Open AccessMapping the signal‐to‐noise‐ratios of cortical sources in magnetoencephalography and electroencephalography
Author(s) -
Goldenholz Daniel M.,
Ahlfors Seppo P.,
Hämäläinen Matti S.,
Sharon Dahlia,
Ishitobi Mamiko,
Vaina Lucia M.,
Stufflebeam Steven M.
Publication year - 2009
Publication title -
human brain mapping
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.005
H-Index - 191
eISSN - 1097-0193
pISSN - 1065-9471
DOI - 10.1002/hbm.20571
Subject(s) - magnetoencephalography , electroencephalography , eeg fmri , noise (video) , signal to noise ratio (imaging) , signal (programming language) , brain activity and meditation , brain mapping , psychology , sensitivity (control systems) , cortex (anatomy) , pattern recognition (psychology) , audiology , neuroscience , artificial intelligence , computer science , physics , medicine , optics , electronic engineering , image (mathematics) , programming language , engineering
Although magnetoencephalography (MEG) and electroencephalography (EEG) have been available for decades, their relative merits are still debated. We examined regional differences in signal‐to‐noise‐ratios (SNRs) of cortical sources in MEG and EEG. Data from four subjects were used to simulate focal and extended sources located on the cortical surface reconstructed from high‐resolution magnetic resonance images. The SNR maps for MEG and EEG were found to be complementary. The SNR of deep sources was larger in EEG than in MEG, whereas the opposite was typically the case for superficial sources. Overall, the SNR maps were more uniform for EEG than for MEG. When using a noise model based on uniformly distributed random sources on the cortex, the SNR in MEG was found to be underestimated, compared with the maps obtained with noise estimated from actual recorded MEG and EEG data. With extended sources, the total area of cortex in which the SNR was higher in EEG than in MEG was larger than with focal sources. Clinically, SNR maps in a patient explained differential sensitivity of MEG and EEG in detecting epileptic activity. Our results emphasize the benefits of recording MEG and EEG simultaneously. Hum Brain Mapp 2009. © 2008 Wiley‐Liss, Inc.