title: Enhancement of deep epileptiform activity in the EEG via 3-D adaptive spatial filtering.
abstract: The detection of epileptiform discharges (ED's) in the electroencephalogram (EEG) is an important component in the diagnosis of epilepsy. However, when the epileptogenic source is located deep in the brain, the ED's at the scalp are often masked by more superficial, higher-amplitude EEG activity. A noninvasive technique which uses an adaptive "beamformer" spatial filter has been investigated for the enhancement of signals from deep sources in the brain suspected of containing ED's. A forward three-layer spherical model was used to relate a dipolar source to recorded signals to determine the beamformer's spatial response constraints. The beamformer adapts, using the least-mean-squares (LMS) algorithm, to reduce signals from sources distant to some arbitrarily defined location in the brain. The beamformer produces three outputs, being the orthogonal components of the signal estimated to have arisen at or near the assumed location. Simulations were performed by using the same forward model to superimpose realistic ED's on normal EEG recordings. The simulations show the beamformer's ability to enhance signals emanating from deep foci by way of an enhancement ratio (ER), being the improvement in signal-to-noise ratio (SNR) to that observed at any of the scalp electrodes. The performance of the beamformer has been evaluated for 1) the number of scalp electrodes, 2) the recording montage, 3) dependence on the background EEG, 4) dependence on magnitude, depth, and orientation of epileptogenic focus, and 5) sensitivity to inaccuracies in the estimated location of the focus. Results from the simulations show the beamformer's performance to be dependent on the number of electrodes and moderately sensitive to variations in the EEG background. Conversely, its performance appears to be largely independent of the amplitude and morphology of the ED. The dependence studies indicated that the beamformer's performance was moderately dependent on eccentricity with the ER increasing as the dipolar source and the beamformer were moved from the center to the surface of the brain (1.51-2.26 for radial dipoles and 1.17-2.69 for tangential dipoles). The beamformer was also moderately dependent on variations in polar or azimuthal angle for radial and tangential dipoles. Higher ER's tended to be seen for locations between electrode sites. The beamformer was more sensitive to inaccuracies in both polar and azimuthal location than depth of the dipolar source. For polar locations, an ER > 1.0 was achieved when the beamformer was located within +/- 25 degrees of a radial dipole and +/- 35 degrees of a tangential dipole. Similarly, angular ranges of +/- 37.5 degrees and +/- 45 degrees, respectively, for inaccuracies in azimuthal locations. Preliminary results from real EEG records, comprising 12 definite or questionable epileptiform events, from four patients, demonstrated the beamformer's ability to enhance these events by a mean 100% (52%-215%) for referential data and a mean 104% (50%-145%) for bipolar data.
authors.affiliation: Department of Electrical and Electronic Engineering, University of Canterbury, Christchurch, New Zealand.
authors.forename: D M
authors.initials: DM
authors.lastname: Ward
authors.forename: R D
authors.initials: RD
authors.lastname: Jones
authors.forename: P J
authors.initials: PJ
authors.lastname: Bones
authors.forename: G J
authors.initials: GJ
authors.lastname: Carroll
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D016477:Artifacts; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D016018:Least-Squares Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted