Insula White Matter Volume Linked to Binge Drinking

Frequency Through Enhancement Motives in Treated

Adolescents

Tammy Chung and Duncan B. Clark

Background: Given the insula’s role in the representation of bodily states associated with hedonic(i.e., enhancement motives) and aversive (i.e., craving) aspects of substance use, this longitudinal studyexamined associations between insula structure (i.e., white matter [WM] and gray matter [GM] vol-ume), enhancement motives for alcohol and cannabis use, craving for alcohol and marijuana, and alco-hol and cannabis involvement in treated adolescents. Enhancement motives and craving, as consciousrepresentations of bodily states associated with use, were hypothesized as mediators (i.e., linking mech-anisms) of the association between insula volume and substance use.

Methods: Adolescents (age 14 to 18, N = 30) recruited from substance use treatment reported onenhancement motives and obsession/craving for both alcohol and cannabis at baseline (near the start oftreatment), and on alcohol and cannabis involvement (e.g., binge drinking, alcohol abuse/dependencesymptom count) at baseline and over 1-year follow-up. Insula WM and GM volumes were determinedusing FreeSurfer.

Results: Enhancement motives for drinking served as a link between left insula WM volume andfrequency of binge drinking at baseline and 1-year follow-up. This novel finding is consistent with theinsula’s role in representing bodily states (e.g., “high” associated with binge drinking) that can motivatedrinking behavior. Although right insula WM volume was positively correlated with obsession/cravingfor alcohol, and obsession/craving was positively correlated with alcohol outcomes, the indirect effectwas not significant. Insula WM volume was not associated with cannabis-related variables. Insula GMvolume was not associated with enhancement motives, obsession/craving, or alcohol involvement.

Conclusions: Enhancement motives for alcohol use, but not obsession/craving for alcohol, providedan important link between left insula WM volume and frequency of binge drinking in treated adoles-cents. Results are consistent with the insula’s role in the processing of hedonic bodily states available toconscious awareness, particularly in the form of enhancement motives for alcohol use.

Key Words: Insula, Alcohol Use, Binge Drinking, EnhancementMotives, Adolescent.

THE INSULAR CORTEX is thought to play a key rolein the processing of a variety of bodily sensations (e.g.,

the “high” associated with drug use), which are available toconscious perception (Craig, 2009; Duerden et al., 2013).These bodily states can powerfully guide motivated behavior,such as substance use (Damasio, 1994; Verdejo-Garcia et al.,2012). Specifically, substance use may be motivated by“enhancement reasons” (e.g., “to get high”; Cooper, 1994),that is, the hedonic bodily sensations associated with use,which might be represented in the insula. Alternatively,“craving” for a substance could be represented in the insulaas a bodily state of subjective “need” to consume asubstance, similar to hunger or thirst, which serves as a vis-

cerosensory “marker” that motivates compulsive drug seek-ing and consumption (Damasio, 1994; Gray and Critchley,2007). Given the insula’s potential role in representing bodilysensations associated with substance use (Duerden et al.,2013), this study of adolescents in substance use treatmentexamined enhancement motives and craving for substanceuse as possible mechanisms linking insula structure (whitematter [WM] and gray matter [GM] volumes) to substanceuse severity.

Differences in insula structure have been identified in com-parisons of heavy substance users and healthy controls. Typi-cally, substance users have lower insula volume and corticalthinning compared with controls (e.g., alcohol-dependentadults: Durazzo et al., 2011; cocaine-dependent adults: Ma-kris et al., 2008; stimulant-dependent adults: Tanabe et al.,2013; adolescent heavy cannabis users: Lopez-Larson et al.,2011). A study of adolescents found that lower cortical thick-ness was not associated with lifetime marijuana use, suggest-ing that cortical thinness may be a marker of risk for heavyuse, rather than a consequence of heavy use (Lopez-Larsonet al., 2011). Overall, differences in insula structure betweensubstance users and controls were relatively small, with 1

From the Western Psychiatric Institute and Clinic (TC, DBC),University of PittsburghMedical Center, Pittsburgh, Pennsylvania.

Received for publicationMarch 21, 2014; accepted April 2, 2014.Reprint requests: Tammy Chung, PhD, WPIC/Pittsburgh Adolescent

Alcohol Research Center, 3811 O’Hara Street, Pittsburgh, PA 15213;Tel.: 412-246-5147; Fax: 412-246-6550; E-mail: chungta@upmc.edu

Copyright© 2014 by the Research Society on Alcoholism.

DOI: 10.1111/acer.12461

1932 Alcohol Clin Exp Res, Vol 38, No 7, 2014: pp 1932–1940

ALCOHOLISM: CLINICAL AND EXPERIMENTAL RESEARCH Vol. 38, No. 7July 2014

study noting that differences were observed over a relativelylarge area (e.g., FreeSurfer parcellation unit), rather thanbeing of large magnitude within a smaller focal region (Tana-be et al., 2013). Differences in insula structure are consistentwith functional magnetic resonance imaging (fMRI) studiesindicating abnormal insula activity among adolescent mari-juana users (Schweinsburg et al., 2010; Tapert et al., 2007).These cross-sectional neuroimaging studies suggest differ-ences in insula structure between heavy users and controls,but have not addressed the extent to which insula structuralcharacteristics (i.e., WM and GM volumes) might predictlater substance use.Operating as part of a network of brain regions, the insula

specializes in processing information on bodily states (i.e., in-teroception: awareness of the body’s physiological state),such as taste, pain, hunger, intoxication, and craving (Craig,2009). In this role, the insula is thought to provide a con-scious representation of the physiological effects (e.g.,“high”) associated with substance use (Naqvi and Bechara,2010). For example, an fMRI study using intravenouscocaine administration found that subjective “high” was pos-itively correlated with right insula activity, and that subjec-tive “high” was inversely correlated with craving (Risingeret al., 2005). Other fMRI studies demonstrate that insulaactivation is correlated with ratings of urge to use/cravingacross a variety of substances of abuse (review: Naqvi andBechara, 2010). Taken together, these fMRI studies suggestan important role for the insula in the conscious representa-tion of both hedonic (i.e., enhancement motives for use) andaversive (i.e., craving or urges for drug use) bodily statesassociated with substance use.Insula structural characteristics, which might underlie its

functioning, may be associated with substance use throughself-reports of bodily states accessible to consciousness thatmotivate substance use behaviors, such as enhancementmotives for use and craving or preoccupation with sub-stance use. Enhancement motives for use predict substanceinvolvement in both cross-sectional and longitudinal studiesof adolescents (e.g., alcohol: Cooper, 1994; Cooper et al.,2008; cannabis: Fox et al., 2011). In contrast, the associa-tion between craving and substance use remains controver-sial, as indicated by differences in the importance attributedto craving as a factor motivating substance use across theo-ries of addiction (review: Drummond, 2001), and mixedfindings across studies that have examined subjective rat-ings of craving as a predictor of subsequent substance use(review: Heinz et al., 2010). The insula’s role in representingbodily states associated with enhancement motives for use(i.e., “to get high”), and the association between enhance-ment motives and substance use, suggests that enhancementmotives may serve as a mechanism that links insula struc-ture and substance use severity. The more equivocal rolefor craving as a predictor of substance use suggests thatalthough subjective report of craving might involve theinsula, self-reported craving may be less likely to provide alink between insula structure and substance use severity.

Based on the insula’s role in the representation of bodilystates associated with hedonic (i.e., enhancement motives)and aversive (i.e., craving) aspects of substance use, this lon-gitudinal study examined associations between insula struc-ture (i.e., WM and GM volume), enhancement motives foralcohol and cannabis use, craving for alcohol and marijuana,and alcohol and cannabis involvement in a sample of treatedadolescents. Although substance users typically have some-what smaller insula volumes compared with controls, amongsubstance users, greater insula WM and GM volumes maybe positively associated with both enhancement motives andsubjective craving for alcohol and marijuana, such thatgreater insula WM and GM volume may facilitate process-ing of substance-related bodily states (Critchley et al., 2004;Turken et al., 2008). We further predicted that enhancementmotives would be positively associated with substance useseverity, but that there would be a weak association betweencraving and substance use, given inconsistent prediction ofsubstance use with measures of subjective craving. The bivar-iate correlations could support a test of enhancementmotives, in particular, as a mediator (i.e., linking mechanism)in the association between insula WM and GM volume andsubstance involvement (Fig. 1). Increased knowledge of theinsula’s role in relation to youth substance involvementcould help to guide the development of neurobiologicallyinformed interventions.

MATERIALS ANDMETHODS

Participants

Among 38 adolescents (ages 14 to 18) recruited from community-based intensive outpatient (IOP) treatment for substance use, 32cases reported lifetime use of alcohol and marijuana, and had use-able diffusion tensor imaging (DTI) and MRI data (6 cases wereexcluded due to excess motion [n = 3], faulty cortical segmentation[n = 2], or problematic resampling of DTI data [n = 1]; as reportedin Chung et al., 2013). Of the 32 cases, 30 completed 1-year follow-up, and constituted the analysis sample; those who did versus didnot complete 1-year follow-up did not differ on baseline variablesused in the analyses. The analysis sample was 63% male, 90%White, 3% Black, 7% multiracial, and, on average, middle class insocioeconomic status (Hollingshead, 1975; Table 1). Full scale IQscore was in the average range (Wechsler Abbreviated Scale of Intel-ligence; Psychological Corporation, 1999). Most participants (90%)had a current (past 6 months) DSM-IV cannabis use disorder, andalmost half (47%) had a current DSM-IV alcohol use disorder(AUD) at baseline.

Procedure

Youth admitted to IOP were approached to participate in a lon-gitudinal study on treatment outcome over 2-year follow-up (Kinget al., 2009; Maisto et al., 2011). The baseline assessment, whichwas usually completed within 2 weeks after starting IOP, collectedcomprehensive substance use and psychiatric data, and urine drugscreens were used to facilitate valid self-report of substance use; thesame domains were assessed 12 months after baseline in a repeatedmeasures design.

Youth who completed baseline were approached to participate ina neuroimaging protocol (Chung et al., 2011, 2013; Clark et al.,2012; Thatcher et al., 2010), which was approved by the university’s

INSULA AND BINGE DRINKING 1933

Institutional Review Board. Youth were excluded from imagingbased on standard restrictions (e.g., unremovable metal in thebody), and a history of brain injury or concussion. Informed con-sent or assent (with parental consent) for the imaging protocol wasobtained. Youth were scanned, on average, 29.9 days (SD = 18.6)after the baseline assessment. On scan day, youth reported on sub-stance use in the past 30 days; no substance use (except tobacco)was reported <24 hours prior to imaging.

Measures

Frequency of binge drinking in the past year at baseline and 12-month follow-up was assessed by the questionnaire item “Over thepast year, how many times did you drink 5 or more drinks whenyou were drinking?” Responses were coded as the average numberof “binge” episodes per month in the past year (possible range: 0 to30). The binge drinking frequency variable was log-transformed tonormalize the skewed distribution. Frequency of cannabis use in thepast 6 months was assessed at baseline and at 12-month follow-up,and rated on a 9-point scale: 0 = never tried, 1 = no use in past

6 months, 2 = less than once per month, 3 = once per month, 4 = 2to 3 times per month, 5 = once per week, 6 = 2 to 3 times per week,7 = 4 to 6 times per week, 8 = daily.

A modified Structured Clinical Interview for DSM-IV (Firstet al., 2002), which has acceptable reliability and validity with ado-lescents, was used to assess substance use disorder diagnoses andabuse/dependence symptom counts at baseline (lifetime, and past 6months) and 12-month follow-up (past 6 months). Kiddie-Schedulefor Affective Disorders and Schizophrenia (Kaufman et al., 1997),which has good reliability and validity, assessed current (past 6months) DSM-IV psychopathology.

The Time Line Follow Back method (Sobell and Sobell, 1995),which has satisfactory reliability and validity, assessed residence in acontrolled environment over follow-up.

The Motivations for Alcohol Use Questionnaire (Cooper, 1994)includes 20 items rated on a 5-point scale (1 to 5: never or almostnever to always or almost always); the same items were asked sepa-rately for cannabis (Simons et al., 2000). Analyses focused on theEnhancement Motives subscale (sum of 5 items, e.g., “To get high,”“Because it gives you a pleasant feeling”) at baseline (alcoholalpha = 0.92, cannabis alpha = 0.87), because this subscale is mostrelevant to insular functioning (i.e., representation of bodily statesavailable to conscious perception).

The Obsessive Compulsive Drinking Scale (OCDS; Robertset al., 1999) is a widely used measure of self-reported craving, andconsists of 14-items rated on a 5-point (0 to 4) scale, with higherscores indicating greater craving. The 5-item obsession/craving sub-scale (score = sum of 5 items) was used specifically because it asks

Insula white matter volume

Baseline

Enhancement motives for alcohol use

Baseline

Frequency of Binge Drinking in the Past Year

Baseline

A= 96.11**

C’ = -0.05

B= 0.02*

N = 30, R = 0.54, F(4, 25) = 7.4, p = 0.0004. 2

Indirect effect: 1.72* (BCa 95% CI 0.31, 4.28).

Panel A. Mediation model predicting Binge Drinking Frequency at BASELINE controlling for gender and age

Panel B. Mediation model predicting Binge Drinking Frequency at 1-YEAR FOLLOW-UP controlling for gender, age, baseline alcohol diagnosis, and controlled environment status over follow-up

Insula white matter volume

Baseline

Enhancement motives for alcohol use

Baseline

Frequency of Binge Drinking in the Past Year

1-Year Follow-Up

A= 78.86*

C’ = -2.55

B= 0.03*

N = 30, R = 0.59, F(6, 23) = 5.5, p = 0.0012.2

Indirect effect: 2.63* (BCa 95% CI 0.77, 5.60).

Fig. 1. Models of the indirect effect of enhancement motives for drinkingin the association between insula white matter volume and frequency ofbinge drinking. Notes: BCa, bias-corrected and accelerated. Unstandard-ized coefficients are reported. *p < 0.05; **p < 0.01. A = associationbetween independent variable (insula white matter volume) and mediator(enhancement motives for alcohol use). B = association between mediatorand dependent variable (binge drinking frequency). C0 = direct effect ofindependent variable (insula white matter volume) on the dependent vari-able (binge drinking frequency) after controlling for the intervening variable(enhancement motives for alcohol use). Covariate coding: gender (coded0 = female, 1 = male), current alcohol diagnosis at baseline (0 = no,1 = yes), residence in a controlled environment over follow-up (0 = no,1 = yes).

Table 1. Sample Descriptive Statistics at Baseline (N = 30)

Demographics n (%)

GenderFemale 11 (36.7)Male 19 (63.3)

EthnicityEuropean American 27 (90.0)African American 1 (3.3)Multiracial 2 (6.7)

Mean (SD)

Age 16.6 (1.1)Socioeconomic status 2.6 (1.2)WASI IQ score 98.4 (13.0)Years of education completed 9.6 (1.4)

n (%)

Current DSM-IV alcohol use disorder 14 (46.6)Alcohol abuse 10 (33.3)Alcohol dependence 4 (13.3)Current DSM-IV cannabis use disorder 27 (90.0)Cannabis abuse 18 (60.0)Cannabis dependence 9 (30.0)Current DSM-IV nicotine dependence diagnosis 10 (33.3)Current “other” DSM-IV substance use disorder (see note) 13 (43.3)Current presence of any of the following DSM-IV diagnoses 19 (63.3)Major depression 5 (16.7)Generalized anxiety disorder 1 (3.3)Attention Deficit Hyperactivity Disorder (ADHD) 12 (40.0)Conduct Disorder 10 (33.3)Oppositional Defiant Disorder 3 (10.0)

SD = standard deviation; Current = past 6 months; WASI = WechslerAbbreviated Scale of Intelligence. “Other substance use disorder” includesthe presence of any of the following: cocaine (n = 6; n = 4 abuse), opiate(n = 10; n = 6 abuse), sedative (n = 2, n = 2 dependence), stimulant(n = 1, n = 1 abuse), hallucinogen (n = 2, n = 2 abuse).

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about urge to use, as well as preoccupation with substance-relatedthoughts (e.g., “How strong is the drive to consume alcoholic bev-erages?,” “How much of your time when you’re not drinking isoccupied by ideas, thoughts, impulses, or images related to drink-ing?”). The 5 obsession/craving items also were asked separatelyfor cannabis. The OCDS was completed at baseline (obsession/craving subscale: alcohol alpha = 0.82; cannabis alpha = 0.85).

Image Acquisition and Processing

A Siemens 3T Allegra Scanner (Siemens Medical Systems, Erlan-gen, Germany) was used to acquire T1-weighted magnetization-pre-pared rapid gradient echo images (scan parameters:TR = 1,400 ms; TE = 2.48 ms; FOV = 256 9 256; 176 1-mmslices 9 2; matrix 256 9 256). Diffusion images were acquiredusing standard fast echo-planar imaging (TR = 6,500 ms;TE = 88 ms; FOV = 205 9 205; b = 1,000 s/mm2; 46 3-mmslices 9 12 directions in addition to b = 0). Images were collectedtwice to optimize the signal-to-noise ratio.

Image processing has been detailed elsewhere (Chung et al.,2013; Clark et al., 2012). Briefly, FreeSurfer (Dale et al., 1999; Fis-chl et al., 2002, 2004) was used to create GM and WM regions ofinterest (ROIs) based on standard parcellation units (Desikan et al.,2006). Cortical reconstruction processing and volumetric segmenta-tion were conducted according to standard procedures using Free-Surfer. Processing included motion correction, removal of nonbraintissue, automated Talairach transformation, segmentation and vol-umetry of the subcortical WM and deep GM structures, intensitynormalization, tessellation of the GM/WM boundary, automatedtopology correction, and surface deformation following intensitygradients to optimally locate the GM/WM white and GM/cerebro-spinal fluid borders. Registration to standard space using individualcortical folding patterns to match cortical geometry across subjectswas then conducted, followed by parcellation of the cerebral cortexinto units based on gyral and sulcal structure. Next, WM parcella-tion was performed, such that WM volumes were calculated foreach cortical parcellation. FreeSurfer measurements and WM/GMparcellation have been validated against histological and manualmeasurements (Han et al., 2006; Kuperberg et al., 2003; Rosaset al., 2002). ROIs created by FreeSurfer parcellation were visuallyinspected to ensure anatomical accuracy, and to exclude any casesdue to excess motion. DTI images were processed using Free Fur-fer’s dt_recon processing stream. DTI data were motion and distor-tion corrected. DTI General Linear Model Fit was used to fit atensor to corrected diffusion data at each voxel, resulting in frac-tional anisotropy (FA) maps for each participant. FA images wereresampled into each participant’s structural space using FreeSurfer’s mri_vol2vol, followed by extraction of mean FA valueswithin Free Surfer-defined ROIs using Free Surfer’s mri_segstats.Parcellation resulted in left and right hemisphere insula volumes,which were adjusted for total intracranial volume. The ROIapproach used here, compared with whole-brain voxel-basedapproaches (e.g., tract-based spatial statistics), permits greater sensi-tivity in testing hypotheses for specific brain regions (Han et al.,2006; Niogi et al., 2007).

Data Analysis

Bivariate correlations were computed to determine the utility oftesting the hypothesized indirect effect models. Tests of indirecteffects were conducted based on bivariate correlation results (i.e.,statistically significant correlation between independent variableand mediator, and mediator and dependent variable). In particular,an indirect effect of alcohol enhancement motives as a mediator(i.e., linking mechanism) of the association between left insula WMvolume and alcohol involvement at baseline at 1-year follow-up(Fig. 1) was supported by bivariate correlation results, and tested.

These associations were examined at 2 time points: at baseline(within a few weeks of starting treatment) and at 1-year follow-up.The baseline analyses are cross-sectional, and provide limited dataon the temporal ordering of the variables (e.g., enhancementmotives may reflect the result of frequent binge drinking, ratherthan temporally preceding binge drinking frequency). The analysesof 1-year outcomes provide clearer information on the extent towhich insula volumes and cognitive factors (e.g., enhancementmotives) precede and prospectively predict the outcome, an impor-tant consideration in testing mediation.

Given results indicating correlations of insula WM volumes withalcohol-related variables, we conducted post hoc tests comparingthose with (47%) and without (53%) a current DSM-IV AUD atbaseline on insula volume and alcohol enhancement motives andobsession/craving. Preliminary analyses indicated that AUD and noAUD groups did not differ on demography (age, sex, and socioeco-nomic status), IQ score, substance use, or co-occurring psychopa-thology (p > 0.05). Because 90% had a cannabis diagnosis atbaseline, post hoc comparisons based on cannabis diagnosis werenot possible.

Tests for indirect effects (product of coefficients: AB in the Fig. 1)used a bootstrapping procedure (5,000 resamples) programmed asan SPSS macro (IBM Corp. Released 2012. IBM SPSS Statistics forWindows, Version 21.0; IBM Corp., Armonk, NY) (Preacher andHayes, 2004). A significant indirect effect was indicated when the95% bias-corrected and accelerated (BCa) confidence intervalaround the unstandardized coefficient did not include zero(Preacher and Hayes, 2004). Importantly, an indirect effect can bedetected in the absence of a significant direct effect (Hayes, 2009;MacKinnon, 2008); that is, there does not need to be a significantassociation between independent and dependent variables. Theanalysis sample size meets the minimum to test for indirect effects,and uses bootstrapping, a preferred method for testing indirecteffects with small sample size (Preacher and Hayes, 2004). Analysesof indirect effects controlled for gender (cf. Thatcher et al., 2010;coded: 0 = female, 1 = male), and age (due to WM maturationthrough adolescence; Giorgio et al., 2008) for analyses of baselinevariables. For 1-year outcome analyses, in addition to gender andage, other covariates were: the presence of a current alcohol diagno-sis at baseline (included as a proxy for baseline alcohol use severity;coded: 0 = no, 1 = yes) and residence in a controlled environmentin 6 months prior to 1-year follow-up (included to account for possi-ble limited access to alcohol; coded: 0 = no, 1 = yes).

RESULTS

Descriptive Statistics and Bivariate Correlations

Table 2 presents descriptive statistics for WM and GMinsula volumes, enhancement motives and obsessive think-ing/craving at baseline, and alcohol and cannabis involve-ment at baseline and 1-year follow-up. Alcohol involvementat baseline and 1-year follow-up did not differ (binge drink-ing frequency: t = �0.31, df = 29, p = 0.8; alcohol abuse/dependence symptom count: t = 1.05, df = 29, p = 0.3). Fre-quency of cannabis use declined over 1-year follow-up,t = 2.86, df = 29, p < 0.01.Table 3 presents relevant correlations. Consistent with

prediction, left insula WM volume was positively correlated(r = 0.55, p < 0.01) with alcohol enhancement motives.However, left insula WM volume was not correlated withalcohol obsession/craving, although right insulaWMvolumewas (r = 0.36, p < 0.05). Left insula WM volume also was

INSULA AND BINGE DRINKING 1935

correlated with current alcohol abuse/dependence symptomcount at 1 year (r = 0.39, p < 0.05), but right insula WM vol-ume was not associated with either alcohol or cannabis use.Insula GM volumes were not associated with enhancementmotives or obsession/craving for alcohol or cannabis(Table 3).

Post hoc analyses comparing those with (n = 14) and with-out (n = 16) a DSM-IV alcohol diagnosis at baseline indi-cated that those with an alcohol diagnosis had greater leftinsula WM volume compared with those with no alcoholdiagnosis (0.57 � 0.04 vs. 0.55 � 0.03, t = �2.12, p < 0.05,respectively, Cohen’s d = 0.78: medium to large effect).Alcohol diagnosis groups did not differ on right insula WMvolume (p = 0.05), insula GM volumes (p > 0.30), or alcoholobsession/craving (p = 0.14). Although not statistically sig-nificant (p = 0.11), those with an alcohol diagnosis endorsedalcohol enhancement motives to a greater extent com-pared with those with no diagnosis (mean = 18.7 � 5.8,14.8 � 7.4, respectively).

Alcohol enhancement motives were positively correlatedwith binge drinking frequency and alcohol abuse/dependencesymptom count at baseline and 1-year follow-up. Given thepositive association of alcohol enhancement motives with leftinsula WM volume and with indicators of alcohol involve-ment, alcohol enhancement motives might serve as a variablethat links left insulaWM volume to binge drinking frequencyand alcohol abuse/dependence symptom count (Fig. 1).Likewise, bivariate correlations supported a test of indirecteffects involving alcohol obsession/craving as a possiblemediator of the association between right insulaWM volumeand binge drinking frequency at baseline and 1 year.

Tests of Indirect Effects

Test of indirect effects linking left insula WM volumewith frequency of binge drinking, through enhancementmotives for alcohol use, indicated a significant indirecteffect at baseline (adjusting for gender and age). The pointestimate for the indirect effect was 1.72 (BCa 95% CI0.31, 4.28); parameter estimates are presented in Table 4.Likewise, left insula WM volume had a significant indirecteffect on binge drinking frequency over 1-year follow-upthrough enhancement motives for drinking (adjusting for

Table 2. Descriptive Statistics for Insula Volume, Enhancement Motives,and Substance Use

Insula volume

Total sample(N = 30)

Alcoholdiagnosis(n = 14)

No alcoholdiagnosis(n = 16)

Mean SD Mean SD Mean SD

Left, white matter 0.56 0.03 0.57 0.04 0.55 0.03Right, white matter 0.54 0.03 0.56 0.02 0.53 0.04Left, gray matter 0.43 0.03 0.43 0.03 0.42 0.03Right, gray matter 0.42 0.03 0.42 0.02 0.42 0.04

Mean SD

BaselineAlcohol enhancement motives 16.6 6.9Alcohol obsessive thinking/craving 3.8 3.5Cannabis enhancement motives 17.8 6.4Cannabis obsessive thinking/craving 6.7 4.9Alcohol binge frequency per month (past year) 2.3 2.9Cannabis use frequency (past 6 months) 5.5 2.6Current DSM-IV alcohol abuse/dependencesymptom count

1.6 1.9

1-Year follow-upAlcohol binge frequency per month (past year) 3.5 5.8Cannabis use frequency (past 6 months) 3.5 2.8Current DSM-IV alcohol abuse/dependencesymptom count

1.2 1.9

n (%)

In a controlled environment over 1-year follow-up 7 (23.3)

N = 30. SD = standard deviation; alcohol diagnosis = presence of cur-rent alcohol use disorder at baseline. Frequency of alcohol and cannabisuse: 0 = never tried, 1 = no use in past 6 months, 2 = less than once permonth, 3 = once per month, 4 = 2 to 3 times per month, 5 = once perweek, 6 = 2 to 3 times per week, 7 = 4 to 6 times per week, 8 = daily.

Table 3. Correlations Among Insula Volume, Enhancement Motives, and Substance Use

Insula volume

White matter Gray matter Alcohol

Left Right Left Right Enhance motives Obsess thinking

BaselineAlcohol: Enhancement motives 0.55** 0.23 0.32 �0.09 — —Alcohol: Obsessive thinking/craving 0.18 0.36* 0.03 �0.05 0.45* —Cannabis: Enhancement motives 0.20 �0.13 0.12 �0.17 0.45* 0.23Cannabis: Obsessive thinking/craving 0.11 0.00 �0.02 �0.03 0.08 0.44*Binge frequency per month (log) 0.28 0.35 0.25 0.12 0.53** 0.56**Cannabis frequency (past 6 months) 0.14 �0.06 0.26 0.12 0.12 0.19Current alcohol abuse/dependence symptom count 0.26 0.30 0.14 0.02 0.40* 0.50**

1-Year follow-upBinge frequency per month (log) 0.21 0.16 0.11 �0.24 0.52** 0.45*Cannabis frequency(past 6 months) �0.02 �0.05 �0.08 �0.37* 0.30 0.28Current alcohol abuse/dependence symptom count 0.39* 0.21 0.12 �0.15 0.40* 0.26In a controlled environment over 1-year follow-up 0.44** 0.29 0.12 �0.04 0.44* 0.24

*p < 0.05; **p ≤ 0.01.N = 30. Current = past 6 months; enhance motives = enhancement motives for alcohol; obsess thinking = obsessional thinking about alcohol;

log = log-transformed. Binge frequency per month is coded for the past year at each time point.

1936 CHUNGAND CLARK

gender, age, baseline alcohol use diagnosis, residence in acontrolled environment over follow-up). The point esti-mate for the indirect effect was 2.63 (BCa 95% CI 0.77,5.60; see Table 4 for parameter estimates). In both bingedrinking models, greater left insula WM volume was asso-ciated with greater enhancement motives for drinking, andgreater enhancement motives were associated with greaterfrequency of binge drinking.Indirect effect models examining left insula WM volume,

enhancement motives for drinking, and alcohol symptomoutcomes at baseline and 1-year follow-up were not signifi-cant. Indirect effect models examining right insula WM vol-ume, alcohol obsession/craving (possible mediator), andbinge drinking frequency also were not significant.

DISCUSSION

As hypothesized, enhancement motives for drinkingserved as a mechanism linking left insula WM volume andfrequency of binge drinking at baseline and at 1 year.Although the bivariate association between left insulaWM volume and binge drinking frequency was not signifi-

cant, left insula WM volume was indirectly linked specifi-cally with binge drinking frequency (and not alcohol-related problems more generally) through conscious per-ception of a desired bodily state (i.e., enhancementmotives for drinking). The novel finding of enhancementmotives as a link between left insula WM volume andbinge drinking frequency is consistent with a possible rolefor the insula in representing bodily states (e.g., “high”associated with binge alcohol use) that may be associatedwith substance use (Naqvi and Bechara, 2010).Other predictions, however, were not supported.

Although right insula WM volume was positively correlatedwith alcohol obsession/craving, and alcohol obsession/crav-ing was positively associated with binge drinking frequencyat baseline and at 1 year, indirect effects were not statisticallysignificant. The absence of an indirect effect for alcoholobsession/craving likely reflects the weaker associationbetween insula WM volume and alcohol obsession/craving,relative to enhancement motives, although enhancementmotives and alcohol obsession/craving were positively corre-lated. The weaker association between insula WM volumeand alcohol obsession/craving might be explained, in part,because the OCDS obsession/craving subscale assesses notonly craving or urge to use, but also preoccupation with sub-stance use, which may be less relevant to the processing ofbodily states in the insula. Further, alcohol preoccupation,obsessional thoughts, and craving may be relatively limitedamong young drinkers in this sample, most of whom were intreatment for cannabis use. In addition, the insula appearsto encode the intensity, rather than hedonic value, associatedwith a stimulus (Naqvi and Bechara, 2010), which also mayexplain the apparently stronger association of insula WMvolumes with alcohol enhancement motives relative to alco-hol obsession/craving, which was fairly low.Insula GM volumes were not associated with alcohol-

related measures of motives, obsession/craving, or consump-tion, suggesting a greater role for insula WM, relative toGM, volume with regard to associations with enhancementmotives and obsessive thinking about alcohol. In this regard,WM volume might be particularly relevant in facilitatingcommunication among brain regions that interact with theinsula in the processing of hedonic bodily states. This study’sGM findings differ from other research, which found anassociation between insula GM volume and the accuracy ofperceiving bodily states (Critchley et al., 2004). Differencesin results across studies might be explained by the particularcharacteristics of the sample and specific bodily states exam-ined. Among the indicators of substance involvement thatwere analyzed, only frequency of cannabis use at 1 year wassignificantly correlated (negative association) with rightinsula GM volume.In addition to stronger associations of alcohol-related cog-

nitions with insula WM, relative to GM, statistically signifi-cant correlations of insula WM with enhancement motivesand obsession/craving were specific to alcohol (relative tomarijuana). Significant correlations between insula WM and

Table 4. Parameter Estimates for Model Testing Indirect Effects ofEnhancement Motives on the Association Between Left Hemisphere

InsulaWhite Matter Volume and Binge Frequency

B SE t p

BaselineA path: “mediator” = enhancement 96.11 31.23 3.08 0.005B path 0.02 0.01 2.14 0.04C path 1.67 1.41 1.18 0.25C0 path �0.05 1.55 �0.03 0.98ControlsGender �0.09 0.10 �0.88 0.39Age 0.14 0.04 3.64 0.001Model summary: R2 = 0.54, F(4, 25) = 7.4, p = 0.0004

1-Year follow-upA path: “mediator” = enhancement 78.86 35.56 2.22 0.04B path 0.03 0.01 2.98 0.01C path 0.08 2.25 0.04 0.97C0 path �2.55 2.15 �1.19 0.25ControlsGender 0.18 0.13 1.38 0.18Age 0.14 0.05 2.66 0.01Alcohol diagnosis at baseline 0.30 0.13 2.27 0.03Controlled environment �0.01 0.17 �0.09 0.93Model summary: R2 = 0.59, F(6, 23) = 5.5, p = 0.0012

N = 30. The outcome, past year binge drinking frequency, was log-transformed. B = unstandardized coefficient; SE = standard error. “Media-tor” = intervening variable being tested (alcohol enhancement motives).Alcohol diagnosis at baseline (no alcohol diagnosis in past 6 months = 0,alcohol abuse or dependence diagnosis in past 6 months = 1). Gender(0 = female, 1 = male). Race/ethnicity (0 = Minority, 1 = White). A path(Fig. 1): independent variable (insula white matter volume) to interveningvariable (enhancement motives). B path: direct effect of intervening vari-able (enhancement motives) on dependent variable (past year binge drink-ing frequency). C path: Total effect of independent variable (insula whitematter volume) on dependent variable (past year binge drinking fre-quency). C0 path: Direct effect of independent variable (insula white mattervolume) on dependent variable (past year binge drinking frequency), aftercontrolling for the intervening variable (enhancement motives). Controls:partial effect of control variables on the dependent variable.

INSULA AND BINGE DRINKING 1937

alcohol outcomes also were specific to frequency of bingedrinking, and not alcohol abuse/dependence symptom count.Prior analyses involving this adolescent sample (Chung et al.,2013) also found stronger associations of regional (e.g., pre-frontal) WM integrity with alcohol outcomes, relative to can-nabis. The finding of an indirect effect for binge drinkingfrequency, rather than alcohol abuse/dependence symptomcount, might reflect the importance of acute intoxication (i.e.,bodily sensation of alcoholic “high”) with regard to theinsula, rather than alcohol-related problems. Future researchcould use a measure that specifically assesses intensity of sub-jective stimulant and sedative effects of alcohol (Chung andMartin, 2009) in relation to insula characteristics.

More generally, the specificity of the associations ofinsula WM volumes with alcohol enhancement motives andobsession/craving (in the context of no significant associa-tion between insula WM volumes and cannabis enhance-ment motives and obsession/craving) is consistent with theidea of substance-specific hedonic and motivational states(Naqvi and Bechara, 2010). Bodily sensations that areencoded and processed by the insula also may be moreimportant for certain substances (e.g., nicotine), relative toothers (e.g., marijuana; Naqvi and Bechara, 2010). Signifi-cant findings for left (but not right) insula WM volume inthe mediation analyses suggest some possible laterality,which is in accord with a theory proposing that lateraliza-tion (or asymmetry) in the brain might be related to aparallel asymmetry in parasympathetic and sympatheticpathways of the autonomic nervous system (Craig, 2005).According to this theory, left forebrain is generally associ-ated with parasympathetic activity (e.g., appetitive behav-ior, positive affect), which could help to explain theassociation between left insula WM volume and alcoholenhancement motives (i.e., appetitive behavior).

The post hoc finding that youth with an alcohol diagnosisversus without a diagnosis had greater left insulaWMvolumesuggests the possibility, while speculative, of greater effi-ciency, within the AUD subgroup, of processing hedonicbodily states, which may be available to consciousness asalcohol enhancement motives. Although the AUD and noAUD groups did not differ on demography, IQ, substanceuse, or co-occurring psychopathology, the groups might havediffered on unmeasured variables (e.g., family history ofAUD). The absence of significant correlations between leftinsulaWM volume and the substance use variables examinedsuggests that the difference in volume might have preceded,or at least appears to be unrelated to, substance use.

Greater knowledge of the insula’s role in relation to youthsubstance involvement could have long-term implicationsfor the development of neurobiologically informed interven-tions that are targeted to individual needs (Naqvi and Bec-hara, 2010). For example, the finding that greater left insulaWM volume among youth with an alcohol diagnosis, andits positive association with greater enhancement motivesfor drinking, suggest that left insula WM volume mightidentify a subgroup of youth who are at risk for engaging in

more frequent binge drinking, particularly if youth endorseenhancement motives for use. Although most studies ofadolescent drinkers have reported reduced WM integrity inspecific brain regions, such as the superior longitudinal fas-ciculus (review: Elofson et al., 2013), 1 study reportedgreater FA in limbic regions among youth with an AUDcompared with controls (Cardenas et al., 2013), a result,which was cautiously interpreted as possibly reflectinggreater efficiency in the processing of the rewarding effectsof substance use due to greater WM integrity. These find-ings suggest that interventions, which modulate insula func-tioning (e.g., mindfulness-based; Holzel et al., 2011) andwhich address enhancement motives for drinking couldpotentially reduce risk for certain subgroups of youth insubstance use treatment.

Study limitations warrant comment. Sample size was rela-tively small, and may have provided limited power to detectcertain effects. Although gender was considered as a covari-ate, sample size precluded tests of gender as a moderating fac-tor (cf. Tanabe et al., 2013). Generalizability of results maybe limited, given that the sample consisted of a majority ofmales and White youth, recruited from substance use treat-ment primarily for cannabis use, with particular patterns ofco-occurring psychopathology. However, the sample is gen-erally representative of the demographic characteristics ofyouth in substance use treatment (SAMHSA, 2012). We didnot collect data on family history of AUD, which might havedistinguished AUD and noAUD groups; or on enhancementmotives and obsession/craving at the time of the scan. A rela-tively large number of analyses were conducted, which urgesreplication of these findings. A healthy control group was notexamined, because “craving”may bemore relevant to heaviersubstance users, such as youth in treatment. This adolescentsample reported relatively low levels of alcohol obsession/craving. FreeSurfer parcellation did not involve smaller insu-lar subunits (e.g., anterior and posterior) that have been asso-ciated with relatively distinct functions (Craig, 2009).

This study provides preliminary novel results indicatingthat enhancement motives for alcohol use provide animportant link between left insula WM volume and fre-quency of binge drinking in treated adolescents. Resultsare consistent with theories of addiction (Naqvi and Bec-hara, 2010) that address the insula’s role in the processingof hedonic bodily states, which are available to consciousawareness (e.g., enhancement motives for alcohol use), andthe importance of these bodily states, as represented in theinsula, in motivating substance use behavior, particularlyfrequency of binge drinking. Further research on insulastructural characteristics, and functioning, could informthe development of targeted interventions for adolescentsubstance users.

ACKNOWLEDGMENTS

Support for the conduct of the research and preparationof the manuscript was provided by funding from the

1938 CHUNGAND CLARK

National Institute on Alcohol Abuse and Alcoholism andNational Institute on Drug Abuse (R01 AA014357, R21DA021028, R21 AA016272, R21 AA017128, R21 AA04357,K02 AA018195, U01 AA021690).

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