The DOI matches its Crossref record; 216 of the 217 references it cites were found in a registry or an index.
Multimodal Functional Neuroimaging: Integrating Functional MRI and EEG/MEG
Open accessAbstract
Noninvasive functional neuroimaging, as an important tool for basic neuroscience research and clinical diagnosis, continues to face the need of improving the spatial and temporal resolution. While existing neuroimaging modalities might approach their limits in imaging capability mostly due to fundamental as well as technical reasons, it becomes increasingly attractive to integrate multiple complementary modalities in an attempt to significantly enhance the spatiotemporal resolution that cannot be achieved by any modality individually. Electrophysiological and hemodynamic/metabolic signals reflect distinct but closely coupled aspects of the underlying neural activity. Combining fMRI and EEG/MEG data allows us to study brain function from different perspectives. In this review, we start with an overview of the physiological origins of EEG/MEG and fMRI, as well as their fundamental biophysics and imaging principles, we proceed with a review of the major advances in the understanding and modeling of neurovascular coupling and in the methodologies for the fMRI-EEG/MEG simultaneous recording. Finally, we summarize important remaining issues and perspectives concerning multimodal functional neuroimaging, including brain connectivity imaging.
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“Their complementary strengths and limitations have motivated researchers to integrate EEG/MEG and fMRI towards a multimodal imaging tool that is more powerful than each of them alone (115–117).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [115]
In the citing paper
“When fMRI is utilized to help solve the EEG/MEG inverse problem (i.e. fMRI-constrained EEG/MEG ESI), the solution benefits from the spatial precision and resolution of fMRI while inheriting the intrinsic temporal resolution from EEG/MEG (115, 117).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [115]
In the citing paper
“It is feasible to model the relationship between fMRI and EEG/MEG given relatively simple stimuli that repeat as discrete events and/or in alternating blocks (115).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [115]
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Citations
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Items 201–216 of 216
Integration of EEG/MEG with MRI and fMRI in Functional Neuroimaging
Liu, Z., Ding, L., & He, B. (2006) · Europe PMC (PubMed Central) · Cited by 33
Self-citationNoninvasive Study of Neurovascular Coupling during Graded Neuronal Suppression
Zhang, N., Liu, Z., He, B., & Chen, W. (2007) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600531 · Cited by 30
Self-citationArthurs, O. J., Donovan, T., Spiegelhalter, D. J., Pickard, J. D., & Boniface, S. J. (2006) · Cerebral Cortex · doi:10.1093/cercor/bhk014 · Cited by 30
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Functional cortical source imaging from simultaneously recorded ERP and fMRI
Im, C., Liu, Z., Zhang, N., Chen, W., & He, B. (2006) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2006.03.015 · Cited by 25
Self-citationA modified electrode cap for EEG recordings in MRI scanners
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Self-citationHigh-resolution intersubject averaging and a coordinate system for the cortical surface
Fischl, B., Sereno, M. I., Tootell, R. B. H., & Dale, A. M. (1999) · Human Brain Mapping · doi:10.1002/(sici)1097-0193(1999)8:4
Flagged first, then by citations
1 of the 217 references couldn’t be matched to a known paper.
Research works printed but not linked: 2
- liu, 2008, Multimodal Functional Neuroimaging Integrating Functional Magnetic Resonance Imaging and Electroencephalography
- 2004, Modeling and Imaing of Bioelectrical Activity Principles and Applications
Cited by
Sorted by citations
Brain-computer interfaces for communication and control
McFarland, D. J., & Wolpaw, J. R. (2011) · Communications of the ACM · doi:10.1145/1941487.1941506 · Cited by 541
Brain–Computer Interfaces Using Sensorimotor Rhythms: Current State and Future Perspectives
Yuan, H., & He, B. (2014) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2014.2312397 · Cited by 508
Self-citationElectrophysiological source imaging: A noninvasive window to brain dynamics
He, B., Sohrabpour, A., Brown, E., & Liu, Z. (2018) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-062117-120853 · Cited by 297
Self-citationElectrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities
He, B., Yang, L., Wilke, C., & Yuan, H. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2139210 · Cited by 300
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Self-citation
Metadata
- Authors
- He, B., & Liu, Z.
- Affiliations
- University of Minnesota (US)
- Corresponding author
- He, Bin
- Venue
- IEEE Reviews in Biomedical Engineering
- Published
- 2008
- Volume
- 1
- Pages
- 23-40
- ISSN
- 1937-3333 (ISSN-L)
- 1941-1189
- PMC
- PMC2903760
- OpenAlex
- W2128390591
- Cited by
- 171
- References
- 217
- Citations by year
- 2026: 9 · 2025: 19 · 2024: 15 · 2023: 7 · 2022: 12 · 2021: 5 · 2020: 6 · 2019: 10 · 2018: 15 · 2017: 4 · 2016: 7 · 2015: 13 · 2014: 19 · 2013: 6 · 2012: 5
- FWCI
- 0.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- Locations
- IEEE Reviews in Biomedical Engineering (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Biomedical Imaging and Bioengineering (R01-EB-00178, R01EB000178, R01EB007920)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- simultaneous recording, spatiotemporal resolution, neurovascular coupling, hemodynamic response, electrophysiological signals
- MeSH terms
- Animals, Brain, Brain Mapping, Electroencephalography, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging
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