Electrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities
Open accessAbstract
Unlocking the dynamic inner workings of the brain continues to remain a grand challenge of the 21st century. To this end, functional neuroimaging modalities represent an outstanding approach to better understand the mechanisms of both normal and abnormal brain functions. The ability to image brain function with ever increasing spatial and temporal resolution has made a significant leap over the past several decades. Further delineation of functional networks could lead to improved understanding of brain function in both normal and diseased states. This paper reviews recent advancements and current challenges in dynamic functional neuroimaging techniques, including electrophysiological source imaging, multimodal neuroimaging integrating fMRI with EEG/MEG, and functional connectivity imaging.
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Electrophysiological source imaging can help to understand and disentangle functional segregation and integration processes.
“ESI can help to understand and disentangle these processes (6).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [6]
Electrophysiological source imaging allows mapping functional and effective connectivity in source space, a notion of the electrophysiological connectome (eConnectome).
“ESI allows to map functional/effective connectivity in source space – a notion of the electrophysiological connectome (eConnectome) (6, 97).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [6]
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Self-citation
- Authors
- He, B., Yang, L., Wilke, C., & Yuan, H.
- Affiliations
- University of Minnesota (US)
- Corresponding author
- Bin He
- Venue
- IEEE Transactions on Biomedical Engineering
- Published
- 2011-07
- Volume
- 58
- Issue
- 7
- Pages
- 1918-1931
- ISSN
- 0018-9294 (ISSN-L)
- 1558-2531
- PMC
- PMC3241716
- OpenAlex
- W2147326914
- Cited by
- 300
- References
- 121
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 19 · 2023: 14 · 2022: 19 · 2021: 15 · 2020: 22 · 2019: 20 · 2018: 31 · 2017: 24 · 2016: 27 · 2015: 18 · 2014: 28 · 2013: 14 · 2012: 20
- FWCI
- 1.80
- 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)
- Funders
- National Institute of Biomedical Imaging and Bioengineering (R01EB007920, R01EB006433, T32EB008389)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- multimodal neuroimaging, MEG, functional brain networks, brain dynamics, spatiotemporal resolution
- MeSH terms
- Brain, Brain Mapping, Electroencephalography, Humans, Magnetic Resonance Imaging, Nerve Net, Magnetoencephalography
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