Is Cognitive Functioning Impaired in Methamphetamine …

Review

Is Cognitive Functioning Impaired in Methamphetamine Users?A Critical Review

Carl L Hart*1,2,3, Caroline B Marvin1, Rae Silver1,4,5 and Edward E Smith1,6

1Department of Psychology, Columbia University, New York, NY, USA; 2Division on Substance Abuse, New York State Psychiatric Institute and

Department of Psychiatry, College of Physicians and Surgeons of Columbia University, New York, NY, USA; 3Institute for Research in African-

American Studies, Columbia University, New York, NY, USA; 4Department of Psychology, Barnard College of Columbia University, New York, NY,

USA; 5Department of Anatomy and Cell Biology, Columbia University, New York, NY, USA; 6Division of Cognitive Neuroscience, New York State

Psychiatric Institute and Department of Psychiatry, College of Physicians and Surgeons, Columbia University, New York, NY, USA

The prevailing view is that recreational methamphetamine use causes a broad range of severe cognitive deficits, despite the fact that

concerns have been raised about interpretations drawn from the published literature. This article addresses an important gap in our

knowledge by providing a critical review of findings from recent research investigating the impact of recreational methamphetamine use

on human cognition. Included in the discussion are findings from studies that have assessed the acute and long-term effects of

methamphetamine on several domains of cognition, including visuospatial perception, attention, inhibition, working memory, long-term

memory, and learning. In addition, relevant neuroimaging data are reviewed in an effort to better understand neural mechanisms

underlying methamphetamine-related effects on cognitive functioning. In general, the data on acute effects show that methamphetamine

improves cognitive performance in selected domains, that is, visuospatial perception, attention, and inhibition. Regarding long-term effects

on cognitive performance and brain-imaging measures, statistically significant differences between methamphetamine users and control

participants have been observed on a minority of measures. More importantly, however, the clinical significance of these findings may be

limited because cognitive functioning overwhelmingly falls within the normal range when compared against normative data. In spite of

these observations, there seems to be a propensity to interpret any cognitive and/or brain difference(s) as a clinically significant

abnormality. The implications of this situation are multiple, with consequences for scientific research, substance-abuse treatment, and

public policy.

Neuropsychopharmacology (2012) 37, 586–608; doi:10.1038/npp.2011.276; published online 16 November 2011

Keywords: amphetamines; methamphetamine; cognition; impairment

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INTRODUCTION

Amphetamine is a class of compounds that includes drugsused for both medical and recreational purposes. Of thisclass, d-amphetamine and methamphetamine are approvedin several countries to treat a variety of disorders, includingattention-deficit hyperactive disorder (ADHD), narcolepsy,and obesity. Over the past two decades, however, excessiveillicit amphetamine use has become a major global concern.According to data from the United Nations Office on Drugsand Crime in 2008, amphetamine is used at rates higherthan cocaine and heroin combined, and while use hasstabilized somewhat in European, North American, and

African countries, amphetamine is becoming increasinglypopular in South and Central America and in the Near andMiddle East (2008 Global ATS Assessment). Amphetamineuse continues to be most prevalent in Oceania, NorthAmerica, and East and Southeast Asia, where approximately1–2% of the respective adult populations report annual use(2008 Global ATS Assessment). Like other illicit drug use,amphetamine use is associated with increased hospitaladmissions, treatment admissions, and arrests (Dobkin andNicosia, 2009). In some countries, the perception ofproblems associated with the abuse (The terms ‘abuse’and ‘dependence’, as they are used throughout this review,conform to the Diagnostic and Statistical Manual of MentalDisorders 4th Edition (DSM-IV-TR) and InternationalStatistical Classification of Diseases and Related HealthProblems (ICD-10) definitions of substance abuse anddependence. DSM-IV-TR and ICD-10 terminology are usedto avoid the use of pejorative words and terminologythat have multiple meanings.) of amphetamine has becomeso worrisome that drastic measures have been taken.

Received 17 July 2011; revised 19 September 2011; accepted 9October 2011

*Correspondence: Dr CL Hart, New York State Psychiatric Institute atColumbia University, 1051 Riverside Drive, Unit 120, New York,NY 10032, USA, Tel: + 1 212 543 5884, Fax: + 1 212 543 5991,E-mail: [email protected]

Neuropsychopharmacology (2012) 37, 586–608

& 2012 American College of Neuropsychopharmacology. All rights reserved 0893-133X/12

www.neuropsychopharmacology.org

http://dx.doi.org/10.1038/npp.2011.276

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In response to reports of precipitous increases in metham-phetamine abuse, in 1996 the government of Thailandbanned all uses of amphetamine, including those formedical purposes (Pilley and Perngparn, 1998). Othergovernments have also taken steps to restrict legal uses ofamphetamine, although most have not been as extreme asthose taken in Thailand. For example, in the UnitedKingdom and New Zealand, while d-amphetamine remainsavailable for medical purposes, any use of methamphet-amine (including medical use) has been banned.

There are several amphetamines used recreationally,including d-amphetamine, methamphetamine, 3,4-methyle-nedioxyamphetamine, and 3,4-methylenedioxymethamphet-amine. Of these compounds, methamphetamine hasgenerated the greatest amount of concern. Indeed, periodi-cally there are statements in the scientific and popularliterature attesting to methamphetamine’s greater potencyand ‘addictive’ potential, relative to other amphetamines.Such statements, however, are inconsistent with datacollected in humans, which show that d-amphetamine andmethamphetamine produce nearly identical physiologicaland behavioral effects (eg, Martin et al, 1971; Sevak et al,2009; Kirkpatrick et al, in press a). One reason for theunfounded beliefs about the drugs might be related to thefact that methamphetamine is more readily available onthe illicit market owing to its apparent easier synthesis. Aquick search of the Internet can provide the surfer withdozens of ‘How to make meth’ recipes within minutes.According to these recipes and law enforcement personnel,methamphetamine can be ‘easily’ made from a few commonproducts, the most important of which is the over-the-counter cold medication, pseudoephedrine. As a result, it isnot surprising that methamphetamine is the most frequentlyabused amphetamine.

Methamphetamine abuse is associated with multipledeleterious medical consequences, including paranoiamimicking full-blown psychosis (Grelotti et al, 2010) andhypertensive crisis leading to stroke (Ho et al, 2009). Whileserious, such cases are rare, and entail the long-term use ofextremely large doses. A more commonly describedunfavorable effect associated with methamphetamine abuseis extreme tooth decay (‘meth mouth’). Several reportsdescribing this phenomenon have appeared in the scientificliterature (for a review, see Hamamoto and Rhodus (2009)).In general, researchers conclude that methamphetaminerestricts salivary flow leading to xerostomia (dry mouth).Because xerostomia can increase the likelihood of plaqueand dental caries (tooth decay), this condition mightunderlie the dramatic pictures of ‘meth mouth’ seen inthe popular media. Xerostomia is a relatively common sideeffect associated with many widely used medications,including the popular antidepressant Duloxetine (Cymbalta)and the ADHD medication d-amphetamine (Adderall:combination of amphetamine and d-amphetamine mixedsalts). Despite the fact that these medications are used dailyand frequently prescribedFeach year both are among thetop 100 most prescribed drugs in the United States(Bartholow, 2010)Fthere are no published reports ofdental problems associated with their use. Given thestructural and pharmacological similarities of methamphet-amine and d-amphetamine, this suggests that the phenom-enon of ‘meth mouth’ has less to do with the direct

pharmacological effects of methamphetamine and more todo with non-pharmacological factors, ranging from poordental hygiene to media sensationalism. Indeed, much ofthe evidence linking methamphetamine abuse and toothdecay is anecdotal; detailed investigations of the impact ofmethamphetamine abuse on dental health with suitable oralhealth assessments are lacking (ADA, 2005; Cretzmeyeret al, 2007; but see, Shetty et al, 2010).

Another frequently reported deleterious effect associatedwith methamphetamine abuse and dependence is cognitiveimpairment. Unlike the scant literature examining theeffects of the drug on dental health, there is a burgeoningamount of information detailing the impact of methamphet-amine on cognitive functioning. The dominant view is thatillicit methamphetamine use causes a broad range ofcognitive impairments (for a review, see Scott et al(2007)). Important shortcomings of the research perpetuat-ing this perspective have received only limited attention.For example, in many of the studies the performance ofmethamphetamine abusers did not differ from controls onthe majority of cognitive tasks employed. Importantly,although methamphetamine abusers performed signifi-cantly worse than controls on some cognitive tasks, theirperformance remained within the age- and education-matched normal range. Furthermore, previous discussionsof the impact of methamphetamine-related effects onhuman cognition have neglected data from researchassessing the immediate effects of the drug on cognitiveperformance. These studies can provide crucial comple-mentary information because they assess cognitive perfor-mance immediately before and after administration of thedrug. The rationale for this approach is that if metham-phetamine produces cognitive deficits, one might predictthat methamphetamine-induced disruptions would beobserved following acute administration of large doses.

This article addresses an important gap in our knowledgeby providing a critical review of findings from recentresearch investigating the impact of recreational metham-phetamine use on human cognition. The discussion ofmethamphetamine on cognition is divided into three maincategories: (1) the acute effects that occur shortly after thedrug has been administered and are assessed while the drugis still in the body; (2) the long-term effects of repeated usethat are typically assessed when the drug is no longer in thebody; and (3) finally, relevant neuroimaging data will beevaluated in an effort to shed light on the neuralmechanisms underlying methamphetamine-related effectson cognitive functioning. The review begins with a briefoverview of methamphetamine neuropharmacology.

Methamphetamine Neuropharmacology

Over the past several decades, data from basic research havecontributed to an increased understanding of neuronalmechanisms involved in the effects of amphetamine,including methamphetamine. A comprehensive review ofamphetamine neuropharmacology is beyond the scope ofthe current article, and excellent reviews already exist (eg,Sulzer et al, 2005; Fleckenstein et al, 2007). Nonetheless, abrief overview will provide insight into the neurotransmit-ters involved in the actions of amphetamine. As can be seenin Figure 1, amphetamine-related drugs bear a striking

Cognitive functioning and methamphetamineCL Hart et al

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resemblance to the catecholamine neurotransmitters dopa-mine (DA) and norepinephrine (NE). The structuralsimilarities between amphetamine and catecholamine neu-rotransmitters provide clues about the drugs’ mechanismsof action.

Multiple lines of evidence demonstrate that amphetaminecauses release of monoamines from the neuronal cytosol viaplasmalemmal uptake transporters, particularly the DAtransporter (DAT), the NE transporter, and the serotonin(5-HT) transporter, an action often called ‘reverse trans-port.’ Although the actions of amphetamine on thesetransporters are generally comparable, most of the pub-lished research has focused on the DAT because it has beenmost often implicated in the reinforcing effects of this classof drug. Therefore, the discussion of plasmalemmaltransporters herein focuses on the DAT.

Raiteri and co-workers (1979) provided early evidencesuggesting that amphetamine increased DA release via aDAT mechanism when they showed that amphetamine-induced DA release was prevented by nomifensine, a DATinhibitor. Subsequently, Zaczek et al (1991a ,b) used ratbrain synaptosomes to demonstrate active uptake ofamphetamine by DAT. Strong support indicating thatamphetamine analogs are substrates for the DAT came froma report by Sonders et al (1997), who used electrophysio-logical recording techniques to show that amphetamineelicited DA-like transporter-associated currents. Othersreplicated these findings (eg, Sitte et al, 1998), so that theevidence that amphetamine is accumulated by monoaminetransporters is now quite strong. It is widely thought thatamphetamine is selectively transported into cells andsomehow causes DA, which normally is also taken up bythese transporters, to be transported out. Although this isbelieved to occur because amphetamine changes theconformation of the transporters to favor reverse transport,the means by which this occurs are still unknown. Moreover,amphetamine blocks DA reuptake (Schmitz et al, 2002),illustrating that the actions of amphetamine are complex.

Another mechanism through which amphetamine causesDA release is by disrupting the activity of the vesicularmonoamine transporter-2 (VMAT-2). One prominentperspective is that amphetamine administered in largerdoses gains access to the neuron through the DAT anddiffusion; once in the cell, it diffuses through the vesicularmembrane and accumulates in vesicles, which disrupts thepH gradient required for vesicular DA sequestration, anaction termed ‘the weak base hypothesis.’ However,amphetamine is also a VMAT-2 substrate, so that some ofthe drug is actively accumulated in the vesicles, and as withthe DAT, acts as a competitive inhibitor and furtherdisrupts the pH gradient. In any case, these actions causeDA to accumulate in the cytoplasm (Mosharov et al, 2009),which alters the concentration gradient and likely helpsfavor the reverse transport of DA via the DAT (for a review,see Sulzer et al (2005)).

An accumulating amount of evidence shows that amphet-amine, when administered repeatedly in large doses,promotes the formation of reactive oxidative species.Following release of DA, the neurotransmitter is inactivatedby monoamine oxidase-catalyzed oxidative deaminationand may also undergo autoxidation. Both of these pathwayshave been shown to generate reactive oxidative species.Hence, abnormally enhanced DA activity has been hypoth-esized to produce an increased formation of oxidative stressand thereby cause cell injury (Cadet and Krasnova, 2009).This effect is particularly prominent within the cell cytosol.This, in turn, could lead to persistent deficits in dopami-nergic functioning. Several researchers have found thatlarge doses of methamphetamine, for example, decreasedstriatal DA content, DAT density, and the activity oftyrosine hydroxylase (DA rate-limiting enzyme) in labora-tory animals (Cadet and Krasnova 2009).

This knowledge has raised concerns about the potentialdeleterious central nervous system consequences ofmethamphetamine abuse in humans, in part, becauseDA-rich areas subserve a wide range of important human

Figure 1 Chemical structure of neurotransmitters and amphetamines.


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functions ranging from movement to learning and memory.Indeed, a substantial database collected in laboratoryanimals suggests that acute and long-term administrationof amphetamine produces disruptive effects in severalcognitive domains (for a review, see Marshall et al(2007)). There is, however, an important limitationassociated with many of these studies when extrapolatingthe findings to humans: the dosing regimens used did notcapture key elements of human recreational amphetamineuse, specifically gradual dose escalation. Typically, investi-gators administered large bolus doses of methamphetaminerepeatedly for one or more consecutive days to drug-naı̈veanimals, whereas human recreational drug users usuallyincrease their doses gradually over time as their drug useprogresses. This difference is not trivial because thedeleterious neurobiological and behavioral changes thatoccur in response to repeated large doses of methamphet-amine can be prevented with previous exposure to severaldays of escalating doses (Segal et al, 2003; O’Neil et al, 2006;Belcher et al, 2008). Given this situation, it is criticallyimportant to employ more ecologically relevant models infuture animal studies investigating the impact of amphet-amine use on cognitive functioning. These issues under-score the importance of carefully assessing cognition inhuman recreational methamphetamine users.

Review of the Acute Effects of Methamphetamine onCognition

The influence of methamphetamine on cognitive function-ing is highly dependent on the neurotransmitters and brainstructures that are impacted by the drug. As noted above,acutely, methamphetamine causes a release of the mono-amines DA, NE, and 5-HT. These neurotransmitters areproduced in neurons located in the midbrain and brainstemand project widely throughout the brain. For example, DA isproduced in both the substantia nigra and the ventraltegmental area (VTA). The substantia nigra sends projec-tions to the dorsal striatum (caudate–putamen), anddamage to this pathway has been implicated in Parkinson’sdisease. This pathway is also thought to play a crucial rolein feedback-based reward learning (Shohamy et al, 2008).The VTA projects to the ventral striatum (nucleusaccumbens and olfactory tubercle) and limbic structuresand has been implicated in reward-related behaviors(Hyman et al, 2006). In addition, the VTA sends projectionsto the prefrontal cortex, which is known to play a role in awide range of cognitive functions, including attention,inhibition, and working memory. Thus, it is possible thatoptimal levels of dopaminergic activity, that is, the amountproduced by low to moderate oral doses of amphetamine,might actually improve functioning in some cognitivedomains, including visuospatial perception, attention, andinhibition. Conversely, excessive dopaminergic activity, thatis, the amount produced by large amphetamine dosesadministered repeatedly, might result not only in neuro-toxic effects, but also might produce deficits in the above-mentioned cognitive domains.

Effects of methamphetamine on performance of infre-quent stimulant users. To better understand the directpharmacological effects of methamphetamine on cognitive

functioning, researchers typically assess performance im-mediately before, and repeatedly after, drug administration.Table 1 summarizes the studies that have evaluated theacute effects of methamphetamine on various domains ofhuman cognition. These double-blind laboratory studiesemploy carefully controlled, within-participant designs,during which participants: (1) complete a baseline cognitivebattery; (2) are administered a methamphetamine dose(ranging from placebo to 50 mg); and (3) are reassessed onthe cognitive battery at predetermined time points forseveral hours after drug administration. In an earlierinvestigation of this type, Hart et al (2002) conducted anoutpatient study in which participants who reportedinfrequent use of stimulants were administered oralmethamphetamine (0, 5, 10, and 20 mg) and performancein various cognitive domains was assessed over the courseof several weeks. Before beginning the study, participantsreceived extensive training on the cognitive battery so thatthe tasks were well learned and performance was stablebefore any drug administration. The battery assessedperformance in the domains of visuospatial perception,inhibition, long-term memory, and learning. It alsoincluded a measure of response speed (simple reactiontime). Methamphetamine improved performance in thedomains of learning and memory, visuospatial perception,and response speed; no drug-related disruptions werenoted. These findings are consistent with data frominvestigations that have studied similar doses in individualswith limited stimulant drug experience (eg, Johnson et al,2000; Silber et al, 2006; Marrone et al, 2010; Kirkpatricket al (in press b), although there were no effects on anycognitive domains in a few studies (Comer et al, 2001; Hartet al, 2001; Sevak et al, 2009).

Effects of methamphetamine on performance of metham-phetamine abusers. Although the above observations arecongruent with the use of oral methamphetamine in thetreatment of ADHD, a largely cognitive disorder character-ized by deficits in attention and inhibition, they appear tobe inconsistent with the view that methamphetamine causesdisruptions in a range of cognitive functions. It isconceivable that the lack of acute methamphetamine-relateddisruptive effects on cognitive functioning in the studiesdescribed above may be related to the research participantsstudied and/or to the doses and route of drug administra-tion examined. In the natural setting, for example,methamphetamine abusers’ dose selection may not beguided by clinical recommendations and often exceedsdoses tested in the laboratory. In addition, all of the abovestudies investigated the effects of methamphetamineadministered orally, a route least often associated withdrug abuse and toxicity in the natural setting, to non-drugabusers. Route of administration is a critical determinant ofneurochemical consequences associated with stimulantadministration, in part because neurochemical effectsdepend on the rate of the rise of drug concentrations andthe maximum drug concentrations achieved (Gerasimovet al, 2000). Thus, it is possible that methamphetamineadministered to abusers in larger doses and via routesother than oral, for example, intranasal or intravenous,might produce more disruptive effects on cognitivefunctioning.


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Table 1 Acute Effects of Methamphetamine Studies

Investigators Domain Methamphetamineroute and dose

Participants and design Cognitive findings Caveats

Comer et al (2001) Immediate and long-term memory (digit-recall task); visuospatial perception (DSST);reaction time, vigilance, and inhibitory control(DAT); sustained attention and inhibitorycontrol (RIT); learning/memory (RAT)

Oral: 0, 5, 10 mg Participants reported limitedexperience with stimulants, but did notmeet the DSM-IV criteria for a MA-usedisorderN¼ 7 (within-subjects design)

MA produced no consistent effects ontask performance

Doses examined were lower than those usedrecreationallyRoute of administration used is not typicallyassociated with abuseSmall number of participants studied

Hart et al (2001) Same as above Oral: 0, 5, 10 mg Participants reported previousexperience with stimulants, but did notmeet the DSM-IV criteria for a MA-usedisorderN¼ 8 (within-subjects design)

MA produced no consistent effects ontask performance

Doses examined were lower than those usedrecreationallyRoute of administration used is not typicallyassociated with abuseSmall number of participants studied

Hart et al (2002) Same as above Oral: 0, 5, 10, 20 mg Participants reported previousexperience with stimulants, but did notmeet the DSM-IV criteria for a MA usedisorderN¼ 6 (within-subjects design)

m Visuospatial perceptionm Reaction timem Learning/memory2Immediate and long-term memory2Vigilance2Inhibitory control2Sustained attention

Route of administration used is not typicallyassociated with abuseRepeated-dosing effects were not investigatedSmall number of participants studied

Hart et al (2008) Same as above Intranasal: 0, 12, 25, 50 mg/70 kg Participants met the DSM-IV criteria forMA-use disorderN¼ 11 (within-subjects design)

m Visuospatial perceptionmReaction timem Vigilance2Immediate and long-term memory2Inhibitory control2 Sustained attention2 Learning/memory

Repeated-dosing effects were not investigated

Johnson et al (2000) Sustained attention (RVIPT); conceptualability (LRT); psychomotor skill (FTT)

Oral: 0, 0.21, 0.42 mg/kg(equivalent dose: B15, 30 mg)

Drug-naı̈ve participantsN¼ 18 (within-subjects design)

m Sustained attentionm Conceptual ability2 Psychomotor skill

Route of administration used is not typicallyassociated with abuseRepeated-dosing effects were not investigated

Johnson et al (2005) Sustained attention (RVIPT); visuospatialperception (DSST)

Intravenous: 0, 15, 30 mg Participants met the DSM-IV criteria forMA-use disorderN¼ 19 (within-subjects design)

m Sustained attentionm Visuospatial perception


Johnson et al (2007) Same as above Intravenous: 0, 15, 30 mg Participants met the DSM-IV criteria forMA-use disorderN¼ 10 (within-subjects design)

m Sustained attentionm Visuospatial perception


Kirkpatrick et al (2008) Metacognition (Judgment of agency task) Intranasal: 0, 12, 25, 50 mg/70 kg Participants met the DSM-IV criteria forMA-use disorderN¼ 10 (within-subjects design)

m Metacognition Repeated-dosing effects were not investigate

Kirkpatrick et al (in press) Immediate and long-term memory (digit-recall task); visuospatial perception (DSST);reaction time, vigilance and inhibitory control(DAT); sustained attention and inhibitorycontrol (RIT); learning/memory (RAT)

Oral: 0, 20, 40 mg Participants reported previousexperience with MA, but did not meetthe DSM-IV criteria for a MA-usedisorderN¼ 11 (within-subjects design)

m Visuospatial perceptionm Reaction timem Vigilancem Learning/memory2Immediate and long-term memory2Inhibitory control2Sustained attention

Repeated-dosing effects were not investigate

Marrone et al (2010) Speech (quantity, fluency); speech perception(ratings made by naı̈ve listeners)

Oral: 0, 20, 40 mg Participants reported previousexperience with MA, but did not meetthe DSM-IV criteria for a MA-usedisorderN¼ 11 (within-subjects design)

m Speechm Speech perception

Repeated-dosing effects were not investigate

Mohs et al (1978) Information processing (visual search task);Divided attention (DAT); Time estimation(Time production task)

Oral: 0, 10 mg Participants’ drug-use histories notreportedN¼ 24 (within-subjects design)

m Information processing2 Divided attention2 Time estimation

Only one active dose studiedDose examined was lower than those usedrecreationally

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Table 1 Continued

Investigators Domain Methamphetamineroute and dose

Participants and design Cognitive findings Caveats

Route of administration used is not typicallyassociated with abuseRepeated-dosing effects were not investigated

Mohs et al (1980) Learning/memory (Sternberg’s memoryscanning task, Buschke’s selective remindingtask); Time estimation (Time productiontask)

Oral: 0, 10 mg Participants’ drug-use histories notreportedN¼ 10 (within-subjects design)

2 Learning/memory2 Time estimation

Only one active dose studiedDose examined was lower than those usedrecreationallyRoute of administration used is not typicallyassociated with abuseRepeated-dosing effects were not investigated

Rush et al (2011) Visuospatial perception (DSST) Intranasal: 0, 2.5, 5, 10, 20 mg Participants met the DSM-IV criteria fora stimulant-use disorder

m Visuospatial perception Repeated-dosing effects were not investigated

Sevak et al (2009) Visuospatial perception (DSST) Oral: 0, 2.5, 5, 10, 15 mg All participants reported previousstimulant use, but did not meet theDSM-IV criteria for a MA-use disorderN¼ 10 (within-subjects design)

2 Visuospatial perception Doses examined were lower than those usedrecreationallyRoute of administration used is not typicallyassociated with abuseRepeated-dosing effects were not investigated

Silber et al (2006) Psychomotor function (Tracking task, TMT);working memory (Digit span forward andbackward); sustained attention (Digitvigilance), simple attention (Movementestimation); visuospatial perception (DSST);Perceptual speed (Inspection time task)

Oral: 0, 0.42 mg/kg (maximumdose: approximately 30 mg)

All participants reported previouslimited stimulant use, but did not meetthe DSM-IV criteria for a MA-usedisorderN¼ 20 (within-subjects design)

d,l-Methamphetamine:m Sustained attentionm Visuospatial perceptionm Psychomotor function (Tracking task)2 Psychomotor function (TMT)2 Working memory2 Perceptual speed2 Simple attentiond-methamphetamine:m Sustained attentionm Perceptual speed2 Working memory2 Visuospatial processing (performedworse than placebo in first session andbetter than placebo in second)2 Psychomotor function2 Simple attention

Only one active dose studiedRoute of administration used is not typicallyassociated with abuseRepeated-dosing effects were not investigated

Talland and Quarton(1965)

Shifting attention (Running digit span task) Intravenous: 0, 15 mg/68 kg Participants’ drug-use histories notreportedN¼ 18 (within-subjects design)

2 Shifting attention Only one active dose studiedDose examined was lower than those usedrecreationallyRepeated-dosing effects were not investigated

Abbreviations: DAT, divided attention task; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders 4th Edition; DSST, digit-symbol substitution task; FTT, finger tapping task; LRT, logical reasoning task;MA, methamphetamine; RAT, repeated acquisition task; RIT, rapid information task; RVIPT, rapid visual information processing task; TMT, Trail making task.Cognitive performance: m, MA improved performance; 2, MA produced no effect on performance.

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Towards this end, we examined the impact of a range ofintranasal methamphetamine doses, including doses largerthan those previously investigated (0, 12, 25, and 50 mg/70 kg), on the cognitive functioning of methamphetamineabusers (Hart et al, 2008). All active methamphetaminedoses improved reaction time and sustained attention, butonly the two intermediate doses (12 and 25 mg) significantlyimproved visuospatial perception. Importantly, metham-phetamine-induced disruptions were not observed in anycognitive domain. These findings are similar to those fromthe few other intranasal studies, during which methamphet-amine (12 mg) enhanced metacognition (knowledge aboutthe efficacy of one’s own actions: Kirkpatrick et al,2008)Fand (10, 20 mg) improved visuospatial perception(Rush et al, 2011). Similar results have been reported whenthe drug was administered intravenously to methamphet-amine abusers (Johnson et al, 2005, 2007). Anecdotally,methamphetamine is sometimes abused in a binge pattern(multiple doses administered repeatedly) at doses largerthan those studied thus far (eg, Cho et al, 2001). Thus,it is possible that cognitive functioning would be dis-rupted, and not enhanced, following larger methamphet-amine doses administered repeatedly. It is important tonote, however, that methamphetamine doses tested in thestudies described above are well within the range typi-cally used by recreational users to produce euphoriaand other desired effects. Nonetheless, future studiesevaluating the effects of repeated methamphetamine admin-istration on cognitive functioning are best suited to resolvethis issue.

Review of the Long-term Effects of Methamphetamineon Human Cognition

Data from a growing number of laboratory studies havedemonstrated that low and moderate doses of methamphe-tamine improve cognitive functioning in some domains,even when the drug is administered via routes associatedwith abuse. The impact of larger drug doses administeredrepeatedly over extended periods is less clear owing toethical considerations that limit drug exposure duringparticipation in laboratory studies. An alternative approachto determining possible detrimental effects of largemethamphetamine doses on cognitive performance hasbeen to study the brain and cognitive performance ofabstinent long-term methamphetamine abusers. The idea isthat regular use of illicit methamphetamine via routes otherthan oral administration over several years may result inneurotoxic effects, especially to monoamine neurons, whichcan have deleterious consequences on cognitive function-ing. Below, we review studies that have: (1) combined brain-imaging techniques with some cognitive tasks in an effort tocorrelate methamphetamine abusers’ cognitive functioningwith brain structure integrity and/or activity; and (2)employed comprehensive neuropsychological batteries toinvestigate methamphetamine abusers’ cognitive function-ing. We also include the few studies that have used positronemission tomography (PET) imaging (without testing anycognitive task) to investigate methamphetamine abusers’brain structure integrity and/or activity, because thesestudies have the potential to provide more specificinformation about methamphetamine-related DA neuro-

toxicity. A caveat to this statement is that dopaminergicneuronal toxicity cannot be definitely determined in PETstudies alone, as changes in tracer binding may reflectadaptation and not toxicity. (Studies that included HIV +individuals were excluded in an effort to minimize theimpact of potentially confounding variables.)

PET studies investigating DAT and DA receptor avail-ability of abstinent methamphetamine users. Becausethere are ample data collected in laboratory animalsdemonstrating that large repeated methamphetamine dosesdecrease several DA markers, including DAT density (eg,Cadet and Krasnova 2009), some have reasoned that long-term methamphetamine abuse by humans should produce areduction in DAT density and DA receptor availability.Table 2 summarizes the studies that have used PET to assessdifferences in DAT and DA receptor availability whenabstinent illicit methamphetamine users were comparedwith control participants. In one of the first studies of thistype, McCann et al (1998) conducted a PET study using[11C]WIN-35428, a DAT ligand, to evaluate whetherdifferences exist in striatal DAT density of methamphet-amine users when compared with multiple other groups.Four groups of participants were studied: methamphet-amine users (N¼ 6); methcathinone users (N¼ 4); Parkin-son’s disease patients (N¼ 3); and controls (N¼ 10).Methamphetamine users reported being abstinent for anaverage of 32±22 (±SD) months before their studyparticipation. Despite this extended period of abstinence,methamphetamine participants (as well as methcathinoneusers and Parkinson’s disease patients) had significantlylower [11C]WIN-35428 binding potentials in both thecaudate nucleus and putamen compared with controlparticipants. It should be noted, however, that there wasconsiderable overlap in the binding potentials of metham-phetamine participants and control group individuals, thatis, binding potential values for some methamphetamineusers were equal to or higher than those of some individualsin the control group. Other caveats associated with thisstudy included the small number of participants studiedand the inability to control for the influence of otherrecreational drug use, that is, all methamphetamineparticipants reported using additional illicit drugs, makingit impossible to isolate methamphetamine-induced effectson DAT availability.

In an attempt to minimize the impact of other illicit druguse, Sekine et al (2001) conducted a similar PET studyin which Japanese methamphetamine users without otherillicit drug-use histories (N¼ 11) were compared with amatched control group (N¼ 9). In general, their data wereconsistent with those obtained by McCann et al (1998) inthat striatal DAT binding potentials were approximately20% lower in methamphetamine users than in controlparticipants. These findings suggest that the differentialbinding potential values obtained in the two studies werenot attributable to other illicit drug use; both groupsof researchers argued that the data lend support to theview that chronic illicit methamphetamine use producespersistent reductions in human DAT density that maybe related to damage of striatal DA axons and axonterminals. Furthermore, these as well as other investigators


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Table 2 PET Studies

Investigators Domain tested Participants Period of abstinence Cognitive and brain findings Caveats

Dopamine-related (DAT, D2/D3 receptor, VMAT-2) ligands

Boileau et al (2008) Attention/psychomotor function (TMT-A,Grooved pegboard); Immediate and delayedmemory (CVLT); Working memory (Letter-Number Sequencing and Visual MemorySpanFbackwards subtests of WMS-III);Set-shifting/executive function (TMT-B)Note that the complete test battery was notreported

MA users met the DSM-IV criteriafor a MA-use disorder: N¼ 16Controls: N¼ 14

Mean: 19±24 days Cognitive:k Attention/psychomotor functioningk Delayed memory2 Working memory2Set-shifting/executive functionBrain:m VMAT-2 BP in caudate, putamen, andventral striatum

Controls had higher levels of educationCognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Johanson et al (2006) Attention/psychomotor function (TMT-A,Grooved pegboard, Finger-tapping task,Rapid visual information processing(CANTAB)); Visuospatial perception(DSST); Immediate and delayed memory(CVLT, PAL); Working memory (Spatialworking memory and Delayed match tosample tasks (CANTAB)); Set-shifting/executive function (TMT-B, Verbal fluencytest: FAS, Animal fluency, Intra/extradimensional shift and Stocking ofCambridge tasks (CANTAB))

MA users met the DSM-IV criteriafor MA dependence: N¼ 16Controls: N¼ 18

Mean: 3.4 years, range 3 months–18years (required 3-month minimum)

k Visuospatial perceptionk Immediate and delayed memory(CVLT only)2 Attention/psychomotor function(3 out of 4 tests)2 Working memory2Set-shifting/executive functionBrain:k DAT BP in all regions of the striatum(including caudate, putamen, and ventralstriatum)k VMAT-2 BP in the striatum overall(including caudate and anterior putamen)

MA users’ cognitive performance on all tests fellwithin the normal range when data comparedagainst normative data setThe influence of drug use other than MA notcontrolledThe influence of comorbid psychiatric disorderssuch as ADHD and depression not controlledNo relationship between imaging data andcognitive deficits was observedSmall number of participants studied

Lee et al (2009) Cognitive testing not included MA users met the DSM-IV criteriafor MA dependence: N¼ 22Controls: N¼ 30

All had positive urine testsupon entry

Cognitive:Not includedBrain:k D2/D3 BP in the striatum (caudatenucleus, putamen, and ventral striatum)

Participant educational information not reportedRelationship between cognitive functioning andbrain activity could not be determined becauseno cognitive measure was includedThe influence of drug use other than MA notcontrolled

McCann et al (1998) Cognitive testing not included MA users (diagnostic informationnot provided): N¼ 6Controls: N¼ 10

Range 4–65 months Cognitive:Not includedBrain:k DAT BP in the caudate nucleus andputamen

Relationship between cognitive functioning andbrain activity could not be determined becauseno cognitive measure was includedThe influence of drug use other than MA notcontrolledSmall number of participants studied

McCann et al (2008) Attention/psychomotor function (TMT-A,Grooved pegboard, Finger-tapping task,Stroop);Learning/memory (WMS-III LogicalMemory); Working memory (Letter-NumberSequencing and Visual Memory Span-backwards subtests of WMS-III); Responseinhibition (Stroop); Set-shifting/executivefunction (TMT-B, WCST, Boston namingtask, Verbal concept attainment scale, Newadult reading test, Controlled oral wordassociation test)

Cognitive testing:MA users (diagnostic informationnot provided): N¼ 22Controls: N¼ 17Imaging subset:MA users: N¼ 7Controls: N¼ 16

Cognitive testing: mean 28.90±64.77months, range 0.5–300 monthsImaging subset: mean 77.43±102.21months, range 8–300 months

2 Attention/psychomotor function(3 out of 4)2 Learning/memory (3 out of 5)2 Working memory2 Set-shifting/executive functionBrain:k DAT BP in the bilateral caudate andleft putamen

Cognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledThe influence of comorbid psychiatric disorderssuch as ADHD and depression not controlledSmall number of participants studied

Sekine et al (2001) Cognitive testing not included MA users (diagnostic informationnot provided): N¼ 11Controls: N¼ 9

Range 7 days–1.5 years Cognitive: Not includedBrain:k DAT BP in the striatum (caudate,putamen, and ventral striatum) and PFC

Relationship between cognitive functioning andbrain activity could not be determined becauseno cognitive measure was includedSmall number of participants studied

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Table 2 Continued


Volkow et al (2001b) Attention/psychomotor function (TMT-A,Grooved pegboard, Timed gait task, Stroop,CalCAP); Visuospatial perception (DSST);Learning/memory (AVLT)


Mean 5.9±9.0 months (required 2-week minimum)

Cognitive: Comparisons between the twogroups not reported, but significantcorrelations between striatal DAT andperformance in some cognitive domainswere noted for the MA group (ie,psychomotor function, learning/memory)Brain: k DAT BP in the caudate andputamen

Participant educational information not reportedCognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Volkow et al (2001c) Cognitive testing not included MA users met the DSM-IV criteriafor MA dependence: N¼ 15Controls: N¼ 20

Data not reported Cognitive: Not includedBrain: k D2 BP in the caudate and putamen

Participant educational information not reportedRelationship between cognitive functioning andbrain activity could not be determined becauseno cognitive measure was includedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Volkow et al (2001d) Psychomotor function (Grooved pegboard,Timed gait task); Learning/memory (AVLT)

MA users met the DSM-IV criteriafor MA dependence: N¼ 5evaluated twice (early andprotracted abstinence); N¼ 5additionalControls: N¼ 11

Early: mean 3±1.6 monthsProtracted (9 months later): 14±2monthsOther group: mean 17±10 months

Cognitive: Comparisons between the MAand control groups not reported2 Cognitive performance was not alteredas a function of abstinence statusBrain:k DAT BP in the caudate andputamen in early abstinence, relative tocontrolsm DAT BP in the caudate and putamenwith protracted abstinence


FDG ligand

Berman et al (2008) Vigilance (auditory vigilance task) MA users met the DSM-IV criteriafor MA dependence: N¼ 10Controls: N¼ 12

Test 1: mean 6.7±1.6 daysTest 2: mean 27.6±0.96 days

Cognitive: 2 Vigilance (auditory vigilancetask)Brain: m rCMRglc between tests 1 and 2 inthe neocortex (in MA users)2 rCMRglc between tests 1 and 2 insubcortical regions (in MA users)

Only one cognitive measure includedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Kim et al (2005) Set-shifting/executive function (WCST) MA users met the DSM-IV criteriafor an MA-use disorder: N¼ 35Controls: N¼ 21

Mean 19.14±27.20 months (required4-week minimum)

Cognitive: k Set-shifting/executive function:males2 Set-shifting/executive function: femalesBrain: 2 rCMRglc levels in the rightsuperior frontal WM (females)k rCMRglc levels in the right superiorfrontal WM (males)

Controls had higher levels of educationOnly one cognitive measure included and it wasnot compared against normative data set, whichmakes it difficult to determine the clinicalimportance of findingsThe influence of drug use other than MA notcontrolled

Kim et al (2009) Same as above MA users met the DSM-IV criteriafor an MA-use disorder: N¼ 24Controls: N¼ 21

Mean 20.5±8.3 days (required 1-weekminimum)

Cognitive:k Set-shifting/executive functionBrain: k Metabolism in the left inferiorfrontal WM

Controls had higher levels of educationOnly one cognitive measure included and it wasnot compared against normative data set, whichmakes it difficult to determine the clinicalimportance of findingsPerformance on the WCST was not correlatedwith brain activity

London et al (2004) Attention/vigilance (CPT) MA users (diagnostic informationnot provided): N¼ 14Controls: N¼ 13

Range 4–7 days Cognitive: 2 Attention/vigilanceBrain: 2 No difference in global glucosemetabolismk Relative rCMRglc in infragenual ACCm Activity in one cluster extending frommiddle to posterior portions of dorsalcingulate gyrusm Relative rCMRglc in the ventral striatum

Controls had higher levels of educationOnly one cognitive measure includedThe influence of drug use other than MA notcontrolledSmall number of participants studied

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Table 2 Continued


London et al (2005) Same as above MA users (diagnostic informationnot provided): N¼ 17Controls: N¼ 16

Range 4–7 days Cognitive:k Attention/vigilanceBrain: MA users: Negative correlationsbetween error rates and relative activity inanterior and middle cingulate gyrus andinsulaControls: Positive correlations betweenerror rates and activity in the cingulatecortex

Controls had higher levels of educationOnly one cognitive measure included and it wasnot compared against normative data set, whichmakes it difficult to determine the clinicalimportance of findingsThe influence of drug use other than MA notcontrolledSmall number of participants studied

Volkow et al (2001a) Attention/psychomotor function (TMT-A,Grooved pegboard, Timed gait task, Stroop,CalCAP); Visuospatial perception (DSST);Learning/memory (AVLT)


Required 2-week minimum Cognitive: Results not reportedBrain: k Glucose metabolism in thethalamus, caudate, and putamenm Glucose metabolism in parietal cortex

Participant educational information not reportedClinical importance and relationship betweencognitive functioning and brain activity could notbe determined because no cognitive results notreportedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Wang et al (2004) Same as above MA users met the DSM-IV criteriafor MA dependence: N¼ 5evaluated twice (short andprotracted abstinence); N¼ 8additionalControls: N¼ 11

Short: mean 3±1.6 monthsProtracted:Original 5 MA users: mean 14±2monthsAdditional 8 MA users: mean 17±10months

Cognitive: Comparisons between the twogroups not reported, but significantcorrelations between thalamic activitychanges and performance in some cognitivedomains were noted for the MA group (ie,psychomotor function (timed gait), learning/memory (delayed recall))Brain: MA users evaluated twice:m Thalamic metabolism in protractedabstinence relative to short abstinence2 Global metabolism or absolutemetabolic measures in the striatum,thalamus, or occipital cortex between short(o6 months) and protracted (12–17months) abstinence2 Striatal metabolism in protractedabstinence relative to short abstinenceComparison with controls:k Striatal metabolism in protractedabstinence and short abstinence relative tocontrolsk Thalamic metabolism in short abstinencerelative to controls2 Absolute global brain metabolismamong short and protracted abstinence andcontrols2 Thalamic metabolism in protractedabstinence relative to controls


Abbreviations: ACC, anterior cingulate cortex; AVLT, Rey auditory verbal learning test; BP, binding potential; CalCAP, California computerized assessment package; CANTAB, Cambridge automated neuropsychologicalassessment battery; CPT, continuous-performance task; CVLT, California verbal learning task; DAT, dopamine transporter; DSM-IV, Diagnostic and Statistical Manual of Mental Disorders 4th Edition; DSST, digit-symbolsubstitution task; FDG, [18F]fluorodeoxyglucose; MA, methamphetamine; PAL, paired associates learning task; PET, positron emission tomography; PFC, prefrontal cortex; rCMRglc, regional cerebral metabolic rate forglucose; TMT-A, Trail making test, part A; TMT-B, Trail making test, part B; VMAT-2, vesicular monoamine transporter-2; WCST, Wisconsin card sorting test; WM, white matter; WMS-III, Wechsler memory scale-III.Cognitive performance: k, MA users performed more poorly than controls; 2, MA users and controls performed equally.Brain activity: k, decreased activity in MA users; m, increased activity in MA users; 2, no difference in activity between MA users and controls.

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(eg, Volkow et al, 2001b) have suggested that lower DATdensity contributes to clinical pathology (eg, cognitiveimpairments, psychotic symptoms) reported to be asso-ciated with long-term methamphetamine use. Althoughinterpretations from both studies are tempting, theirgenerality or clinical importance remain uncertain owingto a few important limitations. For example, both studiesevaluated only a small number of participants. Moreimportantly, however, it is unclear whether an approxi-mately 20% difference in DAT density, as measure withconventional PET-imaging techniques, is within the normalrange of human variability or whether this difference isassociated with alterations in cognitive functioning. In otherwords, the clinical relevance of such findings is impossibleto determine because cognitive functioning was notassessed. The point here is not to give precedence tobehavioral over neuroimaging data, but to emphasize theneed to include relevant functional outcomes that allow us tounderstand the consequences of the neural activity. Withoutbehavioral measures, we may be enticed to make unwarr-anted speculations about the neural basis of behavior.

Addressing some of the shortcomings of previousinvestigations, Johanson and co-workers (2006) conducteda PET study that did include cognitive assessment. Thisgroup of researchers used an extensive cognitive battery tocompare functioning of abstinent methamphetamine abus-ers (N¼ 16) with control participants (N¼ 18). They used[11C]methylphenidate and [11C]dihydrotetrabenazine todetermine striatal levels of DAT and VMAT-2, respectively.They found that although striatal DAT and VMAT-2binding potentials were 10–16% lower in methamphetamineusers, cognitive performance on the majority of tasks wasnot significantly different. Neither neuroimaging norcognitive data were correlated with methamphetamineabstinence duration. Methamphetamine users did, however,perform more poorly than controls on tasks that tapped thedomains of sustained attention and immediate and long-term memory. Importantly, though, the methamphetamineusers’ performance remained within the normal range fortheir age and educational group. The authors appropriatelyconcluded that while their imaging data showing differencesbetween abstinent long-term methamphetamine users andcontrols were consistent with previous investigations (eg,McCann et al, 1998; Volkow et al, 2001b; see also, Boileauet al, 2008), the functional significance of these differencesmight be limited because methamphetamine users’ perfor-mance on most tests was equal to controls and norelationship between the imaging data and cognitive deficitswas observed. While the number of participants studied waslarger than that examined in most previous PET studies, itis possible that greater numbers are necessary to observeclinically meaningful cognitive impairments.

Another point relevant to the above discussion is that theconclusions drawn by Johanson et al (2006) appear toconflict with those of a similar subsequent study. McCannet al (2008) found that methamphetamine users exhibitedsignificantly lower DAT binding (13–23%), poorer perfor-mance on a minority of cognitive tasks (tasks measuringattention and long-term memory), and no relationshipbetween duration of abstinence and neuroimaging results orcognitive performance. These data are in agreement withthe findings of Johanson et al (2006). Despite this, McCann

et al (2008) interpreted their data as evidence demonstrat-ing a connection between recreational methamphetamineuse and pathology. Given that the data alone do notcontradict each other, the apparent incongruence inconclusions drawn centers on the interpretations of thecognitive findings obtained.

Recognizing this distinction between results and inter-pretation of results, we can now highlight a prevalentconcern throughout the body of scientific literatureinvestigating methamphetamine-associated effects onhuman cognition. If we limit our focus to cognitiveperformanceFthe behavior of interest hereFwe can seethat control subjects outperformed methamphetamine userson a few tasks in both studies. The clinical implications ofsuch differences, however, are nearly impossible todetermine without knowledge of the expected performancefor a particular group, taking into account group members’age and education (ie, normative data). While Johansonet al, interpreted their cognitive findings within the contextof these important constraints, McCann et al provided nosuch comparative information, which makes it difficult toevaluate the clinical import of neurocognitive differences.When we compared the cognitive performance mean scoresof the methamphetamine users in the McCann et al study,with normative scores, none of the former were outside ofthe normal range. Even scores obtained on measures thatshowed statistically significant differences betweenmethamphetamine users and controls were within thenormal range. This observation not only calls into questionthe clinical significance of the cognitive differencesobserved in the McCann et al study, but it also underscoresthe importance of interpreting cognitive findings within therange of performance for age- and education-matchedcontrols. Otherwise, we run the risk of stigmatizingindividuals, which could have debilitating consequences.

The preceding point is worth elaborating. The literatureon methamphetamine use is focused on ‘impairment,’ andseems to conflate two different meanings of this term. Onemeaning is captured by the canonical situation in which onegroup of participants performs statistically significantly lesswell on a task than does a control group. Although there is astatistically significant difference, its clinical relevance, oreveryday import, is rarely specified. A second meaning of‘impairment’ is that of a substantial loss of function, adysfunction, in which performance may even fall outside ofnormal range and bears clinical significance. (The twomeanings probably represent end points on a continuum ofmeanings of ‘impairment’ that appears in the generalliterature on group differences.) The problem in theliterature on methamphetamine use is that in many studiesthe results support only the first or difference interpreta-tion, but the results are discussed in terms of the‘dysfunctional’ interpretation. In essence, the English word‘impairment’ (or ‘deficit’) is ambiguous, and researchersin this field often switch meanings in moving fromactual findings to discussion of the implications of thesefindings.

PET studies investigating brain metabolism of abstinentmethamphetamine users. Other researchers have used PETimaging to evaluate brain glucose metabolism in abstinentmethamphetamine users while they perform some cognitive


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task. Because all neurons use blood glucose for their energy,this strategy provides an indirect measure of neuronalactivity. Table 2 summarizes the studies that have used thisapproach to compare regional brain activity of metham-phetamine users with that of control participants. Themajority of these studies have found some differencesbetween the groups. In one series of studies, London andco-workers used [18F]flurodeoxyglucose (FDG) as the ligandto evaluate recently abstinent methamphetamine abusersand control participants while performing a 30-minauditory continuous-performance or sustained attentiontask. These investigators reported that the two groups didnot differ on task performance, but did differ on measuresof relative regional glucose metabolism: methamphetamineabusers exhibited lower metabolism in the anteriorcingulate and insula and higher metabolism in other areas,including the amygdala and ventral striatum (London et al,2004). These findings provide additional evidence that braindifferences observed between methamphetamine abusersand controls may not necessarily reflect cognitive impair-ments. However, the investigators did find that themethamphetamine users scored higher on Beck DepressionInventory and State-Trait Inventory scales than thecontrols. Even though these inventories alone are not useddiagnostically, this led them to conclude that their findingsidentify ‘brain dysfunction that may underlie affectivedeficits in methamphetamine abusersy .’

There are at least two concerns associated with thisconclusion. First, it is impossible to state with any degree ofcertainty that increased or decreased relative regionalglucose metabolism in a particular brain region is‘dysfunctional,’ especially without knowledge of the normalrange of functioning. Again, the results show that there is adifference, but the interpretation goes beyond that to posit adysfunction. This point is even clearer when it comes to thefinding that methamphetamine users had higher BeckDepression Inventory and State-Trait Anxiety Inventoryscores than the control group. The mean scores formethamphetamine users on these inventories did notapproach the clinically significant range, for example,methamphetamine users did not approach the thresholdfor clinical depression. Here, we have a clear case ofdifference that does not meet an accepted standard ofclinical dysfunction. This case illustrates the propensity tointerpret any brain difference as pathology, even when thereare no differences on functional outcome measures (thecognitive measure) or there are differences (the affectivescales), but the clinical importance of the differences isunclear.

In subsequent studies, differences in cognitive function-ing, as well as brain glucose metabolism, have been noted(eg, London et al, 2005; Kim et al, 2005). In one recentstudy, Kim et al (2009) compared abstinent Koreanmethamphetamine abusers (N¼ 24) with control partici-pants (N¼ 21) and reported that methamphetamine usershad significantly lower inferior frontal cortex restingactivity. Further, the methamphetamine users performedmarkedly worse on the Wisconsin card sorting task(WCST), which is a measure of set-shifting (or cognitiveflexibility), attention, and inhibition. However, performanceon the WCST was not correlated with brain activity. Hence,the researchers’ conclusion that their findings provide

evidence of ‘frontal abnormalities’ and ‘executive dysfunc-tion’ in methamphetamine abusers is somewhat misleading.In addition, there is the usual caveat that it is criticallyimportant to interpret cognitive functioning data within theconstraints of the larger normative data set. Otherwise, it isdifficult to make definitive statements about the functionalsignificance of the data. Kim et al (2009) did not report thistype of comparison in their study, perhaps, in part, becausethere are no published Korean norms for the WCST. Forthese reasons, speculations about ‘frontal executive dys-function’ in the methamphetamine users studied seemunwarranted.

The Kim et al (2009) study raises two other issues. First, itis inappropriate to conclude that individuals who performmore poorly than controls on the WCST have ‘executivedeficits’ (which include deficits in attention, inhibition, andworking memory). Performance on multiple tasks, whichassess the same domains, should be evaluated beforemaking such claims because individual tasks may tapslightly different components of the domain of interest (ie,the measures must be functionally validated in advance).Thus, there is a lack of construct validity here, which tosome extent is true of other studies that include only asingle task to measure a cognitive domain. Second, theremay be many reasons for poor relative task performance inKim et al (2009). One potential explanation for the findingscould be related to educational level. Control participantshad a significantly higher level of education than metham-phetamine users, and individuals with more education havebeen demonstrated to outperform those with less educationon the WCST (Boone et al, 1993; Heaton et al, 1993).

In general, studies using PET imaging have producedinconsistent results. Some data demonstrate DAT bindingpotential, DA receptor availability, and brain glucosemetabolism differences between abstinent methamphet-amine users and control participants. Several researchershave found lower striatal DAT and DA D2 receptor levels inlong-term methamphetamine users, although there isconsiderable overlap between methamphetamine usersand control participants. In addition, some reports suggestextended abstinence increases methamphetamine users’DAT levels (Volkow et al, 2001d), but others failed toobserve similar findings (McCann et al, 2008). Despite this,duration of abstinence appears to have little effect oncognitive performance (eg, Volkow et al, 2001d; Johansonet al, 2006; McCann et al, 2008). While findings from brainglucose metabolism studies indicate that methamphetamineusers, in comparison with control participants, display adifferent pattern of activity in some regions, many of thesedifferences have not been replicated by independent groupsof researchers. For example, Volkow et al (2001a) foundthat methamphetamine users had higher absolute regionalcerebral glucose metabolism, whereas London et al (2004)reported that methamphetamine users and controls did notdiffer on this measure. As usual, evidence of the impact ofthe observed brain differences on cognitive functioningappears to be limited. In the few studies that have includeda comprehensive cognitive battery, methamphetamine usersperform similarly to controls on the vast majority of tasks,and even on tasks in which significant group differenceswere noted, methamphetamine-using individuals’ perfor-mance was within the normative range for their age- and


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education-matched cohort (eg, Johanson et al, 2006).Moreover, in the majority of studies, methamphetamineusers reported extensive use of other psychoactive drugs,while comparison groups reported only limited drug use(see Table 2). This makes it extremely difficult todisentangle methamphetamine-related effects on cognitivefunctioning from those of other drugs. Despite theseimportant caveats, the PET-imaging literature is repletewith a general tendency to characterize any brain and/orcognitive performance differences as dysfunctions uniqueto methamphetamine users.

MRI studies investigating brain structure sizes ofabstinent methamphetamine users. As seen in Table 3, agrowing number of investigators have used magneticresonance imaging (MRI) procedures combined withcognitive testing to understand the impact of long-termrecreational methamphetamine use on cognitive function-ing. One advantage of MRI, relative to PET, is that MRIprovides high-resolution images of brain structure sizes andthickness. The use of MRI is also less invasive; unlike PET,it does not require the injection of radioactive compounds.In one of the most highly cited scientific articles in this areaof research (also featured in The New York Times, 20 July2004: see Blakeslee (2004)), Thompson and co-workers(2004) used MRI to compare brain structure volume andcognitive performance of methamphetamine-dependentindividuals (N¼ 22) with control participants (N¼ 21).They found that, relative to controls, methamphetamineusers had lower gray matter volumes in the right cingulategyrus (�11.3%) and hippocampal region (�7.8%), althoughno differences were observed in total cerebral or total graymatter volumes. In contrast, total white matter volumes( + 7.0%) and right lateral ventricles ( + 25.2%) were greaterin the methamphetamine users. The four cognitive tasksadministered involved only long-term memory (ie, word-and picture-recall and word- and picture-recognition), andonly performance on the word-recall task was positivelycorrelated with hippocampal volume. Further, there was nodata comparing methamphetamine users with controls onany memory task. Yet, the investigators concluded that‘ychronic methamphetamine abuse causes a selectivepattern of cerebral deterioration that contributes toimpaired memory performance.’

This interpretation clearly goes far beyond the data. First,brain images were collected at only one time point forboth groups of participants. This makes it virtuallyimpossible to determine whether methamphetamine caused‘cerebral deterioration,’ as pre-existing differences betweenthe two groups of participants cannot be ruled out.Furthermore, the functional significance of the structuraldifferences is in doubt. Based on the limited cognitiveresults presented, it appears that the brain structural sizedifferences were not predictive of overall memory perfor-mance. The only statistically significant cognitive findingwas a correlation of hippocampal volume and performanceon one of the four tasks. This finding is the basis for theclaim that methamphetamine users had memory impair-ments, because the hippocampus is known to play a role insome long-term memory; however, other neural areas arealso involved in mediating long-term memory (eg, overlying

temporal neocortex), and one of them could have been thecritical mediator of performance in this study. Anotherpertinent issue was that control participants had markedlyhigher levels of schooling than methamphetamine users(15.2 vs 12.8 years, respectively); it is well established thateducational level modulates long-term memory (Mitrushinaet al, 2005). In light of these considerations, it is somewhatdisconcerting that the results from the study were construedas findings of pathology rather than preliminary evidence ofgroup differences that appear to have limited or doubtfulfunctional significance.

Another line of research aimed at understanding theimpact of methamphetamine use on cognition and brainfunctioning is the use of perfusion MRI to determineregional cerebral blood flow. Chang and co-workers (2002)evaluated 20 abstinent methamphetamine abusers and 20control participants with this procedure and assessed theircognitive performance using an extensive neuropsycholo-gical test battery. Although the groups did not differ onglobal measures of brain volumes or cerebrospinal fluid,methamphetamine users were reported to have lowerrelative regional cerebral blood flow bilaterally in theputamen/insular cortices (B�11%) and in the right lateralparietal cortex (�11%). In contrast, the methamphetamineusers were found to have greater relative regional cerebralblood flow in the left temporoparietal white matter ( + 13%),the left occipital brain region ( + 10%), and the rightposterior parietal region ( + 24%). When methamphetamineusers’ cognitive performance was compared with age- andeducation-matched normative data, their performance waswithin the normal range for all tasks, including thoseassessing attention and long-term memory, as well as thosereflecting psychomotor speed, fine motor speed (Groovedpegboard), and gross motor functioning (Timed gait). Onan additional test battery (customized California Comput-erized Assessment Package: CalCAP), methamphetamineusers, relative to controls, exhibited slower reaction timeson some tasks, although task accuracy was overwhelminglysimilar. As a result of these findings, Chang et al (2002)concluded that methamphetamine users ‘not only hadcerebral perfusion abnormalities, but also demonstratedcognitive deficits.’ They further noted that the imagingtechnique used appeared to be a more sensitive measure fordetecting brain function abnormalities.

Such conclusions are puzzling. The conclusion thatmethamphetamine users had cognitive deficits was basedprimarily on the reaction time, not the accuracy, of theresults obtained during some CalCAP tasks, which suggest amotor slowing, rather than cognitive deficits. Furthermore,there are problems in interpreting differences. As notedearlier, if one wants to determine whether an individual’sperformance is normal, a fundamental requirement is thatthe performance has to be compared against a normativescore, taking into consideration the individual’s age andlevel of education. To avoid misinterpretations (such asoverpathologizing), normative data are imperative becausethey allow us to take into account the relative contributionof age and education in terms of the individual’s score andadjust the score accordingly. With regard to CalCAPperformance in the study by Chang et al (2002), this wasnot done, and the range of normative scores was notpresented. Similarly, the brain-imaging results obtained in


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Table 3 MRI Studies


MRI

Chang et al (2005) Attention/psychomotor function (TMT-A,Grooved pegboard, Timed gait task, Stroop,CalCAP); Visuospatial perception (DSST);Learning/memory (AVLT, Rey–Osterriethcomplex figure test); Working memory(CalCAP); Response inhibition (Stroop,CalCAP); Set-shifting/executive function (TMT-B,New adult reading test)

MA users met the DSM-IV criteria forMA dependenceCognitive testing: MA users: N¼ 44Controls: N¼ 28Imaging: MA users: N¼ 50Controls: N¼ 50

Mean 4.0±6.2 months(required 1-week minimum)

Cognitive: 2 No differences on cognitive testsobserved after co-varying for educationBrain: 2 Whole brain volumesm Globus pallidus volumesm Putamen volumes

Controls had higher levels of educationThe influence of drug use other than MA notcontrolled

Kim et al (2006) Attention/psychomotor function (TMT-A);Response inhibition (Stroop); Set-shifting/executive function (TMT-B, WCST)

MA users met the DSM-IV criteria forMA dependenceShort term (o6 months): MA users:N¼ 11Long term (46 months): MA users:N¼ 18Controls: N¼ 20

Long-term: mean 30.6±39.2 monthsShort-term: mean 2.6±1.6 months

Cognitive: k Set-shifting/executive function(WCST): short-term4long-term4controls2 Attention/psychomotor function2 Response inhibition2 Set-shifting/executive functionBrain: k GM density in R. middle frontal gyrus(short-term abstinentolong-termocontrols)2 WM density

Controls had higher levels of educationCognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Thompson et al (2004) Immediate and delayed memory (word-recalland recognition; picture-recall and recognition);Attention/psychomotor function (TMT-A);Visuospatial perception (DSST)

MA users met the DSM-IV criteria forMA dependence: N¼ 22Controls: N¼ 21

Participants reported having used MA amajority of the past 30 days

Cognitive: Comparisons between the twogroups not reported, but a significantcorrelation between hippocampal volume andperformance on the word-recall task was notedfor all participantsBrain: k GM in the cingulate cortexk GM in the limbic cortexk GM in the paralimbic cortexk Hippocampal volumesm WM hypertrophy2 Total cerebral volume2 Total GM

Controls had higher levels of educationClinical importance and relationship betweencognitive functioning and brain activity could not bedetermined because limited cognitive data notreported and cognitive data not compared againstnormative data setThe influence of drug use other than MA notcontrolledSmall number of participants studied

pMRI

Chang et al (2002) Attention/psychomotor function (TMT-A,Grooved pegboard, Timed gait task, Stroop,CalCAP); Visuospatial perception (DSST);Learning/memory (AVLT); Working memory(CalCAP); Response inhibition (Stroop,CalCAP); Set-shifting/executive function (TMT-B,New adult reading test)

MA users met the DSM-IV criteria forMA dependence: N¼ 20Controls: N¼ 20

Mean 8.0±2.2 months Cognitive: 2 Regarding the standard cognitivethat was compared against a normative dataset, no differences on task accuracy noted forany testsCalCAP Performance:kReaction time on several tasksk Accuracy on 1-increment and 2-backworking memory tasksBrain:k rCBF in bilateral putamenk rCBF in bilateral insulak rCBF in right lateral parietalm rCBF in left temporoparietal WMm rCBF inleft occipitalm rCBF in right posterior parietal

Clinical importance and relationship betweencognitive functioning and brain activity could not bedetermined because CalCAP data was notcompared against normative data setThe influence of drug use other than MA notcontrolledSmall number of participants studied

DTI

Chung et al (2007) Set-shifting/executive function (WCST) MA users met the DSM-IV criteria forMA dependence: N¼ 32Controls: N¼ 30

Males: mean 24.3±37.5 monthsFemales: mean 43.1±65.9 months

Cognitive: k Set-shifting/executive function(WCST)Brain: k FA values in bilateral frontal WMat AC–PC planek FA values in right frontal WM at 5 mm aboveAC–PC plane

Controls had higher levels of educationOnly one cognitive measure included and it was notcompared against normative data set, which makesit difficult to determine the clinical importance offindingsThe influence of drug use other than MA notcontrolled

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Table 3 Continued


Salo et al (2009a) Attention/response inhibition (Stroop) MA users met the DSM-IV criteria forMA dependence: N¼ 37Controls: N¼ 17

Mean 20.98±31.9 months(required 3-week minimum)

Cognitive: k Response inhibitionBrain: 2 FA, ADC, or diffusion along directionof axonal fiber in genu or splenium of CC

Controls had higher levels of education and IQ(NART)Only one cognitive measure included and it was notcompared against normative data set, which makesit difficult to determine the clinical importance offindingsThe influence of drug use other than MA notcontrolled

fMRI

Hoffman et al (2008) Impulsivity (Delayed discounting task) MA users met the DSM-IV criteria forMA dependence: N¼ 19Controls: N¼ 17

Mean 48±17 days Cognitive:k MA users preferred smallerimmediate reward, ie, discounted more steeplyBrain: k Bilateral precuneusk Right caudate nucleusk ACCk DLPFC

Only one cognitive measure included and there areno normative data set for which the data can becompared, which makes it difficult to determine theclinical importance of findingsThe influence of drug use other than MA notcontrolledMA-dependent participants testedon an in-patient basis, while controlstested on an outpatient basisSmall number of participants studied

Leland et al (2008) Response inhibition (Go/No-go task) MA users met the DSM-IV criteria forMA dependence: N¼ 19Controls: N¼ 19

Mean 33.9±5.9 days Cognitive: 2 Response inhibitionBrain: m Cue-related activation in two ACCROIs

Only one cognitive measure includedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Monterosso et al (2007) Impulsivity (Delayed discounting task) MA users met the DSM-IV criteria forMA dependence: N¼ 12Controls: N¼ 17

Range 5–7 days Cognitive: k MA users preferred smallerimmediate reward, ie, discounted more steeplyBrain: k Differences in activation between hardand easy choices in left DLPFC and intraparietalsulcus

Participant educational information not reportedOnly one cognitive measure included and there areno normative data set for which the data can becompared, which makes it difficult to determine theclinical importance of findingsNo correlation between delayed discounting andbrain data observedThe influence of drug use other than MA notcontrolledSmall number of participants studied

Paulus et al (2002) Decision-making (Two-choice prediction task) MA users met the DSM-IV criteria forstimulant dependence: N¼ 10Controls: N¼ 10

Mean 22.4±3.5 days Cognitive: MA users more influenced byimmediately preceding outcomeBrain: k Activation in DLPFC during2-choice prediction task compared to2-choice response taskk No activation in ventromedial cortex in2-choice prediction task compared to2-choice response task

Only one cognitive measure included and there areno normative data set for which the data can becompared, which makes it difficult to determine theclinical importance of findingsThe influence of drug use other than MA notcontrolledSmall number of participants studied

Paulus et al (2003) Same as above MA users met the DSM-IV criteria forstimulant dependence: N¼ 14Controls: N¼ 14

Mean 25.0±2.7 days Cognitive: 2 Decision-making (but greaterwin-stay/lose-shift consistent responses)Brain: k Task-related activation in ACC,DLPFC, orbitofrontal, and parietal cortex

Controls had higher levels of educationOnly one cognitive measure included and there areno normative data set for which the data can becompared, which makes it difficult to determine theclinical importance of findingsThe influence of drug use other than MA notcontrolledSmall number of participants studied

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methamphetamine users were not compared with nor-mative data, which again limit speculations about abnorm-alities. Yet, it was suggested that the modest observedbrain-imaging differences provided a more sensitive mea-sure of brain function abnormalities. This interpretationseems particularly inappropriate in light of the fact thatmethamphetamine users’ overall cognitive performance(a crucial measure of brain functioning) was nearly identicalto that of the control group.

A different MRI technique used to study methamphet-amine users is diffusion tensor imaging (DTI), which can beused to assess brain white matter integrity and to localizefocal lesions respective to major white matter tracts. Themost frequently used dependent measures derived from DTIscans are: (1) fractional anisotropy, a measure of thedirectionality of diffusion; and (2) apparent diffusioncoefficient, a measure of the magnitude of the diffusion.Using this method, Salo et al (2009a) compared brainactivity during Stroop task performance in methampheta-mine abusers (N¼ 37) and control participants (N¼ 17).They found that the groups did not differ on any of thequantitative parameters derived from DTI or the number oferrors made on the Stroop task. The only statisticallysignificant difference obtained was that methamphetamineusers performed more slowly on the Stroop task than thecontrols. However, this effect was no longer significantwhen participants’ National Adult Reading Test scores wereincluded as a covariate in the analysis. Longer responsetimes on the Stroop task were significantly correlatedwith lower fractional anisotropy values in the genu ofcorpus callosum, but there was no interaction withgroup, that is, whether or not the participant was amethamphetamine user had no effect on the correlation.Similarly, duration of methamphetamine use or length ofmethamphetamine abstinence were not significantly corre-lated with any of the DTI measures. Despite the study’slimitations (see Table 3) and modest findings, it wasconcluded that ‘disruption of neural function in the rostralACC (anterior cingulate cortex) and adjacent WM (whitematter) produces a disruption in the pathways that areinvolved in behavioral regulation’ (Salo et al, 2009a). Formany of the same aforementioned concerns, a moretempered interpretation of the collected data would appearto be in order.

Functional MRI (fMRI) has also been used to study long-term methamphetamine abusers. Functional MRI reflectsbrain blood flow and other factors, and its signal increaseswhen neurons become more active. In this way, fMRI canprovide an indirect measure of neural activity. For example,Salo and co-workers (2009b) employed fMRI to image brainactivity of methamphetamine users (N¼ 12) and controlparticipants (N¼ 16) while they completed a Stroop task.Although no group differences were observed on taskaccuracy, the methamphetamine users, unlike the controls,did not show trial-to-trial reaction time improvements. Thiseffect corresponded with reduced activation in the rightprefrontal cortex of methamphetamine users, which led theinvestigators to conclude that their ‘data provide prelimin-ary evidence that methamphetamine abuse is associatedwith deficits in behavioral regulation associated withabnormal prefrontal cortex activationy .’ Again, this seemsto be an overinterpretation of modest results. As notedT

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601


before, meaningful group differences should be observed onmultiple measures of a particular cognitive domain (atten-tion and inhibition in the case of Stroop) before makingassertions about deficits in this domain. Also, again the onlydifference obtained in this study was that methamphet-amine users performed the task more slowly than their non-drug-using counterparts, although their accuracy rates wereequal, which is consistent with response slowing rather thana cognitive deficit. Similarly, prefrontal cortex activation inthe methamphetamine users was said to be ‘abnormal,’ butthe range of normal human activation was not presented ordiscussed.

Overall, MRI observations are consistent with data fromPET studies in that several brain-imaging differences havebeen noted between methamphetamine users and controls,but few of these findings have been independentlyreplicated. Unlike PET studies, where the focus, for themost part, has been appropriately limited to monoamine-rich brain areas, fMRI studies do not appear to have aconsistent rationale for targeting regions of interest. Withregard to cognitive functioning, few statistically significantdifferences have been observed between methamphetamineusers and control participants. Even when differences werefound, it is difficult to contextualize their functionalsignificance because frequently they are not correlated withmethamphetamine-use indicators (eg, duration of absti-nence, duration of methamphetamine abuse, frequency ofmethamphetamine use) and they are often not comparedagainst normative scores.

Comprehensive neuropsychological testing of abstinentmethamphetamine abusers. A major weakness associatedwith much of the neuroimaging literature is that moststudies have included limited cognitive testingFonly oneor two cognitive domains are assessed, and each by only asimple task. This makes it extremely difficult to drawconclusions about the clinical significance of the datacollected. To address this concern, as is shown in Table 4,some researchers have focused their efforts exclusively onassessing cognitive functioning of methamphetamine usersin comparisons with control participants. Typically, absti-nent methamphetamine abusers and controls complete acomprehensive battery of neuropsychological testing overthe course of several hours, and the results are compared todetermine whether or not the cognitive performance of themethamphetamine groups is normal. Of course, as notedabove, normality is a relative concept that should bedetermined by comparing performance of a targeted groupwith scores from a normative data set. Although this is afundamental requirement of neuropsychological testing, ithas been frequently ignored in the methamphetamine/cognition literature.

For example, Simon et al (2002) compared cognitivefunctioning of 40 methamphetamine abusers with 40control participants using a standard neuropsychologicaltest battery, which assessed functioning in several areasincluding attention, working memory, inhibition, long-termmemory, and perceptual speed. They found that, comparedwith controls, methamphetamine-abusing participants per-formed significantly worse on tests measuring: (1) inhibi-tion (Stroop, WCST); (2) attention and cognitive flexibility

(WCST); and (3) psychomotor function and speed. As aresult of these statistical differences between the groups, theauthors concluded that methamphetamine users wereimpaired in multiple cognitive domains. Recall our earlierdiscussion of the ambiguity of ‘impairment’ and ouremphasis on the importance of comparing performancescores of methamphetamine users against normative scoresbefore drawing inferences about the clinical significanceof a difference on cognitive tests. The data from the Simonet al, study were not interpreted within these confines.However, when we compared the mean neuropsychologicalscores of the methamphetamine abusers in the Simon et alstudy against published normative scores, none of metham-phetamine users’ scores fell outside of the normal range.Moreover, in a subsequent study, this same group ofresearchers failed to replicate any of their earlier statisticallysignificant findings (Simon et al, 2010). Taken together,these observations further emphasize the importance ofcomparing performance against appropriate normativescores and they also demonstrate the value of havingresults replicated before making global statements abouttheir clinical importance.

In a similar study (Kalechstein et al, 2003), theperformance of abstinent methamphetamine-dependentindividuals (N¼ 27) and control participants (N¼ 18) werecompared across several cognitive domains includingvisuospatial perception, attention, inhibition, and responsespeed. An important strength of this study was that multipletasks were assessed to determine functioning in a particulardomain and published norms were taken into considerationwhen the study’s findings were interpreted. In this way, itwas possible to obtain convergent findings and theirfunctional significance could be determined, which wouldincrease confidence in the results and conclusions drawn.The researchers found that methamphetamine users andcontrols did not differ on most tests (eg, Stroop and TrailMakingFboth measures of attention and inhibition), but agreater proportion of the methamphetamine users wereclassified as being impaired within a particular domainbecause their individual score was at least 2 SDs below themean for published normative data. On average, perfor-mance in at least one domain for approximately 7 of the 27methamphetamine users met this stringent impairmentcriterion, whereas this number was 2 of 18 for the controls.This indicates that methamphetamine users were more thantwice as likely as control participants to be classified asbeing impaired in at least one domain, which suggests thatthe scale of impairment in this sample was substantial.A closer examination of the data, however, suggests thatthis interpretation might be an overstatement. Sample sizewas relatively small, which increases the likelihood ofdata distortion. That is, when we look at the number ofparticipants in each group that were determined to beimpaired in the domain of working memory, for example,we see that only two control participants (11%) and onemethamphetamine user (4%) met this criterion. Cognitivefunctioning fell within the normal range for the vastmajority of study participants, including those dependenton methamphetamine. Also, while several other investiga-tors have reported some differences in cognitive functioningbetween methamphetamine abusers and controls (eg, Hoff-man et al, 2006; Han et al, 2008), the pattern of effects in the


602


Table 4 Studies that have Included Neuropsychological Test Batteries Only

Investigators Domain tested Participants Period of abstinence Cognitive findings Caveats

Henry et al (2009) Facial affect recognition (Pictures of FacialAffect); Theory of mind (Mind in the Eyestest); Executive functioning (Verbal fluencytest: FAS, Hayling Sentence CompletionTest); Learning/memory (AVLT)

MA users met the DSM-IV criteriafor MA dependence (currently intreatment): N¼ 20Controls: N¼ 20These are the same participants asthose in Rendell et al (2009)

Mean: 5.9±1.41 months k Facial affect recognitionk Theory of mindk Executive function(1 out of 2 tests)k Learning/memory2 Delayed recall

Cognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledMA-dependent participants tested on an in-patient basis, while controls tested on anoutpatient basisSmall number of participants studied

Hoffman et al (2006) Visuospatial perception (Rey–OsterriethComplex Figure Test); Visual memory (Rey–Osterrieth Complex Figure Test);Immediate and long-term memory (BabcockStory Recall); Learning/memory (AVLT);Attention/psychomotor function (TMT-A,Stroop, Grooved pegboard); Responseinhibition (Stroop); Set-shifting/executivefunction (WCST, TMT-B); IQ (ShipleyVocabulary)

MA users met the DSM-IV criteriafor MA dependence (currently intreatment): N¼ 41Controls: N¼ 41

Mean: 6.52±6.30 months k Long-term memoryk Learning/memory2 Visuospatial perception2 Visual memory2 Immediate memory2 Attention/psychomotor function2 Response inhibition2 Set-shifting/executive function2 IQ

Controls had higher levels of education than MAusersCognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolled

Kalechstein et al (2003) Attention/psychomotor function (TMT-A,Symbol Digit Modalities Test, StroopColor); Visuospatial perception (ReyComplex Figure TaskFcopy subtest);Learning/memory (AVLT, WMS-III LogicalMemory; Rey Complex FigureTestFdelayed recall); Working memory(Letter-Number Sequencing and VisualMemory SpanFbackwards subtests ofWMS-III); Response inhibition (Stroop);Set-shifting/executive function (TMT-B,Controlled Oral Word Association,Ruff Figural Fluency Test)


Current users (provided negative urinesample on the day of testing)

k Learning/memory (3 out of 4 tests)k Verbal fluency2 Attention/psychomotor function(2 out of 3 tests)2 Visuospatial perception2 Working memory2 Response inhibition2 Set-shifting/executive function

The influence of drug use other than MA notcontrolledSmall number of participants studied

Rendell et al (2009) Prospective memory (Virtual Week task);Executive function (Verbal fluency test: FAS,Hayling Sentence Completion Test);Learning/memory (AVLT); Working memory(Digits forward and backward)

MA users met the DSM-IV criteriafor MA dependence (currently intreatment): N¼ 20Controls: N¼ 20These are the same participants asthose in Henry et al (2009)

Mean 5.90±1.41 months k Executive functionk Retrospective memoryk Prospective memoryk Working memory

Cognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledMA-dependent participants tested on an in-patient basis, while controls tested on anoutpatient basisSmall number of participants studied

Simon et al (2000) Attention/psychomotor function (TMT-A,Digit Symbol, Stroop); Immediate Memory(word-recall and recognition; picture-recalland recognition); Response inhibition(Stroop); Set-shifting/executive function(WCST, TMT-B, Verbal fluency test: FAS);Working memory (Digits backward); IQ(Shipley–Hartford Vocabulary and AbstractThinking)

Current MA users: N¼ 65; noinformation reported aboutwhether participants met theDSM-IV criteria for an MA-usedisorderControls: N¼ 65

MA group was required to submit urinepositive for MA, but negative for allother drugs on the day of testing

k Immediate memory(word- and picture-recall)k Response inhibitionk IQ (1 out of 2 tests: Abstract Thinking)2 Immediate memory(word and picture recognition)2 Attention/psychomotor function(2 out of 3 tests)2Set-shifting/executive function(2 out of 3 tests)2 Working memory

Cognitive data not compared against normativedata set. Thus, the clinical importance of findingscould not be determinedThe influence of drug use other than MA notcontrolledThe influence of comorbid psychiatric disorderssuch as ADHD and depression not controlled

Simon et al (2002) Same as above MA users met the DSM-IV criteriafor MA-use disorder: N¼ 40

MA group was required to submit urinepositive for MA, but negative for all

k Attention/psychomotor function(2 out of 3 tests)

Cognitive data not compared against normativedata set. Thus, the clinical importance of findings

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Kalechstein et al study (ie, in terms of clinical impairments)has yet to be replicated.

CONCLUSIONS

For more than a decade, research investigating the effects ofmethamphetamine use on human cognition has steadilyincreased. Diverse methodologies have been employed,including basic human laboratory studies, during whichthe acute effects of the drug on cognitive performance areassessed, and studies that combine brain imaging withneuropsychological evaluation. In general, the humanlaboratory data show that short-term, acute methamphet-amine improves cognitive performance of both metham-phetamine abusers and non-users in some domains, forexample, visuospatial perception, sustained attention, andresponse speed, even when larger intranasal and intrave-nous doses are tested. Although enhanced cognitiveperformance was not observed in a few studies, it isimportant to note that methamphetamine-induced disrup-tive cognitive effects were not observed and therefore rarelyreported. It is possible that if larger doses, administeredrepeatedly, had been studied, more negative effects oncognition would have been observed. This would not besurprising given that it is true with other psychoactiveagents, including the legal recreational drugs, alcohol, andcaffeine. Note, however, that most of the doses tested in thelaboratory studies were within the range needed to induceeuphoria in the natural setting. Nonetheless, a morecomprehensive understanding of the acute effects ofmethamphetamine on cognition would require testing oflarger doses.

With regard to brain-imaging studies, several researchershave reported neural differences between methampheta-mine users and control participants. One consistent PETfinding was lower striatal DAT density in methamphet-amine users. Data from MRI and fMRI studies also revealedsome differences in brain structure volume and integrity,and activity differences, between the groups, but there havebeen few replications of specific findings among studies.This is a crucial factor to consider when reading studies thatpurport to have identified regional differences betweenmethamphetamine-using participants and controls becausesuch findings might be spurious and unrelated to metham-phetamine use. In addition, despite the fact that mostneuroimaging studies included only limited cognitivemeasures and despite the fact that cognitive functioningof methamphetamine users generally fell within the normalrange, researchers frequently interpreted any brain differ-ences as indicative of cognitive pathologies caused by theabuse of methamphetamine.

Studies solely focused on assessing the cognitive func-tioning of abstinent methamphetamine users are plagued bysimilar interpretation concerns. That is, even thoughmethamphetamine users’ performance overwhelminglyremained within the normal range, most researchersconcluded that they showed evidence of global cognitiveimpairments (the dysfunction meaning of ‘impairment’).For example, the findings of Simon et al (2002) led themto warn:T

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604


The national campaign against drugs should incorpo-rate information about the cognitive deficits associatedwith methamphetamineyLaw enforcement officers andtreatment providers should be aware that impairments inmemory and in the ability to manipulate informationand change points of view (set) underlie comprehensionymethamphetamine abusers will not only have diffi-culty with inferencesybut that they also may havecomprehension deficitsythe cognitive impairmentassociated with [methamphetamine abuse] should bepublicizedy

Such warnings were based on measures that revealedstatistically significant differences between methamphet-amine users and controls, which alone are insufficient todetermine true cognitive dysfunctions. Nevertheless, theapparent methamphetamine abuse-cognitive impairmentlink has been widely publicizedFnumerous articles haveappeared in scientific journals and the popular pressFdespite the fact that it is not supported by evidence fromresearch.

IMPLICATIONS

Many researchers in this area begin with the assumptionthat methamphetamine abusers exhibit cognitive dysfunc-tion, and that their research bears this out. Findings fromthis review suggest that this assumption should be re-evaluated to document the actual pattern of cognitive effectscaused by the drug. For example, this prevailing assumptionhas provided the fuel for a growing number of neuroima-ging studies assessing the impact of prenatal methamphet-amine exposure. Hopefully, more caution will be exercisedwhen interpreting these findings than was exercised whenresults were interpreted from studies of infants prenatallyexposed to cocaine, who were erroneously and too readilycondemned to a life of learning disabilities, psychologicaldisturbances, and crime. From a substance-abuse treatmentperspective, it has been suggested that cognitive impair-ments seen in methamphetamine users have the potential tocompromise their ability to engage in, and benefit from,cognitive-behavioral therapy, arguably the most effectivetreatment (Simon et al, 2002). Findings from this reviewargue that such concerns are not warranted. Finally, from apublic policy perspective, several governments have takendrastic measures in an effort to limit the use ofmethamphetamine, in part, because of the perceivedpernicious effects the drug has on cognitive functioning.In Thailand, amphetamines are banned for all purposesFincluding medical. In the United States, methamphetamine-related violations are punished more harshly than thoserelated to other illicit drugs, with the exception of crackcocaine. It is only recently that penalties associatedwith crack cocaine violations were reduced. This changecame after nearly 25 years of criticism of the law becauseit was inconsistent with the scientific evidence and itexaggerated the harms associated with crack cocaine use.The monetary and human costs of this misunderstandingare incalculable.

As a final thought, note the parallel here: Many of theclaims about methamphetamine-associated cognitive im-pairments are reminiscent of statements made about crack

cocaine more than two decades ago before the empiricalevidence was clear. Taken together, these observationslead us to speculate whether we are headed down this pathonce again.

ACKNOWLEDGEMENTS

Helpful comments were received on an earlier draft of thispaper from James D Rose, Charles Ksir, David Sulzer, andDaniel Wolfe, Don Habibi. Responsibility for the content ofthe paper in its present form, of course, rests with theauthors. The support of the Open Society Foundation andNational Institute on Drug Abuse (Grant numbers DA-03746 and DA-019559) is gratefully acknowledged.

DISCLOSURE

The authors declare no conflict of interest.

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