Quantitative electroencephalographic analyses in cocaine-preferring polysubstance abusers during abstinence

PSYCHIATRY RESEARCH NEUROIMAGING

ELSEVIER

Psychiatry Research 58 (1995)247-257

Quantitative electroencephalographic analyses in cocaine-preferring polysubstance abusers during abstinence Richard A. Roemer* a, Anna Cornwell”, Dorothy Dewart a, Pearleen Jacksona, Dragoslav V. Ercegovacb ‘Neuroscience Research Group, Department of Psychiatry, Temple University Health Sciences Center, 4200 Monument Road, Philadelphia, PA 19140, USA bDepartment of Psychophysiology and Clinical Neurophysiology, Institute for Mental Health, Belgrade, Yugoslavia

Received 4 January 1994,revision received 3 January 1995;accepted 25 January 1995

Quantitative electroencephalographic (QEEG) analyses are presented for a group of 90 subjects recovering from polysubstance abuse (median = 90 days abstinent) who preferentially used cocaine. QEEGs showed significant decreases from normal in both absolute and relative delta power and decreased theta power in both absolute and relative power. Significantly increased relative but not absolute alpha and beta power was found. Asymmetry of frontal delta, theta, and alpha power differed from normal with right power greater than left. Globally, reduced interhemispheric coherence was found in delta and theta bands and frontally in the beta band. An atypical EEG pattern was observed in about half of the subjects. This was a paroxysmal-like EEG alpha pattern reminiscent of vertex waves typically associated with drowsiness but lacking the waxing and waning of alpha and the slow lateral eye drift associated with drowsiness. Keywords: Electrophysiology; Substance abuse; Cocaine; Alcohol; Marijuana

1. Introduction

Substance abuse, especially cocaine abuse, constitutes a serious public health problem. The National Institute of Drug Abuse estimated, in 1990, that there were approximately 6 million cocaine users in the United States (about 2% of the population). Cardiovascular complications are among the * Corresponding author, Tel: +I 215 707-7283;Fax: +I 215 7074086; E-mail: [email protected]

most common and dangerous complications of cocaine abuse, ranging from episodic arrhythmias to myocardial infarction, strokes, cardiomyopathy, and sudden death (Perper and Van Thiel, 1992). With abstinence, these cardiovascular anomalies generally appear to resolve over time. A pressing problem is documenting the extent to which chronic exposure to cocaine leads to central nervous system (CNS) alterations and the extent to which alterations continue to be present during abstinence. Such sequelae may have an effect on

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treatment and relapse. Little is known, however, about the basic neurophysiological effects of the chronic abuse of cocaine or residual effects that may be seen during abstinence from abuse in humans. Therefore, increased understanding of brain mechanisms in substance abuse and dependence is needed. Development of an objective profile of CNS recovery from cocaine exposure would be a major contribution. Few physiopathological studies of the acute and residual effects of cocaine in humans using neuroimaging methods, such as quantitative electroencephalography (QEEG), evoked potential topographical mapping, positron emission tomography, or single photon emission computed tomography, have been presented. The studies examining the residual effect of chronic cocaine use in humans that have been published typically involved relatively small groups of cocaine users. Imaging studies of cerebral anatomy and morphology have not revealed structural anomalies (Cascella et al., 1991; Amass et al., 1992). However, MacKay et al. (1993) reported preliminary evidence of damage to cell membranes using “Pmagnetic resonance spectroscopy in eight cocainedependent polydrug abusers. While functional abnormalities might be related to the profound vasoconstrictor effects or toxicity of cocaine, interactions with the use of multiple substances, including cannabis and alcohol, may also contribute. In general, evidence is emerging that indicates scattered functional brain abnormalities in chronic cocaine-dependent polydrug users during abstinence, with more frequent anomalies being found in frontal regions (Volkow et al., 1988, 1990, 1991, 1993; Alper et al., 1990; Tumeh et al., 1990; Dhuna et al., 1991; Holman et al., 1991, 1993; Cornwell et al., 1993; Roemer et al., 1993; Weber et al., 1993; Strickland et al., 1993). As evidence of the infancy of neuroimaging studies in these subjects, it should be noted that the cited reports encompass fewer than 300 total subjects. Here, we present QEEG observations in a group of subjects with an extensive history of polysubstance dependence. This is essentially an independent replication and extension of the findings of Alper et al. (1990). We also report an

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atypical seizure-like EEG pattern found in about half of the subjects. Our subjects preferentially used cocaine, in addition to having a history of alcohol and marijuana abuse that predated cocaine dependence. 2. Methods 2.1. Subjects Presented are data of 90 patients who were recovering from psychoactive substance dependence. Histories of substance abuse were obtained from all subjects. All subjects met DSM-III-R psychoactive substance abuse criteria (American Psychiatric Association, 1987) for cocaine dependence (304.20); 26 reported use between 3 and 14 days previously, 18 more had used cocaine within 3 months, 21 had used cocaine between 3 and 6 months previously, and 25 had been abstinent for over 6 months and thus met DSM-III-R criteria for full remission. Table 1 lists the demographic and clinical variables and the histories of cocaine and alcohol abuse in this group. All but one subject had a history of preferential abuse of cocaine with use of at least 0.5 g/week for over 3 months (mean 6.2 g/week); the remaining subject had typically used 0.1 g/week of cocaine during the previous 7 years. Subjects who were seropositive for the human immunodeliciency virus are excluded from this report as are any subjects with overt psychotic symptoms (e.g., schizophrenia). Seventy subjects (78%) had histories of alcohol abuse or dependence (mean 67.6 oz/week, range 4.2-314.3 otiweek) and usually, but not exclusively, used alcohol during the periods of cocaine use. Seventythree (81%) had a history of using marijuana (A-9tetrahydrocannabinol) more than 10 times per month for up to 35 years. Data on the actual amount of marijuana used were not obtained. When other substances were abused, the age of first meeting criteria for alcohol abuse (median = 15 years of age) and the age of first meeting criteria for marijuana abuse (median age = 15) both predated that of first cocaine use (median age at first use = 24). All reported abstinence from cocaine use for from 3 to 1830 days (median = 90 days). The only urine tests positive

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Table 1 Subject characteristics (n = 90) Race

Gender

n

Age (years) Mean

Black Black White White

Female Male Female Male

33 41 2 14

38.7 36.5 31.0 36.2

Days abstinent from cocaine

Cocaine use (p/week)

Median

Range

Mean

SD

162 65 61 I8

3-2100 3-1640 5-127 4-1830

6.7 6.7 I.5 3.4

6.6 15.1 0.7 3.9

SD 6.1 6.9 2.8 II.4

for cocaine were found in seven subjects reporting 54 days of cocaine abstinence. Subjects reported abstinence from alcohol or marijuana for at least as long as their abstinence from cocaine. The subjects consented to participate in the electrophysiological recordings and structured diagnostic interviews. A licensed clinical psychologist without knowledge of the electrophysiological results and trained in using the Structured Clinical Interview for DSM-III-R Patient Version (Spitzer and Williams, 1986) evaluated all subjects to document DSM-III-R Axis I diagnoses. Twenty-nine of the 90 (32%) had no DSM-III-R Axis I diagnoses other than psychoactive substance abuse disorder; 19 (21%) met criteria for a current anxiety disorder; 20 (22%) met criteria for major depressive disorder; and 22 (24%) met criteria for both a current anxiety disorder and for current or previous major depressive disorder. None had taken psychotropic medications for at least 2 weeks before EEG recording. It should be noted that of the 48 (53%) subjects with a diagnosis of an anxiety disorder, all but one had onset of at least one anxiety disorder before 16 years of age, generally in late childhood or early adolescence (median age of first anxiety disorder = 9 years, range = 4-20). While 12 (13%) had been hospitalized five or more times, 48 (53%) had no prior psychiatric hospitalizations. 2.2. EEG data acquisition Eyes-closed, resting EEG was recorded from 19 monopolar electrodes (referred to linked earlobes) of the lo/20 system using a Cadwell Spectrum 32 data acquisition system. Amplifier bandpass was OS-70 Hz (3 dB points) without notch filtering.

Alcohol use (oz./week) Mean

SD

56.5 60.8 73.2 98.8

45.9 43.5 66.8 59.2

Data were digitized at 200 Hz with 12-bit resolution. Following the standardized Spectrum 32 recording protocol, 15 min of continuous EEG data were collected on optical disk for subsequent editing and analyses. At the time this study was initiated, we did not directly record eye movements concomitantly with EEG. Consequently, such data were not available for about 30% of the subjects. 2.3. Data analyses EEG records were evaluated visually by readers who were unaware of the drug histories of the subjects. A paroxysmal-like EEG pattern reminiscent of vertex waves associated with drowsiness was found in about half of the subjects (as described in the results section). Data were also edited using computer-assisted artifact detection in conjunction with visual inspection to select 24 artifact-free 2.5s epochs of EEG from the 19 channels for quantitative analyses. These epochs were selected to exclude the above-mentioned EEG patterns. We did not incorporate a formal protocol specifying the exact recording times from which to select epochs. In general, epochs were taken from the first half of the recording session. Quantitative analyses of the EEG used neurometric methods of John et al. (1988) as implemented on the Cadwell Laboratories’ Spectrum 32. Raw data were digitally filtered yielding a 0.5to 30-Hz band pass. Power spectral analysis was performed using Fast Fourier Transformation. For each of the 19 channels, absolute power and relative (%) power were computed in the delta (1.5-3.5 Hz), theta (3.5-7.5 Hz), alpha (7.5-12.5 Hz), and beta (12.5-25 Hz) frequency bands. Also

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computed were asymmetry of power and coherence between homologous derivations of the two hemispheres in these four frequency bands. QEEG features of the power spectral analyses are subjected to log transformation and age regression. These analytical methods have been well documented (John et al., 1988; Alper et al., 1990). On the basis of distribution statistics obtained from a group of 150 normal subjects, ages 17-90, z values (standard scores) were computed for the index subjects for each of the QEEG features. 3. Results 3.1. QEEG features in relation to diagnoses of anxiety or major depressive disorder The total group comprised subjects with and without diagnoses of anxiety disorder or mood disorder. A pertinent issue is the extent to which deviations from normal values of the QEEG features described below are simply related to other DSM-III-R Axis I diagnoses. To test this possibility, QEEG features of the four groups, with and without anxiety disorder and with and without mood disorder, were compared. Individual repeated measures analyses of variance (BMDP2V) were carried out for each frequency band (4) and for each type of QEEG feature (absolute power, relative power, interhemispheric asymmetry, and interhemispheric coherence) with anxiety disorder diagnosis (present/absent) and major depressive disorder diagnosis (present/absent) as betweensubjects factors and the respective QEEG measure for the several leads as the within-subjects factor. Huynh-Feldt adjustments to Q values were applied to correct for departures from sphericity of the repeated measures. No main effects for anxiety or depression were found. Three lead x anxiety interactions were found. Subjects without a diagnosis of anxiety disorder had higher anterior absolute alpha power than those with an anxiety disorder diagnosis. Those without anxiety disorder had lower relative delta power over the central and temporal regions and greater frontal coherence in the delta band. An interaction for theta asymmetry was found; subjects without a diagnosis of major depressive disorder (either current or previous) had greater anterior asymmetry and lesser

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posterior asymmetry of theta power. None of these four interactions are easily interpreted as confounding interpretations of the QEEG results described below. Fig. 1 presents topographic maps of mean z scores of the entire group of 90 subjects for relative power, interhemispheric power asymmetry, and interhemispheric coherence for each of the four frequency bands. The gray-scale values indicate the probability of a given value falling within OL< 0.01 confidence limits of features extracted from EEG measures based on the normative data. In this case, regions of gray indicate group mean z values that fall within the confidence limits, regions of white indicate z values that fall below the confidence limits, and regions of black indicate z values that fall above the confidence limits. The normative population against which the sample population is compared has a group mean z value of 0, and a standard deviation of 1.0. Up to 84 statistical comparisons involving QEEG features were carried out on data of the group under study (n = 90) requiring adjustment to CY. Thus, setting (Y at 0.0006 yields a Bonferroni-corrected two-tailed CY level of 0.01, A difference of f 0.40 z-score units between the group mean and the mean of the normative population (zero) meets this criterion. It should be acknowledged that this is a very stringent criterion minimizing the likelihood of a type 1 error. The major QEEG findings in this population were reduced delta and theta power values in both delta = -1.67; absolute (mean z values: theta = -0.69) or relative measures of power (mean z values: delta = -1.33; theta = -0.52). Absolute delta z values were significantly lower than normal at all 21 leads, and absolute theta z values were significantly lower than normal at 17 of the 21 leads. Relative delta z values were significantly lower than normal at all 21 leads, and relative theta z values were significantly lower than normal at 16 of the 21 leads. None of the absolute alpha z values differed from normal values, whereas for the relative alpha power measure, values at all 21 leads were higher than normal (mean z across all leads = 0.77). None of the absolute beta z values differed from normal. Relative beta power was greater than normal anteriorly.

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58 (1995) 247-257

RELATIVE POWER

INTERHEMI ASYMMETRY

INTERHEMI COHERENCE

0

DELTA

THETA

ALPHA

BETA

Fig. 1. Topographic head maps for group (n = 90) mean z values for relative power, interhemispheric power asymmetry, and interhemispheric coherence for each of the four frequency bands. The maps represent the mean normalized deviates of the patients based on a healthy control population reference group (not shown). The scaling of the maps yields a region of white where the group-mean z value (-0.40) is lower than expected (P < 0.05) and a region of black where the value (0.40) is greater than expected (P < 0.05). Anterior is at the top of each map; occipital regions are at the bottom. Left hemisphere is on left.

Analyses of interhemispheric relationships indicated several departures from normal. Analyses of interhemispheric asymmetry revealed greater than normal asymmetry, with the EEG power over the right frontal region being greater than that over the left in delta, theta, and alpha bands. Analyses of interhemispheric coherence revealed lower than normal values in the delta, theta, and beta bands. Lower than normal interhemispheric coherence was found in-both the delta (mean z across all lead pairs = -0.50) and the theta bands (mean z across all lead pairs = -0.44) between homologous leads over most of the head. Frontal hypocoherence was found in the beta band. 3.2, Relationships between QEEG features and exposure to drugs of abuse Five measures of drug abuse were obtained dur-

ing patient interviews: duration of alcohol use in years, duration of cocaine use in years, duration of marijuana use in years, amount of alcohol usually consumed weekly (expressed as oz of absolute alcohol), and g/week of cocaine usually used. We were interested in provisionally exploring the extent to which lifetime exposure to cocaine, lifetime exposure to alcohol, and duration of marijuana use could be related to the QEEG deviations reported above (amount of marijuana usually used by the subjects was not available to us). Evidence of significant relationships between exposure to substances of abuse and EEG activity would further implicate CNS sequelae to such exposure. Thus, lifetime exposure to cocaine was estimated by multiplying the years of cocaine use by the amount of weekly cocaine use in grams. In like manner, lifetime exposure to alcohol was com-

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puted by the product of years of alcohol use and the amount of weekly alcohol use in ounces of absolute alcohol. We carried out multiple partial correlation analyses to partial out the relationships of any two of the three abuse measures from the relationship between the third and QEEG measures in each of the four frequency bands. This provided an opportunity to begin to tease apart the independent contribution of each abused drug to the QEEG deviations presented above. The approach is seen to be exploratory as the population size is small for the number of analyses done and Bonferroni adjustments to (Ywere not made. Increasing cocaine exposure was significantly correlated with: (1) reduced right anterior delta power; (2) reduced occipital power in the beta band; (3) alpha band interhemispheric asymmetry frontally; (4) beta band interhemispheric asymmetry frontally; and (5) central hypocoherence in the delta band. Increasing exposure to alcohol was correlated with: (1) reduced delta power, mainly frontally and temporally; (2) reduced frontal beta power; and (3) greater left than right hemisphere theta power asymmetry. Only two relevant multiple partial correlations involving duration of marijuana use were found: (1) greater left than right power asymmetry in the beta band and (2) occipital hypercoherence in the beta band. These analyses suggest that the three substances of abuse may have differing long-term effects on EEG activity. 3.3. Paroxysmal alpha pattern Visual examination of EEG recordings revealed atypical alpha bursts that had paroxysmal characteristics. We have denoted these as Ccomplexes. This paroxysmal-like alpha band pattern was clearly present in over 40 of the cocaineand alcohol-abstinent subjects. This pattern or variations of it appeared in over 80% of the subjects. It should be noted that the Spectrum 32 permits selective display of user-specified montages and band-passes to facilitate interpretation of the analog records; quantitative analysis uses a band pass of 0.5-30 Hz. Fig. 2 illustrates the C-complex pattern in a subject using a 1.6- to 70-Hz band pass. The pattern generally has a duration of 4-5 s; the onset and offset points in time for this pa-

tient are denoted by the letter A at the bottom of each trace. The pattern begins with a suppression of background activity, lasting about 0.5 s. This suppression mimics drowsiness but lacks the waxing and waning of the alpha rhythm as well as the slow lateral eye drift at F,i and FP2 associated with drowsiness. The C-complexes are sometimes accompanied by slow vertical eye movements, but there is no clear correlation. Opening of the eyes during the burst does not block the activity, and C-complexes can be seen during vertex drowsiness. There seems to be a time course, such that the events are markedly present during the first 6 months of abstinence with a subsequent diminution of their magnitude and frequency during a 2to 3-year period of abstinence. A board-certified neurologist specializing in epileptic disorders blindly interpreted a sample of 17 EEG records composed of nine subjects who were judged to have C-complexes and eight who were judged not to have C-complexes but to occasionally have vertex waves. All records considered to be normal were so interpreted by the neurologist; eight of the nine C-complex records were interpreted by the neurologist as atypical records. These were variously noted as atypical alpha bursts, excessive frontal slowing, or simply as unusual. The pattern has two components that occur independently of each other but can appear concomitantly (see components B and C in Fig. 2). Following the suppression, alpha reemerges in the occipital regions of the head bilaterally but at a slower frequency than the background alpha (indicated by B) (background alpha = 9-10 Hz, pattern alpha frequency = 7.5-8 Hz). Pattern alpha follows a “marching” progression from the occipital to the frontal lobes bilaterally, becoming generalized for l-2 s (indicated by C); then pattern alpha digresses to the posterior head regions. Once again, background activity suppresses (duration 0.5 s), and a normal waking record resumes with no evidence of the paroxysm that had preceded it. Also occurring in these subjects is frontal focal slowing (3-5 Hz). This focal frontal theta is seen in wakeful and in drowsy states (sleep tracings are not available). The bursts originate at F, (frontocentral location according to the international

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sells:

Comn:

5uU/nm

HP.

70Hz

Lt-:

1,60Hz

Fpl-AlA FpP-AlA F7-RlR2 F8-AlA F3-RlR2 F4-AlA Fz-AlA T3-AlA T4-RlA2 C3-AlA ct-RlA2 Cz-RlA2 TS-AlA T6-AlA P3-AIR2 P4-AlA Pz-AlR2 Ol-AlA OZ-AlA ACTZ-RE FICT3-RC ACT4-Fp

Fig. 2. Paroxysmal-like C-complexes in an abstinent subject. A indicates onset and offset of event. B indicates alpha over the posterior scalp, and C indicates generalized frontal activity. Dark vertical lines denote 1 s.

lo-20 system of electrode placement) and spread discretely to those areas adjacent and lateral to F,. As pattern alpha reaches this centrofrontal area, it is sometimes replaced by the theta bursts. This focal representation occurs more often in these tracings than the marching pattern alpha, but it is not at all unusual for the focal theta to appear amid the “march of alpha.” These subjects do not generate a well-organized sustained alpha in their background EEG. Pattern alpha tends to be organized and rhythmical. Frontal alpha reported here is less continuous, dense, and organized than that reported to be associated with cannabis abuse (Struve et al., 1989, 1991).

the onset of pattern-

4. Discussion The study population consisted of predominantly abstinent subjects who, in addition to histories of alcohol and marijuana dependence predating cocaine dependence, had preferential abuse of cocaine. The main EEG findings may be summarized as follows. First, we found global reduction of low frequency EEG power. The reduction in low frequency (delta and theta) activity anteriorly was associated with increased interhemispheric power asymmetry (left less than right) and decreased interhemispheric coherence involving the same regions. Second, lower than normal absolute EEG

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power in delta and beta frequency bands was correlated with lifetime exposure to cocaine but not lifetime exposure to alcohol or duration of exposure to marijuana. Lifetime exposure to alcohol was mainly correlated with theta band activity (power, asymmetry, and coherence), whereas duration of marijuana use was mainly correlated with beta band activity (asymmetry and coherence). Third, seizure-like EEG patterns were found in a majority of the subjects. Decreased frontal delta power was reported previously by Alper et al. (1990). We found decreased delta power in all frontal leads with both absolute and relative measures. This represents an independent confirmation of hypofrontal delta activity in abstinent cocaine abusers. Deviations from normal of frontal activity have been noted with other types of brain imaging in such subjects (Tumeh et al., 1990; Holman et al., 1991; Roemer et al., 1993; Volkow et al., 1991; Weber et al., 1993). Dhuna et al. (1991) found decreased relative alpha over the frontotemporal and temporoparietal areas in neuroleptic-treated chronic cocaine abusers with atypical psychoses. They were compared with a group of neuroleptic-treated patients with atypical psychoses that were not considered to be related to drug use. We did not replicate this tinding of reduced relative alpha in the substance abusers. None of our subjects had psychotic symptoms. Thus, the two populations do not seem directly comparable. Further, the quantitative methods differed between the studies as did the comparison populations. The algorithms for age regression and transformation to gaussian distribution of QEEG features and the composition of the normal comparison group used by the Cadwell Spectrum 32 are detailed in John et al. (1988). We did find that half of our subjects failed to generate well-organized and sustained background alpha activity. Our observation of increased relative alpha power is most likely secondary to the marked reduction in lower frequency power. However, it may be considered a replication of the report of Alper et al. (1990) of increased relative alpha in abstinent cocaine abusers. Altered interhemispheric EEG relationships have not been reported previously in abstinent

Research 58 (1995) 247-257

cocaine-preferring polysubstance abusers. Duration of marijuana use and lifetime exposure to alcohol and cocaine are correlated with measures of interhemispheric power asymmetry. Conlirmation awaits replication with larger groups of subjects. The usefulness of QEEG analyses in a clinical setting remains controversial (Fisch and Pedley, 1989; John, 1989). The present study bears on at least two of the points of controversy identified by Fisch and Pedley: (1) it was a controlled study that included “blind” data analysis; (2) it was an independent, controlled corroborating study of Alper et al. (1990). Attention should be drawn to the Neurometric normative data base that was used in this study. Criteria for normality for inclusion in the normative data base, in addition to artifact control in recording and analyses, included being selfsupporting and functioning in job- or householdrelated activities, no history of head injury or loss of consciousness, no history of EEG abnormalities or neurological disorders, no current prescription medications (except antihypertensives), no history of drug or alcohol abuse, no subjective complaints of cognitive dysfunction, and IQ estimated to be within the normal range (Prichep et al., 1986). Investigators in eight countries have found that normal subjects display few QEEG values that fall outside normal predicted values. This is also our experience in QEEG analyses of 50 control subjects. We did not present our own control subject data as a comparison group because they do not match our index subjects in age. A major advantage is realized by using the normative data base. It should be recognized that the data set was acquired under the same recording conditions at different sites (John et al., 1988), which reduces the likelihood of idiosyncratic data. The availability of the Neurometric normative data sets permits direct comparison of QEEG results between laboratories. Results based on the normative data base yield an index of the extent to which a group of subjects under study differs from that data set. That data set is widely available whereas a unique data set from a laboratory such as ours is not. Thus, results based on the Neurometric normative data base may be more generalizable than those

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based on locally obtained comparison groups. Further, it should be noted that age-regressed QEEG data of index subjects are compared to the age-regressed normative sample. This tends to reduce but not necessarily eliminate age-related influences. Alper et al. (1990) found increased absolute and relative alpha values. We confirm this finding only for relative measures of alpha activity. Alper et al. (1990) reported high-amplitude alpha. This observation appears to be related to the pattern-alpha we report. Their data, particularly the middle subject of their Fig. 2, illustrates a 2.5-s portion of the EEG which is similar to that of the C-complexes reported here. It should be noted that pattemalpha differs from the hypersynchronous alpha seen in chronic cannabis abusers (Struve et al., 1989, 1991). Electroencephalographers may tend to interpret C-complexes as vertex waves associated with drowsiness. Such interpretations do not appear to be compatible with the overall pattern of the C-complexes or the circumstances in which they are recorded. These waves lack the waxing and waning of alpha and the slow lateral eye drift seen in drowsiness. In our subjects, C-complexes are seen in those who have had a history of concurrent cocaine, alcohol, and marijuana abuse. We have not observed such patterns in abusers of marijuana alone, cocaine and marijuana, cocaine and heroin, or abusers of alcohol alone; data on these subjects are not presented here. Alper et al. (1990) reported their subjects used alcohol in association with periods of cocaine use, but they did not comment on the use of cannabis. It is tempting to speculate that C-complexes may be a residual effect of a (possibly toxic) interaction between cocaine and alcohol. A potential mechanism for an interaction between a stimulant - cocaine - and a depressant - alcohol - is cocaethylene. Cocaethylene is a cocaine metabolite uniquely produced by the liver in the presence of alcohol (Hearn et al., 1991; Hime et al., 1991; Jatlow et al., 1991; Roberts et al., 1992). According to Steriade et al. (1990), one type of pathological wave within the theta frequency is a slowing down of the mean alpha frequency, which is seen in mild degrees of renal or hepatic encephalopathies and mild to moderate hypoxia,

255

cerebrovascular disease, and dementias. The slowing of alpha into the theta band reported here as part of the C-complex may reflect a type of subclinical metabolically induced EEG deviation brought about by this cocaine metabolite or other metabolic factors which may have a long-lasting neurotoxic effect. Studies of EEG with concurrent measures of cocaine metabolites may shed light on this conjecture. Another issue deals with the mechanisms by which chronic substance abuse produces lower than normal delta activity during abstinence. Speculation on this point is based on neurotransmitter-neurophysiological interactions derived from in vivo studies on infrahumans and on in vitro studies of human and infrahuman brain tissue. Several basic types of electrophysiological responding have been identified in thalamic and/or cortical neurons. These include cells exhibiting burst-firing patterns, regular spiking, thin spiking, or tonic firing (McCormick, 1992). Burst-firing neurons appear to have the neuroanatomical localization and physiological characteristics compatible with generation of delta activity. Delta waves are thought to be generated by dipoles between superficial cortical layers and layer V that reflect sequences of excitatory and inhibitory processes of cortical neurons (Steriade et al., 1990). Burst-firing cells are thought to be pyramidal cells, found predominantly in layer V, with apical dendrites that ascend superficially into layer I. Burst-tiring thalamic neurons and burstfiring cortical neurons have been found to change firing patterns from rhythmic burst firing in the delta frequencies to tonic single spike activity by tonic depolarization. That is, changes in tonic depolarization can switch the firing pattern of a neuron from burst tiring to single spike firing and vice versa. The above discussion can be considered in relationship to the view that chronic use of cocaine results in down-regulation of the major biogenic amines: dopamine, norepinephrine, and serotonin. If down-regulation is associated with cocaine use, then up-regulation during abstinence would be predicted. Burst-firing cell rhythmic activity, which has frequency components in the delta band, can be decreased by increased levels of

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several neurotransmitters: dopamine, norepinephrine, serotonin, and acetylcholine. These would be up-regulated during abstinence. Several neurotransmitters - serotonin, norepinephrine, histamine, and acetylcholine - have been shown to switch burst-firing cells to tonic firing via such depolarization when applied to the neurons (McCormick, 1992). This could provide a substrate for the reduced delta activity. Noradrenalin applied to cortical pyramidal cells results in both excitation and inhibition. Excitation is thought to be due to the activation of & adrenergic receptors, while inhibition is thought to be due to activation of ar-adrenergic receptors. Stimulation of the locus ceruleus, which contains cells of origin of norepinephrine, suppresses neuronal activity in layers II-IV and is facilitative in layers V and VI. Facilitation would, presumably, be a reflection of depolarization, switching from burst firing to single firing and reduction of delta activity. Application of serotonin to cortical neurons also results in both excitation and inhibition, which can change from one to the other depending on the basal firing rate of the neuron, increasing the “signal-to-noise” ratio of neurons (Foote and Morrison, 1986; McCormick, 1992). Application of dopamine generally results in inhibition of neuronal activity (Bunney and Aghajanian, 1976). Reduction in cholinergic activity appears to be associated with increased incidence of delta waves (Detari and Vanderwolf, 1987). This is compatible with observations that application of acetylcholine or noradrenalin depolarizes burst-firing neurons in layer V out of a slow oscillatory mode and into a single spike mode of activity (McCormick, 1992). All three of the former would be increasing with up-regulation secondary to cocaine abstinence. The extent to which a model of pharmacological modulation of delta activity is tenable can be tested experimentally with pharmaceutical agents that alter activity of specific neurotransmitters. Postsynaptic blockade of adrenergic receptors should prevent tonic depolarization of burst-firing cells and yield increased delta activity. Reuptake blockade with the subsequent increase in postsynaptic activation would result in tonic depolarization of burst-firing cells to regular spiking and decreased delta activity. Cholinergic agonists

should reduce delta activity, while cholinergic antagonists should increase delta activity. Identilication of those compounds that increase or decrease EEG delta activity promises to shed light on the mechanisms of delta generation and contribute to our understanding of the neurophysiological alterations that accompany chronic polysubstance abuse. Acknowledgments This research was supported, in part, by DA06728 from the National Institute of Drug Abuse, the Fulbright Program (Dr. D.V. Ercegovac was a Senior Fulbright Scholar), BSRG MO1 -RROO349, GCRC S07-RR05417, and the Einstein Society. References Alper, K.R., Chabot, R.J., Kim, A.H., Prichep, L.S. and John, E.R. (1990) Quantitative EEG correlates of crack cocaine dependence. Psychiatry Res Neuroimaging 35, 95- 105. Amass, L., Nardin, R., Mendelson, J.H., Teoh, SK. and Woods, B.T. (1992) Quantitative magnetic resonance imaging in heroin- and cocaine-dependent men: a preliminary study. Psychiatry Res Neuroimaging 45, 15-23. American Psychiatric Association. (1987) DSM-III-R: Diagnostic and Statistical Manual of Mental Disorders. 3rd rev. edn. American Psychiatric Press, Washington, DC. Bunney, B.S. and Aghajanian, G.K. (1976) Dopamine and norepinephrine innervated cells in the rat prefrontal cortex: pharmacological differentiation using microiontophoretic techniques. Life Sci 19, 1783-1792. Cascella, N.G., Pearlson, G., Wong, D.F., Broussolle, E., Nagoshi, C., Margolin, R.A. and London, E.D. (1991) Effects of substance abuse on ventricular and sulcal measures assessed by computerized tomography. Br J Psychiatry 159, 217-221. Cornwell, A., Roemer, R.A., Dcwart, D.B. and Jackson, P. (1993) Paroxysmal EEG activity in cocaine abstinence. NIDA Res Monogr 141, 163. Detari, L. and Vanderwolf, C.H. (1987) Activity of cortically projecting and other basal forebrain neurons during large slow wave and cortical activation in anesthetized cat. Brain Res 437, I-8. Dhuna, A., Pascual-Leone, A., Langendorf, F. and Anderson, D.C. (1991) Epileptogenic properties of cocaine in humans. Neurotoxicology 12, 62 l-626. Fisch, B.J. and Pedley, T.A. (1989) The role of quantitative EEG topographic mapping or “neurometrics” in the diagnosis of psychiatric and neurological disorders: the cons. Electroencephalogr Clin Neurophysiol 73, 5-9. Foote, S.L. and Morrison, J.H. (1986) Extrathalamic modulation of cortical function. Annu Rev Neurosci IO, 67-95.

R.A. Roemer et al. /Psychiatry Research 58 (1995) 247-257

Hearn,

W.L.,

Flynn,

D.D.,

Hime, G.W.,

Rose,

S., Cofinio,

J.C., Mantero-Atienza, E., Wetli, C.V. and Mash, DC. (1991) Cocaethylene: a unique cocaine metabolite displays high affinity for the dopamine transporter. J Neurochem 56, 698-701. Hime, G.W., Hearn, G.W., Rose, S. and Cofinio, .I. (1991) Analysis of cocaine and cocaethylene in blood and tissues by GC-NPD and GC-ion trap mass spectrometry. J Anal Toxicol 15, 241-245. Holman, B.L., Carvalho, P.A., Mendelson, J., Teoh, SK., Nardin, R., Hallgring, E., Hebben, N. and Johnson, K.A. (1991) Brain perfusion is abnormal in cocaine-dependent polydrug users: a study using technetium-99m-HMPAO and ASPECT. J A&f Med 32, 1206-1210. Holman, B.L., Mendelson, J., Garada, B., Teoh, S.K., Hallgring, E., Johnson, K.A. and Mello, N.K. (1993). Regional cerebral blood flow improves with treatment in chronic cocaine polydrug users. .I Nucl Med 34, 723-727. Jatlow, P., Elsworth, J.D., Bradberry, C.W., Winger, G., Taylor, J.R., Russel, R. and Roth, R.H. (1991) Cocaethylene: a neuropharmacologically active metabolite associated with concurrent cocaine-ethanol ingestion. Life Sci 48, 1787-1794. John, E.R. (1989) The role of quantitative EEG topographic mapping or “neurometrics” in the diagnosis of psychiatric and neurological disorders: the pros. Elecrroencephalogr Clin Neurophysiol 73, 2-4. John, E.R., Prichep, L.S., Fridman, J. and Easton, P. (1988) Neurometrics: computer-assisted differential diagnosis of brain MacKay, Fein, lites

dysfunctions. Science 239, 162- 169. S., Meyerhoff, D.J., Dillon, W.P., Weiner, M.W. and G. (1993) Alteration of brain phospholipid metaboin cocaine-dependent polysubstance abusers. Biol

Psychiatry 34, 261-264. McCormick, D.A. (1992) Neurotransmitter thalamus and cerebral cortex and neuromodulation of thalamocortical

actions in the their role in activity. Prog

Neurobiol 39, 337-388. Pet-per, J.A. and Van Thiel, D.H. (1992) Cardiovascular complications of cocaine abuse. Recent Dev Alcohol 10, 343-361. Prichep, L.S., Lieber, A.L., John, E.R., Alper, K., GomezMont, F., Essig-Peppard, T. and Flitter, M. (1986) Quantitative EEG in depressive disorders. In: Shagass, C., Josiassen, R.C. and Roemer, R.A. (Eds.), Brain Electrical Potentials and Psychopathology. Elsevier Science Publishing Co., Inc., New York, pp. 223-244. Roberts, S.M., Roth, L., Harbison, R.D. and James, R.C. (1992) Cocaethylene hepatotoxicity in mice. Biochem Pharmacol43,

1989-1995.

251

Roemer, R.A., Shagass, C. and Dewart, D. (1993) Evoked potential excitability cycles during early cocaine abstinence. NIDA Res Monogr 132. 342. Spitzer, R.L. and Williams, J.B.W. (1986) Structured Clinical Interview for DSM-III-R - Patient Version. New York State Psychiatric Institute, New York. Steriade, M., Gloor, P., Llinas, R.R., Lopes da Silva, F.H. and Mesulam, M.M. (1990) Basic mechanisms of cerebral rhythmic activities. Electroencephalogr Clin Neurophysiol 76, 481-508. Strickland, T.L., Mena, I., Villanueva-Meyer, J., Miller, B.L., Cummings, J., Mehringer, CM., Satz, P. and Myers, H. (1993) Cerebral perfusion and neuropsychological consequences of chronic cocaine use. f Neuropsychiatry Cfin Neurosci 5, 419-27. Struve, F.A., Straumanis, J.J., Patrick, G. and Price, L. (1989) Topographic mapping of quantitative EEG variables in chronic heavy marihuana users: empirical findings with psychiatric patients. Clin Electroencephalogr 20, 6-23. Struve, F., Straumanis, J., Patrick, G. and Raz, Y. (1991) Quantitative EEG studies of chronic THC abuse: (I) Replications of topographic findings, (2) Within EEG band spectral power shifts, (3) Discriminant function analysis of chronic use vs. non-use. NIDA Res Monogr 105, 608-609. Tumeh, S.S., Nagel, J.S., English, R.J., Moore, M. and Holman, B.L. (1990) Cerebral abnormalities in cocaine abusers: demonstration by SPECT perfusion brain scintigraphy: work in progress. Radiology 176, 821-824. Volkow, N.D., Fowler, J.S., Wang, G.J., Hitzemann, R., Logan, J., Schlyer, D., Dewey, S.L. and Wolf, A.P. (1993) Decreased dopamine D, receptor availability is associated with reduced frontal metabolism in cocaine abusers. Synapse 14, 169-177. Volkow, N.D., Fowler, J.S., Wolf, A.P., Hitzemann, R., Dewey, S., Bendriem, B., Alpert, R. and Hoff, A. (1991) Changes in brain glucose metabolism in cocaine dependence and withdrawal. Am J Psychiatry 148, 621-626. Volkow, N.D., Fowler, J.S., Wolf, A.P., Schlyer, D., Shiue, C.Y., Alpert, R., Dewey, S.L., Logan, J., Bendriem, B., Christman, D., Hitzemann, R. and Henn, F. (1990). Effects of chronic cocaine abuse on postsynaptic dopamine receptors. Am J Psychiatry 147, 719-724. Volkow, N.D., Mullanie, N., Gould, K.L., Adler, S. and Krajewski, K. (1988) Cerebral blood flow in chronic cocaine users. Br J Psychiatry 152, 641-648. Weber, D.A., Franceschi, D., Ivanovic, M., Atkins, H.L., Cabahug, C., Wong, C.T. and Susskind, H. (1993). SPECT and planar brain imaging in crack abuse: iodine-123iodoamphetamine uptake and localization. J Nucl Med 34. 899-907.