Topography (publishedVersion)
- PubMed (publishedVersion)
- Swinburne figshare (Swinburne University of Technology) (submittedVersion)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Optical Imaging and Spectroscopy Techniques
- Keywords
- EEG inverse problem
- MeSH terms
- Brain, Electroencephalography, Humans, Magnetic Resonance Imaging, Models, Neurological, Synapses, Tomography, Emission-Computed, Magnetoencephalography
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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