NeuroImage 44 (2009) 1178–1187

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The bivalent side of the nucleus accumbens

Liat Levita a,⁎, Todd A. Hare b, Henning U. Voss c, Gary Glover d, Douglas J. Ballon c, B.J. Casey a

a Sackler Institute for Developmental Psychobiology, Institute of Psychiatry, Weill Cornell Medical College, New York, NY, USAb California Institute of Technology, Division of the Humanities and Social Sciences, Pasadena, CA, USAc Citigroup Biomedical Imaging Center, Weill Cornell Medical College, New York, NY, USAd Lucas Magnetic Resonance Image Center, Stanford University, Palo Alto, CA, USA

⁎ Corresponding author. The Sackler Institute for DWeill Cornell Medical College, 1300 York Ave, Box 140, N+1 212 746 5755.

E-mail address: lil2017@med.cornell.edu (L. Levita).

1053-8119/$ – see front matter © 2008 Elsevier Inc. Alldoi:10.1016/j.neuroimage.2008.09.039

a b s t r a c t

a r t i c l e i n f o

Article history:

An increasing body of evid Received 6 June 2008Revised 10 September 2008Accepted 21 September 2008Available online 11 October 2008

ence suggests that the nucleus accumbens (NAcc) is engaged in both incentivereward processes and in adaptive responses to conditioned and unconditioned aversive stimuli. Yet, it hasbeen argued that NAcc activation to aversive stimuli may be a consequence of the rewarding effects of theirtermination, i.e., relief. To address this question we used fMRI to delineate brain response to the onset andoffset of unpleasant and pleasant auditory stimuli in the absence of learning or motor response. IncreasedNAcc activity was seen for the onset of both pleasant and unpleasant stimuli. Our results support theexpanded bivalent view of NAcc function and call for expansion of current models of NAcc function that aresolely focused on reward.

© 2008 Elsevier Inc. All rights reserved.

The role of the nucleus accumbens (NAcc) in behavior has tendedto focus largely on responses toward rewarding and appetitive stimuliand events. However, based on evidence from both human neuroima-ging studies and animal-based research, a broader role for NAccfunction has been proposed in behavior modulated by aversive events.This imaging study has been designed to test the proposed bivalentfunction of the NAcc in behavior by addressing two arguments thathave been raised against this idea: 1) that activation of the NAcc toaversive stimuli is secondary to some kind of relief as a result of thetermination of that event; and 2) that it is a consequence ofpreparation and regulation of instrumental motor action.

The NAcc has been viewed as the key site for transference ofmotivational and other emotional signals received from the prefrontalcortex, amygdala and hippocampus to adaptive behavioral responses,and dopamine has been strongly implicated in facilitating this process(Laviolette, 2007; Meredith, 1999). However, this role has largelyfocused on rewarding appetitive processes (Day and Carelli, 2007),which has tended to overshadowwork that has also demonstrated theinvolvement of the NAcc and the dopaminergic system in aversiveemotional processes (Blackburn et al., 1992). For example, dopami-nergic midbrain neurons increase firing in response to conditionedand unconditioned aversive stimuli (Guarraci and Kapp,1999; Horvitz,2000; but see, Ungless et al., 2004 and Schultz, 1997), as well as novelor unpredicted stimuli (Miller et al., 1981; Rasmussen et al., 1986).Moreover, while the abuse potential of drugs such as amphetamineand cocaine is largely attributed to their rewarding actions, the effects

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of these drugs are not always hedonic, and there is evidence that theiranxiogenic and psychomimetic effects (Mathias et al., 2008; Ravenet al., 2000) might also be mediated by the NAcc and its dopaminergicinnervation (Broderick et al., 2003; Hunt et al., 2005; Koob et al., 1989;Miczek et al., 1999).

Indeed, the function of the NAcc in gating and modulating goal-directed action (Cardinal et al., 2002) requires the detection of bothsafety and danger cues in the environment. Thus, an expanded,bivalent view of NAcc function has been advocated, whereby the NAccis engaged in processing of both rewarding and aversive stimuli(Becerra et al., 2001; Jensen et al., 2003; Reynolds and Berridge, 2002).Consistent with the idea that the NAcc role in behavior is bivalent isthat it is richly innervated, not only by the amygdala, which signals thesalience of both positive and negative stimuli (Breiter et al., 1996;Demos et al., 2008; Hamann and Mao, 2002; Hamann et al., 2002;Paton et al., 2006), but also by other regions that process both aversiveand reward information, such as the orbitofrontal cortex, insula,cingulate cortex, and the midline- and intra-laminar thalamic nuclei(Bourgeais et al., 2001; Haber et al., 2006; Hsu et al., 2000; Vogt,2005). In turn the NAcc can affect the expression of emotion via tworoutes: 1) It can influence motor action in response to emotive stimulivia its projections to the substantia nigra and ventromedial globuspallidus, which belong to the basal ganglia system involved in motorprogramming (Zahm and Heimer, 1993); and 2) It can inducesignificant changes in autonomic and physiological processes tothese same stimuli, since it also projects to the lateral hypothalamus,which participates in the autonomic and endocrine expression ofemotion (Kirouac and Ganguly, 1995).

The functional significance of the anatomical connectivity of theNAcc is reflected at the physiological level where different neurons inthe NAcc can respond to either aversive or appetitive stimuli (Roitman

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et al., 2005; Setlow et al., 2003; Wheeler et al., 2008; Wilson andBowman, 2005; Yanagimoto andMaeda, 2003). In addition, behavioralstudies in both rodents and non-human primates have shown that theNAcc plays a critical role in aversive conditioning and active avoidancebehavior (Ammassari-Teule et al., 2000; Hoebel et al., 2007; Iordanovaet al., 2006; Levita et al., 2002; Schwienbacher et al., 2004), and anincreasing number of human imaging studies have shown enhancedactivity in this region in response to both conditioned and uncondi-tioned aversive stimuli (Becerra et al., 2001; Gottfried et al., 2002;Jensen et al., 2003). Finally, in a manner similar to that previouslydemonstrated for the amygdala (Etkin et al., 2004; Stein et al., 2007;Straube et al., 2007), studies in non-human primates and humanshave demonstrated that the positive association between anxietylevels and responses to aversive and anxiety-evoking stimuli is alsomodulated by the degree of NAcc activation (Kalin et al., 2005; Sturmet al., 2003).

A role for the NAcc in negative contexts is further supported bystudies implicating the NAcc in contextual Pavlovian aversiveconditioning (Haralambous and Westbrook, 1999; Levita et al., 2002;Westbrook et al., 1997), as well as conditioned inhibition of ongoinginstrumental action (Parkinson et al., 1999). The latter is consistentwith evidence implicating the NAcc in mediating the interactionbetween Pavlovian and instrumental contingencies (Hall et al., 2001).However, in contrast to the detrimental effect of lesions of theamygdala on fear learning (for review see, Maren, 2001; Phelps andLeDoux, 2005), some studies have failed to find an effect of lesions orpharmacological manipulations of the NAcc on discrete cue Pavlovianaversive conditioning (e.g., Levita et al., 2002; Westbrook et al., 1997).This finding is also mirrored in a number of human imaging studiesfailing to show NAcc activation in response to conditioned aversivestimuli (Chandrasekhar et al., 2008; Hamann and Mao, 2002; Phelpset al., 2004). Moreover, it could be argued that NAcc activity observedin anticipation of, or response to, negative events, is due to therewarding effects of termination of an aversive event rather than aresult of a response to the noxious stimuli (Ikemoto and Panksepp,1999). Additionally, since the NAcc influences instrumental behaviorby allowing Pavlovian conditioned stimuli (CSs) to affect the level ofinstrumental responding (Cardinal et al., 2002), the engagement of theNAcc in some studies may reflect its role in modulating instrumentalmotor actions dissociable from emotion.

To address these two possibilities, we designed an fMRI study inwhich we could dissociate brain activation to the initiation andtermination of unpleasant and pleasant auditory stimuli in theabsence of learning or a motor response. Consequently, in this studysubjects were required to passively listen to pleasant and unpleasantauditory stimuli that were randomly presented in a long-eventrelated design while skin conductance response (SCR) was recorded.To dissociate activation related to onset versus offset, the duration ofpositively and negatively valenced auditory stimuli were jittered andregressors were created for onset and offset of the negative andpositive stimuli. We predicted that NAcc activation would beobserved for the initiation, but not termination of the unpleasantsounds, results that would be consistent with the idea of bivalentNAcc function.

Materials and methods

Subjects

Twenty right-handed adults (10 male, 10 female; age: range 20–31, mean 25.7±0.6; IQ=116±2.7) took part in the study. Subjectswere free of any medical or neurological problems, and had nocurrent or previous diagnosis of psychiatric or neurological disorder.All subjects gave informed consent in accordance with Weill MedicalCollege of Cornell University IRB committee, and were paid for theirparticipation.

Stimuli and apparatus

Auditory stimuli consisting of two unpleasant (negative tones: n1and n2) and two pleasant (positive tones: p1 and p2) tones were usedin this study. These tones were presented for 2, 4, and 6 s. The auditorystimuli used were modified and generated using the digital audioeditors: Audacity 1.2.6 (http://audacity.sourceforge.net) and PRAATVersion 4.5.08 (www.praat.org). The auditory stimuli generated wereof 2 s duration and were looped to generate 4 and 6 s segments.Stimuli: n1, a combined 1000 Hz tone and white noise, which wasintensity tiered for smooth onset and offset; n2, four bursts of a1000 Hz square wave tone, duration 0.4 s, and silence 0.1 s; p1, a windchime recording that was modified for a smooth rise and fall; p2, asecond chime recording amplified and modified, like p1, for a smoothrise and fall. All stimuli were modified so they would have the sameintensity (95 dB in scanner; Headphones; fMRI Devices Corporation,Waukesha, WI). These stimuli were chosen after a pilot study was runto select the most pleasant and unpleasant sounds from a selection ofeight. In the pilot study a randomly mixed sequence of the eightsounds was presented three times to 11 subjects (age 26–36) whorated them individually on a 20-point unpleasantness–pleasantnessscale. There was a significant difference in rating the pleasant andunpleasant sounds (pb0.001). Average rating for the aversive soundswas 3.7±0.33 and 17.1±0.31 for pleasant sounds. From these eightsound stimuli the two sounds that were rated as most unpleasant andthe two sounds that were rated as most pleasant were selected for theimaging study.

Skin conductance response

A skin conductance response (SCR) MRI compatible system(SCR100C Biopac, Goleta, CA) together with the AcqKnowledge(Biopac) software was used to monitor the SCR as it varied with theeccrine sweat gland activity. The computer running AcqKnowledgeand the computer running E-prime (Psychology Software Tools, Inc,Pittsburgh, PA) were interfaced allowing generation of digital TTLtimestamps for each stimulus on the Biopac channel recording, so thatstimuli presentations during scanwere co-registered with SCR record.The SCR was sampled at 200 Hz using disposable electrodermal gelelectrodes (Biopac model EL507) attached to the distal phalanx of thepointer and middle fingers of the left hand. The electrodes wereconnected to an MRI compatible cable set (MECMRI-TRANS) thatinterfaced with the SCR100C amplifier and the control panel. TheSCR100C used a constant voltage (0.5 V) to measure skin conductance.The SCR was digitized at the electrodes and 1 Hz filter applied (Gain2 μmho/V). Subjects were asked to wash their hands with water anddry them gently before the electrodes were attached. SCRs wereanalyzed by subtracting the peak skin conductance responseoccurring in a time window of 1–5 s after stimulus onset from abaselinemeasure just prior to the stimulus onset. The small number ofsubjects which we successfully recorded SCR from (n=7) precludedthe inclusion of the SCR measures in our fMRI analysis.

Experimental task

Subjects completed a passive listening task in which they heardpleasant and unpleasant sounds. Stimuli duration varied between 2, 4,and 6 s in order to deconvolve stimulus onset and offset BOLDresponses. The interstimulus interval was 12 s (Fig. 1A). The entireexperiment consisted of 5 runs, each lasting 212 s. A total of 60 stimuliwere presented, 30 negative and 30 positive sounds. The stimuli werepresented in a pseudorandom order, with never more than twosounds of the same valence type following each other. Before the startof the experiment participants were told that they would hear soundsthat were pleasant and unpleasant in nature and that no action wasrequired on their part except to continue to pay attention to tones that

Fig. 1. Behavioral task and validation of stimulus valence. (A) The paradigm consisted of presentations of negative and positive sound stimuli of variable duration (2, 4 or 6 s)presented with a fixed inter-stimulus interval (ISI) of 12s. In total 30 negative and 30 positive auditory stimuli were presented in a pseudorandom order. (B) While in the scannersubjects rated the sounds as either pleasant or unpleasant on a 5 point rating scale, 1 being most unpleasant, and 5 being most pleasant. (C) Skin conductance response (SCR) to thenegative and positive auditory stimuli.

1180 L. Levita et al. / NeuroImage 44 (2009) 1178–1187

would be presented. In addition, participants were instructed to closetheir eyes throughout the experiment, and were reminded of this atthe beginning of each run. At the end of the experiment, while still inthe scanner, subjects heard the auditory stimuli presented throughoutthe experiment, and rated their subjective experience of each tone ona 5-point scale (1 as most unpleasant and 5 as the most pleasant). Thescanner was on during subjective rating so that the sounds would beexperienced under the same conditions as during the experimentaltask. Subjects made their responses on a five button response glove.Stimuli and response collection (valence ratings of stimuli) werepresented with the integrated functional imaging system (IFIS; PST,Pittsburgh) using an LCD video display in the bore of the MR scannerand a fiber optic response collection device. Self report ratings of stateand trait anxiety were measured using the Spielberger's State-TraitAnxiety Inventory (Spielberger, 1983) administered following thescanning session.

Image acquisition

Subjects were scanned with a General Electric Signa Excite 3.0 TfMRI scanner (General Electric Medical Systems, Milwaukee, WI) witha quadrature head coil. Foam padding placed around the head wasused to reduce motion. A whole brain, high resolution, T1 weightedanatomical scan (a 3D SPGR; 256×256 in-plane resolution, 240 mmfield of view [FOV]; 124 1.5-mm axial slices) was acquired for eachsubject for transformation and localization of functional data intoTalairach space (Talairach and Tournoux, 1988). A spiral in and outsequence (Glover and Thomason, 2004) was used to collect functionaldata (TR=2000, TE=30, FOV=200 mm, Flip angle=90 and 64×64matrix). We obtained 29, 5 mm thick coronal slices with an in-planeresolution of 3.125×3.125 mm that covered the entire brain except forthe posterior portion of the occipital lobe.

Imaging data analysis

Functional imaging datawere preprocessed and analyzed using theAFNI software package (Cox, 1996). The first 4 volumes (8 s) from eachrun were discarded to allow the scanner to reach magnetizationequilibrium. Following slice time correction, images were registeredto the first image volume following the high-resolution anatomicaldataset using rigid body transformations and smoothed using anisotropic 6 mm Gaussian kernel. Head motion was examined toconfirm that all subjects had less than 2 mm of translation or 2° ofrotational movement. Time series were normalized to percent signalchange to allow comparisons across runs and individuals by dividingsignal intensity at each time point by the mean intensity for that voxeland multiplying the result by 100. Four regressors were created foronset and offset of negative and positive sounds by convolving thestimulus timing files with a gamma-variant hemodynamic response

function. Linear regression modeling was performed to fit the percentsignal change time courses to each regressor. Linear and quadratictrends were modeled in each voxel time course to control forcorrelated drift. Motion parameters were included in the GLM ascovariates of no interest. The resulting regression coefficientsrepresent an estimate of percent signal change from the mean.

Group level analyses were conducted on the regression coefficientsfrom the individual analysis after transformation into the standardcoordinate space of Talairach and Tournoux (1988), using parametersobtained from the transformation of each subjects' high-resolutionanatomical scan. Talairached transformed images had a re-sampledresolution of 3×3×3 mm. Normalization to Talairach space was doneusing automatic Talairach transformation in AFNI, where the anato-mical volume was warped using 12-parameter affine transform to atemplate volume (TT_N27) in Talairach space. An omnibus 2 (valence;negative/positive)×2 (time; onset/offset) way ANOVA that includedsubject as a random factor was conducted to determine the maineffects of valence, time, and valence×time interaction. Correction formultiple comparisonswas applied at the cluster level followingMonteCarlo simulations conducted in the AlphaSim program within AFNI.Clusterwise false-positive rates of pb0.05 corrected for multiplecomparisons were determined for whole brain analyses. Additionalsimulations were restricted to the NAcc and amygdala based on thesize of these regions unilaterally derived from the Talairach atlasincluded in the AFNI distribution (Volume: amygdala ∼890 mm3;Nucleus accumbens ∼1000 mm3). Whole brain simulations wereconducted at individual voxel α probabilities set at 0.01, 0.001 and0.0001 to allow identification of both broad and focal activations.Individual voxel α probabilities were set at 0.025 for simulationswithin the amygdala and NAcc. Only clusters with more than threevoxels were considered for analysis.

For functional region of interest (ROI) analyses, anatomical masksof the NAcc and amygdala ROIs were defined from the Talairach atlasincluded in the AFNI software distribution. Voxels within these masksthat showed activation above the threshold of pb0.025 for thevalence×time interaction at the group level were included in thefunctional ROI analysis. To address the concern that our group levelfunctional ROI (defined by the average group level of activation)represented the same anatomical region in different participants weTalairach transformed individual anatomical ROIs for the NAcc andamygdala generated with FreeSurfer to compare the individualFreeSurfer ROIs with the Talairached group functional ROIs. Parcella-tion of the subcortical anatomy into regions of interest was performedusing the FreeSurfer software suite (Fischl et al., 2002). These toolsdelineate anatomical divisions via automatic parcellation methods inwhich the statistical knowledge base derives from a training setincorporating the anatomical landmarks and conventions describedby Duvernoy (1991). The resulting segmentation maps were viewedand the FreeSurfer derived-segmentation of regions of interest were

Table 1Interaction of valence (positive vs. negative)×time (onset vs. offset)

Brain region Talairach coordinates (CM)

Side RL AP IS Size(mm3)

F stats Onset Offset

Medial frontal gyrus L 6.2 −1.7 19.1 1026 29.9 nNp nNpInferior frontal gyrus L 43.8 −17.1 5.5 108 32.1 nNp n=pTemporal gyrusand insula

L 39.3 24.5 13.2 1350 27.6 nNp nNp

Insula R −43.5 24.9 15.5 810 27.0 nNp n=pInsula L 31.6 −22.6 9.2 513 27.6 nNp nNpCingulate gyrus L 8.8 −13.5 36.4 270 28.4 nNp nNpCingulate gyrus R −8.7 −10.3 −10.3 270 27.8 nNp nNpInsula L 33.5 −7.1 5.8 243 30.5 nNp nNpInsula R −38.3 12.3 6.1 243 28.1 nNp nNpGlobus pallidus L 9.8 3.5 1.9 243 26.6 nNp nNpThalamus L 11.7 17.3 11.3 1350 29.4 n=p nNpThalamus R −5.9 11.2 10.8 108 25.1 n=p nNpCerebellum R −22.9 48.5 −23.3 189 29.0 nNp nNpBrain stem 3.1 27.0 15.7 1431 29.7 nNp nNpNucleus accumbens R −12.9 −4.5 −1.1 189⁎ 8.7 nNp n=pAmygdala R −25.7 3.3 −14.3 702⁎ 11.8 n=p nNpAmygdala L 19.1 4.5 −14.2 270⁎ 8.0 nNp nNp

Group analysis ANOVA. CM, center of mass; L, Left; R, Right. Whole brain p=0.0001,corrected to pb0.05.⁎ Region of interest correction p=0.025, corrected to pb0.05.

Table 2Whole-brain contrast analysis probing the main effect of valence

Brain region Talairach coordinates (CM)

NegativeNpositivea Side RL AP IS Size (mm3) T stats

Striatum, insula, globus pallidus,thalamus and brainstem

R&L −3.8 14.7 4.3 41094 4.67

Amygdala R −28.9 −0.2 −17.2 189 4.35Cingulate gyrus R&L −0.9 −9.3 39.6 5265 4.47Posterior cingulate gyrus R&L −0.5 −23.0 40.8 324 44.5Insula and Inferior frontal gyrus L 37.5 −11.8 9.8 375 4.33Cerebellum R&L 35.2 49.5 −25.9 594 4.31Cerebellum R −23.6 47.2 −25.6 459 4.21

Contrast Analysis: positive minus negative. CM, center of mass; L, Left; R, Right.Whole brain pN0.001, corrected to pN0.05.

a No brain regions with greater activation to the positive tones were found.

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evaluated and manually edited when found to be incorrect. We foundthat all subjects showed overlap within each of the two regionsof interest, demonstrating that our group functional ROIs fit theindividual subject anatomical data.

To examine the time course of activation, mean BOLD responseswere plotted for selected clusters. To that end we applied functionalmasks of these clusters (based on the group level analysis) to extractindividual time series averaged across voxels for each subject's fMRItime series. From these, percent signal change for each event wascalculated relative to the mean of the two TRs prior to stimulus onsetin a time window of 0 to 12 s. We also analyzed our data using themean as the baseline which did not appear to change any of theresults. In addition, BOLD signal attenuation or enhancement withrepeated presentations of the negative and positive stimuli wasexamined in individual subjects in two regions of interest, the NAccand amygdala. In this analysis the peak hemodynamic response foreach stimulus in each run was measured in the significant clustersobserved after group analysis in the right NAcc and right amygdala.Mean of peak BOLD signal in early runs (1 and 2) and late runs (3 and4) in these regions was calculated and a slope of best fit for earlyversus late trial peak response was generated. The gradient of theslope was taken as a measure of either habituation or sensitization torepeated presentation of stimuli across the experiment. Positiveslopes are indicative of an increase in activation (sensitization) withtime, whereas negative slopes are indicative of a decrease in activation(habituation) to the repeatedly presented stimuli.

Moreover, the interaction of the activity in the NAcc and amygdalain response to the onset of the negative and positive stimuli with theactivity of other brain regions was characterized by performing afunctional connectivity analysis. This analysis was computed in AFNIand performed by using the right amygdala functional ROI (derivedfrom group analysis results valence×time). Individual time serieswere extracted from the amygdala cluster for each subject's fMRI timeseries and averaged across voxels. Linear trend removal was firstconducted on the entire time series. Deconvolution was then run onthe seed time series, and an interaction regressor created [decon-volved seed time series×events of interest− the onset of the negative(ni) and positive (pi) stimuli]. Single subject GLMwas then run exactlyas for a regular analysis, but here, adding the two additional regressorsof interest. In addition, all of the original regressors of interest (events)and no interest (motion parameters) were included to account for all

sources of variability in the dataset. The resulting correlationcoefficients for the interaction regressors were transformed to anormal distribution using Fisher's Z transformation before groupanalyses on these values.

All statistical analysis of the data was conducted in SPSS 15.0 (SPSSInc. Chicago, IL).

Results

Validation of stimulus valence

At the end of the experimental session, while still in the scanner,subjects rated the auditory stimuli presented with respect to theirpositive and negative stimulus valence. There was a significantdifference in valence ratings between the positive and negativestimuli presented (Fig. 1B), where positive sounds were rated aspleasant and negative sounds were rated as unpleasant (Z=−3.9,p≤0.001). No gender differences were found in valence rating, nor didvalence ratings differ with respect to the duration of the stimulipresentation (2, 4, or 6 s).

Skin conductance response

Dissociation between the positive and negative sound stimuli wasalso found at the physiological level. Significantly greater skinconductance response (SCR) was observed to the negative versusthe positive auditory stimuli (Fig. 1C; Z=−2.67, p=0.008). Measure-ment noise caused by the scanner environment prohibited reliableSCR in the majority of subjects tested, consequently the small numberof subjects with robust SCR (n=7) precluded the inclusion of the SCRmeasures in our fMRI analysis. No evidence was found of a SCR to thetone offset.

Imaging results

Whole brain analysisThe fMRI data were analyzed using a generalized linear model

(GLM) that evaluated BOLD responses to the initiation and termina-tion of the auditory stimuli. While this study was focused on NAccactivation, we first performed a whole-brain analysis to determineregions activated by negative versus positive stimuli at onset andoffset using a 2 (valence; negative versus positive)×2 (time; onsetversus offset) ANOVA. The complete list of brain regions showingmaineffects and interactions is given in Table 1 and in SupplementaryTables 1 and 2. Whole-brain contrast analysis probing the main effectof valence revealed greater activation to negative rather than positiveauditory stimuli in the greater part of the striatal complex, as well as inthe right amygdala (Table 2, and supplemental Fig. 1). Moreover,whole brain contrast analysis for the main effect of time (stimulusoffset minus onset) for the negative as well as the positive stimuli did

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not reveal any brain regions showing activation on termination ofeither of these stimuli (data not shown).

Valence×time interaction (Fig. 2) revealed greater activation forthe negative auditory stimuli in the inferior frontal gyrus, cingulatecortex (Fig. 2B), anterior and posterior insula (Fig. 2C), globus pallidus,and cerebellum, all associated with greater relative deactivation onthe offset of the negative stimulus. In contrast, the peak magnitude ofonset BOLD activation was equivalent for both valence types inclusters observed in areas of the thalamus (Fig. 2D) and the superiortemporal gyrus (STG). However, these thalamic and STG activationswere associated with greater relative deactivation on the offset of thenegative stimulus.

Functional region of interest analysisWe conducted a functional region of interest (ROI) analysis on the

NAcc to test our prior hypothesis regarding activation in response topositively and negatively valenced stimuli. Voxels within the NAccthat showed activation at the group level for the valence×timeinteraction were included in this functional ROI. For this analysis, ananatomical mask of the NAcc was defined from the Talairach atlasincluded in the AFNI software distribution. Voxels within the NAcc

Fig. 2. Activation of nociceptive/emotive brain regions. (A) Coronal sections illustrating regcorrected to pb0.05). Activations are displayed over a Talairach-normalized coronal templnegative aversive stimuli in the (B) cingulate cortex (CIG), (C) insular cortex (IN), and cerebellthalamus (TH). Line plots represent mean±standard error of the mean (SEM) across partici

were corrected for multiple comparisons at the pb0.05 level usingcluster thresholds determined by AlphaSim. The AlphaSim MonteCarlo simulations were run using an individual voxel threshold ofpb0.025 within an anatomical mask of the NAcc taken from theAFNI Talairach atlas.

Within the NAcc there was a main effect of time, whereby bilateralactivation of the NAcc was observed in response to the onset of thepositive and negative stimuli. No main effect of valence was observed.However, there was a significant interaction between valence andstimulus onset and offset in the right NAcc (Figs. 3A and B, Table 1),with significantly greater response to unpleasant than pleasant soundstimuli (t=−3.61 p=0.002) at onset. Moreover, no evidence foractivation of NAcc activity on offset of the positive or negative stimuliwas found (Fig. 3B). Further analysis of activation of the NAcc revealeda positive correlation between the mean BOLD activation to the onsetof negative and positive stimuli, such that subjects who showed a highresponse magnitude to the positive stimuli, also showed a heightenedresponse to the negative stimuli (Fig. 3D; Pearson's r=0.881;pb0.001; n=20). We also found that NAcc activation to the negativeand positive stimuli remained largely constant throughout theexperiment, as measured by comparing mean response magnitude

ions that showed significant activation in group analysis of valence×time (pb0.0001,ates in radiological convention (right is left). Greater activation was observed for theum (CB). (D) No difference in activation to negative and positive sounds was observed inpants. Anterior/posterior y-coordinates are specified below the coronal sections.

Fig. 3. Bivalent activation of the nucleus accumbens. (A) NAcc activation map in the coronal plane (pb0.05, corrected). (B) Activation in right NAcc on onset but not offset of bothnegative and positive events. (C) Time course for the hemodynamic response in the right NAcc cluster. Image is in radiological format (right is left). (D) Scatter plot of the positivecorrelation of individual subject's mean peak activation of the NAcc to the positive and negative stimuli throughout the experiment. Peak activationwas defined for each individual byplotting the bold response for each event, and taking the peak value observed in resulting hemodynamic response function. Bar and line plots represent mean±standard error of themean (SEM).

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during early, middle and late trials (valence, F1,38=2.71; timeF1,38=0.43, valence×time, F1,38=0.001; Supplemental Fig. 2).

To examine regional specificity in response to aversive andpleasant stimuli, we investigated the response of the amygdala, aregion implicated in affective processes and which sends significantprojections to the NAcc. This analysis was performed in the samemanner in which we conducted the functional ROI analysis for theNAcc. The amygdala functional ROI was defined by voxels showing asignificant valence×time interaction using small volume correctionwithin an anatomical mask of the amygdala at pb0.05. Within theamygdala there was a main effect of time as well as valence×timeinteraction, but no main effect of valence. Post hoc t-tests on themain effect of time (onset vs. offset) revealed bilateral activation ofthe amygdala to both the negative and positive stimuli, as didvalence×time interaction (Fig. 4, Table 1, and Supplementary Table 2).We also found sensitization of the amygdala, as indicated byincreased amygdala activity to repeated presentations of the negativestimuli, but not positive stimuli. This increase was associated withself-ratings of anxiety, such that an increased amygdala activity withrepeated presentations of the negative stimuli predicated greaterstate and trait anxiety in individual subjects (State; Pearson'sr=0.674; p=0.001; Trait; Pearson's r=0.642, p=0.003, Fig. 4C). Nosuch association was found for the NAcc (State; Pearson's r=0.051;Trait; Pearson's r=−0.094).

Based on anatomical data demonstrating NAcc-amygdala connec-tivity, we also conducted functional connectivity analysis with theright amygdala cluster set as the seed region (Fig. 4A). We found apositive correlation between activity in the right amygdala and theright NAcc during the presentation of the negative, but not positivestimuli (Figs. 4D and E; and Supplemental Table 3).

Notably in this study auditory stimuli of different durations werepresented to allow us to deconvolve stimulus onset versus offset.Plots of the hemodynamic response to the positive and negativestimuli of different durations revealed that only regions such as thesuperior temporal gyrus, which is involved in auditory perception,were sensitive to stimulus duration. In contrast, this was not thecase in our regions of interest, the NAcc or amygdala, where theBOLD hemodynamic response was independent of stimulus duration(Fig. 5, and Supplemental Fig. 3).

Discussion

We found that the NAcc responds to the onset of both positive andnegative stimuli. Onset and offset analysis of activation of the NAcc topleasant and unpleasant sounds in a passive listening paradigmconfirmed a direct activation of this region by aversive stimuli, ratherthan an effect secondary to some kind of relief, or a result ofpreparation and regulation of instrumental motor action. Theseresults support the expanded view of NAcc function, whereby theNAcc plays a key role in modulating behavior to aversive and painfulstimuli, and not just to stimuli that are rewarding in nature. Ourfindings are consistent with several studies that have reported striatalactivity, including the NAcc, for primary and conditioned aversivestimuli (Blazquez et al., 2002; Ravel et al., 1999; Williams et al., 1993),as well as enhanced dopamine release in this region in response tosimilar events (Horvitz, 2002; Salamone et al., 2005). Moreover,consistent with the idea that the BOLD activations observed in thisstudy did not reflect a simple sensory percept but rather valence, wefound that neither the amygdala nor NAcc were sensitive to stimulusduration, unlike the superior temporal gyrus, a region involved in

Fig. 4. Bivalent amygdala activation. (A) Coronal slice showing right and left amygdala clusters. (B) Time course for the hemodynamic response in the right amygdala cluster. Imagesare in radiological format (right is left). Line plot represent mean±standard error of the mean (SEM) across participants. (C) Scatter plot of the correlation between trait anxiety andchange in right amygdala activation through time. Trait anxiety scores were positively correlated with increased amygdala activity on repeated presentations of the negative auditorystimuli. The y-axis represents rate of change in amygdala activation, positive values indicate sensitization, and negative scores indicate habituation. The x-axis represents traitanxiety score. D&E. Functional connectivity analysis with the right amygdala fROI cluster set as the seed region; Significant functional connectivity was observed between the rightNAcc and right amygdala during presentation of the negative (D) but not positive tones (E). FC, functional connectivity; R, right; L, left.

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auditory perceptual processes (Pandya, 1995). Bivalent activation ofthe NAcc in this study is further supported by the clear dissociation insubjects' subjective valence rating of the positive and negative stimulias being pleasant and unpleasant, respectively, which was alsoreflected in dissociable physiological response (SCR) to these stimuli.Nevertheless, it is possible that the NAcc was responding to the

Fig. 5. Nucleus accumbens and amygdala activation are not sensitive to stimulus durationnegative (n) stimuli (2, 4, and 6 s) in the right superior temporal gyrus (A), right nucleus accumLine plots represent mean±standard error of the mean (SEM).

arousing or attention-grabbing quality of the stimuli presented ratherthan their valence, which would be consistent with studies that havesuggested that the NAcc maybe responding to stimulus salience (Zinket al., 2006), or with other studies which find that both valence andsalience are critical for NAcc activation (Cooper and Knutson, 2008).However, in this study, the responses we observe in the NAcc are not

. Time course of the hemodynamic response on presentation of the different durationbens (B) and right amygdala (C) clusters from group analysis valence×time interaction.

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solely a reflection of stimuli's salience, since in auditory sensory areasas well as the thalamus we see equivalent activation to the positiveand negative tones presented to the participants, suggesting matchingof stimuli in terms of salience.

In this study we did not find activation of the NAcc on the offset ofan aversive event. However, our negative result on offset of anaversive event needs to be interpreted with caution. It is possible thatsubjects would never have felt relief on the offset of the aversivesound, since the scanner environment may in itself have been anunpleasant setting.

Notably, in this study we did not observe a dissociable temporalactivation profile for NAcc activation in response to positive andnegative primary auditory stimuli, as previously reported for condi-tioned aversive stimuli (Gottfried et al., 2002). Gottfried et al (2002)found that the NAcc showed significant activation to the aversivelyconditioned stimulus (CS+) early but not late in learning, the reversebeing the case for the appetitive CS+. These temporal differences mayrelate to cue learning rather than unconditioned stimuli (US)responses as investigated in this study. They may also explain thefailure to observe NAcc activation in some human imaging aversiveconditioning studies (Chandrasekhar et al., 2008; Delgado et al., 2006;Hamann and Mao, 2002), since activation of the region in response toaversive CS+ may be masked if time is not a factor in the analysis.

Previous studies have suggested that the NAcc may play a role inthe expression of anxiety (Kalin et al., 2005; Sturm et al., 2003).However, here we did not find an association between the rate ofhabituation of the NAcc to the negative auditory stimuli and subjects'self-rating of anxiety. Yet, consistent with previous studies (Etkin etal., 2004; Hare et al., 2008) the change in amygdala activity to thenegative stimuli over time was associated with subjects' anxietylevels. The amygdala, specifically the basolateral nucleus, sendssignificant projections to the NAcc (Nauta, 1982) and hence if highanxiety levels enhance output from the amygdala, it might be thattarget sites like the NAcc would also show the same phenotype.Indeed, functional connectivity analysis revealed a positive couplingbetween the amygdala and the NAcc when subjects were exposed tothe aversive, but not positive stimuli. However, while amygdala inputcan affect NAcc function (Cardinal et al., 2004; Setlow et al., 2002),other pathways to the NAcc can act to offset or change the degree bywhich the amygdala can drive this region (Everitt et al., 1999; Grace,2000; Jackson and Moghaddam, 2001; Setlow et al., 2002). More-over, a lack of correlation between levels of anxiety and NAccactivation may be a result of the passive nature of our task. Thus,while our task design enabled us to examine the response of theNAcc to emotive stimuli in the absence of possible confoundsstemming from motor responses, it did not allow us to examine fullythe functional significance of these activations in modulation ofbehavior. Tasks that involve instrumental approach–avoidancebehavior may be more likely to demonstrate correlations betweenindividual anxiety levels and both task performance and the degreeof brain activation in the NAcc.

In this study, the amygdala, like the NAcc, showed a bivalentpattern of activation, consistent with a large body of evidencedemonstrating that while the amygdala responds most reliably tonegative stimuli (Hariri et al., 2000; Phelps et al., 2001; Whalen et al.,1998), it also performs operations such as signaling the salience ofpositive stimuli (Breiter et al., 1996; Demos et al., 2008; Hamann andMao, 2002; Hamann et al., 2002). However, while the NAcc andamygdala respond to similar types of bivalent information, and areintimately connected, they belong to functionally dissociable neuralcircuits: 1) An amygdala-centered circuit that acts as a rapid responsemodule that can engage affective response units even prior toconscious stimulus identification (Morris et al., 2001); and 2) ANAcc-centered circuit that can only fully engage down-stream sites foraction-selection once stimulus identity has been established and itssignificance evaluated. Thus, while NAcc neurons respond to emotion-

eliciting stimuli, they do so in a manner that is largely dependent onindividual stimulus identity, i.e., object-specific, rather than respon-ding to a single common physical or psychological property of thesestimuli (Roitman et al., 2005; Setlow et al., 2003;Wilson and Bowman,2005; Yanagimoto and Maeda, 2003). This is in sharp contrast toneurons in the amygdala which tend to respond to a single commonpsychological property (Belova et al., 2007; Maeda et al., 1993; Patonet al., 2006; Salzman et al., 2007).

The stimulus-identity dependency of NAcc neurons is consistentwith the NAcc being a part of an approach–avoidance behaviornetwork. Such a system must first be able to process informationabout the identity and value of unconditioned stimuli that can acteither as rewards or punishers, and that once these events occur,motor systems must re-direct behavior to gain maximal utility fromrewarding events (Day and Carelli, 2007), or be engaged in a way thatwill allow the organism to avoid threat and aversive outcomes (Faureet al., 2008; Reynolds and Berridge, 2001). This idea is consistent withthe role of the NAcc in both negative and positive reinforcementprocesses, for example in humans anticipating monetary gain and loss(Cooper and Knutson, 2008), and the damaging effect of NAcc lesionsand pharmacological manipulations in tasks that require behavioralinhibition and modulation of instrumental action to optimize rewardgain and avoid risk (Cardinal et al., 2004; Christakou et al., 2004;Martinez et al., 2002; Salamone et al., 1997; Wadenberg et al., 1990).

Concluding remarks

In this study we were able to show that just as the amygdala is notsolely responsive to negative events, the NAcc is not only responsive toanticipated positive rewards, but also aversive events. These resultssupport models of NAcc function that are not solely focused onreward. This broader bivalent role for the NAcc is consistent with theanatomical connectivity of the NAcc that allows it to integrate asubstantial amount of information from regions that process bothpositive and negative valence. Future work needs to investigate theprecise role of this integration in emotional regulation via outputs ofthe NAcc to motor, cognitive and autonomic centers.

Acknowledgments

Wewould like to thank Bruce McCandliss and Jason Zevin for theirthoughtful discussions about this work. This research was supportedin part by the National Institute of Drug Abuse Grant R01 DA018879(BJC), NIH P50 MH52196 and MH079513, the Mortimer D. Sacklerfamily and Dewitt-Wallace Reader's Digest Foundation.

Appendix A. Supplementary data

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.neuroimage.2008.09.039.

References

Ammassari-Teule, M., Passino, E., Restivo, L., deMarsanich, B., 2000. Fear conditioning inC57/BL/6 and DBA/2 mice: variability in nucleus accumbens function according tothe strain predisposition to show contextual- or cue-based responding. Eur. J.Neurosci. 12, 4467–4474.

Becerra, L., Breiter, H.C., Wise, R., Gonzalez, R.G., Borsook, D., 2001. Reward circuitryactivation by noxious thermal stimuli. Neuron 32, 927–946.

Belova, M.A., Paton, J.J., Morrison, S.E., Salzman, C.D., 2007. Expectation modulatesneural responses to pleasant and aversive stimuli in primate amygdala. Neuron 55,970–984.

Blackburn, J.R., Pfaus, J.G., Phillips, A.G., 1992. Dopamine functions in appetitive anddefensive behaviours. Prog. Neurobiol. 39, 247–279.

Blazquez, P.M., Fujii, N., Kojima, J., Graybiel, A.M., 2002. A network representation ofresponse probability in the striatum. Neuron 33, 973–982.

Bourgeais, L., Monconduit, L., Villanueva, L., Bernard, J.F., 2001. Parabrachial internallateral neurons convey nociceptive messages from the deep laminas of the dorsalhorn to the intralaminar thalamus. J. Neurosci. 21, 2159–2165.

1186 L. Levita et al. / NeuroImage 44 (2009) 1178–1187

Breiter, H.C., Etcoff, N.L., Whalen, P.J., Kennedy, W.A., Rauch, S.L., Buckner, R.L., Strauss,M.M., Hyman, S.E., Rosen, B.R., 1996. Response and habituation of the humanamygdala during visual processing of facial expression. Neuron 17, 875–887.

Broderick, P.A., Rahni, D.N., Zhou, Y., 2003. Acute and subacute effects of risperidone andcocaine on accumbens dopamine and serotonin release using in vivo micro-voltammetry on line with open-field behavior. Prog. Neuropsychopharmacol. Biol.Psychiatry 27, 1037–1054.

Cardinal, R.N., Parkinson, J.A., Hall, J., Everitt, B.J., 2002. Emotion and motivation: therole of the amygdala, ventral striatum, and prefrontal cortex. Neurosci. Biobehav.Rev. 26, 321–352.

Cardinal, R.N., Winstanley, C.A., Robbins, T.W., Everitt, B.J., 2004. Limbic corticostriatalsystems and delayed reinforcement. Ann. N. Y. Acad. Sci. 1021, 33–50.

Chandrasekhar, P.V., Capra, C.M., Moore, S., Noussair, C., Berns, G.S., 2008. Neurobio-logical regret and rejoice functions for aversive outcomes. NeuroImage 39,1472–1484.

Christakou, A., Robbins, T.W., Everitt, B.J., 2004. Prefrontal cortical–ventral striatalinteractions involved in affective modulation of attentional performance: implica-tions for corticostriatal circuit function. J. Neurosci. 24, 773–780.

Cooper, J.C., Knutson, B., 2008. Valence and salience contribute to nucleus accumbensactivation. NeuroImage 39, 538–547.

Cox, R., 1996. AFNI: software for analysis and visualization of functional magneticresonance neuroimages. Comput. Biomed. Res. 29, 162–173.

Day, J.J., Carelli, R.M., 2007. The nucleus accumbens and Pavlovian reward learning.Neuroscience 13, 148–159.

Delgado, M.R., Olsson, A., Phelps, E.A., 2006. Extending animal models of fearconditioning to humans. Biol. Psychol. 73, 39–48.

Demos, K.E., Kelley, W.M., Ryan, S.L., Davis, F.C., Whalen, P.J., 2008. Human amygdalasensitivity to the pupil size of others. Cereb. Cortex. doi:10.1093/cercor/bhn034.

Duvernoy, H., 1991. The Human Brain. Springer–Verlag, Vienna.Etkin, A., Klemenhagen, K.C., Dudman, J.T., Rogan, M.T., Hen, R., Kandel, E.R., Hirsch, J.,

2004. Individual differences in trait anxiety predict the response of the basolateralamygdala to unconsciously processed fearful faces. Neuron 44, 1043–1055.

Everitt, B.J., Parkinson, J.A., Olmstead, M.C., Arroyo, M., Robledo, P., Robbins, T.W., 1999.Associative processes in addiction and reward. The role of amygdala–ventral striatalsubsystems. Ann. N. Y. Acad. Sci. 877, 412–438.

Faure, A., Reynolds, S.M., Richard, J.M., Berridge, K.C., 2008. Mesolimbic dopamine indesire and dread: enabling motivation to be generated by localized glutamatedisruptions in nucleus accumbens. J. Neurosci. 28, 7184–7192.

Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A.,Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., Dale, A.M.,2002. Whole brain segmentation: automated labeling of neuroanatomicalstructures in the human brain. Neuron 33, 341–355.

Glover, G.H., Thomason, M.E., 2004. Improved combination of spiral-in/out images forBOLD fMRI. Magn. Reson. Med. 51, 863–868.

Gottfried, J.A., O'Doherty, J., Dolan, R.J., 2002. Appetitive and aversive olfactorylearning in humans studied using event-related functional magnetic resonanceimaging. J. Neurosci. 22, 10829–10837.

Grace, A.A., 2000. Gating of information flow within the limbic system and thepathophysiology of schizophrenia. Brain Res. Brain Res. Rev. 31, 330–341.

Guarraci, F.A., Kapp, B.S., 1999. An electrophysiological characterization of ventraltegmental area dopaminergic neurons during differential Pavlovian fear condition-ing in the awake rabbit. Behav. Brain Res. 99, 169–179.

Haber, S.N., Kim, K.S., Mailly, P., Calzavara, R., 2006. Reward-related cortical inputsdefine a large striatal region in primates that interface with associative corticalconnections, providing a substrate for incentive-based learning. J. Neurosci. 26,8368–8376.

Hall, J., Parkinson, J.A., Connor, T.M., Dickinson, A., Everitt, B.J., 2001. Involvement of thecentral nucleus of the amygdala and nucleus accumbens core in mediatingPavlovian influences on instrumental behaviour. Eur. J. Neurosci. 13, 1984–1992.

Hamann, S., Mao, H., 2002. Positive and negative emotional verbal stimuli elicit activityin the left amygdala. NeuroReport 13, 15–19.

Hamann, S.B., Ely, T.D., Hoffman, J.M., Kilts, C.D., 2002. Ecstasy and agony: activationof the human amygdala in positive and negative emotion. Psychol. Sci. 13,135–141.

Haralambous, T., Westbrook, R.F., 1999. An infusion of bupivacaine into the nucleusaccumbens disrupts the acquisition but not the expression of contextual fearconditioning. Behav. Neurosci. 113, 925–940.

Hare, N., Tottenham, A., Galvan, H., Voss, G., Glover, B., Casey, B., 2008. Biologicalsubstrates of emotional reactivity and regulation in adolescence during anemotional go-nogo task. Biol. Psychiatry 63 (10), 927–934.

Hariri, A.R., Bookheimer, S.Y., Mazziotta, J.C., 2000. Modulating emotional responses:effects of a neocortical network on the limbic system. NeuroReport 11, 43–48.

Hoebel, B.G., Avena, N.M., Rada, P., 2007. Accumbens dopamine–acetylcholine balancein approach and avoidance. Curr. Opin. Pharmacol. 7, 617–627.

Horvitz, J.C., 2000. Mesolimbocortical and nigrostriatal dopamine responses to salientnon-reward events. Neuroscience 96, 651–656.

Horvitz, J.C., 2002. Dopamine gating of glutamatergic sensorimotor and incentivemotivational input signals to the striatum. Behav. Brain Res. 137, 65–74.

Hsu, M.M., Kung, J.C., Shyu, B.C., 2000. Evoked responses of the anterior cingulate cortexto stimulation of the medial thalamus. Chin. J. Physiol. 43, 81–89.

Hunt, M.J., Kessal, K., Garcia, R., 2005. Ketamine induces dopamine-dependentdepression of evoked hippocampal activity in the nucleus accumbens in freelymoving rats. J. Neurosci. 25, 524–531.

Ikemoto, S., Panksepp, J., 1999. The role of nucleus accumbens dopamine in motivatedbehavior: a unifying interpretation with special reference to reward-seeking. BrainRes. Brain Res. Rev. 31, 6–41.

Iordanova, M.D., Westbrook, R.F., Killcross, A.S., 2006. Dopamine activity in the nucleusaccumbens modulates blocking in fear conditioning. Eur. J. Neurosci. 24,3265–3270.

Jackson, M.E., Moghaddam, B., 2001. Amygdala regulation of nucleus accumbensdopamine output is governed by the prefrontal cortex. J. Neurosci. 21, 676–681.

Jensen, J., McIntosh, A.R., Crawley, A.P., Mikulis, D.J., Remington, G., Kapur, S., 2003.Direct activation of the ventral striatum in anticipation of aversive stimuli. Neuron40, 1251–1257.

Kalin, N.H., Shelton, S.E., Fox, A.S., Oakes, T.R., Davidson, R.J., 2005. Brain regionsassociated with the expression and contextual regulation of anxiety in primates.Biol. Psychiatry 58, 796–804.

Kirouac, G.J., Ganguly, P.K., 1995. Topographical organization in the nucleus accumbensof afferents from the basolateral amygdala and efferents to the lateral hypothalamus.Neuroscience 67, 625–630.

Koob, G.F., Wall, T.L., Bloom, F.E., 1989. Nucleus accumbens as a substrate for the aversivestimulus effects of opiate withdrawal. Psychopharmacology (Berl) 98, 530–534.

Laviolette, S.R., 2007. Dopamine modulation of emotional processing in cortical andsubcortical neural circuits: evidence for a final common pathway in schizophrenia?Schizophr. Bull. 33, 971–981.

Levita, L., Dalley, J.W., Robbins, T.W., 2002. Disruption of Pavlovian contextualconditioning by excitotoxic lesions of the nucleus accumbens core. Behav. Neurosci.116, 539–552.

Maeda, H., Morimoto, H., Yanagimoto, K., 1993. Response characteristics ofamygdaloid neurons provoked by emotionally significant environmental stimuliin cats, with special reference to response durations. Can. J. Physiol. Pharmacol.71, 374–378.

Maren, S., 2001. Neurobiology of Pavlovian fear conditioning. Annu. Rev. Neurosci. 24,897–931.

Martinez, G., Ropero, C., Funes, A., Flores, E., Landa, A.I., Gargiulo, P.A., 2002. AP-7 intothe nucleus accumbens disrupts acquisition but does not affect consolidation in apassive avoidance task. Physiol. Behav. 76, 205–212.

Mathias, S., Lubman, D.I., Hides, L., 2008. Substance-induced psychosis: a diagnosticconundrum. J. Clin. Psychiatry 69, 358–367.

Meredith, G.E., 1999. The synaptic framework for chemical signaling in nucleusaccumbens. Ann. N. Y. Acad. Sci. 877, 140–156.

Miczek, K.A., Mutschler, N.H., van Erp, A.M., Blank, A.D., McInerney, S.C., 1999.D-amphetamine “cue” generalizes to social defeat stress: behavioral sensitizationand attenuated accumbens dopamine. Psychopharmacology (Berl) 147, 190–199.

Miller, J.D., Sanghera, M.K., German, D.C., 1981. Mesencephalic dopaminergic unitactivity in the behaviorally conditioned rat. Life Sci. 29, 1255–1263.

Morris, J.S., Buchel, C., Dolan, R.J., 2001. Parallel neural responses in amygdalasubregions and sensory cortex during implicit fear conditioning. NeuroImage 13,1044–1052.

Nauta, W.J., 1982. Limbic innervation of the striatum. Adv. Neurol. 35, 41–47.Pandya, D.N., 1995. Anatomy of the auditory cortex. Rev. Neurol. (Paris) 151, 486–494.Parkinson, J., Robbins, T., Everitt, B., 1999. Selective excitotoxic lesions of the nucleus

accumbens core and shell differentially affect aversive Pavlovian conditioning todiscrete and contextual cues. Psychobiology 27, 256–266.

Paton, J.J., Belova, M.A., Morrison, S.E., Salzman, C.D., 2006. The primate amygdalarepresents the positive and negative value of visual stimuli during learning. Nature439, 865–870.

Phelps, E.A., Delgado, M.R., Nearing, K.I., LeDoux, J.E., 2004. Extinction learning inhumans: role of the amygdala and vmPFC. Neuron 43, 897–905.

Phelps, E.A., LeDoux, J.E., 2005. Contributions of the amygdala to emotion processing:from animal models to human behavior. Neuron 48, 175–187.

Phelps, E.A., O'Connor, K.J., Gatenby, J.C., Gore, J.C., Grillon, C., Davis, M., 2001. Activationof the left amygdala to a cognitive representation of fear. Nat. Neurosci. 4, 437–441.

Rasmussen, K., Strecker, R.E., Jacobs, B.L., 1986. Single unit response of noradrenergic,serotonergic and dopaminergic neurons in freely moving cats to simple sensorystimuli. Brain Res. 369, 336–340.

Ravel, S., Legallet, E., Apicella, P., 1999. Tonically active neurons in the monkey striatumdo not preferentially respond to appetitive stimuli. Exp. Brain Res. 128, 531–534.

Raven, M.A., Necessary, B.D., Danluck, D.A., Ettenberg, A., 2000. Comparison of thereinforcing and anxiogenic effects of intravenous cocaine and cocaethylene. Exp.Clin. Psychopharmacol. 8, 117–124.

Reynolds, S.M., Berridge, K.C., 2001. Fear and feeding in the nucleus accumbens shell:rostrocaudal segregation of GABA-elicited defensive behavior versus eatingbehavior. J. Neurosci. 21, 3261–3270.

Reynolds, S.M., Berridge, K.C., 2002. Positive and negative motivation in nucleusaccumbens shell: bivalent rostrocaudal gradients for GABA-elicited eating, tasteqlikingq/qdislikingq reactions, place preference/avoidance, and fear. J. Neurosci. 22,7308–7320.

Roitman, M.F., Wheeler, R.A., Carelli, R.M., 2005. Nucleus accumbens neurons areinnately tuned for rewarding and aversive taste stimuli, encode their predictors,and are linked to motor output. Neuron 45, 587–597.

Salamone, J.D., Correa, M., Mingote, S.M., Weber, S.M., 2005. Beyond the rewardhypothesis: alternative functions of nucleus accumbens dopamine. Curr. Opin.Pharmacol. 5, 34–41.

Salamone, J.D., Cousins, M.S., Snyder, B.J., 1997. Behavioral functions of nucleusaccumbens dopamine: empirical and conceptual problems with the anhedoniahypothesis. Neurosci. Biobehav. Rev. 21, 341–359.

Salzman, C.D., Paton, J.J., Belova, M.A., Morrison, S.E., 2007. Flexible neural representa-tions of value in the primate brain. Ann. N. Y. Acad. Sci. 1121, 336–354.

Schultz, W., 1997. Dopamine neurons and their role in reward mechanisms. Curr. Opin.Neurobiol. 7, 191–197.

Schwienbacher, I., Fendt, M., Richardson, R., Schnitzler, H.U., 2004. Temporary

1187L. Levita et al. / NeuroImage 44 (2009) 1178–1187

inactivation of the nucleus accumbens disrupts acquisition and expression of fear-potentiated startle in rats. Brain Res. 1027, 87–93.

Setlow, B., Holland, P.C., Gallagher, M., 2002. Disconnection of the basolateral amygdalacomplex and nucleus accumbens impairs appetitive Pavlovian second-orderconditioned responses. Behav. Neurosci. 116, 267–275.

Setlow, B., Schoenbaum, G., Gallagher, M., 2003. Neural encoding in ventral striatumduring olfactory discrimination learning. Neuron 38, 625–636.

Spielberger, C., 1983. Manual for the State-Trait Anxiety Inventory (STAI). ConsultingPsychologists Press, Palo Alto, CA.

Stein, M.B., Simmons, A.N., Feinstein, J.S., Paulus, M.P., 2007. Increased amygdala andinsula activation during emotion processing in anxiety-prone subjects. Am. J.Psychiatry 164, 318–327.

Straube, T., Mentzel, H.J., Miltner, W.H., 2007. Waiting for spiders: brain activationduring anticipatory anxiety in spider phobics. NeuroImage 37, 1427–1436.

Sturm, V., Lenartz, D., Koulousakis, A., Treuer, H., Herholz, K., Klein, J.C., Klosterkotter, J.,2003. The nucleus accumbens: a target for deep brain stimulation in obsessive–compulsive- and anxiety-disorders. J. Chem. Neuroanat. 26, 293–299.

Talairach, J., Tournoux, P., 1988. Co-planar Stereotaxic Atlas of the Human Brain. Thieme,New York.

Ungless, M.A., Magill, P.J., Bolam, J.P., 2004. Uniform inhibition of dopamine neurons inthe ventral tegmental area by aversive stimuli. Science 303, 2040–2042.

Vogt, B.A., 2005. Pain and emotion interactions in subregions of the cingulate gyrus. Nat.Rev. Neurosci. 6, 533–544.

Wadenberg, M.L., Ericson, E., Magnusson, O., Ahlenius, S., 1990. Suppression of

conditioned avoidance behavior by the local application of (−)sulpiride into theventral, but not the dorsal, striatum of the rat. Biol. Psychiatry 28, 297–307.

Westbrook, R.F., Good, A.J., Kiernan,M.J.,1997.Microinjection ofmorphine into thenucleusaccumbens impairs contextual learning in rats. Behav. Neurosci. 111, 996–1013.

Whalen, P.J., Bush, G., McNally, R.J., Wilhelm, S., McInerney, S.C., Jenike, M.A., Rauch, S.L.,1998. The emotional counting Stroop paradigm: a functional magnetic resonanceimaging probe of the anterior cingulate affective division. Biol. Psychiatry 44,1219–1228.

Wheeler, R.A., Twining, R.C., Jones, J.L., Slater, J.M., Grigson, P.S., Carelli, R.M., 2008.Behavioral and electrophysiological indices of negative affect predict cocaine self-administration. Neuron 57, 774–785.

Williams, G.V., Rolls, E.T., Leonard, C.M., Stern, C., 1993. Neuronal responses in theventral striatum of the behaving macaque. Behav. Brain Res. 55, 243–252.

Wilson, D.I., Bowman, E.M., 2005. Rat nucleus accumbens neurons predominantlyrespond to the outcome-related properties of conditioned stimuli rather than theirbehavioral-switching properties. J. Neurophysiol. 94, 49–61.

Yanagimoto, K., Maeda, H., 2003. The nucleus accumbens unit activities related to theemotional significance of complex environmental stimuli in freely moving cats.Neurosci. Res. 46, 183–189.

Zahm, D.S., Heimer, L., 1993. Specificity in the efferent projections of the nucleusaccumbens in the rat: comparison of the rostral pole projection patterns with thoseof the core and shell. J. Comp. Neurol. 327, 220–232.

Zink, C.F., Pagnoni, G., Chappelow, J., Martin-Skurski, M., Berns, G.S., 2006. Humanstriatal activation reflects degree of stimulus saliency. NeuroImage 29, 977–983.