Algorithm to find high density EEG scalp coordinates and analysis of their correspondence to structural and functional regions of the brain

BACKGROUND Interpretation and analysis of electroencephalography (EEG) measurements relies on the correspondence of electrode scalp coordinates to structural and functional regions of the brain. NEW METHOD An algorithm is introduced for automatic calculation of the International 10-20, 10-10, and 10-5 scalp coordinates of EEG electrodes on a boundary element mesh of a human head. The EEG electrode positions are then used to generate parcellation regions of the cerebral cortex based on proximity to the EEG electrodes. RESULTS The scalp electrode calculation method presented in this study effectively and efficiently identifies EEG locations without prior digitization of coordinates. The average of electrode proximity parcellations of the cortex were tabulated with respect to structural and functional regions of the brain in a population of 20 adult subjects. COMPARISON WITH EXISTING METHODS Parcellations based on electrode proximity and EEG sensitivity were compared. The parcellation regions based on sensitivity and proximity were found to have 44.0 ± 11.3% agreement when demarcated by the International 10-20, 32.4 ± 12.6% by the 10-10, and 24.7 ± 16.3% by the 10-5 electrode positioning system. CONCLUSIONS The EEG positioning algorithm is a fast and easy method of locating EEG scalp coordinates without the need for digitized electrode positions. The parcellation method presented summarizes the EEG scalp locations with respect to brain regions without computation of a full EEG forward model solution. The reference table of electrode proximity versus cortical regions may be used by experimenters to select electrodes that correspond to anatomical and functional regions of interest.

[1]  Bart Vanrumste,et al.  Review on solving the forward problem in EEG source analysis , 2007, Journal of NeuroEngineering and Rehabilitation.

[2]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

[3]  D. Louis Collins,et al.  Twenty New Digital Brain Phantoms for Creation of Validation Image Data Bases , 2006, IEEE Transactions on Medical Imaging.

[4]  Valer Jurcak,et al.  10/20, 10/10, and 10/5 systems revisited: Their validity as relative head-surface-based positioning systems , 2007, NeuroImage.

[5]  Anders M. Dale,et al.  Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature , 2010, NeuroImage.

[6]  Masako Okamoto,et al.  Three-dimensional probabilistic anatomical cranio-cerebral correlation via the international 10–20 system oriented for transcranial functional brain mapping , 2004, NeuroImage.

[7]  David A. Rottenberg,et al.  Quantitative comparison of four brain extraction algorithms , 2004, NeuroImage.

[8]  Peter Stiers,et al.  Unravelling the Intrinsic Functional Organization of the Human Lateral Frontal Cortex: A Parcellation Scheme Based on Resting State fMRI , 2012, The Journal of Neuroscience.

[9]  Jacques Felblinger,et al.  Automated cortical projection of EEG sensors: Anatomical correlation via the international 10–10 system , 2009, NeuroImage.

[10]  Marisa O. Hollinshead,et al.  The organization of the human cerebral cortex estimated by intrinsic functional connectivity. , 2011, Journal of neurophysiology.

[11]  Bruce Fischl,et al.  Within-subject template estimation for unbiased longitudinal image analysis , 2012, NeuroImage.

[12]  P. Mitra,et al.  The Brain Atlas Concordance Problem: Quantitative Comparison of Anatomical Parcellations , 2009, PloS one.

[13]  Jacques Felblinger,et al.  Automatic localization and labeling of EEG sensors (ALLES) in MRI volume , 2008, NeuroImage.

[14]  D. A. Driscoll,et al.  EEG electrode sensitivity--an application of reciprocity. , 1969, IEEE transactions on bio-medical engineering.

[15]  T. Gasser,et al.  Test-retest reliability of spectral parameters of the EEG. , 1985, Electroencephalography and clinical neurophysiology.

[16]  M. Murray,et al.  EEG source imaging , 2004, Clinical Neurophysiology.

[17]  Richard M. Leahy,et al.  Brainstorm: A User-Friendly Application for MEG/EEG Analysis , 2011, Comput. Intell. Neurosci..

[18]  Masako Okamoto,et al.  Virtual spatial registration of stand-alone fNIRS data to MNI space , 2007, NeuroImage.

[19]  J. Rothwell,et al.  Transcranial magnetic stimulation in cognitive neuroscience – virtual lesion, chronometry, and functional connectivity , 2000, Current Opinion in Neurobiology.

[20]  Théodore Papadopoulo,et al.  OpenMEEG: opensource software for quasistatic bioelectromagnetics , 2010, Biomedical engineering online.

[21]  Ping He,et al.  A practical method for quickly determining electrode positions in high-density EEG studies , 2013, Neuroscience Letters.

[22]  Archana K. Singh,et al.  Virtual 10–20 measurement on MR images for inter-modal linking of transcranial and tomographic neuroimaging methods , 2005, NeuroImage.

[23]  T. Musha,et al.  Forward and inverse problems of EEG dipole localization. , 1999, Critical reviews in biomedical engineering.

[24]  Alan C. Evans,et al.  Transcranial Magnetic Stimulation during Positron Emission Tomography: A New Method for Studying Connectivity of the Human Cerebral Cortex , 1997, The Journal of Neuroscience.

[25]  A. Dale,et al.  Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System , 1999, NeuroImage.

[26]  K. K. Tan,et al.  The spatial location of EEG electrodes: locating the best-fitting sphere relative to cortical anatomy. , 1993, Electroencephalography and clinical neurophysiology.

[27]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[28]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

[29]  Robert Oostenveld,et al.  The five percent electrode system for high-resolution EEG and ERP measurements , 2001, Clinical Neurophysiology.

[30]  A. Sack Transcranial magnetic stimulation, causal structure–function mapping and networks of functional relevance , 2006, Current Opinion in Neurobiology.

[31]  Olivier D. Faugeras,et al.  A common formalism for the Integral formulations of the forward EEG problem , 2005, IEEE Transactions on Medical Imaging.

[32]  Paolo Giacometti,et al.  Compliant head probe for positioning electroencephalography electrodes and near-infrared spectroscopy optodes , 2013, Journal of biomedical optics.

[33]  H. Jasper,et al.  The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. , 1999, Electroencephalography and clinical neurophysiology. Supplement.

[34]  Max E Valentinuzzi,et al.  Honoring Leslie A. Geddes - Farewell ... , 2010, Biomedical engineering online.