Localizing functional activity in the brain through time-frequency analysis and synthesis of the EEG

Multichannel electroencephalograms (EEGs) are processed using time-frequency (TF) analysis and synthesis techniques to geometrically localize neuroelectric generators of specific activity contained within the observed EEG. The TF domain techniques are utilized to separate the signals of interest from the remainder of the EEG, by allowing the definition of regions of interest which contain the signals for which we desire to localize the underlying neuronal generators. This approach essentially introduces a filtering technique which allows the distortionless separation of the signals of interest from all other components recorded. The source of the functional activity in the brain is estimated and mapped numerically by a least-squares approach. We have applied these techniques to identify the anatomical location of the sleep spindle, a component of the EEG observed during sleep, which is of importance in understanding the generation of sleep and sleep patterns.

[1]  R. Bayley,et al.  The electrical field produced by the eccentric current dipole in the nonhomogeneous conductor. , 1962, American heart journal.

[2]  B. Noble Applied Linear Algebra , 1969 .

[3]  R. M. Harper,et al.  Laboratory computers in neurophysiology , 1973 .

[4]  N. Kawabata A nonstationary analysis of the electroencephalogram. , 1973, IEEE transactions on bio-medical engineering.

[5]  T. Estrin,et al.  Time series analysis and sleep research , 1974 .

[6]  H. J. Hoffman,et al.  A 90-min cardiac biorhythm: methodology and data analysis using modified periodograms and complex demodulation. , 1974, IEEE transactions on bio-medical engineering.

[7]  Dietrich Lehmann,et al.  Evaluation of Methods for Three-Dimensional Localization of Electrical Sources in the Human Brain , 1978, IEEE Transactions on Biomedical Engineering.

[8]  M. Portnoff Time-frequency representation of digital signals and systems based on short-time Fourier analysis , 1980 .

[9]  G. Eichmann,et al.  Two-dimensional optical filtering of 1-D signals. , 1982, Applied optics.

[10]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[11]  Thomas W. Parks,et al.  Time-varying filtering and signal estimation using Wigner distribution synthesis techniques , 1986, IEEE Trans. Acoust. Speech Signal Process..

[12]  J. D. Munck The potential distribution in a layered anisotropic spheroidal volume conductor , 1988 .

[13]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[14]  M. Hämäläinen,et al.  Realistic conductivity geometry model of the human head for interpretation of neuromagnetic data , 1989, IEEE Transactions on Biomedical Engineering.

[15]  C M Michel,et al.  Intracerebral dipole source localization for FFT power maps. , 1990, Electroencephalography and clinical neurophysiology.

[16]  J.C. Mosher,et al.  Multiple dipole modeling and localization from spatio-temporal MEG data , 1992, IEEE Transactions on Biomedical Engineering.

[17]  Kan Chen,et al.  Optimal biorthogonal functions for finite discrete-time Gabor expansion , 1992, Signal Process..

[18]  F. Hlawatsch,et al.  Linear and quadratic time-frequency signal representations , 1992, IEEE Signal Processing Magazine.

[19]  Mingui Sun,et al.  Time-Frequency Domain Problems in the Neurosciences , 1992 .

[20]  B. Lütkenhöner Frequency-domain localization of intracerebral dipolar sources. , 1992, Electroencephalography and clinical neurophysiology.

[21]  R. Ilmoniemi,et al.  Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain , 1993 .

[22]  Mingui Sun,et al.  Partially reconstructible wavelet decomposition of evoked potentials for dipole source localization , 1993, Proceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Societ.

[23]  Mingui Sun,et al.  Multiresolution source localization using the wavelet transform , 1993, 1993 IEEE Annual Northeast Bioengineering Conference.

[24]  T. Sejnowski,et al.  Thalamocortical oscillations in the sleeping and aroused brain. , 1993, Science.

[25]  D. Dijk,et al.  Dynamics of electroencephalographic sleep spindles and slow wave activity in men: effect of sleep deprivation , 1993, Brain Research.

[26]  Shie Qian,et al.  Discrete Gabor transform , 1993, IEEE Trans. Signal Process..

[27]  I. Johnstone,et al.  Ideal spatial adaptation by wavelet shrinkage , 1994 .

[28]  MARC JOBERT,et al.  Wavelets—a new tool in sleep biosignal analysis , 1994, Journal of sleep research.

[29]  Douglas L. Jones,et al.  Improved time-frequency filtering using an STFT analysis-modification-synthesis method , 1994, Proceedings of IEEE-SP International Symposium on Time- Frequency and Time-Scale Analysis.

[30]  B. N. Cuffin,et al.  A method for localizing EEG sources in realistic head models , 1995, IEEE Transactions on Biomedical Engineering.

[31]  W. Orrison,et al.  Functional Brain Imaging , 1995 .

[32]  William J. Williams,et al.  Time-frequency analysis of electrophysiology signals in epilepsy , 1995 .

[33]  Blanco,et al.  Time-frequency analysis of electroencephalogram series. , 1995, Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics.

[34]  Z Lin,et al.  Advances in time-frequency analysis of biomedical signals. , 1996, Critical reviews in biomedical engineering.