Electroencephalography and Clinical Neurophysiology
Assessing the accuracy of topographic EEG mapping for determining local brain function
Introduction
Considerable research in electroencephalography has focused upon what is usually termed the `inverse problem,' or the identification of intracerebral current sources for specific surface potentials (cf. Nunez, 1981; Scherg, 1992). This avenue of research commonly models a dipole source for a surface potential associated with a disease process (e.g. spike-and-wave discharges in epilepsy) or with a cognitive state (e.g. the P300 waveform and selective attention). Usually, these sources do not immediately underlie a particular recording electrode, and may be found at a distant lesion site or in a deep brain structure some distance from any electrode. Approaches to the inverse problem frequently employ numerical models to relate deep, remote sources to the signals recorded at the surface.
A complementary problem could be called the `topographic problem,' or that of determining local brain function immediately under each electroencephalogram (EEG) recording electrode. Approaches to this problem do not focus on any single potential or waveform, but instead analyze background EEG activity at each electrode to generate a frequency spectrum and characterize the function of immediately underlying brain tissue. Rather than modeling a focal source distant from a particular electrode, this approach examines the source(s) under each electrode site. A number of investigators have cautioned that since EEG activity recorded at a single electrode may arise from local or distant sources, topographic maps may not accurately characterize local brain function (American Academy of Neurology, 1989; Nuwer, 1996) and interpretations must be appropriately modest.
One factor which may impact upon how accurately topographic analysis reflects local brain function is the particular measure of EEG energy which is selected for mapping. Two energy measures are most widely used: absolute power, or the intensity of energy at an electrode site in a specific frequency band measured in μV2; and, relative power, or the proportion of power at an electrode site in a given frequency band, measured as a percentage of total absolute power across the spectrum. Previous research has shown that absolute and relative power are complementary measures which may convey substantially different information about brain function (Leuchter et al., 1993).
A second factor which has been suggested as influencing the accuracy with which topographic maps reflect brain function is the choice of electrode montage. Frequently, EEG maps are based upon a linked ear or other referential montage. The reference montage offers the advantage that potential differences for all electrodes are measured from an identical voltage baseline, facilitating comparison across electrode sites. A disadvantage of the common reference approach, however, is that voltage measurements at any one recording electrode may be contaminated with electrical activity from a distant, possibly unrelated site. Other alternative montage approaches include the use of the source derivation montage (Hjorth, 1975, Hjorth, 1980), or the bipolar montage (Pfurtscheller and Lopes da Silva, 1988). Each of these strategies has its uses and limitations, since there is no ideal uncontaminated montage, and it has not been established how accurately any of these montages reflect underlying local brain activity.
One approach for examining the accuracy of each montage would be to compare the data resulting from that specific montage with a `gold standard' of local brain function, such as cerebral perfusion measured with H215O positron emission tomography (PET). In this study, we collected EEG simultaneously during PET scanning, and calculated EEG power with several different montages. We examined the associations between the EEG measures and cerebral perfusion underlying the electrode using the different montages and the absolute and relative power measures, to determine the accuracy with which each montage or power measure characterized local cerebral function.
Section snippets
Subjects
Six right-handed, healthy male subjects, aged 22 to 30 (mean age 28), with no history of neurologic or psychiatric disease, were recruited for this study. Exclusion criteria included a history of head trauma, skull breech, or use of any medications known to affect brain function within 2 weeks of the study. All subjects underwent a magnetic resonance imaging scan and had no structural brain abnormalities. All experimental procedures were approved by the UCLA Human Subjects Protection Committee
Results
There were significant linear relationships between EEG power and perfusion in many frequency bands (Fig. 2, with thresholds to indicate where the significance of the correlation is associated with a P value of 0.05, 0.01, or 0.001). The strength and sign of the relationship were heavily dependent upon (1) the type of power measure, and (2) the referencing strategy, although the pattern of the relationship across bands was similar. Absolute power generally had much weaker associations with
Discussion
Our examination of simultaneous EEG and cerebral perfusion measures clarifies the importance of choice of EEG power measure and of electrode montage in using electroencephalography to characterize local cerebral function. These results indicate that absolute and relative power differ considerably in the extent to which they reflect the activity of brain tissue underlying scalp electrodes. Absolute power has a consistently weaker association with cerebral perfusion in all frequency bands than
Acknowledgements
We are grateful for the assistance of Suzanne Hodgkin, R.EEG.T., and Denise Hannon, EEG.T., in recording the EEG data, and Mariahn Smith, R.EEG.T., in recording and processing the data. Finally, Mychelle Garrigan, M.S.W. provided assistance in the preparation of the manuscript and figures. This work was supported in part by Research Grant R01-MH40705 and Research Scientist Development Award K02-MH01165 from the National Institute of Mental Health, Grant P30-AG10123 to the UCLA Alzheimer Disease
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