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Neuroscience and Biobehavioral Reviews xxx (2013) xxx– xxx

Contents lists available at ScienceDirect

Neuroscience and Biobehavioral Reviews

j ourna l ho me pa ge: www.elsev ier .com/ locate /neubiorev

eview

ffects of non-invasive neurostimulation on craving: A meta-analysis

ochem M. Jansena,b,∗, Joost G. Daamsc, Maarten W.J. Koetera, Dick J. Veltmana,d,im van den Brinka,b, Anna E. Goudriaana,b,e

Academic Medical Centre, Department of Psychiatry, University of Amsterdam, Amsterdam, The NetherlandsAmsterdam Institute for Addiction Research, University of Amsterdam, Amsterdam, The NetherlandsAcademic Medical Centre, Medical Library, University of Amsterdam, Amsterdam, The NetherlandsVUmc, VrijeUniversiteitMedisch Centrum, Amsterdam, The NetherlandsArkin Mental Health, Amsterdam, The Netherlands

r t i c l e i n f o

rticle history:eceived 28 January 2013eceived in revised form 10 July 2013ccepted 14 July 2013

eywords:ranscranial magnetic stimulation

a b s t r a c t

This meta-analysis was conducted to evaluate the available evidence regarding the effects of non-invasiveneurostimulation of the dorsolateral prefrontal cortex (DLPFC), on craving in substance dependence andcraving for high palatable food. Non-invasive neurostimulation techniques were restricted to repetitiveTranscranial Magnetic Stimulation (rTMS) and transcranial Direct Current Stimulation (tDCS). A total of17 eligible studies were identified. Random effects analysis revealed a pooled standardized effect size(Hedge’s g) of 0.476 (CI: 0.316–0.636), indicating a medium effect size favouring active non-invasive

TMSirect current stimulation

DCSddictionravingLPFC

neurostimulation over sham stimulation in the reduction of craving (z = 5.832, p < 0.001). No significantdifferences were found between rTMS and tDCS, between the various substances of abuse and betweensubstances of abuse and food, or between left and right DLPFC stimulation. In conclusion, this meta-analysis provides the first clear evidence that non-invasive neurostimulation of the DLPFC decreasescraving levels in substance dependence.

© 2013 Elsevier Ltd. All rights reserved.
on-invasive neurostimulation
ontents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

2.1. Inclusion criteria for the selection of studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.2. Search strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.3. Study selection and data extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 002.4. Data analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 003.1. Search results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 003.2. Heterogeneity between studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 003.3. Main findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00

Please cite this article in press as: Jansen, J.M., et al., Effects of non-invasivRev. (2013), http://dx.doi.org/10.1016/j.neubiorev.2013.07.009

Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Appendix A. Supplementary data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

∗ Corresponding author at: Room PA3-220, AMC, Department of Psychiatry, 1100DD AmE-mail addresses: [email protected], [email protected] (J.M. Jansen

[email protected] (D.J. Veltman), [email protected] (W. van den Brink), a.e.g

149-7634/$ – see front matter © 2013 Elsevier Ltd. All rights reserved.ttp://dx.doi.org/10.1016/j.neubiorev.2013.07.009

e neurostimulation on craving: A meta-analysis. Neurosci. Biobehav.

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sterdam, The Netherlands. Tel.: +31 633692340.), [email protected] (J.G. Daams), [email protected] (M.W.J. Koeter),[email protected] (A.E. Goudriaan).

dx.doi.org/10.1016/j.neubiorev.2013.07.009


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J.M. Jansen et al. / Neuroscience and

. Introduction

Substance dependence is a chronic relapsing brain disorderhat inflicts great costs to affected patients and society in generalKalivas, 2005). Alcohol dependence alone accounts for approxi-

ately 4% of the global mortality rate and substance dependencen general ranks as the 8th cause of death globally (Rehm et al.,009; WHO, 2010). Furthermore, alcohol and other substance useisorders account for 5.4% of the total global burden of diseaseWHO, 2010). During the development of substance dependence,ncentive salience of drug related stimuli increases whereas thealience of natural reinforcers declines (Everitt and Robbins, 2005;yman, 2005). Impaired inhibitory control, increased salience andraving for the abused substance are related to the development,ontinuation, and relapse in addictive disorders (Perry and Carroll,008). These cognitive and motivational changes are associatedith important changes in brain functions in addictive disorders

Kalivas, 2005; Koob and Volkow, 2010). Firstly, repeated drugr alcohol use has been found to lead to neuro-adaptations inhe ventral striatum and ventral tegmental areas, which in turnesult in decreased dopamine secretion (Volkow et al., 2009). Evi-ence from both human and rodent studies suggests that thesehanges are accompanied by increased saliency and craving forhe abused substance, and the increased cue-reactivity relatedo increased salience has its neural basis in increased striatalnd orbitofrontal responses to addiction-related cues (Baler andolkow, 2006; Berridge, 2007; Everitt and Robbins, 2005; Koob andeMoal, 2008). Secondly, diminished functioning of the dorsolat-ral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC)s present in addictive disorders, presumably underlying dimin-shed cognitive and behavioural control and a higher tendency toue-induced relapse in alcohol or drug use (Garavan, 2007; vanolst and Schilt, 2011). Furthermore, diminished functioning of

rontal brain circuits is related to a higher susceptibility to stressnd stress-induced relapse, in the rat brain (Capriles et al., 2003).ogether, these compromised brain activity patterns are associatedith a higher chance to relapse in methamphetamine, nicotine and

ocaine dependent subjects (Janes et al., 2010; Kosten et al., 2006;aulus et al., 2005).

Drug craving is assumed to be an important risk factor forelapse in patients with substance dependence and, higher crav-ng has indeed been found to be related to higher relapse ratesOslin et al., 2009; Sinha et al., 2006). Although craving poses aisk for relapse, it can be counteracted by exerting cognitive andehavioural control over the increased motivational drive of crav-

ng. Therefore, craving for substances in persons with an addictiveisorder presents a problem specifically when the ability to inhibithe drive to use the relevant substance is affected.

Craving for food has been, and often still is, a useful and adap-ive process through which the body communicates its needs. Forxample, craving has been important from an evolutionary per-pective for building food reserves during periods of food shortage,nd one may crave meat when low on iron (Levin, 2007). How-ver, with the current widespread availability of (processed) highugar and fat foods in western countries, those previously bene-cial cravings pose a risk for developing obesity or binge-eatingisorder (May et al., 2012). There is a growing body of evidence sug-esting a role for craving in the obesity epidemic (Pelchat, 2009a).urthermore, there is an ongoing debate on whether there is some-hing like ‘food addiction’ (Corsica and Pelchat, 2010; Ziauddeennd Fletcher, 2013) and if so whether this is mainly true for bingeating behaviour (Gearhardt et al., 2011; Smith and Robbins, 2013;


mberg et al., 2012). Independent of the debate on food addiction,raving for food is well documented (Hill, 2007; Sobik et al., 2005).urthermore, deficient control processes are frequently reported inbese and binge eating people (Pelchat, 2009b; Volkow et al., 2011;

PRESSavioral Reviews xxx (2013) xxx– xxx

Yanovski, 2003). The combination of loss of control in combinationwith higher food cravings – especially cravings for palatable or highcaloric food, may lead to loss of control over food intake and there-fore weight gain. Consistent with this, higher craving for food hasbeen related to higher weight and lack of success in weight lossprogrammes (Lafay et al., 2001; Vander Wal et al., 2007; Wurtmanand Wurtman, 1986).

The neurobiological correlates of craving are hypothesized tobe shared between substance dependent patients and people whoare craving for high palatable food (Volkow et al., 2013). In fact,there is considerable evidence from human neuroimaging studiesimplicating the same neural structures in both food and drug crav-ing. The orbitofrontal cortex (OFC) is related to salience attributionto potentially rewarding stimuli, such as food or drugs (Volkowet al., 2013). Increased salience attribution to drugs is an impor-tant aspect of addiction (Dom et al., 2005). Increased OFC activityhas also been linked to increased food craving in lean healthycontrols (Wang et al., 2004). Other studies have also shown thatdopamine is related to the desire for both drugs and food (Blumet al., 2011; Volkow et al., 2002). Furthermore, brain activationsin amygdala, insula, bilateral orbitofrontal cortex and striatumoverlap for food and smoking cues in normal weight individuals(Tang et al., 2012). Moreover, D2-dopamine receptor density in thestriatum has been negatively correlated with BMI of obese people(Wang et al., 2001). Lower D2-dopamine receptor density in thestriatum is also related cocaine dependence, heavy nicotine andalcohol use (Connor et al., 2007); nicotine craving (Connor et al.,2007; Erblich et al., 2005; Heinz et al., 2004; Volkow et al., 1993);and reduced frontal metabolism in cocaine dependence (Volkowet al., 1993).

Reduced (pre)frontal activation has been reported in obesepatients, with and without binges, in reaction to food and foodcues. Hypo-activation of the (pre)frontal cortex has been impli-cated in deficient inhibitory control and hyper-activation of DLPFCin reaction to food stimuli was related to craving for food (Karhunenet al., 2000; Wang et al., 2004). Obese patients show less activa-tion in DLPFC compared to healthy controls after a meal, indicatingreduced reactivity to ingestion of food, which may be related tosatiation (Le et al., 2006). Also, decreased blood flow in the pre-frontal cortex has been associated with higher weight in healthysubjects (Willeumier et al., 2011, 2012). Impaired executive con-trol has been reported in obese women (Kishinevsky et al., 2012)whereas successful dieters activate their DLPFC/OFC while eat-ing (DelParigi et al., 2007). Together, these findings implicate thepresence of disrupted motivational neural processes and impulsecontrol in obesity (Nijs et al., 2009).

Addiction and obesity are among the biggest health problemsof the western world today (Hedley et al., 2004; WHO, 2010). Sub-stance dependence is known for its high relapse rates (Dutra et al.,2008) and as noted before, craving is an important risk factor forrelapse (Oslin et al., 2009; Sinha et al., 2006). In a review, McLellanet al. (2000) concluded that only 40–60% of all treatment seek-ing substance dependent patients were still abstinent at 1 yearfollow-up. Relapse rates for nicotine dependence are estimated tobe around 85% for counselling therapy alone and 78% for coun-selling combined with medication (Fiore et al., 2008). Furthermore,weight loss programmes are often ineffective for obese patients,as 33% to 66% of patients regain all weight that was lost, or gaineven more (Bacon and Aphramor, 2011; Mann et al., 2007). There-fore, the available treatment options are ineffective for a substantialproportion of these patients and new treatment options are clearlyneeded. Non-invasive neurostimulation such as repetitive trans-


cranial magnetic stimulation (rTMS) and transcranial direct currentstimulation (tDCS) are new intervention methods that may targetthe reduction of craving levels in substance dependence and obeseor binge eating groups. By reducing craving levels, it would become


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asier for people with addictive disorders, obesity, or binge eatingroups, to maintain control over intake or to remain abstinent.

Transcranial magnetic stimulation (TMS) and transcranial directurrent stimulation (tDCS) have proven to be effective techniquesor altering brain activity (Barr et al., 2008; George and Aston-ones, 2010). Both techniques induce small electrical currents inhe brain that cause alterations in neuronal firing [for a moreetailed description, see George and Aston-Jones (2010)]. Theseechniques can exert both inhibitory and excitatory effects on therain, depending on the stimulation frequency. In general, low fre-uency stimulation (<1 Hz) is considered to exert inhibitory effects,hereas high frequency stimulation (>5 Hz) is considered to exert

xcitatory effects on the brain (Hoffman, 2002; Ziemann et al.,008). The effects of repeated stimulation (repetitive TMS or rTMSnd tDCS), have been proven to last beyond the actual time of stim-lation, enabling altered brain activity for an extended period ofime (Ziemann et al., 2008). These prolonged effects have potentialn the treatment of a variety of disorders. Previous randomized con-rolled trials of rTMS in depression have indeed shown a decreasen depressive symptoms following repeated high frequency stimu-ation (Dell’Osso et al., 2011; Lam et al., 2008; Pascual-Leone et al.,996). The Food and Drug Administration has therefore approvedTMS stimulation as a treatment option for depression (FDA, 2008).urthermore, recent studies show that stimulation of the DLPFCan acutely decrease craving levels after a single administrationf rTMS in samples with nicotine dependence (Amiaz et al., 2009;ichhammer et al., 2003; Johann et al., 2003), alcohol depend-nce (Mishra et al., 2010), marijuana dependence (Boggio et al.,010), cocaine dependence (Politi et al., 2008) and food cravingMontenegro et al., 2012). Although these results seem promising,ther studies have failed to show significant decreases in cravingn similar populations (Barth et al., 2011; Herremans et al., 2012).

The mechanisms through which tDCS and rTMS exert theirffects on the brain are only partly understood, but may involvencreased cognitive control, decreased craving, or both. Most stud-es have used the DLPFC as stimulation site with the aim to reduceraving. Two possible mechanisms through which stimulation mayecrease craving levels have been proposed by Diana (2011). Firstly,

nterconnections of the DLPFC with the ventral tegmental areaVTA) may increase dopamine excretion from the VTA to the ventraltriatum, an area that plays a major role in reward processing. Sec-ndly, stimulation of the DLPFC stimulates glutamate containingortico-fugal fibres, which end on dopamine containing terminalsn the ventral striatum (Strafella et al., 2001), potentially increasingopamine excretion. Both proposed neural mechanisms are sup-orted to some extent by studies in rodents (Carr and Sesack, 2000;eck et al., 2002) and primates (Frankle and Haber, 2006). There isvidence for anatomical connections between DLPFC and VTA, asarr and Sesack (2000) labelled retrograde projections from VTAo DLPFC, showing both GABA-containing meso-accumbens neu-ons and dopamine-containing mesocortical neurons in the rodentrain. Furthermore, Frankle and Haber (2006) reported evidenceor anatomical connections between DLPFC and VTA structuresn primates by anterograde labelling. Keck et al. (2002) showedhat high-frequency rTMS stimulation of the prefrontal rat brainncreased dopamine levels in the dorsal hippocampus and the shellf the nucleus accumbens, and increased extracellular dopamineoncentrations in the dorsal striatum.

As previously mentioned, neurostimulation may also increaseognitive control and cognitive functioning in general, which ismportant for preventing relapse (Garavan, 2007). Another mech-nism through which non-invasive neurostimulation may reduce


raving is through enhancement of DLPFC activity and its connec-ions to the striatum. Cognitive deficiencies related to decreasedrefrontal functioning have been reported in substance depend-nce and might be related to reduced effectiveness of cognitive

PRESSavioral Reviews xxx (2013) xxx– xxx 3

behavioural therapy (Carroll et al., 2011; Vik et al., 2004). Addition-ally, the DLPFC is important for actively reducing negative affectby reappraisal, defined as; ‘reinterpreting the meaning of a stimu-lus to change one’s emotional response to it’ (Ochsner and Gross,2005). For example, changes in craving levels can be achieved byinstructing nicotine dependent subjects to think about either theimmediate positive effects (rewarding) or delayed negative con-sequences (like development of lung cancer) of smoking (Koberet al., 2010a). In this study, subjects reported significantly lowercraving levels in the ‘delayed negative consequences’ condition,suggesting a possible role for cognitive (reappraisal) strategies inreducing craving levels. Kober et al. (2010b) showed that increasedactivation of the DLPFC during regulation of craving for nicotineresulted in a decrease in ventral striatum activity and a subsequentdecrease in craving levels, pointing towards a potential work-ing mechanism for neurostimulation of the DLPFC. Furthermore, aneuro-stimulation induced increase in dopamine secretion couldalso increase dopamine concentrations in DLPFC and thereforepossibly enhance cognitive control (Volkow et al., 2009). Addi-tionally, there is an increased interest for cognitive enhancersfor the treatment of substance dependence (Brady et al., 2011).Cognitive enhancers may improve the cognitive impairments inattention, working memory and response inhibition, which havebeen frequently reported in substance dependence (Schmaal et al.,2011; Sofuoglu, 2010; Sofuoglu et al., 2013). The effects of rTMSon cognitive functioning in patients suffering from psychiatric orneurological conditions have been reviewed by Guse et al. (2010)and include improvement in executive functioning, response inhi-bition and selective attention. Impairments in these cognitivefunctions have been reported in addictive disorders (Fernández-Serrano et al., 2010; Koob and Volkow, 2010; van Holst and Schilt,2011), but little attention has been given to the application ofnon-invasive neurostimulation to improve cognitive functions insubstance dependence.

The meta-analysis presented in this paper therefore evaluatesthe available evidence regarding effects of non-invasive neu-rostimulation (rTMS and tDCS) compared to sham stimulation, insubstance dependence and in craving related to high-palatablefood. With this review, the potential of these neuro-modulationtechniques for the treatment of substance dependence and exces-sive craving for food in obese or binge-eating groups can beassessed. Furthermore, several additional comparisons were made.Firstly, the choice for the DLPFC as stimulation target is very con-sistent across studies, but selecting either the left or the rightDLPFC is not. Therefore, this meta-analysis also evaluates whetherdifferences exist between the effects of left- or right-DLPFC stimula-tion. Secondly, to investigate the applicability of neurostimulationacross substances, effects of neuro-modulation studies in specificsubstances are compared. Thirdly, food craving studies are com-pared to studies that focus on craving in substance dependence,to assess differences in effectiveness. Finally, tDCS and rTMS werecompared in order to assess whether these different stimulationtechniques differ in effectiveness.

2. Methods

2.1. Inclusion criteria for the selection of studies

In order to prevent information bias and to control for placeboeffects, only double-blind RCTs comparing the effect of rTMS ortDCS stimulation with sham stimulation of the DLPFC on crav-


ing levels were included in the meta-analysis. All studies includedin this meta-analysis had craving reduction as a primary out-come measure. The selected studies only concerned high frequencystimulation studies. All studies assessed craving levels in alcohol,


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icotine, cocaine and marijuana dependent patients, and food crav-ng was assessed in people experiencing high cravings for highalatable food. The included studies were not restricted by datef publication, craving assessment tool, or number of stimulationessions.

.2. Search strategy

Based on both reputation and content coverage, we identifiedubmed, Embase, PsycINFO and relevant sections of The Cochraneibrary as the key bibliographic databases for our query. Ournquiry was constructed following to the PICO-method.1 Key ele-ents that we used in our search were the ‘P’ (addicts/addiction to

rugs, food, alcohol and nicotine or individuals experiencing strongraving for food), the ‘I’ (rTMS or tDCS stimulation), the ‘C’ (Activend Sham stimulation) and the ‘O’ (craving levels). To minimizehe risk of bias, no limits were applied. For reasons of transparencynd reproducibility, the complete documentation of the search isncluded in Appendix 1 of this article.2

.3. Study selection and data extraction

The selection of relevant studies consisted of several steps.irstly, all studies were screened based on title and abstract. Sec-ndly, the full text of all studies from this selection was read,nd studies were included in the meta-analyses if all inclusionriteria were met. Two authors independently performed studyelection (J.M.J. and A.E.G.) with disagreements resolved by dis-ussion. Extracted data included side of stimulation (left vs. right),umber of stimulation sessions, stimulation technique (rTMS vs.DCS), substance involved, and standardized effect sizes for theffect of stimulation on craving levels. If relevant, we adjusted forhe dependence of these data [left and right stimulation data wererom the same patients in 4 studies (Boggio et al., 2008, 2010; Fregnit al., 2008a, 2008b)] in the analyses. This was done by taking ‘study’s unit of design instead of the ‘unit for analyses’. Studies in whichoth left and right DLPFC were stimulated were divided into two

units of analysis’, one for left-side and one for right-side stimula-ion. This approach is preferable to the one in which study is takens the ‘unit of analysis’, because in this case no distinction can beade for different designs with different (changing) stimulation

ocations. When reported data were insufficient for data analysis,uthors were contacted in order to retrieve the data. Studies usingtimulation in both left and right DLPFC were parted and includedeparately in order to assess whether side of stimulation exertedifferent effects on craving levels.

.4. Data analysis

All relevant data were entered in the computer programmeomprehensive Meta-Analysis V2 (Borenstein et al., 2011). Stan-ardized mean difference in effect sizes (Hedge’s g) were calculated

n order to assess the difference in craving levels between activend sham stimulation. Hedge’s g is considered to be a conservativestimate, which is useful for studies with small sample sizes, andhe results may be interpreted as reflecting a small (g = 0.2–0.5),

edium (g = 0.5–0.8) or large effect (g > 0.8) (Borenstein et al.,009). For overall between-group analysis a random-effects model


as used, which is in line with the underlying assumption of non-omogeneity between individual study samples. Compared to axed effects model, the random effects model provides a more

1 PICO stands for: Patient/Population, Intervention, Comparison, Outcome.2 Latest search was performed on 13/9/2012.


conservative estimate of precision and is more appropriate for gen-eralization beyond the included studies (Borenstein et al., 2009).An alpha of p < 0.05 was used for all comparisons. Although the pri-mary focus of this meta-analysis was on the effect of non-invasiveneurostimulation on craving levels, we also made several othercomparisons. In order to assess effect differences regarding sideof stimulation, substance involved, and stimulation technique thatwas used, a random effects model was applied. We also comparedstimulation effects on food versus substance craving.

3. Results

3.1. Search results

The initial search resulted in 76 potentially eligible studies,which were then subjected to closer inspection. For several rea-sons, 59 studies were excluded from the meta-analysis (see Fig. 1).Exclusion criteria included: studies assessing the effects of otherstimulation techniques than tDCS or rTMS (such as nervus vagusstimulation and electro convulsive therapy) or studies assessingthe effect of DLPFC stimulation on other topics than craving (e.g.Parkinson’s disease, chronic pain, depressive disorders). Four stud-ies did not report the necessary statistics for the active vs. shamstimulation and authors were contacted in order to obtain thesestatistics. Every effort was made to contact these authors by email,telephone, or letter, and for two out of four studies, the authorsresponded with the required statistics. The other two authors didnot respond and these studies were subsequently excluded fromanalysis (Eichhammer et al., 2003; Staroverov et al., 2009). Thus,17 studies were included in the meta-analysis.3 These included: 5nicotine, 6 food, 5 alcohol and 1 marijuana study. Of these stud-ies, 9 studies stimulated the left DLPFC, 3 studies stimulated theright DLPFC, 1 study stimulated bilaterally (switched after half ofthe 50 sessions), and 4 studies stimulated both left and right DLPFC(in a cross-over design). The studies on food craving included par-ticipants who reported frequent cravings for high palatable foods(Barth et al., 2011; Fregni et al., 2008b; Goldman et al., 2011),Claudino et al. (2011) assessed craving levels in bulimia nervosa andMontenegro et al. (2012) evaluated craving levels in obese subjects.All these studies assesses the effect on cue-induced high palatablefood craving, with the exception of Montenegro et al. (2012) whoassessed the effect of tDCS on baseline craving and craving afterhigh caloric exercise bouts.

3.2. Heterogeneity between studies

We first assessed differences in effect for stimulation techniqueand for side of stimulation, since these might impact the overallcomparison between active and sham stimulation. There was nosignificant difference in the effectiveness of rTMS vs. tDCS tech-niques (Q(1) = 0.27 p = 0.59). Additionally, a comparison was madeto assess difference in effects between the substances that wereincluded. Since only one study included marijuana users, it wasdecided to include only studies in persons with alcohol, nicotineand food craving. This analysis revealed no significant differencein effect between substances (Q(2) = 1.03, p = 0.60) and also no dif-ference in effect between food and substance craving (Q(1) = 0.604,p = 0.44). Finally, a comparison was made between left and right


DLPFC stimulation. The effect sizes differed by approximately 40%,but these differences were not statistically significant (Q(1) = 2.10,p = 0.15). Due to the large (non-significant) difference in effect sizeswe decided to perform a meta-analysis for left and right stimulation

3 Study characteristics are summarized in Table 2.


ARTICLE IN PRESSG Model

NBR-1807; No. of Pages 9

J.M. Jansen et al. / Neuroscience and Biobehavioral Reviews xxx (2013) xxx– xxx 5

Fig. 1. Flow diagram showing the search and selection procedure that was used for this meta-analysis. Reasons for exclusion in ‘not meeting criteria’ included, otherstimulation techniques than tDCS or rTMS (such as nervus vagus stimulation and electro

topics than craving (e.g. effect on chronic pain, Parkinson’s disease and depressive disordanalysis’, one for left and one for right stimulation. This approach enables comparisons be

Table 1Results for the meta-analysis performed for left and right stimulation separately.

Left DLPFC Right DLPFC

Hedge’s g (random effects) 0.375 0.710

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4

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n

t

Z-statistic 4.138 3.847N (studies) 13 7Significance p < 0.001 p < 0.001

eparately; however these results should be interpreted carefullyue to the small sample size. The results are summarized in Table 1nd are for descriptive purposes only. Note that several studiessed both left and right stimulation; therefore some participantsre included in both meta-analyses, which is why these analysesannot be considered independent.

.3. Main findings

For the assessment of the effect of non-invasive neurostimu-ation on craving levels, the effect sizes of the included studies

ere entered in Comprehensive Meta Analyses 2.0 using aandom effects analysis. The test for heterogeneity was signifi-ant (Q = 26.39, df = 16, p = 0.05). This analysis revealed a pooledtandardized effect size (Hedge’s g) of 0.476 (CI: 0.316–0.636), indi-ating a medium effect size favouring active stimulation over shamtimulation (z = 5.83 p < 0.001). In order to check for publicationias,4 both Rosenthal’s and Orwin’s methods5 were used, revea-

ing that 59–243 non-significant studies would have to be addedo the analysis in order to change the cumulative effect to a non-ignificant result, indicating that it is unlikely that our results areaused by publication bias (Table 2).

. Discussion

This random effects meta-analysis of 17 studies revealed a


ignificant medium effect size (Hedge’s g = 0.476) favouring non-nvasive DLPFC neurostimulation over sham stimulation in theeduction of substance or food craving. No significant differences

4 Publication bias results from the inclination of journals to publish positive, sig-ificant studies rather than null-results.5 For Orwin’s method these results are based on a value of 0.1 for ‘criterion for

rivial Hedge’s g’ and a value of 0.0 for mean Hedge’s g in missing studies.

convulsive therapy) and studies assessing the effect of DLPFC stimulation on otherers). Studies that stimulated both left and right DLPFC were used as two ‘units oftween left and right stimulation.

were found between rTMS and tDCS, between the different sub-stances or food, or between left and right DLPFC stimulation. BothrTMS and tDCS were administered without anaesthetics and didnot cause significant side effects.

It should be noted that several studies were excluded fromanalysis. Two of those studies did not compare active stimulationwith a sham control group. However, both did find a significantdecrease in craving levels for cocaine and therefore corroboratethe results of this meta-analysis (Camprodon et al., 2007; Politiet al., 2008). Two studies, for which the authors did not respondto our requests to provide details about their data, were excludedfrom this meta-analysis. Both studies reported a decrease in crav-ing levels compared to sham stimulation (Eichhammer et al., 2003;Staroverov et al., 2009). Although these studies were not includedin this meta-analysis, they may also be considered supportive ofour conclusions. The study conducted by Rose et al. (2011) slightlydiffered from other studies, as stimulation focused on the medialprefrontal cortex and the study was therefore excluded from themeta-analysis. Interestingly, in this study craving levels increasedafter active stimulation compared to sham stimulation. We per-formed a post hoc meta-analysis including this study, but it did notchange the result to a non-significant result (z = 4675, p < 0.001).Furthermore, according to the fail-safe N, a total of 59–243 ‘noeffect’ studies would be needed to be unpublished or have beenmissed to change the result of this meta-analysis.

Additional analyses showed no significant differences in effectbetween stimulation techniques, substances of abuse or the side ofstimulation. However, since the standard error in a random effectmeta-analysis is also dependent on the number of studies, giventhe relatively small number of studies, this non-significant differ-ence may reflect a power problem instead of equivalence of effects.This is especially true for the comparison between left and rightside stimulation. Therefore, the question regarding possible differ-ences between left- and right-side stimulation should be regardedas unresolved. If there actually is a difference in the effect of theside of stimulation with a stronger effect after right DLPFC stimu-lation, the results of the main analysis (with a weighted average ofthe left and right side stimulation) represent an underestimationof the potential effect of the most effective (i.e. right DLPFC) form


of neurostimulation.Although these results are very promising, some limitations

need to be considered. Some studies that were included were sin-gle blinded and outcome measurements differed across studies. A


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Table 2Studies included in the meta-analysis. Combined studies used both left and right stimulation in a cross-over design. These studies were entered separately and then combined in the analyses and figure (enabling sub comparisonsfor only left or right stimulation). The size of the ‘squares’ reflect the relative importance of the studies for the pooled estimate. The diamond shape indicates the overall effect size. The study by Boggio et al. (2010), has not beenincluded in the comparison for differences between substances, as it is the only study that assesses the effect of non-invasive neurostimulation on craving marijuana. It is however included in the comparison for substances versusfood. All studies were included in the overall effect of sham vs active stimulation. The study by Wing et al. (2012), has not been included in the left versus right stimulation comparison, as this study used bilateral stimulation(not in a cross-over design) (Amiaz et al., 2009; Barth et al., 2011; Boggio et al., 2008, 2009, 2010; Claudino et al., 2011; Fregni et al., 2008a, 2008b; Goldman et al., 2011; Herremans et al., 2011; Hoppner et al., 2011; Johann et al.,2003; Mishra et al., 2010; Montenegro et al., 2012; Nakamura-Palacios et al., 2011; Uher et al., 2005; Wing et al., 2012).

Study name Technique Stimulationsite

Single or combinedstudy

Number of sessions Number of subjects Hedge’s g

Amiaz et al. (2009) rTMS Left Single Study 10 21 0.888Barth et al. (2011) rTMS Left Single Study 2 10 −0.104Boggio et al. (2008) tDCS Both Combined 2 26 0.98Boggio et al. (2009) tDCS Left Single Study 5 27 0.824Boggio et al. (2010) tDCS Both Combined 1 33 0.587Claudino et al. (2011) rTMS Left Single Study 1 22 0.341Fregni et al. (2008a) (food) tDCS Both Combined 2 46 0.391Fregni et al. (2008b) (smoking) tDCS Both Combined 2 48 0.458Goldman et al. (2011) tDCS Right Single Study 2 19 0.427Herremans et al. (2011) rTMS Right Single Study 1 31 0.08Hoppner et al. (2011) rTMS Left Single Study 10 19 0.069Johann et al. (2003) rTMS Left Single Study 2 11 0.703Mishra et al. (2010) rTMS Right Single Study 10 45 1.165Montenegro et al. (2012) tDCS Left Single Study 2 9 0.694Nakamura-Palacios et al. (2011) tDCS Left Single Study 2 32 0.031Uher et al. (2005) rTMS Left Single Study 1 28 0.809Wing et al. (2012) rTMS Bilateral Single Study 50 13 0.639

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oncern is that the exact location of the DLPFC is unclear in severaltudies. Out of 17 included studies, 4 studies have used the F3 EEGethod, where the active stimulation was applied to the F3 location

n an EEG cap (for tDCS the cathodal electrode was placed over F4).nother 4 studies have used the ‘5 cm’ rule, stating that the DLPFC

s located 5 cm anterior to the abductor pollicis brevis motor cortexegion. The remainder of the studies did not report on the approacho locate the specific DLPFC stimulation location. The exact locationf the DLPFC may be important to improve effectiveness of stimu-ation and therefore, future studies should be more specific on theirpproach (and reporting) of site of stimulation.

Another limitation is that the effects of rTMS on acute cravingn the studies included in the meta-analysis were measured onlyy self-report questionnaires and visual analogue scales, which areubject to socially desirable answers. Some studies indicate that theelation between self-reported craving and physiological measuresf cue-reactivity are complex (Robbins et al., 1997; Sayette et al.,000; Tolliver et al., 2010), but other studies have reported clearssociations between self-reported craving and measurements ofrain activity such as EEG and fMRI (Franken et al., 2008). Moreover,his meta-analysis was based on double-blind RCTs comparing realTMS/tDCS with sham rTMS/tDCS, resulting in a similar small risk ofnformation bias due to socially desirable answers and expectationsn both the sham and real neuromodulation conditions.

Drug craving and craving for high-palatable food have beenreated in this review as being very similar in their phenomenology,eurobiology and clinical relevance. However, there is an on-goingebate on whether these phenomena are comparable (Gearhardtt al., 2009; Pelchat, 2009a). Furthermore, craving reduction inddictive disorders is known to reduce relapse, but the aim of treat-ng food craving is less clear. It may be argued that reduction ofigh-palatable food craving might be beneficial for obese peopletruggling with overweight, for patients with a binge eating disor-er or for patients with bulimia nervosa, because these conditionsre characterized by uncontrollable urges to eat. Given the neu-obiological similarities between craving for high palatable foodnd craving for substances of abuse, as discussed in Section 1 (e.g.olkow et al., 2013) and the lack of differences between the effectf rTMS on substance and food craving in Section 3, we do nothink this has affected the results or the conclusions of the current

eta-analysis. With the exception of only one study (Montenegrot al., 2012), all studies on the reduction of food craving in thiseta-analysis used pictures, videos, or real world examples of high

aloric, fatty or sugar containing food to induce high-palatable foodraving.

Some studies also included a measurement of substance use orood consumption in order to assess whether active stimulationeduced the use of the involved substance or food. Several of thosetudies found a significant decrease in consumption after active,ut not after sham stimulation (Amiaz et al., 2009; Eichhammert al., 2003; Van den Eynde et al., 2010). However, Uher et al. (2005)ound no reduction in snack consumption in the 5-min post stim-lation period, but this may have been due to the small numberf stimulation sessions. A further methodological issue is that thencluded studies differed in number of stimulation sessions. Mosttudies used only a single stimulation session, whereas some stud-es included 10 stimulation sessions and one study 50 sessionssee Table 2). Future research should therefore assess the relationetween craving levels over a prolonged period of time following aange of stimulation sessions. For example, in depression, the effectf stimulation on depressive symptoms is gradual (Loo, 2005) andndings in substance dependence indicate that a similar mecha-


ism may be present: in the study by Politi et al. (2008), whichas excluded from the analysis due to the lack of a sham com-arison, a significant decrease in craving levels was observed onlyfter the seventh stimulation session. The stimulation effects lasted


longer than the actual time of stimulation, since craving measure-ments were acquired post stimulation, yet the duration of a singleneurostimulation session on craving is insufficiently clear.

This is the first meta-analysis showing a medium effectsize favouring non-invasive high-frequency neurostimulationover sham stimulation on craving levels in for food anddrugs/substances. However, important questions remain to beanswered. Future studies should assess the optimal number andfrequency of stimulation sessions and should address the ques-tion whether right DLPFC is indeed more effective than left DLPFCstimulation. In addition, future studies should also include effectsof neurostimulation on improving cognitive control and reducingsubstance use or overeating. Finally, it remains unclear whether theclinical effects of these neurostimulation techniques are effective asstand-alone treatment or as a supplement to already existing treat-ments. In conclusion, this meta-analysis provides the first evidencethat non-invasive neurostimulation of the DLPFC decreases cravinglevels in substance dependence and craving for high-palatable food.

Acknowledgement

The research was funded by The European Foundation for Alco-hol Research (ERAB), EA 10 27 “Changing the vulnerable brain: aneuromodulation study in alcohol dependence”

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at http://dx.doi.org/10.1016/j.neubiorev.2013.07.009.

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