The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Towards the utilization of EEG as a brain imaging tool
Open accessAbstract
Recent advances in signal analysis have engendered EEG with the status of a true brain mapping and brain imaging method capable of providing spatio-temporal information regarding brain (dys)function. Because of the increasing interest in the temporal dynamics of brain networks, and because of the straightforward compatibility of the EEG with other brain imaging techniques, EEG is increasingly used in the neuroimaging community. However, the full capability of EEG is highly underestimated. Many combined EEG-fMRI studies use the EEG only as a spike-counter or an oscilloscope. Many cognitive and clinical EEG studies use the EEG still in its traditional way and analyze grapho-elements at certain electrodes and latencies. We here show that this way of using the EEG is not only dangerous because it leads to misinterpretations, but it is also largely ignoring the spatial aspects of the signals. In fact, EEG primarily measures the electric potential field at the scalp surface in the same way as MEG measures the magnetic field. By properly sampling and correctly analyzing this electric field, EEG can provide reliable information about the neuronal activity in the brain and the temporal dynamics of this activity in the millisecond range. This review explains some of these analysis methods and illustrates their potential in clinical and experimental applications.
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Cites
Investigating causal relations by econometric models and cross-spectral methods
Granger, C. W. J. (1969) · Econometrica · doi:10.2307/1912791 · Cited by 22,989
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Neuronal Oscillations in Cortical Networks
Buzsáki, G., & Draguhn, A. (2004) · Science · doi:10.1126/science.1099745 · Cited by 6,576
Buzsáki, G. (2006) · doi:10.1093/acprof:oso/9780195301069.001.0001 · Cited by 4,873
Consistent resting-state networks across healthy subjects
Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326
Object vision and spatial vision: Two cortical pathways
Mishkin, M., Ungerleider, L. G., & Macko, K. A. (1983) · Trends in Neurosciences · doi:10.1016/0166-2236(83)90190-x · Cited by 2,947
The mismatch negativity (MMN) in basic research of central auditory processing: A review
Näätänen, R., Paavilainen, P., Rinne, T., & Alho, K. (2007) · Clinical Neurophysiology · doi:10.1016/j.clinph.2007.04.026 · Cited by 2,644
Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework
Dehaene, S. (2001) · Cognition · doi:10.1016/s0010-0277(00)00123-2 · Cited by 2,498 · cited 2×
“…large-scale networks that have been repeatedly proposed in the global workspace model of consciousness (Baars, 2002a; Dehaene and Changeux, 2004; Dehaene and Naccache, 2001), and the duration of the " perceptual frame " needed for conscious perception in backward masking studies (Efron, 1970;…”
BackgroundBOLD correlates of EEG topography reveal rapid resting-state network dynamics
Britz, J., Van De Ville, D., & Michel, C. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.052 · Cited by 1,070
Self-citationA new method of the description of the information flow in the brain structures
Kaminski, M. J., & Blinowska, K. J. (1991) · Biological Cybernetics · doi:10.1007/bf00198091 · Cited by 1,047
Cited by
Magnetoencephalography for Brain Electrophysiology and Imaging
Baillet, S. (2017) · Nature Neuroscience · doi:10.1038/nn.4504 · Cited by 992
EEG and MEG: Relevance to Neuroscience
Lopes da Silva, F. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.017 · Cited by 900
Social neuroscience and hyperscanning techniques: past, present and future.
Babiloni, F., & Astolfi, L. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2012.07.006 · Cited by 573
Consortium, T. (2012) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2012.00062 · Cited by 516
Quaresima, V., & Ferrari, M. (2019) · Organizational Research Methods · doi:10.1177/1094428116658959 · Cited by 419
Metadata
- Authors
- Michel, C. M., & Murray, M. M.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-06
- Volume
- 61
- Issue
- 2
- Pages
- 371-385
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1963671300
- Cited by
- 738
- References
- 22
- FWCI
- 13.42
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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