메뉴 건너뛰기




Volumn 19, Issue 5, 2003, Pages 1047-1063

Non-stationary magnetoencephalography by Bayesian filtering of dipole models

Author keywords

[No Author keywords available]

Indexed keywords

BRAIN; COMPUTER SIMULATION; MAGNETIC FIELD EFFECTS; MAGNETOENCEPHALOGRAPHY; NOISE ABATEMENT;

EID: 0142030495     PISSN: 02665611     EISSN: None     Source Type: Journal    
DOI: 10.1088/0266-5611/19/5/304     Document Type: Review
Times cited : (50)

References (24)
  • 4
    • 0001460136 scopus 로고    scopus 로고
    • On sequential Monte Carlo sampling methods for Bayesian filtering
    • Doucet A, Godsill S J and Andrieu C 2000 On sequential Monte Carlo sampling methods for Bayesian filtering Stat. Comput. 10 197-208
    • (2000) Stat. Comput. , vol.10 , pp. 197-208
    • Doucet, A.1    Godsill, S.J.2    Andrieu, C.3
  • 5
    • 0008801593 scopus 로고    scopus 로고
    • Monte Carlo smoothing for non-linear time series
    • Department of Engineering, Cambridge University
    • Godsill S J, Doucet A and West M 2001 Monte Carlo smoothing for non-linear time series Technical Report CUED/F-INFENG/TR Department of Engineering, Cambridge University
    • (2001) Technical Report , vol.CUED-F-INFENG-TR
    • Godsill, S.J.1    Doucet, A.2    West, M.3
  • 6
    • 0141714748 scopus 로고    scopus 로고
    • Maximum a posteriori sequence estimation using Monte Carlo particle filters
    • Godsill S J, Doucet A and West M 2001 Maximum a posteriori sequence estimation using Monte Carlo particle filters Ann. Inst. Stat. Math. 53 82-96
    • (2001) Ann. Inst. Stat. Math. , vol.53 , pp. 82-96
    • Godsill, S.J.1    Doucet, A.2    West, M.3
  • 7
    • 0027580559 scopus 로고
    • Novel approach to nonlinear/non-Gaussian Bayes state estimation
    • Gordon N, Salmond D and Smith A F M 1993 Novel approach to nonlinear/non-Gaussian Bayes state estimation IEE Proc. F 140 107-13
    • (1993) IEE Proc. F , vol.140 , pp. 107-113
    • Gordon, N.1    Salmond, D.2    Smith, A.F.M.3
  • 8
    • 0032359151 scopus 로고    scopus 로고
    • Sequential Monte Carlo methods for dynamical systems
    • Liu J S and Chen R 1998 Sequential Monte Carlo methods for dynamical systems J. Am. Stat. Assoc. 93 1032-44
    • (1998) J. Am. Stat. Assoc. , vol.93 , pp. 1032-1044
    • Liu, J.S.1    Chen, R.2
  • 9
    • 0004286947 scopus 로고    scopus 로고
    • The unscented particle filter
    • Department of Engineering, Cambridge University
    • van der Merwe R, Doucet A, de Freitas N and Wan E 2000 The unscented particle filter Technical Report CUED/F-INFENG/TR 380 Department of Engineering, Cambridge University
    • (2000) Technical Report , vol.CUED-F-INFENG-TR 380
    • Van der Merwe, R.1    Doucet, A.2    De Freitas, N.3    Wan, E.4
  • 11
    • 26244462082 scopus 로고
    • Magnetoencephalography - Theory, instrumentation and applications to noninvasive studies of the working human brain
    • Hämäläinen M, Hari R, Ilmoniemi R J, Knuuttila J and Lounasmaa O V 1993 Magnetoencephalography - theory, instrumentation and applications to noninvasive studies of the working human brain Rev. Mod. Phys. 65 413-97
    • (1993) Rev. Mod. Phys. , vol.65 , pp. 413-497
    • Hämäläinen, M.1    Hari, R.2    Ilmoniemi, R.J.3    Knuuttila, J.4    Lounasmaa, O.V.5
  • 12
  • 13
    • 0028219609 scopus 로고
    • Interpreting magnetic-fields of the brain - Minimum norm estimates
    • Hämäläinen M S and Ilmoniemi R J 1994 Interpreting magnetic-fields of the brain - minimum norm estimates Med. Biol. Eng. Comput. 32 35-42
    • (1994) Med. Biol. Eng. Comput. , vol.32 , pp. 35-42
    • Hämäläinen, M.S.1    Ilmoniemi, R.J.2
  • 14
    • 0027998259 scopus 로고
    • Low-resolution electromagnetic tomography: A new method for localizing electrical activity of the brain
    • Pascual-Marqui R D, Michel C M and Lehman D 1994 Low-resolution electromagnetic tomography: a new method for localizing electrical activity of the brain Int. J. Psychophysiol. 18 49-65
    • (1994) Int. J. Psychophysiol , vol.18 , pp. 49-65
    • Pascual-Marqui, R.D.1    Michel, C.M.2    Lehman, D.3
  • 15
    • 0029033726 scopus 로고
    • Selective minimum-norm solution of the biomagnetic inverse problem
    • Matsuura K and Okabe U 1995 Selective minimum-norm solution of the biomagnetic inverse problem IEEE Trans. Biomed. Eng. 42 608-15
    • (1995) IEEE Trans. Biomed. Eng. , vol.42 , pp. 608-615
    • Matsuura, K.1    Okabe, U.2
  • 16
    • 0033179126 scopus 로고    scopus 로고
    • Visualization of magnetoencephalographic data using minimum current estimates
    • Uutela K, Hämäläinen M S and Somersalo E 1999 Visualization of magnetoencephalographic data using minimum current estimates Neuroimage 10 173-80
    • (1999) Neuroimage , vol.10 , pp. 173-180
    • Uutela, K.1    Hämäläinen, M.S.2    Somersalo, E.3
  • 17
    • 0032901789 scopus 로고    scopus 로고
    • Bayesian inference applied to the electromagnetic inverse problem
    • Schmidt D M, George J S and Wood C C 1999 Bayesian inference applied to the electromagnetic inverse problem Hum. Brain Mapp. 7 195-212
    • (1999) Hum. Brain Mapp. , vol.7 , pp. 195-212
    • Schmidt, D.M.1    George, J.S.2    Wood, C.C.3
  • 18
    • 0023158840 scopus 로고
    • Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem
    • Sarvas J 1987 Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem Phys. Med. Biol. 32 11-22
    • (1987) Phys. Med. Biol. , vol.32 , pp. 11-22
    • Sarvas, J.1
  • 19
    • 0035365514 scopus 로고    scopus 로고
    • State estimation with fluid dynamical evolution models in process tomography - An application with impedance tomography
    • Seppänen A, Vauhkonen M, Vauhkonen P, Somersalo E and Kaipio J 2001 State estimation with fluid dynamical evolution models in process tomography - an application with impedance tomography Inverse Problems 17 467-84
    • (2001) Inverse Problems , vol.17 , pp. 467-484
    • Seppänen, A.1    Vauhkonen, M.2    Vauhkonen, P.3    Somersalo, E.4    Kaipio, J.5
  • 21
    • 0035035210 scopus 로고    scopus 로고
    • A probabilistic solution to the MEG inverse problem via MCMC methods: The reversible jump and parallel tempering algorithms
    • Bertrand C, Ohmi M, Suzuki R and Kado H 2001 A probabilistic solution to the MEG inverse problem via MCMC methods: the reversible jump and parallel tempering algorithms IEEE Trans. Biomed. Eng. 48 533-42
    • (2001) IEEE Trans. Biomed. Eng. , vol.48 , pp. 533-542
    • Bertrand, C.1    Ohmi, M.2    Suzuki, R.3    Kado, H.4
  • 22
    • 77956889087 scopus 로고
    • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    • Green P J 1995 Reversible jump Markov chain Monte Carlo computation and Bayesian model determination Biometrika 82 711-32
    • (1995) Biometrika , vol.82 , pp. 711-732
    • Green, P.J.1
  • 23
    • 0026882264 scopus 로고
    • Multiple dipole modelling and localization from spatio-temporal MEG data
    • Mosher J C, Lewis P S and Leahy R M 1992 Multiple dipole modelling and localization from spatio-temporal MEG data IEEE Trans. Biomed. Eng. 39 541-57
    • (1992) IEEE Trans. Biomed. Eng. , vol.39 , pp. 541-557
    • Mosher, J.C.1    Lewis, P.S.2    Leahy, R.M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.