SOFIA: Spatially optimal fast initial analysis of biomagnetic signals

Physics in Medicine and Biology

Volumn 44, Issue 1, 1999, Pages 87-103

  Bolton, J P R ^a   Gross, J ^b   Liu, L C ^b   Ioannides, A A ^a,b,c  

^a OPEN UNIVERSITY   (United Kingdom)

^b FORSCHUNGSZENTRUM JÜLICH   (Germany)

^c RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER; FILTER; MAGNETIC FIELD; NOISE; PRIORITY JOURNAL; SENSOR; SIGNAL PROCESSING; VIRTUAL REALITY;

ALGORITHMS; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; HUMANS; MAGNETICS; MAGNETOENCEPHALOGRAPHY; PHANTOMS, IMAGING;

EID: 0032892052     PISSN: 00319155     EISSN: None     Source Type: Journal    
DOI: 10.1088/0031-9155/44/1/008     Document Type: Article

References (18)

1. Bamidis P, Hellstrand E, Lidholm H, Abraham-Fuchs K and Ioannides A 1995 MFT in complex partial epilepsy: spatial-temporal estimates of interictal activity Neuroreport 7 17-23
2. Cuffin B and Cohen D 1977 Magnetic fields of a dipole in special volume conductor shapes IEEE Trans. Biomed. Eng. 24 372-81
3. Fieseler T, Nowak H and Ioannides A 1995 Model studies of the accuracy of the conducting sphere model in magnetoencephalography using the spheroid Biomagnetism: Fundamental Research and Clinical Applications ed C Baumgartner et al (Amsterdam: Elsevier) pp 445-9
4. Hämäläinen M, Hari R, Ilmoniemi R, Knuutila J and Lounasmaa O 1993 Magnetoencephalography - theory, instrumentation, and application to noninvasive studies of the working human brain Rev. Mod. Phys. 65 413-97
5. Ioannides A 1994 Estimates of brain activity using magnetic field tomography and large scale communication within the brain Bioelectrodynamics and Biocommunication ed M Ho, F Popp and U Warnke (Singapore: World Scientific) pp 319-53
6. Ioannides A 1995 Estimates of 3d brain activity ms by ms from biomagnetic signals: Methods (mft), results and their significance Quantitative and Topological EEG and MEG Analysis ed E Eiselt, U Zwiener and H Witte (Jena: Universitätsverlag Druckhaus-Maayer) pp 59-68
7. Ioannides A, Bolton J and Clarke C 1990 Continuous probabilistic solutions to the biomagnetic inverse problem Inverse Problems 6 523-42
8. Liu M, Hasson R and Ioannides A 1993 A transputer-based system for magnetic field tomography Transputer Applications and Systems '93 vol 2, ed R Grebe et al (Amsterdam: IOS) pp 1290-7
9. Liu L and Ioannides A 1995 Single Epoch analysis of MEG signals Biomagnetism: Fundamental Research and Clinical Applications ed C Baumgartner et al (Amsterdam: Elsevier) pp 439-44
10. _ 1996 A correlation study of averaged and single trial MEG signals: the average describes multiple histories each in a different set of single trials Brain Topogr. 8 385-96
11. Liu L, Ioannides A and Müller-Gärtner H 1998 Bi-hemispheric study of single trial meg signals of the human auditory cortex Electroenceph. Clin. Neurophysiol. 106 64-78
12. Lütkenhöner B, Pantev C, Grunwald A and Menninghaus E 1995 Source-space projection of single trials of the auditory evoked field Biomagnetism: Fundamental Research and Clinical Applications ed C Baumgartner et al (Amsterdam: Elsevier) pp 347-51
13. Mosher J, Lewis P, Leahy R and Singh M 1990 Multiple dipole modeling of spatio-temporal MEG data Proc. SPIE 1351 364-75
14. Robinson S 1989 Theory and properties of lead field synthesis analysis Advances in Biomagnetism ed S Williamson et al (New York: Plenum) pp 599-602
15. Sarvas J 1987 Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem Phys. Med. Biol. 32 11-22
16. Sekihara K and Scholz B 1996 Generalized Wiener estimation of three-dimensional current distribution from biomagnetic measurements IEEE Trans. Biomed. Eng. 43 281-91
17. Spencer M, Leahy R, Mosher J and Lewis P 1992 Adaptive filters for monitoring localized brain activity from surface potential time series Proc. 26th Asilomar Conf. on Signals, Systems and Computers pp 156-61
18. Tesche C, Uusitalo M, Ilmoniemi R, Huotilainen M, Kajola M and Salonen O 1995 Signal space projections of MEG data characterize both distributed and well-localized neuronal sources Electroenceph. Clin. Neurophysiol. 95 189-220