Source localisation in concurrent EEG/fMRI: applications at 7T.
This paper investigates the application of source reconstruction methodologies to EEG data recorded in concurrent EEG/fMRI experiments at 7T. An EEG phantom containing a dipolar current source is described and used to investigate the accuracy of source localisation. Both dipole fitting and beamformer algorithms are shown to yield accurate locations for the dipole within the phantom. Source reconstruction methodologies are also shown to reduce significantly the level of interference in the recorded EEG, caused by the MR scanner. A comparison between beamformer and dipole fitting approaches is made and it is shown that, due to its adaptive weighting parameters, the beamformer provides better suppression of interference when compared to the dipole fit. In addition it is shown that, in the case of the beamformer, use of a high EEG channel density improves the level of interference reduction, and the ratio of measured signal to interference can be improved by a factor of approximately 1.6 if the number of EEG electrodes is increased from 32 to 64. The interference reduction properties of source localisation are shown theoretically, in simulation, and in phantom data. Finally, in-vivo experiments conducted at 7T show that effects in the gamma band can be recorded using simultaneous EEG/fMRI. These results are achieved by application of beamformer methodology to 64 channel EEG data.
Brookes
Matthew J
MJ
Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK. matthew.brookes@nottingham.ac.uk
Vrba
Jiri
J
Mullinger
Karen J
KJ
Geirsdóttir
Gerda Björk
GB
Yan
Winston X
WX
Stevenson
Claire M
CM
Bowtell
Richard
R
Morris
Peter G
PG
D000465:Algorithms; D001921:Brain / Q000502:physiology*; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008959:Models, Neurological