Three-Dimensional Imaging of Complex Neural Activation in Humans From EEG
Open accessAbstract
Electro- or magnetoencephalography (EEG/MEG) are of utmost advantage in studying transient neuronal activity and its timing with respect to behavior in the working human brain. Direct localization of the neural substrates underlying EEG/MEG is commonly achieved by modeling neuronal activity as dipoles. However, the success of neural source localization with the dipole model has only been demonstrated in relatively simple localization tasks owing to the simplified model and its insufficiency in differentiating cortical sources with different extents. It would be of great interest to image complex neural activation with multiple sources of different cortical extensions directly from EEG/MEG. We have investigated this crucial issue by adding additional parameters to the dipole model, leading to the multipole model to better represent the extended sources confined to the convoluted cortical surface. The localization of multiple cortical sources is achieved by using the subspace source localization method with the multipole model. Its performance is evaluated with simulated data as compared with the dipole model, and further illustrated with the real data obtained during visual stimulations in human subjects. The interpretation of the localization results is fully supported by our knowledge about their anatomic locations and functional magnetic resonance imaging data in the same experimental setting. Methods for estimating multiple neuronal sources at cortical areas will facilitate our ability to characterize the cortical electrical activity from simple, early sensory components to more complex networks, such as in visual, motor, and cognitive tasks.
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For far-field measurements like EEG/MEG, a pair of current monopoles can be represented as a current dipole.
“For far-field measurements like EEG/MEG, such a pair of current monopoles can be represented as a current dipole.”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [12]
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Electrophysiological source imaging: A noninvasive window to brain dynamics
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Self-citation
- Authors
- Ding, L., Zhang, N., Chen, W., & He, B.
- Affiliations
- University of Minnesota (US)
- Corresponding author
- He, Bin
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2009-08
- Volume
- 56
- Issue
- 8
- Pages
- 1980-1988
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- PMC
- PMC2811716
- OpenAlex
- W2110491212
- Cited by
- 4
- References
- 34
- Citations by year
- 2018: 1 · 2016: 1 · 2015: 1 · 2012: 1
- FWCI
- 0.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- IEEE Transactions on Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship@UMassChan (submittedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke (P30NS057091)
- National Institute of Biomedical Imaging and Bioengineering (R01EB000178, R01EB007920)
- National Center for Research Resources (P41RR008079)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Computer Science › Signal Processing › Direction-of-Arrival Estimation Techniques
- Keywords
- multipole model, neural source localization, dipole model, visual stimulation, EEG, MEG, cortical electrical activity
- MeSH terms
- Algorithms, Brain, Brain Mapping, Electroencephalography, Evoked Potentials, Visual, Female, Humans, Magnetic Resonance Imaging, Male, Models, Neurological, Visual Cortex, Imaging, Three-Dimensional
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