Minimum-norm least-squares estimation: magnetic source images for a spherical model head

The minimum-norm least-squares inverse approach to a local spherical model for the conductivity geometry of the human head is extended. In simulations of cortical activity of the human brain, the magnetic field pattern across the scalp is interpreted with prior knowledge of anatomy, and the properties of intraneuronal current flow to yield a unique magnetic source image across a portion of cerebral cortex. Influences on the quality of magnetic source images from the noise in measurements, the position errors in determining the image surface, and the number of sensors are evaluated in detail.<<ETX>>

[1]  L. Kaufman,et al.  Magnetic source images determined by a lead-field analysis: the unique minimum-norm least-squares estimation , 1992, IEEE Transactions on Biomedical Engineering.

[2]  R. Parker Understanding Inverse Theory , 1977 .

[3]  B. Roth,et al.  Magnetic determination of the spatial extent of a single cortical current source: a theoretical analysis. , 1988, Electroencephalography and clinical neurophysiology.

[4]  William J. Dallas,et al.  A Linear Estimation Approach to Biomagnetic Imaging , 1989 .

[5]  J. Sarvas Basic mathematical and electromagnetic concepts of the biomagnetic inverse problem. , 1987, Physics in medicine and biology.

[6]  L. Kaufman,et al.  Modulation of Spontaneous Brain Activity during Mental Imagery , 1990, Journal of Cognitive Neuroscience.

[7]  R. Penrose A Generalized inverse for matrices , 1955 .

[8]  M. Singh,et al.  Reconstruction of Images from Neuromagnetic Fields , 1984, IEEE Transactions on Nuclear Science.

[9]  R. Plonsey Capability and limitations of electrocardiography and magnetocardiography. , 1972, IEEE transactions on bio-medical engineering.

[10]  A. Ioannides,et al.  Continuous probabilistic solutions to the biomagnetic inverse problem , 1990 .

[11]  B. Neil Cuffin,et al.  Magnetic Fields of a Dipole in Special Volume Conductor Shapes , 1977, IEEE Transactions on Biomedical Engineering.

[12]  N. G. Sepulveda,et al.  Using a magnetometer to image a two‐dimensional current distribution , 1989 .

[13]  B. Hoenders The Uniqueness of Inverse Problems , 1978 .

[14]  L. Kaufman,et al.  Changes in cortical activity when subjects scan memory for tones. , 1992, Electroencephalography and clinical neurophysiology.

[15]  W. Dallas Fourier space solution to the magnetostatic imaging problem. , 1985, Applied optics.

[16]  A. Ioannides,et al.  Localised and Distributed Source Solutions for the Biomagnetic Inverse Problem II , 1989 .

[17]  William J. Dallas,et al.  Fourier Imaging of Electrical Currents in the Human Brain from Their Magnetic Fields , 1987, IEEE Transactions on Biomedical Engineering.

[18]  H. Helmholtz Ueber einige Gesetze der Vertheilung elektrischer Ströme in körperlichen Leitern mit Anwendung auf die thierisch‐elektrischen Versuche , 1853 .

[19]  J Z Wang,et al.  On cortical folds and neuromagnetic fields. , 1991, Electroencephalography and clinical neurophysiology.

[20]  J Z Wang,et al.  Imaging regional changes in the spontaneous activity of the brain: an extension of the minimum-norm least-squares estimate. , 1993, Electroencephalography and clinical neurophysiology.

[21]  B. Roth,et al.  The magnetic field of cortical current sources: the application of a spatial filtering model to the forward and inverse problems. , 1990, Electroencephalography and clinical neurophysiology.

[22]  B N Cuffin The role of model and computational experiments in the biomagnetic inverse problem. , 1987, Physics in medicine and biology.

[23]  W E Smith,et al.  Linear estimation theory applied to the reconstruction of a 3-D vector current distribution. , 1990, Applied optics.