Insidious errors in dipole parameters due to shell model misspecification using multiple time-points

Abstract

Insidious errors in dipole modeling due to shell model misspecification in a spherical model were examined analyzing multiple time-points using the constraints of a commonly-used DSL (Dipole Source Localization) method. The computer simulation examined the differences in the fit dipole parameters for the same generator under two circumstances: 1) when computed as a single dipole active alone, and 2) when computed as a member of a simultaneously-active dipole pair. The computations were done using a simplification by which the dipole parameters computed from multiple time-points can be correctly assessed by computing dipole parameters at only two virtual time-points. Using multiple time-points in the DSL generally resulted in less error than if only a single time-point was used. However, how much improvement cna be achieved by using multiple time-points, as compared with a single time-point, is a function of many factors, such as the location and orientation of the dipoles, and the relative magnitudes and overlap of the waveforms (i.e., time-varying magnitudes) of the dipoles, as well as the model used in the fitting. Further, it was shown that it is incorrect to assume that a multiple-time-point DSL will compute a zero magnitude for generators during quiescent intervals. Additionally, it was shown that a "correction" to reduce error for one pair of waveforms will not be applicable to other waveforms. Also, even if location errors are eliminated, magnitude and orientation errors can still be shown to be present. Finally, iterative reduction of the least-square error between the observed and predicted surface maps leads to increasing errors in dipole parameters. We conclude that a DSL with model misspecification can contain insidious (undetectable) errors.

Event‐related potential activity in the basal ganglia differentiates rewards from nonrewards: Temporospatial principal components analysis and source localization of the feedback negativity

“…Mirrored dipoles were used because the neuroimaging literature indicates that even lateralized activity often involves both homologous hemispheric locations. The use of more than a pair of dipoles was avoided because of findings that localization accuracy suffers when trying to model simultaneous dipoles [Zhang et al, 1994], and indeed a major impetus for the use of the PCA was to avoid having to do so. Successfully meeting the generally accepted guideline for a good quality solution [residual variance (RV) no >10% RV] was taken as evidence that no more dipoles were needed for a given solution.…”

Localizing Sites of Activation in Primary Visual Cortex Using Visual-Evoked Potentials and Functional Magnetic Resonance Imaging

“…This increase in standard error is most likely due to distortion of EP data from the MRI scanner magnetic field and normalizing fMRI data to MRI space. Main sources of error in dipole source localization are due to solving for a single dipole when multiple dipoles exist and an inaccurate head model (Zhang et al, 1994). Despite the dominance of a V1 response to a flickering checkerboard, other sources of activity exist, contaminating the V1 dipoles when those extra dipoles are not accounted for.…”

“…They found the first component showed a polarity shift between the upper and lower hemifield that corresponds to the anatomy of V1. However, even with a high percentage of VEP data accounted for by the single source solution (average of 51.5%), it is likely that there are additional sources (Moradi et al, 2003) producing shifts in the V1 source locations (Zhang et al, 1994).…”

Pilot study: Polygraph decision support system using event resolution imaging for the relevant/irrelevant format

“…Many spatial filtering methods (Nunez, 1988) have been investigated with physiological data, including Principal Component Analysis, Singular Value Decomposition, and Eigenvalue Analysis (Golub, & Van Loan, 1989;Horn, & Johnson 1985;Chapman, & McCrary, 1995;Achim, & Marcantoni, 1997;Wood, & McCarthy, 1984). Various source localization methods (Scherg, 1990;Scherg, & Berg, 1991;Scherg, 1992;Cardenas et al, 1995) have been applied to estimate the locations of important electrical activity within the brain (Scherg, & Ebersole, 1993;Fuchs et al, 1995;Nunez, 1986;Turetsky et al, 1990;Zhang, & Jewett, 1993;Zhang et al, 1994;Buchner et al, 1994;Ebersole, 1991). While powerful for spatial source localization, these techniques tend to ignore frequency and temporal information.…”