TY - GEN
T1 - Array response kernel for EEG in four-shell ellipsoidal geometry
AU - Gutiérrez, David
AU - Nehorai, Arye
PY - 2006
Y1 - 2006
N2 - We present an analytical forward modeling solution in the form of an array response kernel for electroencephalography (EEG) assuming a four-shell ellipsoidal geometry that approximates the anatomy of the brain, cerebrospinal fluid (CSF), skull, and scalp, while a current dipole models the source. The use of an ellipsoidal geometry is useful for cases when incorporating the anisotropy of the head is important but a better model cannot be defined. The structure of our forward solution facilitates the analysis of the inverse problem by factoring the lead field into a product of the current dipole source and a kernel containing the information corresponding to the head geometry and location of the source and sensors. This factorization allows the inverse problem to be approached as an explicit function of just the location parameters, which reduces the complexity of the estimation solution search. Furthermore, we introduce an schematic representation to easily derive the conductivity function involved in our forward solution. This schematic representation generalizes the calculation of the conductivity function for any number of shells, and offers a better understanding of the effect of the geometry on the shell conductivities.
AB - We present an analytical forward modeling solution in the form of an array response kernel for electroencephalography (EEG) assuming a four-shell ellipsoidal geometry that approximates the anatomy of the brain, cerebrospinal fluid (CSF), skull, and scalp, while a current dipole models the source. The use of an ellipsoidal geometry is useful for cases when incorporating the anisotropy of the head is important but a better model cannot be defined. The structure of our forward solution facilitates the analysis of the inverse problem by factoring the lead field into a product of the current dipole source and a kernel containing the information corresponding to the head geometry and location of the source and sensors. This factorization allows the inverse problem to be approached as an explicit function of just the location parameters, which reduces the complexity of the estimation solution search. Furthermore, we introduce an schematic representation to easily derive the conductivity function involved in our forward solution. This schematic representation generalizes the calculation of the conductivity function for any number of shells, and offers a better understanding of the effect of the geometry on the shell conductivities.
UR - http://www.scopus.com/inward/record.url?scp=39749135495&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2006.356604
DO - 10.1109/ACSSC.2006.356604
M3 - Conference contribution
AN - SCOPUS:39749135495
SN - 1424407850
SN - 9781424407859
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 151
EP - 155
BT - Conference Record of the 40th Asilomar Conference on Signals, Systems and Computers, ACSSC '06
T2 - 40th Asilomar Conference on Signals, Systems, and Computers, ACSSC '06
Y2 - 29 October 2006 through 1 November 2006
ER -