Meth addiction diagnostics using EEG


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Kyongsik Yun, Hee-Kwon Park, Do-Hoon Kwon, Yang-Tae Kim, Sung-Nam Cho, Hyun-Jin Cho, Bradley S. Peterson, Jaeseung Jeong. "Decreased cortical complexity in methamphetamine abusers" (2012) Psychiatry Research: Neuroimaging

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Meth addiction diagnostics using EEG

  1. 1. PSYN-09834; No of Pages 7 Psychiatry Research: Neuroimaging xxx (2012) xxx–xxx Contents lists available at ScienceDirect Psychiatry Research: Neuroimaging j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / p s yc h r e s n sDecreased cortical complexity in methamphetamine abusersKyongsik Yun a, 1, Hee-Kwon Park b, 1, Do-Hoon Kwon c, Yang-Tae Kim c, Sung-Nam Cho c, Hyun-Jin Cho c,Bradley S. Peterson d, Jaeseung Jeong a, d,⁎a Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 305-701, Republic of Koreab Department of Neurology, Seoul National University Hospital, Seoul 110-744, Republic of Koreac Department of Psychiatry, Bugok National Hospital, Gyeongnam 635-890, Republic of Koread Department of Psychiatry, Columbia University, College of Physicians and Surgeons, New York, NY 10032 USAa r t i c l e i n f o a b s t r a c tArticle history: This study aimed to investigate if methamphetamine (MA) abusers exhibit alterations in complexity of theReceived 24 November 2010 electroencephalogram (EEG) and to determine if these possible alterations are associated with their abuseReceived in revised form 18 May 2011 patterns. EEGs were recorded from 48 former MA-dependent males and 20 age- and sex-matched healthyAccepted 11 July 2011 subjects. Approximate Entropy (ApEn), an information-theoretical measure of irregularity, of the EEGs wasAvailable online xxxx estimated to quantify the degree of cortical complexity. The ApEn values in MA abusers were significantlyKeywords: lower than those of healthy subjects in most of the cortical regions, indicating decreased cortical complexity ofMethamphetamine MA abusers, which may be associated with impairment in specialization and integration of cortical activitiesEEG owing to MA abuse. Moreover, ApEn values exhibited significant correlations with the clinical factorsCortical dynamics including abuse patterns, symptoms of psychoses, and their concurrent drinking and smoking habits. TheseApproximate Entropy findings provide insights into abnormal information processing in MA abusers and suggest that ApEn of EEG recordings may be used as a potential supplementary tool for quantitative diagnosis of MA abuse. This is the first investigation to assess the “severity-dependent dynamical complexity” of EEG patterns in former MA abusers and their associations with the subjects abuse patterns and other clinical measures. © 2012 Published by Elsevier Ireland Ltd.1. Introduction Methamphetamine (MA) is a potent neurotoxin causing long-term damage to the central nervous system. Animal studies suggest that The abuse of methamphetamine (“speed”) and its pure crystalline continuous administration of MA produces long-lasting reductions inform (“crystal meth”, “ice”, or “glass”) has reached epidemic pro- striatal dopamine (DA) concentrations, DA transporter levels, and rate-portions. The estimated lifetime prevalence of methamphetamine limiting synthetic enzymes, as well as autophagocytosis of the neuritisabuse is 5.3% in the United States, and 33 states exhibited a 100% and apoptosis of the DA neurons in the striatum (Ricaurte et al., 1980;increase in the numbers of people admitted to treatment centers for Wagner et al., 1980; Villemagne et al., 1998). In vivo studies on acutemethamphetamine abuse between the years of 1992 and 2001 (Office neurobiological effects of MA in humans have documented markedof Applied Studies, 2005). On the other side of the world, the United alterations to the DA neurotransmitter systems and rates of neuralNations reported that approximately 33.4 million people use meth- metabolism in the cerebrum and the basal ganglia. Recent neuroimagingamphetamine in Asia, particularly in eastern and southeast Asian studies have shown that long-term use of MA decreases the density ofcountries such as Japan and South Korea, where its abuse is one of the DA transporters in reward circuits (McCann et al., 1998; Sekine et al.,most pressing social concerns (Farrell et al., 2002; Chung et al., 2004; 2001; Volkow et al., 2001a,b; Sekine et al., 2003) and the density ofKulsudjarit, 2004). These behaviors frequently lead to profoundly serotonin transporters in cortical regions (Sekine et al., 2006). Inharmful social and public health consequences (Seivewright, 2000; particular, long-term MA abuse is associated with glucose hypometa-London et al., 2004; Sekine et al., 2006). Despite the high prevalence bolism in the frontal regions (Kim et al., 2005b), low activity in theand destructive effects of methamphetamine abuse, the long-term dorsolateral and ventromedial prefrontal cortices (Paulus, 2002), andeffects of methamphetamine on the neurodynamics of the cortical cortical structural abnormalities of the medial temporal lobe and thenetwork are poorly understood. cingulate-limbic cortex (Thompson et al., 2004; Kim et al., 2005a). These studies suggest that MA intoxication is not limited to the subcortical structures, but also extends to cortical regions. Only a few studies have investigated patterns of the electroenceph- ⁎ Corresponding author at: Department of Bio and Brain Engineering, KAIST, Daejeon305-701, Republic of Korea. Tel.: + 82 42 350 4319; fax: + 82 42 350 4310. alogram (EEG) that characterize MA abusers to detect electrophysio- E-mail address: (J. Jeong). logical abnormalities of their cortical networks and their associations 1 Indicating authors of equal contribution. with behavioral factors, including reduced working memory0925-4927/$ – see front matter © 2012 Published by Elsevier Ireland Ltd.doi:10.1016/j.pscychresns.2011.07.009 Please cite this article as: Yun, K., et al., Decreased cortical complexity in methamphetamine abusers, Psychiatry Research: Neuroimaging (2012), doi:10.1016/j.pscychresns.2011.07.009
  2. 2. 2 K. Yun et al. / Psychiatry Research: Neuroimaging xxx (2012) xxx–xxxperformance (Newton et al., 2004). Power spectrum analysis revealed (N = 20, average age = 34.5± 7.7 years, range= 23–48 years, all males)an apparent EEG slowing in MA abusers (Newton et al., 2003, 2004), but were recruited from Bugok National Hospital in South Korea. The MAcorrelations with abuse patterns and social factors were not examined. abusers were hospitalized patients who met the Diagnostic and While pre-clinical and clinical investigations have shown that Statistical Manual of Mental Disorders, 4th edition (DSM-IV) (Spitzermethamphetamine (MA) causes long-term damage to the DA reward et al., 1994) criteria for lifetime MA abuse (N = 31) or dependencecircuits resulting in motor and cognitive deficits (Volkow et al., 2001b; (N = 17). There were no significant correlations between abused andJohanson et al., 2006; McCann et al., 2008), but little is known about dependent patients in the period of MA use (p = 0.970), the age of firstdynamical disturbance of cortical network in MA abusers. The aim of the abuse (p = 0.437), and the cumulative amount of MA (p = 0.820). Allpresent study was to determine whether abstinent MA abusers exhibit subjects were men only because of extensive prior evidence that MA-alterations in complexity of the EEG. Tononi et al.(1998) suggested that induced neurotoxicity is sex-specific, particularly greater in men than inoptimal brain functioning requires the dynamic interplay between local women (Wagner et al., 1980; Dluzen et al., 2002; DAstous et al., 2005;specialization and global integration of brain activity. They proposed Kim et al., 2005b). They showed no signs of neurological abnormalitiesthat this optimal state produces complex activity and that a neural such as seizure, dyskinesia, or coma. MA abusers were excluded if theycomplexity measure is capable of estimating the optimal balance had a past or present history of a comorbid psychiatric illness exceptbetween localization and integration of neural networks (Tononi et al., substance abuse (DSM-IV axis I or II diagnosis). After complete1998; Tononi and Edelman, 1998; Sporns et al., 2000). Indeed, reduced description of the study, written informed consent was obtained fromcomplexity of EEG patterns has been reported in patients with all subjects prior to participation, in compliance with the procedures ofAlzheimers disease (Jeong et al., 1998; Abasolo et al., 2005), the Ethics Committee of the Bugok National Hospital.schizophrenia (Roschke et al., 1994; Breakspear et al., 2003; Paulus For the accuracy of patient profiles, detailed clinical information onand Braff, 2003; Keshavan et al., 2004; Micheloyannis et al., 2006), and MA use patterns was obtained through interviews with the abuser anddepression (Roschke et al., 1994; Thomasson et al., 2002; Bob et al., his family members as well as by referral to patient medical records2006; Fingelkurts et al., 2007), many of whom are hypothesized to suffer using the Structured Clinical Interview for DSM-IV (SCID). The clinicalfrom reduced functional connectivity between cortical regions. A information includes the period of MA use, the age of first abuse, andprevious study also found that EEG complexity is reduced as sleep other substance abuse such as nalbuphine, nicotine, alcohol, andgoes deeper and increased during REM sleep (Burioka et al., 2005b). inhalant solvents. A heavy drinker was defined as consuming onThus, in this study, we examined the interplay between the functional average more than four drinks daily, and a heavy smoker was defined asintegration and segregation of cortical networks and consequently the smoking two or more packs per day. We also obtained the clinicalefficiency of information processing the cortex through quantification of information about sexual exploitation and criminal records. In the MAthe complexity in EEG patterns in MA abusers. binge abuse cycle, during the initial response of the rush, the MA To estimate complexity of EEG patterns in MA abusers, we used abusers heartbeat races and metabolism, blood pressure, and pulseApproximate Entropy (ApEn), an information-theoretic measure of increase. During this "high," they partake in a wide range of riskyirregularity. ApEn can stably quantify the complexity of a noisy and behaviors that include having an increased level of sexual behaviorshort time series as in physiological recordings (Pincus, 1991; Pincus, (sexual exploitation) and that incorporate unsafe behaviors, driving, or1995). Several studies have reported that ApEn can be used to discern committing crimes.various neuropsychiatric conditions such as Alzheimers disease, These evaluations were performed within 3 days of the EEGcoma (Abasolo et al., 2005; Lin et al., 2005), and epilepsy examination by a trained research psychiatrist blind to the EEG data.(Radhakrishnan and Gangadhar, 1998; Hornero et al., 1999; Burioka All MA abusers had taken MA intravenously for at least least 2 years,et al., 2005a). A previous study also reported that ApEn analysis of and each subject had been abstinent for more than 6 days at the timeheart rate in cocaine abusers showed reduced complexity, suggesting of the EEG examination. The drug was only to be taken intravenouslythat impaired function, isolation and network diminution are since this is the most common method of use in South Korea (Chungmanifest across multiple axes (Newlin et al., 2000). et al., 2004). Urine tests were performed just prior to EEG recording MA is known to induce a variety of symptomatic behaviors during for the proof of negative current intoxication.intoxication or withdrawal that include irritability, anxiety, excitement, The controls were recruited from the local community in Bugokhallucinations, paranoia (both delusional and psychotic), and aggressive and Busan, South Korea. They were group-matched with the MAbehavior. Social abnormalities such as criminal misconduct or sexual abusers by age, sex, and socioeconomic status (income: b$25,000;intercourse are also observed in MA abusers during MA intoxication. education: college or high school graduates). They had no history ofPsychotic behaviors of MA users are correlated with their ages, possibly MA use or abuse of other substances. None had a personal or familialassociated with disturbance of neurotransmitters in cortical–subcortical history of psychiatric illness based on an unstructured interviewcircuits during the aging process (Chen et al., 2003). Another conducted by a trained psychiatrist. No subjects could be takingcommonality found among MA abusers is the consumption of other medication at the time of the study, and all had negative urine toxinsubstances such as alcohol and nicotine during MA intoxication. These screens to ensure the absence of psychoactive drug use. Controls weremultifaceted factors result in the difficulties in treating MA dependen- excluded if they reported drinking alcohol more than once per day orcies in abusers. Despite the prominent and detrimental effects of MA on N40 g per week or reported smoking more than 10 cigarettes per day.the nervous systems and social behavior, few neuroimaging or After evaluation of the EEG, IQ was measured for all subjects as theelectrophysiological studies have been performed to investigate the psychometric index of intellectual functioning (Sattler, 2001) usingrelationship between cortical alterations and critical factors including the Korean–Wechsler Adult Intelligence Scale (K-WAIS)-Short formabuse patterns and social behaviors. Therefore, we aimed to determine (Yeom et al., 1992). The four sections of this shortened test requiredthe association between the complexity of EEG patterns in MA abusers the subjects to answer questions about the information that wasand their drug abuse patterns. provided, picture completion, arithmetic, and block designs. It was revised and given in Korean. The estimated IQ score was normalized2. Methods according to the respondents age.2.1. Subjects 2.2. EEG recording Currently abstinent MA abusers (N = 48, average age = 36.7 ± EEGs were recorded from 16 channels using EEG amplifier (Model 95.8 years; range= 26–49 years, all males) and 20 control subjects EEG Grass Instrument Co.) in the morning (10:30–11:30 AM) to Please cite this article as: Yun, K., et al., Decreased cortical complexity in methamphetamine abusers, Psychiatry Research: Neuroimaging (2012), doi:10.1016/j.pscychresns.2011.07.009
  3. 3. K. Yun et al. / Psychiatry Research: Neuroimaging xxx (2012) xxx–xxx 3minimize the circadian and homeostatic modulation of wakefulness Table 1(Taillard et al., 2003). Subjects were instructed to lie with their eyes Demographic profile of the study samples.closed, think of nothing in particular, and not fall asleep in a sound- MA group (n = 48) Control group (n = 20)attenuated room. Ag-AgCl electrodes were placed according to the Age (years) 37.0 (5.8) 34.5 (7.7)international 10–20 System. Data were collected using a Cz referential IQ (points) 97.8 (6.1) 116.5 (5.3)⁎montage and were digitized at 200 EEG samplings per second which Duration of MA use (years) 11.8 (6.5) N/Awere obtained by the QUINGY, MASS system (bandpass filtered 0.3– Abstinence period (days) 30.5 (27.2) N/A Total amount in a previous year (g) 1.125 (1.095) N/A70 Hz). At least 20 min of EEG activity was recorded and a minimum of30 s of artifact-free EEG was selected by visual inspection and then was Means are presented with standard deviations in parentheses. ⁎ p b 0.05.analyzed. To obtain maximally long stationary EEG data, the first 2 minof data were discarded. Three epochs of 10-s of EEG recordings wererandomly selected to estimate the ApEn values and their means were between the groups. Thus, we employed ‘Levenes Test for Equality ofused. An additional three epochs of 10 s of EEG recordings were Variances’ to select a proper statistic. Levenes Test with p b 0.05randomly selected. We found that the ApEn values were robust to epoch indicated that variance was not homogeneous. If Levenes Test indicatedselection and the results were consistent in that MA abusers exhibited that variances were homogeneous between groups, then Students t-decreased ApEn values compared with those of the healthy subjects in test was used. Otherwise, Welchs t-test was used. Welchs t-test is aall 15 channels (p b 0.001) except F4 (p N 0.05). There was no effect of variation of Students t-test intended for use with two samples havingepoch selection (p N 0.3). Using stationary EEG data and random epoch unequal variances.selection might help to control the possibly variable cognitive processesinvolved in the resting state. Moreover, robustness of the ApEn results to 3. Resultsepoch selection might indicate that a rather consistent cognitive statewas maintained in our resting supine condition. 3.1. Decreased cortical complexity of MA abusers2.3. Approximate Entropy analysis Table 1 summarizes the demographic characteristics displaying the similarities between the former MA abuser and control groups. The two The recorded EEG data were reformatted offline to compute the groups did not differ significantly in age, but there was a difference inpower spectrum (see supplementary material for power spectrum their IQ levels (p b 0.05). To assess the possible presence of abnormalanalysis and results) and ApEn values. First introduced by Pincus, the complexity of cortical activity in MA abusers, we estimated the ApEnApEn is an index that quantifies the irregularity or complexity of a values of EEG patterns in 48 MA abusers and compared them with thosedynamical system (Pincus, 1991). It is particularly efficient to use with of 20 control subjects. We found that MA abusers exhibited decreasedshort and noisy time-series data such as physiological data. The ApEn ApEn values compared with those of the healthy subjects in all 16measures the logarithm frequency with which neighborhoods of channels (Students t-test; p b 0.00001) (Fig. 1). We also calculated atemporal patterns of length m that are within a certain distance (r) in multivariate general linear model (dependent variables: ApEn values ofphase space remain close together (br) for patterns that are augmented 16 channels, fixed factor: MA abusers/controls, covariate: IQ, smokingby one point of time (i.e., for patterns of length m + 1) (see amount). Including IQ and smoking amount as a covariate decreased thesupplementary material for detailed algorithm). Thus, smaller values statistical difference between MA and control groups. However, mostof the ApEn imply stronger regularity or persistence in a time series. channels were still significantly different between groups (Fp1, T6, O1,Conversely, larger values of the ApEn signify the presence of greater O2, p b 0.0001; T5, p b 0.001; Fp2, P3, P4, F7, F8, T3, p b 0.01; F3, C3,C4, T4,fluctuations, or irregularity, in a time series. ApEn values of EEG are p b 0.05).possibly determined by the balance between the functional segrega- To investigate the effects of severity of MA abuse on the ApEn valuestions and integrations of cortical regions. of EEGs, we classified the MA group into two separate subgroups based on the period of MA abuse and recent intake amount: a moderate and2.4. Statistical analysis a severe MA abuse group. The “severe MA abusers” (average age was 37.7± 5.52 years; age range: 29–49 years; the average cumulative Group comparisons of the demographic variables were conducted amount of MA was 14.3 ± 15.2 g) consisted of subjects who used MAusing t-tests. The average values of the ApEn of the EEG in the MA- for at least 6 years or more than 0.75 g of MA injection in the most recentdependent group and the control group are presented as “mean ± year, compared with ‘moderate MA abusers’ (average age 30.6 ±standard error” across all subjects. The one-way analysis of variance 3.31 years; age range 26–35 years; average MA cumulative amount(ANOVA) procedure was used to compare the severe and moderate MA 0.92 ± 0.52 g). ANOVA analysis revealed that severe and moderate MAabusers and the control group. If the results from the ANOVA achieved abuser groups and the control group exhibited significant differences instatistical significance (pb 0.05), multiple comparisons were performed ApEn values in all channels (p b 0.0001), indicating the significantafterwards (LSD test). The effects of abuse patterns, clinical/socialmeasures, and comorbidity on the cortical complexities of MA abuserswere evaluated separately using t-tests. Pearsons correlation coefficientwas used for the linear correlation analysis, while a statistical softwarepackage (SPSS 11.0.1, SPSS Inc., Chicago, IL, USA) was used. Statisticalsignificance was defined to have an alpha level of 0.05. Adjacentelectrodes were grouped for pair-wise correction for multiple compar-isons (Fp1–F3, Fp2–F4, F7–T3, F8–T4, C3–P3, C4–P4, T5–O1, T6–O2). For normality test of the data, we used the ‘Kolmogorov–Smirnovtest’ before ApEn analysis and did not use outliers to maintain thenormality of the data. Outliers were detected through visual examina-tion of the scattergrams and normal probability distribution plots. Fewerthan three channels out of the total electrodes for each subject were Fig. 1. Topographic map of average ApEn values in (a) healthy subjects and (b) MAremoved from the study through the normality test. In comparisons of abusers. MA abusers exhibited reduced ApEn values compared with healthy subjects intwo samples (t-test), the variances of some EEG data are not equal all channels (Students t-test; p b 0.00001). Please cite this article as: Yun, K., et al., Decreased cortical complexity in methamphetamine abusers, Psychiatry Research: Neuroimaging (2012), doi:10.1016/j.pscychresns.2011.07.009
  4. 4. 4 K. Yun et al. / Psychiatry Research: Neuroimaging xxx (2012) xxx–xxxTable 2 3.2. Correlations of ApEn values with clinical/social measuresSignificant differences of ApEn values of EEGs in MA abusers and controls. Group 1corresponds to a group having lower ApEn values than those of group 2. To investigate the associations between ApEn values and clinical Group 1 Group 2 factors, we divided MA abusers into several groups according to their MA⁎ Control Fp1, Fp2, F3, C3, P3, P4, F7, F8, T3, T4, sexual histories, their drug-related criminal records, and if they T5, T6, O1 experienced common symptoms of psychosis (such as hallucinations Severe-MA⁎ Moderate-MA F3, C3, P3, F7, T5, O1 or delusions). We found no significant correlation between the ApEn No psychosis⁎ Psychosis Fp1, Fp2, F3, F4, C4, P4, F7, F8, T3, T4, value of the EEG and the age at which a subject first used MA. The MA T5, T6, O1, O2 No sex acts⁎ Sex acts C3, P3 patients exhibiting delusions or hallucinations (N = 37) had higher Drug-related No criminal record Fp2, F4, C3, C4, P3, P4, F7, F8, T3, T4, ApEn values in most channels than the abusers without these Criminal records⁎ T5, T6, O1, O2 symptoms (Fp1, Fp2, F3, F4, C4, P4, F7, F8, T3, T4, T5, T6, O1, O2; Heavy smoking⁎ Light smoking C4, P4, F8, T4, T5, T6, O1, O2 p b 0.05) (Fig. 3(a)). MA patients who participated in sexual No nalbuphine⁎ Nalbuphine Fp2, F4, C3, C4, P3, P4, F7, F8, T3, T4, intercourse during their MA binges (N = 25) had higher ApEn values T6, O2 in the centro-parietal areas than the other abusers who did otherSevere-MA: 6 or more years of MA abuse or taking at least 0.75 g of MA in the previous activities (such as driving cars or playing video games) (C3, P3;year.Moderate-MA: under 6 years of MA abuse and taking less than 0.75 g of MA in the p b 0.05) (Fig. 3(b)). The MA patients with drug-related criminalprevious year. records (N = 21) had lower ApEn values than the other subjects (allHeavy smoking: More than or equal to two packs/day. channels, except Fp1 and F3; p b 0.05) (Fig. S2). However, the MALight smoking: Less than two packs/day. patients with other types of criminal records had lower ApEn values ⁎ p b 0.05. that were limited to the centro-parietal areas (C4, P4; p b 0.05). These results demonstrate that reductions in cortical complexity (measured by the ApEn values of the EEGs) of MA abusers are associated with theinfluence of the duration of MA abuse and the dosage received during the pathological behaviors that occur during MA abuse.previous year. To control the possible age difference between groups, weapplied an analysis of covariace (ANCOVA). We selected age, IQ, andsmoking amount as covariates. All channels except F4 were stillsignificantly different between severe and moderate MA abuser andcontrol groups (Fp1, T6, O1, O2, p b 0.0001; P4, T3, T5, p b 0.001; F3, C3,P3, F7, F8, p b 0.01; Fp2, C4, T4, p b 0.05). In post-hoc analyses, thesignificant differences were found between the moderate and the severeMA groups in the left cortical areas (LSD test; F3, t(43.999) = 51.638,p = 0.042; C3, t(44.421) = 65.289, p = 0.031; P3, t(44.793) = 40.909,p = 0.049; F7, t(42.743) = 30.308, p = 0.043; T5, t(41.146) = 25.373,p = 0.037; O1, t(44.979) = 23.934, p = 0.030). The severe MA abusegroup had significantly lower ApEn values than the control group inmost channels (Fp1, Fp2, C3, P3, F7, F8, T3, T5, T6, O1, O2, p b 0.005; F3, C4,P4, T4, p b 0.05). The moderate MA group exhibited significantlydecreased ApEn values of the EEG in Fp1 channel compared with thevalues of the control subjects (LSD test; t(43.592) = 24.366, p b 0.0001)(Table 2). These results indicate the period-dependent, MA-inducedreduction in cortical complexity in the MA group (Fig. 2).Fig. 2. ApEn values of the EEG in control, moderate MA abuse, and severe MA abuse groups. Fig. 3. ApEn values of the EEG correlated with (a) the presence of psychoses and (b) sexualSignificant differences were found in cortical regions marked with an asterisk (*) between intercourse during MA intoxication. The asterisk (*) indicates significant differences inthe moderate and the severe MA user groups (F3, C3, P3, F7, T5, O1; p b 0.05). ApEn values (p b 0.05). Please cite this article as: Yun, K., et al., Decreased cortical complexity in methamphetamine abusers, Psychiatry Research: Neuroimaging (2012), doi:10.1016/j.pscychresns.2011.07.009
  5. 5. K. Yun et al. / Psychiatry Research: Neuroimaging xxx (2012) xxx–xxx 53.3. Correlation of the ApEn values with comorbidity ApEn reflects the dynamic balance between the functional integra- tion and segregation of neural networks (Pincus and Goldberger, 1994; We determined the relationship between the ApEn values of the Tononi et al., 1994). ApEn appears to decrease when the functionalEEGs in MA abusers and the presence of comorbidity of other cortical network is isolated or decoupled, and this reduced integrationsubstance abuse. Although other co-morbid abuse of inhalant solvents leads to hypoactivity, or slow signal transmission in the cortical(N = 7) did not have an effect on the ApEn values, we found heavy networks (Pincus, 1994). This reduction in cortical complexity,smoking (N = 5) (more than or equal to two packs/day) decreased the particularly in the temporal and frontal regions, probably stems fromApEn values in the right frontal and central areas and both sides of the the anatomical and functional disconnections among the regions thattemporal and occipital areas (C4, P4, F8, T4, T5, T6, O1, O2, p b 0.05) are most affected by the long-term toxicity of MA. This speculation may(Fig. S3). The ApEn values revealed that MA abusers who were heavy be consistent with the decreases in the metabolism rates of frontal whitesmokers exhibited greater cortical dysfunctions than those who matter in MA abusers, and it suggests that persisting deficiencies can besmoked fewer cigarettes or did not smoke at all. The abuse of found in the frontal lobes (Kim et al., 2005b). The frontostriatal circuitnalbuphine hydrochloride or other similar opioid medications (N = 7) might be affected in MA abusers so the decreased striatal metabolismincreased the ApEn values in the global cortical areas (Fp2, F4, C3, C4, rates cause the lower levels of metabolism in the frontal cortical regions.P3, P4, F7, F8, T3, T4, T6, O2; p b 0.05) (Fig. 4). This hypo-metabolism found in cortical regions possibly decreases the integrations of the neural networks. This in turn leads to the isolation or4. Discussion decoupling of the network. Alternatively, the reductions in dynamical complexity of EEG In the present study, we detected significantly reduced ApEn values patterns may reflect the toxicity of MA to several cortical monoam-of EEG patterns (i.e. cortical complexity) in former MA abusers in the inergic neurotransmitter systems such as dopamine and noradrenalin,global cortical regions compared with those of healthy subjects. Within and thus reduced local activities of cortical regions. The mostthe MA abuser group, severe MA abusers had more disproportionate prominent and toxic effects are on the neurites of dopaminergicreductions in cortical complexity compared with moderate MA abusers. neurons in the deep brain including the striatum, caudate, andAlthough the EEG has a poor spatial resolution and possibly topograph- putamen (Kraemer and Maurer, 2002; Kita et al., 2003). Brain damageical implications of these findings must be interpreted with extreme by MA is not limited to deep brain structures, but also extends tocaution, this reduction was more prominent in fronto-temporal and global cortical areas (Ciraulo et al., 2003; Kim et al., 2005a). Theoccipital regions. MA patients that suffered from delusions and involvement of dopamine in the process of drug addiction is likely tohallucinations or those that participated in sexual intercourse during be accompanied by functional and structural changes to the circuits,MA intoxication exhibited increased levels of cortical complexity including the cortical areas. The vast damage of cortical andcompared with those MA abusers that had not experienced similar subcortical regions to which these monoaminergic systems projectpsychotic symptoms or sexual intercourse during MA intoxication. MA as found in previous studies may account for the reductions in globalpatients having histories of drug-related criminal activities had the most dynamical complexity observed in the former MA abusers of ourdecreased cortical complexity among the MA abusers. The MA abusers study. Regardless of the resulting reductions in dynamical complexitywho smoked heavily had decreases in cortical complexity in the right that might be consequences of MA abuse on a functionally coupledfrontal, central, temporal, and occipital areas. The subjects concurrently neural system or the drugs comparable effects on multiple mono-using nalbuphine hydrochloride had increases in cortical complexity in amine systems, the estimated duration and amount of MA abusemost areas among the other MA users. These findings indicate overall correlated strongly with global and dynamical EEG complexity acrossreductions in dynamical complexity in the cortical networks of MA all portions of these monoaminergic and functional networks. Theseabusers, possibly due to the severe and long-lasting presence of toxins in findings suggest that the duration and amount of exposure to MAthe monoaminergic neurotransmitter systems of the brain in MA accounts for a substantial amount of variance found in the severity ofabusers. To the best of our knowledge, this is the first investigation to its long-term and system-wide neurotoxic effects in people.assess the “severity-dependent dynamical complexity” of EEG patterns In previous reports, delusions and hallucinations found in MAin former MA abusers and their associations with the subjects abuse abusers were associated with abnormalities in the dopamine receptorspatterns and other clinical measures. or transporters of the caudate, putamen, and nucleus accumbens (Wada and Fukui, 1990; Sekine et al., 2001). The ApEn revealed that MA abusers exhibiting delusions or hallucinations had more complex cortical activity than the abusers without these psychotic symptoms. It seems that psychotic symptoms might not only explain certain dopaminergic system deficits, but the presence of these symptoms might also be the reason for the reorganization or partial recoveries of the deficits (Lautenschlager and Forstl, 2001; Kato et al., 2006) resulting from the toxicity of the drug and the damage to the cortical and sub-cortical systems, such as the serotonergic system, stemming from the psychoses initiated by using MA (Sekine et al., 2006). Elevated complexity in EEG patterns mainly in the left centro- parietal areas was found in those MA abusers that participated in sexual intercourse during their MA binges. Previous reports have suggested that the parietal regions are associated with erotic, especially visual, stimuli (Montorsi et al., 2003; Mouras et al., 2003). Our results suggest that the sexual intercourse that occurs concurrently with MA abuse is, to some extent, associated with relatively intact brain function, rather than a simple recreational behavior. Further investigation is required to examine not only former abusers but also current and potential abusers to confirm the measures diagnostic power.Fig. 4. ApEn values of MA abusers correlated with the presence of nalbuphine abuse. Our findings must be interpreted in light of the limitations of thisThe asterisk (*) indicates significant differences in ApEn values (p b 0.05). study. First, the precise mental processes during resting remain Please cite this article as: Yun, K., et al., Decreased cortical complexity in methamphetamine abusers, Psychiatry Research: Neuroimaging (2012), doi:10.1016/j.pscychresns.2011.07.009
  6. 6. 6 K. Yun et al. / Psychiatry Research: Neuroimaging xxx (2012) xxx–xxxessentially uncontrolled. Different mental states might have influ- Hornero, R., Espino, P., Alonso, A., Lopez, M., 1999. Estimating complexity from EEG background activity of epileptic patients. IEEE Engineering in Medicine and Biologyenced the measured entropy. This is probably the main limitation for Magazine 18, 73–79.utilizing resting state dynamics. However, random mind wandering Jeong, J., Kim, S.Y., Han, S.H., 1998. Non-linear dynamical analysis of the EEG incould be canceled out in between-subjects level statistics. Second, the Alzheimers disease with optimal embedding dimension. Electroencephalography and Clinical Neurophysiology 106, 220–228.duration and amounts of MA use were determined by retrospective Johanson, C.E., Frey, K.A., Lundahl, L.H., Keenan, P., Lockhart, N., Roll, J., Galloway, G.P.,self-reports, which have limited validity and precision. Third, the Koeppe, R.A., Kilbourn, M.R., Robbins, T., 2006. Cognitive function and nigrostriataldecision to study only males, who likely are more susceptible than are markers in abstinent methamphetamine abusers. Psychopharmacology 185, 327–338. Kato, Y., Muramatsu, T., Kato, M., Shibukawa, Y., Shintani, M., Yoshino, F., 2006. Corticalwomen to the neurotoxic effects of methamphetamine, limited the reorganization and somatic delusional psychosis: a magnetoencephalographicgeneralizability of our findings to men only. Fourth, detailed study. Psychiatry Research: Neuroimaging 146, 91–95.neuropsychological testing was not conducted, and therefore the Keshavan, M.S., Cashmere, J.D., Miewald, J., Yeragani, V.K., 2004. Decreased nonlinear complexity and chaos during sleep in first episode schizophrenia: a preliminaryfunctional correlates of the altered EEG complexity patterns detected report. Schizophrenia Research 71, 263– this study could not be assessed. Finally, although we excluded Kim, S.J., Lyoo, I.K., Hwang, J., Chung, A., Hoon Sung, Y., Kim, J., Kwon, D.H., Chang, K.H.,subjects with extensive nicotine or alcohol use, the methamphet- Renshaw, P.F., 2005a. Prefrontal grey-matter changes in short-term and long-termamine abusers likely consumed larger amounts of other drugs during abstinent methamphetamine abusers. The International Journal of Neuropsycho- pharmacology 9, 221–228.their lifetimes than did the comparison group, thereby confounding Kim, S.J., Lyoo, I.K., Hwang, J., Sung, Y.H., Lee, H.Y., Lee, D.S., Jeong, D.U., Renshaw, P.F.,our ability to attribute the causes of hypoactivity to MA alone. 2005b. Frontal glucose hypometabolism in abstinent methamphetamine users.Nevertheless, the complexity analyses from our EEG screenings might Neuropsychopharmacology 30, 1383–1391. Kita, T., Wagner, G.C., Nakashima, T., 2003. Current research on methamphetamine-provide insights into how information is abnormally processed in the induced neurotoxicity: animal models of monoamine disruption. Journal ofcortical networks of MA abusers. This study suggests the possibility of Pharmacological Sciences 92, 178–195.dynamical complexity measures like ApEn as a potential, supplemen- Kraemer, T., Maurer, H.H., 2002. Toxicokinetics of amphetamines: metabolism and toxicokinetic data of designer drugs, amphetamine, methamphetamine, and theirtary quantitative diagnostic tool for MA abuse. N-alkyl derivatives. Theraputic Drug Monitoring 24, 277–289. Kulsudjarit, K., 2004. Drug problem in Southeast and Southwest Asia. Annals of the New York Academy of Sciences 1025, 446–457.Acknowledgments Lautenschlager, N.T., Forstl, H., 2001. Organic psychosis: insight into the biology of psychosis. Current Psychiatry Reports 3, 319–325. The authors thank Mr. Seung Min Shin for his technical assistance of Lin, M.A., Chan, H.L., Fang, S.C., 2005. Linear and nonlinear EEG indexes in relation to the severity of coma. Engineering in Medicine and Biology Society, 2005. IEEE-EMBSEEG recordings. This work was supported by the Korea Science and 2005. 27th Annual International Conference, pp. 4580–4583.Engineering Foundation (KOSEF) grant funded by the Korea government London, E.D., Simon, S.L., Berman, S.M., Mandelkern, M.A., Lichtman, A.M., Bramen, J.,(MOST) (No. R01-2007-000-21094-0 and No. M10644000013- Shinn, A.K., Miotto, K., Learn, J., Dong, Y., 2004. Mood disturbances and regional cerebral metabolic abnormalities in recently abstinent methamphetamine abusers.06N4400-01310). Archives of General Psychiatry 61, 73–84. McCann, U.D., Wong, D.F., Yokoi, F., Villemagne, V., Dannals, R.F., Ricaurte, G.A., 1998. Reduced striatal dopamine transporter density in abstinent methamphetamine andAppendix A. 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  8. 8. Supporting Online Material Decreased Cortical Complexity in Methamphetamine abusers Kyongsik Yun*, Hee-Kwon Park*, Do-Hoon Kwon, Yang-Tae Kim Sung-Nam Cho, Hyun-Jin Cho, Bradley S. Peterson, Jaeseung JeongMaterials and methodsApproximate Entropy EEG can be reconstructed as phase space representation using the method of delays.In this representation, the state at each point in time is represented by a vector generated bytaking successive amplitudes separated by a time lag tau. This reconstruction of theunderlying dynamics is the first step of all techniques of phase space analysis. Thegeometrical properties of the trajectories in the phase space can then be expressedquantitatively using nonlinear measures. Approximate entropy can be represented bydifference between geometrical property of m dimensional phase space trajectory and that ofm+1 dimensional phase space trajectory. In detail, ApEn is derived from the correlation integral Cim (r ) , which represents thenumber of points within a distance r from the ith point when the signal is embedded in an m-dimensional space: N - ( m -1) m -1 C (r ) = ( N - (m - 1)) i å Q(r - Xi - Xj ) j =1 (1)Where Q(t ) is the Heaviside function (if t ³ 0, Q(t ) = 1 ; if t<0, Q(t ) =0) and Xi and Xj arevectors constructed from the time series [ x(1), x(2), . . . , x(N)] as 1
  9. 9. Xi = {x(i ), x(i + t ),..., x(i + (m - 1)t )} Xj = {x( j ), x( j + t ),..., x( j + (m - 1)t )} (2) (i, j = 1,2,...N - (m - 1)t )where t is the time lag at which the mutual information between consecutive samplesbecomes negligible. The ApEn statistic is defined as follows: ApEn(m, r ) = Qm (r ) - Qm +1 (r ) (3) N - ( m -1) Q m (r ) = ( N - (m - 1)) -1 å ln C i m (r ) (4) i =1Entropy can be viewed as a measure of disorder, larger values corresponding more disorder,randomness, or complexity (Williams, 1997). We set the distance, r, to be 0.2 times the SD ofthe original data series to produce reasonable statistical validity of ApEn (Pincus, 1991). Wetested embedding dimension from 2 to 6. We used an embedding dimension of 2 (ie, m = 2)(Peitgen et al., 1992) in which ApEn differences between groups are maximum. Theparameter choices of m = 2 and r = 0.2 SD in the ApEn specification are standard choices andwidely applied in diverse settings. To embed the time series in state space, we used theconcept of time lag. These values were chosen as the time lags that were determined for eachtime series as the lag at which the first minimum of the mutual information in the EEG. ApEnwas computed with a software package (MATLAB 7.0; The MathWorks, Inc).Surrogate dataThe surrogate data are a randomized sequence of the original data having the same linearproperties and the significant differences between the ApEn of original EEG data and theirsurrogate data indicate that the original EEG sequences have a nonlinear structure within thepatterns. Nonlinear indexes such as the ApEn are computed for several surrogate data series.Their values are compared with that assumed by the nonlinear index computed for the 2
  10. 10. original data (Theiler et al., 1992). No statistical difference indicates that the original time series were generated from alinear process, since random shuffling of the original time series, which is surrogate data,does not change the linear properties of the original data. On the contrary, the statisticallysignificant difference in ApEn between the original and surrogate data explains that theoriginal signal contains the nonlinear properties.To test for a statistical significance of difference (ie, the s of Theiler et al. (Theiler et al.,1992)) in ApEn between the original and the surrogate data, 10 surrogate data series weregenerated to match each original signal. Let ApEnorig be the ApEn of the original data, and letApEnsurr be the ApEn of the 10 surrogate series (i = 1,…,10). The mean and SD of ApEnsurr (i= 1,…,10) are estimated as ApEnsurr and SDApEn_surr (Theiler et al., 1992) then is computed asfollows: ApEnorig - < ApEnsurr > Z= (5) SDApEn _ surrThis statistic represents the number of SDs ( s ) distant from ApEnorig. It follows a Student ttest distribution with 9 degrees of freedom ( t9[1- a /2]). For a =0.05, the critical value of tis 2.26. Accordingly, when the s of Theiler et al. (Theiler et al., 1992) is > 2.26, the nullhypothesis is rejected at the 5% probability level, and the original data are considered tocontain nonlinear features. 3
  11. 11. ResultsPower spectrum analysisThe reformatted data were than processed using a fast Fourier transform (MATLAB 7.0; TheMathWorks, Inc) to obtain relative power values in 4 standard frequency bands, delta (0.5–4Hz), theta (4–8 Hz), alpha (8–12 Hz), and beta (12–30 Hz). Relative power values were obtained across the 4 standard EEG bands. Areas inprefrontal, frontal, and temporal regions were decreased (Fp1, F8, T5; p<0.05) in MA-dependent group in delta band. Other EEG bands indicate no significantly different powervalues between MA-dependent and control groups.Surrogate data analysis The test of Theiler et al. (Theiler et al., 1992) was performed for each data seriesseparately to test for nonlinearity (FigS1). The mean (± standard error) values of the test ofTheiler et al. (Theiler et al., 1992) were 41.3 ± 5.3 for ApEn of MA-dependent subjects, 44.2± 6.3 for ApEn of high-dose MA-dependent subjects, 35.5 ± 6.6 for ApEn of low-dose MA-dependent subjects. The mean values of the control group were 2.33 ± 0.5. The signals of allchannels of MA group show clear evidence for nonlinearity) Whereas signals of 8 channelsof control group (Fp2, C3, C4, F8, T3, T4, T5, T6) failed the test signals of 8 other channelsof control group (Fp1, F3, F4, P3, P4, F7, O1, O2) showed nonlinearity. It shows relativelysignificant nonlinear feature in MA-dependent subjects. The signals of all channels of MAgroup show clear evidence for nonlinearity although signals for only 8 channels showsignificant nonlinear feature in the control group.Correlation with abstinence period 4
  12. 12. We could not find the correlation between abstinence period and EEG analyses suchas ApEn and power spectrum. Although Kim et al. (Kim et al., 2005) reported that long-termabstinence could improve prefrontal grey-matter, average duration of long-term abstinenceperiod was over 30 months in that study. In case of our study, the longest abstinence periodwas three months, and the relatively short period of abstinence maybe could not show enoughrecovery of electrophysiologic function. 5
  13. 13. Discussion Brecht and his colleagues (Brecht et al., 2000) examined the possible predictors ofthat could indicate how long MA abusers could wait before relapsing back into abusing thedrug. They found that an abuser experienced a shorter time period before relapse if theindividual had started using MA at an older age, and age was found to be a significantpredictor in that experiment. In our study, the ApEn values of the left frontal areas exhibitnegative correlations with the ages of subjects’ first intakes of the drug. This preliminaryfinding indicates that MA abusers who were older when first exposed to MA have elevatedlevels of susceptibility to reductions in their EEG complexities. It is possible that thedopamine systems is more severely damaged by MA as individual ages since theseneurotransmitter systems are reported to weaken during the course of the normal agingprocess. This might compound the effects of the drug as well (Sheline et al., 2002). Theassociation of ApEn values with the severity of MA abuse and the age at which a user firstuses the drug suggests that EEG complexity measures should be further investigated. The ApEn revealed decreases in the global cortical areas in those MA abusers thathad drug-related criminal records. Drug-related criminality is frequently associated with MAabuse (Keene, 2005; Sindelar & Olmstead, 2006). To investigate certain social aspects, suchas the levels of sociality and aggression in MA abusers, we examined the other criminalrecords unrelated to substance abuse of our subjects in the patient group. We found that thegeneral criminality of MA abusers was associated with decreased complex dynamics in theleft fronto-central and right centro-parietal areas that are known to be associated withincreased hostility (Fallon et al., 2004) and more frequent and intense sexual behaviors(Mouras, 2006). The serotonin transporter likely changes during an individual’s dependenceon MA, leading to elevated levels of aggression even in currently former abusers (Sekine et 6
  14. 14. al., 2006). However, the ApEn analysis revealed increased complexity in these areascorrelated with sexual activity. Thus, this discrepancy suggests that further investigation isnecessary to identify the specific processes of those centro-parietal areas involved in sexualactivity and criminality. In regards to our observations that showed heavy drinking and smoking habits inMA abusers, they were associated with EEG complexity in the left frontal and temporalregions which was consistent with a previous report that stated smoking increased thepsycho-toxic effect of and sensitivity to MA, particularly in the inhibitions of locomotorsensitization (Kuribara, 1999). We should also note that co-morbid use of nalbuphineminimized the ApEn decrease that was induced by MA abuse, or this co-morbid use increasedthe ApEn in most cortical areas of abusers compared to the healthy control subjects. This isconsistent with previous studies performed on animals that reported that stimulation of theopioid receptors plays an inhibitory role in MA-induced and self-injurious behaviors (Mori etal., 2006). The results implicate that ApEn may be able to detect the outcomes of corticaldynamics produced by an interplay between nalbuphine and methamphetamine. Alternatively,nalbuphine may offer some protection against MA-induced reductions in cortical complexityand can play a potential and therapeutic role in treating MA-inducing pathological changes. 7
  15. 15. Supporting ReferencesBrecht, M. L., von Mayrhauser, C., & Anglin, M. D. 2000. Predictors of relapse after treatment for methamphetamine use. J Psychoactive Drugs 32, 211-20.Fallon, J. H., Keator, D. B., Mbogori, J., Turner, J., & Potkin, S. G. 2004. Hostility differentiates the brain metabolic effects of nicotine. Brain Res Cogn Brain Res 18, 142-8.Keene, J. 2005. A case-linkage study of the relationship between drug misuse, crime, and psychosocial problems in a total criminal justice population. Addiction Research & Theory 13, 489-502.Kim, S. J., Lyoo, I. K., Hwang, J., Chung, A., Hoon Sung, Y., Kim, J., Kwon, D. H., Chang, K. H., & Renshaw, P. F. 2005. Prefrontal grey-matter changes in short-term and long- term abstinent methamphetamine abusers. The International Journal of Neuropsychopharmacology 9, 221-228.Kuribara, H. 1999. Does nicotine modify the psychotoxic effect of methamphetamine? Assessment in terms of locomotor sensitization in mice. J Toxicol Sci 24, 55-62.Mori, T., Ito, S., Kita, T., Narita, M., Suzuki, T., & Sawaguchi, T. 2006. Effects of mu-, delta- and kappa-opioid receptor agonists on methamphetamine-induced self-injurious behavior in mice. Eur J Pharmacol.Mouras, H. 2006. Neuroimaging Techniques as a New Tool to Study the Neural Correlates Involved in Human Male Sexual Arousal. Current Medical Imaging Reviews 2, 71-77.Peitgen, H.-O., Jurgens, H., & Saupe, D. (1992). Chaos and fractals : new frontiers of science. New York: Springer-Verlag.Pincus, S. M. 1991. Approximate entropy as a measure of system complexity. Proceedings of National Academy of Sciences 88, 2297-301. 8
  16. 16. Sekine, Y., Ouchi, Y., Takei, N., Yoshikawa, E., Nakamura, K., Futatsubashi, M., Okada, H., Minabe, Y., Suzuki, K., Iwata, Y., Tsuchiya, K. J., Tsukada, H., Iyo, M., & Mori, N. 2006. Brain serotonin transporter density and aggression in abstinent methamphetamine abusers. Archives of General Psychiatry 63, 90-100.Sheline, Y. I., Mintun, M. A., Moerlein, S. M., & Snyder, A. Z. 2002. Greater loss of 5- HT(2A) receptors in midlife than in late life. Am J Psychiatry 159, 430-5.Sindelar, J. L., & Olmstead, T. A. 2006. 8 Illicit drugs and drug-related crime. The Elgar Companion to Health Economics.Theiler, J., Eubank, S., Longtin, A., Galdrikian, B., & Doyne Farmer, J. 1992. Testing for nonlinearity in time series: the method of surrogate data. Physica D: Nonlinear Phenomena 58, 77-94.Williams, G. P. (1997). Chaos theory tamed. Washington, D.C.: Joseph Henry Press. 9
  17. 17. Supporting FiguresFigS1. Surrogate data analysis. A global test of nonlinearity was carried out by a Wilcoxonmatched-pairs signed rank test comparing ApEn values computed on the original data pairedwith the corresponding average ApEn values from the matching surrogate data series. Largersigma values indicate higher nonlinearity. 10
  18. 18. FigS2. Correlation with criminal records. The ApEn values of the EEG correlated withdrug-related criminal records. Asterisk (*) indicates significant difference in the ApEn values. 11
  19. 19. FigS3. Correlation with smoking. The ApEn values of MA abusers correlated withheavy/light smoking. Heavy smoking is defined as more than or equal to 2 packs/day.Asterisk (*) indicates significant difference in the ApEn values. 12