The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.
A new approach to neuroimaging with magnetoencephalography
Open accessAbstract
We discuss the application of beamforming techniques to the field of magnetoencephalography (MEG). We argue that beamformers have given us an insight into the dynamics of oscillatory changes across the cortex not explored previously with traditional analysis techniques that rely on averaged evoked responses. We review several experiments that have used beamformers, with special emphasis on those in which the results have been compared to those observed in functional magnetic resonance imaging (fMRI) and on those studying induced phenomena. We suggest that the success of the beamformer technique, despite the assumption that there are no linear interactions between the mesoscopic local field potentials across distinct cortical areas, may tell us something of the balance between functional integration and segregation in the human brain. What is more, MEG beamformer analysis facilitates the study of these complex interactions within cortical networks that are involved in both sensory‐motor and cognitive processes. Hum. Brain Mapp 25:199–211, 2005. © 2005 Wiley‐Liss, Inc.
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Statistical parametric maps in functional imaging: A general linear approach
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Event-related EEG/MEG synchronization and desynchronization: basic principles
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Neurophysiological investigation of the basis of the fMRI signal
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Nonparametric permutation tests for functional neuroimaging: A primer with examples
Nichols, T. E., & Holmes, A. P. (2002) · Human Brain Mapping · doi:10.1002/hbm.1058 · Cited by 6,256
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Beamforming: a versatile approach to spatial filtering
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Frequency Dependence of Signal Power and Spatial Reach of the Local Field Potential
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Where Does EEG Come From and What Does It Mean?
Cohen, M. X. (2017) · Trends in Neurosciences · doi:10.1016/j.tins.2017.02.004 · Cited by 722
Hillebrand, A., Barnes, G. R., Bosboom, J. L., Berendse, H. W., & Stam, C. J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.005 · Cited by 416
Self-citationMEG: An Introduction to Methods
(2010) · Oxford University Press eBooks · doi:10.1093/acprof:oso/9780195307238.001.0001 · Cited by 408
Disordered connectivity in the autistic brain: Challenges for the ‘new psychophysiology’
Rippon, G., Brock, J., Brown, C., & Boucher, J. (2007) · International Journal of Psychophysiology · doi:10.1016/j.ijpsycho.2006.03.012 · Cited by 308
Salvadore, G., Cornwell, B. R., Colon-Rosario, V., Coppola, R., Grillon, C., Zarate, C. A., & Manji, H. K. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.08.014 · Cited by 277
Metadata
- Authors
- Hillebrand, A., Singh, K. D., Holliday, I. E., Furlong, P. L., & Barnes, G. R.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2005-04-21
- Volume
- 25
- Issue
- 2
- Pages
- 199-211
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2073316336
- Cited by
- 549
- References
- 99
- FWCI
- 8.56
- 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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