Spatiotemporal analysis of brain electrical fields

Abstract

Psychological studies with reaction time methodology show that there is meaningful variability in the performance of cognitive operations when responses are measured in milliseconds. Temporal precision is also required to reveal the rapid neurophysiological events in cortical networks. Sampling the brain's electrical activity at the scalp surface characterizes regional brain function with millisecond temporal resolution. The problem with electroencephalographic (EEG) data is localizing the areas of the cortex that generate the observed scalp fields. Although the eventual goal will be to specify the neural generators of the EEG, we propose that an important first step for functional studies is to examine accurate, time-dynamic maps of the brain's electrical fields at the head surface. Given an adequate spatial sampling of the surface potentials, accurate electrical studies require measures that are independent of the location of the reference sensor. The 2D Laplacian of the potential field may be used to define the local features of the scalp current flow. Because the electrical fields are dynamic, brain mapping with electrical data requires animations rather than static images.

An early electrophysiological response associated with expertise in letter perception

“…Individual bad channels were replaced on a trial-by-trial basis according to a spherical spline algorithm (Srinivasan, Nunez, Silberstein, Tucker, & Cadusch, 1996). EEG was measured with respect to a vertex reference (Cz), but an average-reference transformation was used to minimize the effects of reference-site activity and to estimate accurately the scalp topography of the measured electrical fields (Bertrand, Perin, & Pernier, 1985;Curran, Tucker, Kutas, & Posner, 1993;Dien, 1998;Lehman & Skrandies, 1985;Picton, Lins, & Scherg, 1995;Tucker, Liotti, Potts, Russell, & Posner, 1994). Average-reference ERPs were computed for each channel as the voltage difference between that channel and the average of all channels.…”

Differentiating location- and distance-based processes in memory for time: An ERP study

“…EEG was measured with respect to a vertex reference (Cz), but an average reference transformation was used to minimize the effects of reference site activity and accurately estimate the scalp topography of the measured electrical fields (Bertrand, Perin, & Pernier, 1985;Curran, Tucker, Kutas, & Posner, 1993;Dien, 1998;Lehman & Skrandies, 1985;Picton, Lins, & Scherg, 1995;Tucker, Liotti, Potts, Russell, & Posner, 1994). Average reference ERPs are computed for each channel as the voltage difference between that channel and the average of all the channels.…”

Enhanced extrastriate visual response to bandpass spatial frequency filtered fearful faces: Time course and topographic evoked‐potentials mapping

“…A baseline correction on the prestimulus interval (-100/0 ms) was computed on each individual epoch prior to averaging. Averaged ERPs were rereferenced offline using a common average-reference [Tucker et al, 1994]. Data were low-pass filtered at 30 Hz.…”