Relationship between brain electrical activity and cortical perfusion in normal subjects

Abstract

Cerebral glucose uptake and perfusion are accepted as tightly coupled measures of energy utilization in both normal and diseased brain. The coupling of brain electrical activity to perfusion has been demonstrated, however, only in the presence of chronic brain disease. Very few studies have examined the relationship between cerebral electrical activity and energy utilization in normal brain tissue. To clarify this relationship, we performed 33 H₂¹⁵O-positron emission tomography (PET) scans in six normal subjects both at rest and during a simple motor task, and acquired surface-recorded quantitative electroencephalogram (QEEG) data simultaneously with isotope injection. We examined the associations between cerebral perfusion directly underlying each recording electrode and three QEEG measures (absolute power, relative power, and cordance). All EEG measures had moderately strong coupling with perfusion at most frequency bands, although the directions of the associations differed from those previously reported in subjects with stroke or dementia. Of the three QEEG measures examined, cordance had the strongest relationship with perfusion (multiple R²=0.58). Cordance and PET were equally effective in detecting lateralized activation associated with the motor task, while EEG power did not detect this activation. Electrodes in the concordant state had a significantly higher mean perfusion than those in the discordant state. These results indicate that normal brain electrical activity has a moderately strong association with cerebral perfusion. Cordance may be the most useful QEEG measure for monitoring cerebral perfusion in subjects without chronic brain disease.

Introduction

Cerebral glucose uptake and blood flow long ago were hypothesized to be comparable measures of energy utilization (Roy and Sherrington, 1890). This hypothesis now has been tested with imaging techniques, such as autoradiography, positron emission tomography (PET), and single photon emission computed tomography (SPECT). In normal subjects, cerebral glucose uptake and blood flow generally are accepted as tightly coupled measures of cerebral energy utilization (Des Rossiers et al., 1974; Sokoloff, 1977, Sokoloff, 1981).

Brain electrical activity represents the single greatest demand on cerebral metabolism (Erecinska and Silver, 1989), suggesting that measurement of electrical energy also should be coupled to cerebral metabolism and perfusion. Berger (1938)first hypothesized that the rhythmic activity in the surface-recorded electroencephalogram (EEG) closely reflected brain metabolic activity. Interestingly, however, most previous studies have shown that EEG reflects cerebral energy utilization accurately only under conditions of extreme dysfunction. Animal models using blood vessel occlusion (Cartheuser, 1988) or metabolic suppression with medication (Klementavicius et al., 1996) have demonstrated strong associations between the cerebral metabolic rate for oxygen and EEG power and frequency. Similarly, studies of human subjects suffering from stroke (Tolonen and Sulg, 1981; Nagata et al., 1982; Nagata, 1988), degenerative brain diseases (Stigsby et al., 1981; Wszolek et al., 1992; Passero et al., 1995; Valladeres-Neto et al., 1995), or epilepsy (Jibiki et al., 1994) have found that cerebral perfusion and metabolism have a negative association with slow-wave energy and a positive association with alpha energy.

Very few studies have examined associations between electrical activity and cerebral perfusion in the normal brain. Most studies asserted to examine normal brain actually focused upon the undamaged cerebral hemisphere in stroke patients (Melamed et al., 1975; Nagata, 1989; Nagata et al., 1989). It now is known, however, that the contralateral hemisphere in stroke patients may show changes in metabolism and perfusion (Serrati et al., 1994), perhaps reflecting transcallosal fiber degeneration (Iglesias et al., 1996). Some studies utilized elderly volunteers with incompletely characterized health status (Obrist et al., 1963) or patient volunteers (Ingvar and Risberg, 1967; Ingvar et al., 1976; Ingvar, 1979) who suffered from chronic psychiatric illnesses and/or conditions that are currently recognized as risk factors for brain disease (i.e. alcohol abuse, atherosclerosis). These studies reported relationships between cerebral electrical activity and perfusion which ranged from weak (Obrist et al., 1963) to moderately strong (Ingvar and Risberg, 1967; Ingvar et al., 1976; Ingvar, 1979), but it is not clear that the subjects examined were truly representative of normal function. Only two studies have examined the association between EEG power and PET scanning (using the fluorodeoxyglucose-18 technique) (Buchsbaum et al., 1984) or SPECT scanning (using the Xenon-133 technique) (Okyere et al., 1986) obtained simultaneously in normal subjects. Although both groups found moderately strong associations between electrical activity (in the alpha band) and perfusion, consistent associations were limited to the occipital regions. Examination of other brain regions showed a variable relationship between EEG power and metabolism, with both positive and negative associations in the same EEG frequency band in different brain regions (Buchsbaum et al., 1984).

Because of inconsistencies in the methods and results from previous studies, the relationship between surface-recorded EEG in different frequency bands and the perfusion of underlying brain tissue remains unclear. We performed the current study to clarify the associations between quantitative EEG (QEEG) measures and cerebral perfusion (using ¹⁵O-positron emission tomography) in normal subjects at rest and while performing a motor activation task. A secondary aim of this study was to derive a QEEG index predicting relative perfusion. We examined three QEEG measures: absolute power, relative power, and cordance. Cordance integrates absolute and relative power, and in previous work in subjects with brain disease (i.e. stroke, dementia) has shown more robust and consistent associations with cerebral perfusion (as measured by HMPAO-SPECT) than either power measure alone (Leuchter et al., 1994a, Leuchter et al., 1994b).