Association between quantitative EEG and neurocognition in ...

Clinical Neurophysiology 115 (2004) 194–198 www.elsevier.com/locate/clinph

Association between quantitative EEG and neurocognition in methamphetamine-dependent volunteers Thomas F. Newton*, Ari D. Kalechstein, David J. Hardy, Ian A. Cook, Liam Nestor, Walter Ling, Andrew F. Leuchter Department of Psychiatry and Biobehavioral Sciences, Neuropsychiatric Institute, UCLA School of Medicine, Room A7-372, 760 Westwood Plaza, Los Angeles, CA 90024, USA Accepted 5 September 2003

Abstract Objective: Exposure to methamphetamine is associated with long-lasting reductions in markers for dopaminergic neurons in preclinical models and in humans. These changes may be associated with alterations in brain electrical activity and in cognition. Methods: The sample included 9 methamphetamine-dependent subjects and 10 non-drug-using volunteers. Methamphetamine-dependent subjects were hospitalized for 4 days to document abstinence; non-drug-using volunteers were studied as outpatients. EEGs were recorded in the eyes-closed resting state, and absolute EEG power in each frequency band (0.5– 4 Hz, 4 – 8 Hz, 8 – 12 Hz, and 12 – 20 Hz) was measured using a fast Fourier transform. EEG power was log-transformed prior to analysis. Cognition was measured using computerized reaction time tasks. Results: Within the methamphetamine-dependent group only, increased theta quantitative EEG (QEEG) power correlated significantly with reaction time on tasks that were more difficult or that were degraded by fatigue. Increased theta QEEG power also correlated with reduced accuracy on a working memory task. Conclusions: Increased QEEG power in the theta band is associated with worse performance on reaction time tasks in the methamphetamine-dependent sample but not in the non-drug-using volunteers. Significance: Methamphetamine dependence is associated with pathological alterations in brain electrical activity and in cognitive performance. QEEG appears to provide a sensitive measure of methamphetamine-associated alterations in brain function. q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. Keywords: Addiction; Methamphetamine; Quantitative EEG; Reaction time

1. Introduction Methamphetamine dependence is a global, growing public health problem (Anglin et al., 2000; WHO, 1996). Because methamphetamine dependence is associated with neurotoxic effects in humans in post-mortem studies (Wilson et al., 1996), a series of studies have examined the neurobiological consequences of methamphetamine dependence in vivo using neuroimaging (Chang et al., 2002; Ernst et al., 2000; Fowler et al., 2001; McCann et al., 1998; Sekine et al., 2001), and using quantitative EEG (QEEG) (Newton et al., 2003). Two of these studies also * Corresponding author. Tel.: þ1-310-267-0159; fax: þ 1-310-267-0162. E-mail address: [email protected] (T.F. Newton).

showed that these neuroimaging findings are associated with psychomotor slowing and with deficits in executive functioning (Chang et al., 2002; Volkow et al., 2001). In our previously reported study of QEEG in methamphetamine dependence, we found that patients with methamphetamine dependence had significantly increased power in delta and theta bands compared to non-drug-using controls. Based on these findings, together with results from others suggesting that methamphetamine dependence was associated with psychomotor slowing and deficits in executive functioning (Kalechstein et al., 2003), we sought to determine whether QEEG findings were associated with poorer performance on reaction time tests in volunteers with methamphetamine dependence or in non-drug-using control volunteers.

1388-2457/$30.00 q 2004 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/S1388-2457(03)00314-6

T.F. Newton et al. / Clinical Neurophysiology 115 (2004) 194–198

2. Methods 2.1. Participants Participants included 9 non-treatment seeking, methamphetamine-dependent volunteers and 10 age- and sexmatched non-drug-using volunteers recruited for assessment of reaction time from a sample that was previously described (Newton et al., 2003). Three participants from the larger sample chose not to participate in this aspect of the study and are not included for that reason. Non-drugusing control subjects were recruited from the same regions as methamphetamine-dependent subjects in order to maximize the degree of similarity between the two groups (see Table 1 for demographic profile). The drug-dependent sample met DSM-IV criteria for methamphetamine dependence and did not meet criteria for abuse or dependence on other drugs. None of the control subjects met DSM IV criteria for abuse or dependence on any drug. None of the subjects met criteria for Axis I psychotic or mood disorders by the SCID, administered by a masters-level clinician (Spitzer et al., 1995). Estimated premorbid intelligence was established using the North American Reading Test (Nelson, 1982). Potential participants were excluded for a history of stroke, traumatic brain injury (loss of consciousness greater than 20 min), epilepsy, attention deficit disorder, or for testing HIV seropositive. Methamphetamine-dependent subjects reported a mean use of 2.0 g of methamphetamine per week during the 6 months prior to the study. The routes of methamphetamine administration reported were snorting, smoking and using intravenously. Participants gave written informed consent after being appraised of the study risks and were reimbursed for participation. Methamphetamine-dependent subjects were hospitalized in the general clinical research center (CRC) at UCLA for the duration of the study, with daily urine testing to ensure abstinence from illicit drugs. 2.2. EEG assessment EEGs were recorded on day 4 of the study. The procedures used and results have been described previously Table 1 Demographic data for the study population Variable

Non-drug volunteers (n ¼ 10)

Methamphetaminedependent (n ¼ 9)

Age (years) Education Estimated IQ Beck depression inventory Males/Females

35.7 (7.1) 13.3 (1.6) 108.6 (7.3) 9.5 (3.2) 8/2

33.2 (7.9) 11.7 (0.7)* 105.2 (7.6) 7.8 (6.0) 7/2

In upper portion of table, means are presented with standard deviations in parentheses. Last row of table presents frequency. *P , 0:05, two-tailed t test.

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(Newton et al., 2003). Briefly, participants were evaluated while resting in the eye-closed, maximally alert state in a sound-attenuated room. An electrode cap (ElectroCap, Eaton, OH) with 35 recording electrodes was placed according to the International 10– 20 System was used to record EEG data. A technician reviewed each EEG tracing and selected the first 20 – 32 s of artifact-free data for processing, with selections confirmed by a second technician. Subjects’ identity was masked. The QND system was used to calculated power in 4 frequency bands (0.5 –4 Hz, delta, 4 –8 Hz, theta, 8 –12 Hz, alpha, and 12 – 20 Hz, beta). EEG data were log-transformed prior to analysis to reduce skew. 2.3. Reaction time assessment Participants completed a simple reaction time task, a choice reaction time task, the N-back tasks, and a readministration of the simple reaction time task, in this order. All tasks were programmed with SuperLab (SuperLab, 1997) on a personal microcomputer and utilized a responsebox. Standardized instructions (both written and orally presented) were given for all 3 tasks. Participants were always instructed to respond as quickly and as accurately as possible. Reaction time was assessed only on correct responses. Reaction time tasks were completed at 13:00 h, following lunch at noon. 2.3.1. Simple reaction time task This task involved the presentation of a series of letters, one at a time, at the center of a computer monitor. Participants were instructed to press a red button on the response box with their dominant forefinger as quickly as possible upon the presentation of a letter. Letters were pseudo-randomly presented from the set A, a, G, g, T, t, H, h. Letters were black on a white background and subtended approximately 1:9 £ 1:68. Each letter was presented for 500 ms, with a subsequent letter presented 2500 ms later. A total of 30 trials were presented. 2.3.2. Choice reaction time task The choice reaction time task involved the same presentation of letters. This time, participants were instructed to press using the dominant hand a red button upon the presentation of the letter G, g, H, or h or press the blue button upon the presentation of A, a, T, or t. A total of 30 trials were presented. 2.3.3. Working memory task The working memory task was a variation of an N-back that has been used by Smith et al. (1996). Participants were presented with a series of letters, one at a time, at the center of a computer monitor. In the 1-back condition, a ‘yes’ response was required (with a dominant hand finger-press of a blue button) if the verbal identity of the presented letter matched the verbal identity of the letter presented right

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before it. Otherwise a ‘no’ response was required (dominant hand finger-press of a red button). In the 2-back condition, a ‘yes’ response was required if the verbal identity of the presented letter matched the verbal identity of the letter two trials back. Otherwise a ‘no’ response was required. For both 1-back and 2-back conditions there was an equal chance of a trial requiring a ‘yes’ or ‘no’ response, and letters were pseudo-randomly presented from the set A, a, G, g, T, t, H, h. Note that case of the letter was not relevant to matching verbal identity. Letters were black on a white background and subtended approximately 1:9 £ 1:68. Each letter was presented for 500 ms, with a subsequent letter presented 2500 ms later. There were a total of 40 trials, with 20 trials each for the 1-back and 2-back conditions, presented in this order. Participants completed 10 trials of practice (or more if necessary) before performing each condition. 2.4. Statistical analyses Given the relatively small sample size, a series of procedures were used to minimize the likelihood of Type I error. The first step was to reduce the number of QEEG indices and reaction time measures to be analyzed. For example, the QEEG indices were limited to mean absolute power recorded over the entire scalp in the theta band. This decision was based on our earlier finding that methamphetamine dependence was associated with abnormalities in the delta and theta bands but not the alpha and beta bands. We further focused on activity in the theta band based on the findings from studies of patients with hepatic encephalopathy, closed head trauma, Parkinson’s disease, and prolonged sleep deprivation, in which theta band abnormalities predominated and were correlated with relatively subtle cognitive deficits (Amodio et al., 1998; Fenton, 1996; Lorenzo et al., 1995; Soikkeli et al., 1991). Nonparametric statistical models were used to further reduce the likelihood of Type I error by minimizing the probability that outliers or skewed data distributions would affect the results. Spearman correlations were used to evaluate the associations between QEEG indices and reaction time measures. The Mann-Whitney U test was used to evaluate between-group differences. Because it was hypothesized a priori that poorer performance on the reaction time tests would be associated with increased mean power in theta band QEEG power, one-tailed tests of significance were used. Reaction time data were analyzed descriptively as differences between the groups were not a priori hypothesized.

3. Results As shown in Table 1, the study population consisted primarily of young adult men whose intellect was in the average range. The sample reported that they were experiencing minimal levels of depression.

Table 2 Performance on information processing tasks and QEEG values Task/Measure

Non-drug volunteers

Methamphetaminedependent

Simple reaction time 1 Simple reaction time 2 Choice reaction time SRT2 2 SRT1 CRT 2 SRT1 N-Back 1 (reaction time) N-Back 2 (reaction time) N-Back 1 (% Accuracy) N-Back 2 (% Accuracy)

282 (43) 356 (202) 668 (105) 74 (225) 386 (101) 716 (151) 997 (278) 97.8 (2.6) 75.4 (9.6)

278 (65) 392 (216) 612 (94) 114 (218) 334 (107) 744 (135) 1022 (391) 90.9 (4.8) 65.8 (20.2)

In upper portion of table, means (in milliseconds) are presented with standard deviations in parentheses. Reaction time data were analyzed using analysis of variance and there were no significant differences. Percent accuracy data were analyzed using non-parametric Mann-Whitney U tests, with no significant differences.

Methamphetamine-dependent group had fewer years of education than the control group (t ¼ 2:8, df ¼ 17, P , 0:05); however, education was not correlated with performance on the reaction time measures (P . 0:10). The QEEG power values obtained from this subset of 9 volunteers (delta power ¼ 58:2 mV2/Hz (SD ¼ 21:5), theta power ¼ 46:9 (SD ¼ 39:7)) were very similar to the values previously reported for the complete sample of 11 (delta power ¼ 58:6 (SD ¼ 20:8), theta power ¼ 45:5 (SD ¼ 39:2)). Table 2 shows reaction time and response accuracy data from both the control and the methamphetamine-dependent groups. There were no statistically significant group differences on any of these measures. Spearmen correlations between reaction time tasks and QEEG power are shown in Table 3. Within the methamphetamine-dependent group, increased theta QEEG power correlated significantly with increased median reaction time on the simple reaction time task assessed after completion of a computerized reaction time battery (SRT2), change in simple reaction time over time (SRT2 2 SRT1), and choice reaction time, after Table 3 Spearman correlations between information processing measures and theta EEG power Task/Measure

Non-drug volunteers

Methamphetaminedependent

Simple reaction time 1 Simple reaction time 2 Choice reaction time SRT2 2 SRT1 CRT 2 SRT1 N-Back 1 (reaction time) N-Back 2 (reaction time) N-Back 1 (% Accuracy) N-Back 2 (% Accuracy)

– 0.60 – – – – – – 20.53

– 0.81** – 0.63* 0.60* – – – 20.67*

Only correlations greater than 0.5 are shown. *P , 0:05. **P , 0:01. Significance levels are for one-tailed tests.


Fig. 1. Simple reaction time 2 as a function of theta EEG power. Both the reaction time task and the QEEG measures are log-transformed. Spearman r ¼ 0:81, P , 0:01.

controlling for simple reaction time (CRT 2 SRT1). Reduced accuracy on the N-back 2 task was significantly correlated with increased theta power. Scatterplots of simple reaction time (2) and percent accuracy on the N-back 2 task against theta EEG power are shown in Figs. 1 and 2.

4. Discussion Increased EEG power correlated with slower performance on simple reaction time test (SRT2), but only when assessed following administration of the entire battery. Moreover, fatigue (indexed by SRT2 2 SRT1), was associated with increased EEG power as well. Increased EEG power correlated with slower performance on the complex reaction time task, but only after controlling for

Fig. 2. N-Back 2 percent accuracy as a function of theta EEG power. The QEEG measure is log-transformed. Spearman r ¼ 20:67, P , 0:05.

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individual differences in simple reaction time, indexed by SRT1. Increased theta band QEEG power was associated reduced accuracy on the 2-back task, the more difficult of two tests of working memory. These findings showed that the resultant QEEG abnormalities are likely to manifest as psychomotor slowing. This was most evident when methamphetamine-dependent individuals perform tasks that include a decision-making component (e.g. CRT 2 SRT1), and when the tasks index performance degraded by fatigue (e.g. SRT2 2 SRT1) (Orton and Gruzelier, 1989). Moreover, as task difficulty increases (e.g. the 2-back task), decision-making ability is compromised. There is clear evidence from both preclinical and clinical studies suggesting that methamphetamine produces a range of neurotoxic effects, and these may have contributed to the observed associations in the patient population but not in the non-drug-using controls. In baboons, monkeys, and rats, administration of methamphetamine has been associated with long-lasting reductions in neuronal expression of dopamine neuronal markers, including the DAT, tyrosine hydroxylase, and others (Melega et al., 1998; Ricaurte et al., 1980; Villemagne et al., 1998). Similar changes have been reported in human methamphetamine users (McCann et al., 1998; Sekine et al., 2001; Volkow et al., 2001; Wilson et al., 1996). Working memory and executive function have been shown to be critically dependent on intact dopamine neurotransmission, especially in prefrontal cortex (Sawaguchi and Goldman-Rakic, 1994; Williams and Goldman-Rakic, 1995), suggesting that methamphetamine associated disruption in dopaminergic neurotransmission may account for the observed abnormalities in decisionmaking speed and verbal working memory in the methamphetamine-dependent group. Similarly, pharmacologic disruption of dopaminergic systems by treatment with D1 receptor antagonists has been shown to increase response latency, whereas treatment with D2 receptor antagonists preferentially impaired response accuracy (Harrison et al., 1997; Shoaib et al., 2001). Similar mechanisms may account for the EEG abnormalities observed in methamphetamine dependence. In a preclinical study, catecholamine depletion was associated with increases in low frequency EEG activity (Nakagawa et al., 2000). Further analysis of the power spectra underlying the observed changes in the conventional EEG bands would clarify how methamphetamine dependence altered EEG activity and resulted in increases power in delta and theta EEG bands. Low-frequency EEG activity has also been linked to certain cognitive deficits, including verbal memory impairment (Rice et al., 1991). These observations suggest potential mechanisms by which methamphetamine dependence could be associated with both increases in theta EEG activity and subtle slowing in processing speed and working memory. Such cognitive abnormalities may be subtle, in view of the fact that no

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significant group differences in cognitive performance were observed although raw scores seemed to suggest some degree of cognitive slowing and memory impairment in the methamphetamine group. Nonetheless, considering the relatively small sample sizes in this study, the present findings show considerable promise in delineating the mechanisms of neurophysiological abnormalities and mild cognitive slowing in methamphetamine-dependent adults. There are several limitations to this study. With the relatively small sample size, we were unable to evaluate risk factors within the methamphetamine group, such as duration or amount of methamphetamine use, other drug use, or other factors that might have affected the results. Both groups consisted primarily of males, so we could not determine effects of gender. Finally, the study design used did not allow determination of whether these abnormalities preceded or were caused by methamphetamine dependence.

Acknowledgements This research was supported in part by grants from the National Institutes of Health (DA50038, DA00388, DA07272, MH01483, MH01165 and MO1-RR-00865.)

References Amodio P, Marchetti P, DelPiccolo F, Rizzo C, Iemmolo RM, Caregaro L, Gerunda G, Gatta A. Study on the Sternberg paradigm in cirrhotic patients without overt hepatic encephalopathy. Metab Brain Dis 1998; 13:159–72. Anglin MD, Burke C, Perrochet B, Stamper E, Dawud-Noursi S. History of the methamphetamine problem. J Psychoactive Drugs 2000;32:137– 41. Chang L, Ernst T, Speck O, Patel H, DeSilva M, Leonido-Yee M, Miller EN. Perfusion MRI and computerized cognitive test abnormalities in abstinent methamphetamine users. Psychiatry Res 2002;114:65–79. Ernst T, Chang L, Leonido-Yee M, Speck O. Evidence for long-term neurotoxicity associated with methamphetamine abuse: A 1H MRS study. Neurology 2000;54:1344–9. Fenton GW. The postconcussional syndrome reappraised. Clin Electroencephalogr 1996;27:174–82. Fowler JS, Volkow ND, Logan J, Franceschi D, Wang GJ, MacGregor R, Shea C, Garza V, Pappas N, Carter P, Netusil N, Bridge P, Liederman D, Elkashef A, Rotrosen J, Hitzemann R. Evidence that L-deprenyl treatment for one week does not inhibit MAO A or the dopamine transporter in the human brain. Life Sci 2001;68:2759–68. Harrison AA, Everitt BJ, Robbins TW. Central 5-HT depletion enhances impulsive responding without affecting the accuracy of attentional performance: interactions with dopaminergic mechanisms. Psychopharmacology (Berl) 1997;133:329 –42. Kalechstein AD, Newton TF, Green MF. Methamphetamine dependence is associated with neurocognitive impairment in the initial phases of abstinence. J Neuropsychiatry Clin Neurosci 2003;15:215–20. Lorenzo I, Ramos J, Arce C, Guevara MA, Corsi-Cabrera M. Effect of total sleep deprivation on reaction time and waking EEG activity in man. Sleep 1995;18:346– 54. McCann UD, Wong DF, Yokoi F, Villemagne V, Dannals RF, Ricaurte GA. Reduced striatal dopamine transporter density in abstinent

methamphetamine and methcathinone users: evidence from positron emission tomography studies with [11C]WIN-35,428. J Neurosci 1998; 18:8417– 22. Melega WP, Lacan G, Harvey DC, Huang SC, Phelps ME. Dizocilpine and reduced body temperature do not prevent methamphetamine- induced neurotoxicity in the vervet monkey: [11C]WIN 35,428-positron emission tomography studies. Neurosci Lett 1998;258:17–20. Nakagawa T, Ukai K, Ohyama T, Gomita Y, Okamura H. Effect of dopaminergic drugs on the reserpine-induced lowering of hippocampal theta wave frequency in rats. Nihon Shinkei Seishin Yakurigaku Zasshi 2000;20:71–6. Nelson HE. National Adult Reading Test (NART): Test Manual, NFER Nelson, Windsor, UK; 1982. Newton TF, Cook IA, Kalechstein AD, Duran S, Monroy F, Ling W, Leuchter AF. Quantitative EEG abnormalities in recently abstinent methamphetamine-dependent individuals. Clin Neurophysiol 2003;114:410–5. Orton DI, Gruzelier JH. Adverse changes in mood and cognitive performance of house officers after night duty. Br Med J 1989;298:21–3. Ricaurte GA, Schuster CR, Seiden LS. Long-term effects of repeated methylamphetamine administration on dopamine and serotonin neurons in the rat brain: a regional study. Brain Res 1980;193:153 –63. Rice DM, Buchsbaum MS, Hardy D, Burgwald L. Focal left temporal slow EEG activity is related to a verbal recent memory deficit in a nondemented elderly population. J Gerontol 1991;46:P144–51. Sawaguchi T, Goldman-Rakic PS. The role of D1-dopamine receptor in working memory: local injections of dopamine antagonists into the prefrontal cortex of rhesus monkeys performing an oculomotor delayed-response task. J Neurophysiol 1994;71:515–28. Sekine Y, Iyo M, Ouchi Y, Matsunaga T, Tsukada H, Okada H, Yoshikawa E, Futatsubashi M, Takei N, Mori N. Methamphetamine-related psychiatric symptoms and reduced brain dopamine transporters studied with PET. Am J Psychiatry 2001;158:1206–14. Shoaib M, Bizarro L, Stolerman IP. Impairments in a sustained attention task following dopaminergic, noradrenergic and glutamatergic receptor blockade in rats. J Psychopharmacol 2001;15(3 Suppl):A60. Smith EE, Jonides J, Koeppe RA. Dissociating verbal and spatial working memory using PET. Cereb Cortex 1996;6:11– 20. Soikkeli R, Partanen J, Soininen H, Paakkonen A, Riekkinen Sr P. Slowing of EEG in Parkinson’s disease. Electroenceph clin Neurophysiol 1991; 79:159–65. Spitzer R, Williams J, Gibbon M. Structured clinical interview for DSM-IV (SCID). New York: New York State Psychiatric Institute: Biometrics Research; 1995. SuperLab, SuperLab. Phoenix, AZ: Cedrus Corporation; 1997. Villemagne V, Yuan J, Wong DF, Dannals RF, Hatzidimitriou G, Mathews WB, Ravert HT, Musachio J, McCann UD, Ricaurte GA. Brain dopamine neurotoxicity in baboons treated with doses of methamphetamine comparable to those recreationally abused by humans: evidence from [11C]WIN-35,428 positron emission tomography studies and direct in vitro determinations. J Neurosci 1998;18:419–27. Volkow ND, Chang L, Wang GJ, Fowler JS, Leonido-Yee M, Franceschi D, Sedler MJ, Gatley SJ, Hitzemann R, Ding YS, Logan J, Wong C, Miller EN. Association of dopamine transporter reduction with psychomotor impairment in methamphetamine abusers. Am J Psychiatry 2001;158:377 –82. WHO, Worldwide amphetamine abuse – ‘a particular concern for WHO’ World Health Organization takes the lead in fighting public health consequences of psychostimulant, ‘Epidemics’. WHO press release, 77/ Rev. Geneva: WHO; 1996. Williams GV, Goldman-Rakic PS. Modulation of memory fields by dopamine D1 receptors in prefrontal cortex. Nature 1995;376:572– 5. Wilson JM, Kalasinsky KS, Levey AI, Bergeron C, Reiber G, Anthony RM, Schmunk GA, Shannak K, Haycock JW, Kish SJ. Striatal dopamine nerve terminal markers in human, chronic methamphetamine users. Nat Med 1996;2:699–703.