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Biological Psychiatry

Incentive Processing in Persistent Disruptive Behavior and Psychopathic Traits: A Functional Magnetic Resonance Imaging Study in Adolescents Moran D. Cohn, Dick J. Veltman, Louise E. Pape, Koen van Lith, Robert R.J.M. Vermeiren, Wim van den Brink, Theo A.H. Doreleijers, and Arne Popma ABSTRACT BACKGROUND: Children with early-onset disruptive behavior disorder (DBD), especially those with callousunemotional traits, are at risk of developing persistent and severe adult antisocial behavior. One possible underlying mechanism for persistence is deficient reward and loss sensitivity, i.e., deficient incentive processing. However, little is known about the relation between deficient incentive processing and persistence of antisocial behavior into adulthood or its relation with callous-unemotional and other psychopathic traits. In this study, we investigate the relationship between the neural correlates of incentive processing and both DBD persistence and psychopathic traits. METHODS: In a sample of 128 adolescents (mean age 17.7) with a history of criminal offending before age 12, functional magnetic resonance imaging was performed during a monetary incentive delay task designed to assess neural responses during incentive processing. Neural activation during incentive processing was then associated with DBD persistence and psychopathic traits, measured with the Youth Psychopathic Traits Inventory. RESULTS: Compared with both healthy control subjects and youths who had desisted from DBD, persistent DBD subjects showed lower neural responses in the ventral striatum during reward outcomes and higher neural responses in the amygdala during loss outcomes. Callous-unemotional traits were related to lower neural responses in the amygdala during reward outcomes, while other psychopathic traits were not related to incentive processing. CONCLUSIONS: In the current study, aberrant incentive processing is related to persistence of childhood antisocial behavior into late adolescence and to callous-unemotional traits. This mechanism may underlie treatment resistance in a subgroup of antisocial youth and provide a target for intervention. Keywords: Antisocial behavior, Callous-unemotional, fMRI, Persistence, Psychopathy, Reward http://dx.doi.org/10.1016/j.biopsych.2014.08.017

Juvenile antisocial behavior, clinically diagnosed as a disruptive behavior disorder ([DBD], i.e., oppositional defiant disorder [ODD] or conduct disorder [CD]), causes serious personal and societal harm and is associated with substantial economic costs (1). Importantly, early onset of juvenile antisocial behavior is a potent risk factor for the persistence of such behavior into adulthood (2). General population studies in children strongly suggest that the presence of psychopathic traits (i.e., callous-unemotional traits, grandiose-manipulative traits, and impulsive-irresponsible traits) and more specifically callous-unemotional traits also increase the risk of persistent antisocial behavior [for review, see (3)].1 Notably, these traits 1

While the authors acknowledge the concerns of some scholars that the measurement (48) and the interpretation (52) of psychopathic traits in minors cannot be seamlessly equated with the adult construct of psychopathy, these traits will be referred to as psychopathic traits throughout this article for reasons of brevity and consistency with the

have been added to the DSM-5 as a specifier for conduct disorder under the label of limited prosocial emotions. However, it is largely unknown whether these traits also predict persistence of antisocial behavior in specific samples such as early-onset offenders.

(footnote continued) research field. Notably, psychopathic traits are not a unitary construct but consist of several dimensions with distinct behavioral and neural correlates. While studies in the past have often employed two-factor solutions for psychopathic traits [i.e., affective-interpersonal versus impulsive-antisocial (53)], more recent studies use operationalizations based on three-factor solutions [i.e., affective (callous-unemotional), interpersonal (grandiose-manipulative), and impulsive (impulsive-irresponsible) (54)] or four-factor solutions [i.e., affective, interpersonal, impulsive, antisocial (55)]. In the current study, we employ the threefactor model because it seems to be most consistent with the DSM-5 perspective of limited prosocial emotions as a specifier to conduct disorder.

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Moreover, it is unknown what the underlying neurocognitive mechanisms of persistence and psychopathic traits are in such populations, information that is essential for the development of early prevention and treatment strategies. Most animal and human behaviors, as well as adaptive changes in behavior, are evolutionarily driven by a motivation to achieve reward and avoid punishment (4). As such, one may hypothesize that developmental processes leading to maladaptive persistent antisocial behavior are associated with aberrant sensitivity to positive or negative reinforcers (i.e., incentive processing). Aberrant incentive processing, i.e., excessive or reduced sensitivity to reward, loss, or cues associated with these outcomes, has been associated with a broad range of behavioral problems (5), including pervasive patterns of antisocial behavior during childhood (6), adolescence (7), and adulthood (8). Moreover, aberrant neural responses during incentive processing have been reported in antisocial juveniles and adults (7,9–12). While neuropsychological studies have provided a neurocognitive framework implicating both hyposensitivity to loss and hypersensitivity to reward in antisocial juveniles (13), the neuroimaging literature is not entirely consistent with this framework [for a review, see (14)], suggesting that other neural mechanisms may also be involved. In addition, this inconsistency may result from sample differences and neurobiological heterogeneity within the population of antisocial juveniles. These latter issues can be addressed by taking into account longitudinal (15) and cross-sectional (16) markers of heterogeneity, i.e., by characterizing antisocial youth in terms of distinct developmental profiles (i.e., persisters versus desisters) or phenotypical differences (i.e., psychopathic traits), respectively. Regarding the latter, psychopathic traits are characterized by a continuous distribution (17), continuous criterion validity (18), and neurobiological specificity (19). Moreover, they have been associated with neuropsychological measures of reward dominance (20). Most functional magnetic resonance imaging (fMRI) studies in children with high levels of psychopathic traits, however, focused on the processing of fear and emotional pictures. Although these studies provide clear evidence for reduced amygdala responsivity in such paradigms [e.g., (19,21–23)], they do not allow conclusions about incentive processing. The only studies on the relation between psychopathic traits and neural responses during incentive processing have focused on ventral striatum (VS) responsiveness in healthy adults and reported atypical responses during reward processing (24–26) in relation to impulsive-antisocial traits. It is unknown, however, if these findings generalize to antisocial youths and if such effects can also be observed in other key incentive processing regions (27,28), such as the amygdala and medial prefrontal cortex (mPFC), which have been implicated in decision-making deficits observed in antisocial and psychopathic development (29–31). The current study has three main objectives: 1) to investigate if early-onset antisocial youths with persistent DBD differ from those who desist from DBD and from healthy control subjects with respect to neural responses in the ventral striatum, amygdala, and mPFC during incentive processing; 2) to ascertain that associations between these neural responses and persistence indeed pertain to stable patterns of dysfunction, rather than to current DBD severity, by assessing their

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association with current DBD symptoms; and 3) to investigate the association between these neural responses and psychopathic traits. We performed an fMRI study in a large group of childhood arrestees (i.e., first offense before age 12) followed up until late adolescence using a well-established incentive processing paradigm, i.e., the monetary incentive delay (MID) paradigm (32). Given the inconsistency of previous fMRI studies on incentive processing in antisocial juveniles but consistent theoretical accounts on the relevance of the VS, mPFC, and amygdala for dysfunctional decision making in antisocial development (30,31), we hypothesized that in all these regions, reduced neural responses during reward feedback (7,10,11,33) and higher responses during loss feedback (7,33,34) would uniquely characterize the DBD persister subgroup, as compared with desisters and control subjects, but would be less strongly associated with current DBD severity. We also hypothesized that impulsive-irresponsible traits would be related to lower neural responses during reward anticipation (24) and reward feedback (26), whereas callousunemotional traits would be related to higher neural responses during reward feedback (26).

METHODS AND MATERIALS Participants Participants were recruited from a Dutch cohort of 364 adolescents who had become known to local police services before the age of criminal responsibility (12 years) for a range of acts that would be prosecutable above the age of 12 (e.g., petty theft, arson, vandalism, trespassing, burglary, assault, sexual abuse, and robbery), excluding status offences.2 This longitudinal study had three previous data collection waves (35): mean age at study entrance was 10.9 (SD 1.4) years and 13.1 (SD 1.5) years at wave 3. For the current neuroimaging study (wave 4; mean age 17.7 [SD 1.6] years), a subsample (total n 5 150) representing the entire severity range was recruited, including those at low, medium, and high risk for antisocial development (see Supplement 1 for recruitment strategy) and partly overlapping with our previously published fear conditioning study (36). For the current report, 22 out of the original 150 participants were excluded from analyses because of invalid (i.e., with movement artifacts or poor coverage) or missing MRI data (n 5 10), drug use in last 24 hours before scanning (n 5 3), or task performance rates deviating more than 3 SD from the mean (n 5 9). The excluded group did not differ from the study sample (n 5 128) with respect to current and previous aggression or psychopathic traits scores, DBD diagnosis, age, IQ, gender, ethnicity, or socioeconomic status (all p . .1). To answer our first research question, i.e., how do DBDpersisters (DBD-p) differ from DBD-desisters (DBD-d) and healthy control subjects (HC), these subgroups were defined as follows (see flow chart in Figure S1 in Supplement 1): 1) DBD-p (n 5 22): participants meeting full criteria of DBD on the National Institute of Mental Health Diagnostic Interview Schedule for Children version IV in any of the previous waves 2

Status offenses are acts that are punishable only in minor populations, e.g., running away from home and truancy.

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and with a current DBD diagnosis at wave 4 (10 [45.5%] of 22 participants with current CD and 12 [54.5%] of 22 participants with current ODD); 2) DBD-d (n 5 23): participants meeting criteria of DBD in any of the previous waves but without a current DBD diagnosis at wave 4; and 3) matched HC (n 5 23): selected from the same cohort and meeting the following criteria: 1) no diagnosis of DBD during any of the previous waves; 2) below median aggression scores on the Reactive and Proactive aggression Questionnaire (37) in the current wave; 3) below median psychopathic traits scores on the Youth Psychopathic Traits Inventory (YPI) (38) in the current wave; and 4) no history of any other psychiatric condition (DSM-IV Axis 1 or Axis 2). The remainder of the recruited sample (n 5 60) was not included in the group-wise comparison but was included in the dimensional analysis to cover the full spectrum of disruptive symptoms and psychopathic traits (n 5 128) to answer our second and third research questions, i.e., whether DBD symptoms and psychopathic traits are associated with neural responses during incentive processing.

Procedure This study was approved by the Institutional Review Board of the VU University Medical Center Amsterdam. All participants (and their parents/custodians if age of the participant was below 18) signed informed consent and were visited at home for behavioral testing. On a second occasion, participants were scanned using a Philips 3T Intera MRI scanner (Philips Healthcare, Best, The Netherlands) at the Academic Medical Center Amsterdam, generally within 1.5 months after the behavioral session with few exceptions where the scan was performed after 2 months. Both the parent and youth versions of the National Institute of Mental Health Diagnostic Interview Schedule for Children version IV (39) were used to assess criteria for DSM-IV ODD and CD. A diagnosis of ODD and/or CD was made if children met DSM-IV diagnostic criteria according to either the parent or youth report. We defined desistence as not meeting the DSM-IV criteria during the past given time period for any of these disorders. The YPI (38) is a 50-item self-report instrument for assessment of psychopathic traits in juvenile community samples. To ensure that all participants would understand the questions, the Dutch child version of the YPI was used (40). See Supplement 1 for complete assessment details.

fMRI Task All participants performed a monetary incentive delay task, adapted from Knutson et al. (32), to assess both anticipation and feedback phases of reward and loss processing unbiased by performance or success rate. The task consisted of 24 reward trials, 24 loss trials, and 24 neutral trials in random order. During each trial, participants were shown a geometric shape cue to signal trial type (circles for reward, squares for loss, and triangles for neutral trials; 2000 msec), followed by a fixation-crosshair (variable interval: 2000–2500 msec) and then a white square target to which participants were supposed to respond by pressing a button during its presentation. The target duration time was adapted throughout the task based on the success rate, such that participants would succeed on approximately 66% of the trials. After a jittered delay (700–

2100 msec), participants received feedback (1920 msec) notifying them about their present trial and total score, followed by an intertrial interval of 4000 milliseconds. On reward trials, participants could win €.50 when pressing in time but never lost money when failing to do so. Conversely, loss cues signaled that participants could prevent losing money by successful button press or lose €.50 upon failure. Finally, neutral trials resulted in €.00, irrespective of performance. Participants completed a full run of the MID task before entering the scanner to ensure correct explicit knowledge about the cues and prevent training-related differences during the MRI scan. Participants were rewarded with the monetary outcome of the experiment after the MRI in addition to their financial remuneration for participation in the study.

fMRI Protocol First, T1-weighted anatomical scans, consisting of 180 sagittal 1-mm thickness slices with an in-plane resolution of 1 3 1 mm (field of view 256 3 256 mm, repetition time 9.0 msec, echo time 3.5 msec), were acquired using an 8-channel SENSE head coil (Philips Healthcare). Furthermore, 400 T2* weighted echo-planar images were acquired during the MID task, each volume consisting of 38 ascending slices of 3 mm thickness and 2.29 3 2.29 in-plane resolution, parallel to the anterior commissure-posterior commissure line (field of view 220 3 220 mm, repetition time 2300 msec, echo time 30 msec).

Statistical Analysis Functional MRI data were processed using SPM8 (FIL Methods group (http://www.fil.ion.ucl.ac.uk/spm/; University College London, London, United Kingdom). Preprocessing included realignment, unwarping, slice-time correction to the middle slice, normalization to Montreal Neurological Institute space based on the segmented anatomical scan, and 8 mm full-width at half maximum smoothing. First-level models included separate regressors for each trial type, i.e., anticipation period (up to target), target, and feedback period. Next, contrast images were computed to assess reward anticipation (reward trial anticipation . neutral trial anticipation), loss anticipation (loss trial anticipation . neutral trial anticipation), reward feedback (reward trial hit . reward trial miss), and loss feedback (loss trial miss . loss trial hit), similar to other studies using the MID task (32). These contrast images were entered into second-level analyses for betweengroup comparisons. Analyses were conducted using wholebrain multiple comparison correction, as well as small volume correction (SVC) in a priori regions of interest (ROI), at a stringent family-wise error (FWE) p , .026 [5.05/k^ (1 2 r), with k 5 number of ROIs and r 5 their mean correlation, i.e., adjusted Bonferroni correction for multiple correlated ROIs (41)]. For exploratory purposes and to avoid type II errors, we additionally reported all results significant at pFWE , .05. To reliably assess activation effects in the amygdala and VS, we used a 10 mm radius sphere centered on their peak coordinates in a meta-analysis of incentive processing neuroimaging studies (amygdala: x 5 626, y 5 0, z 5 216; VS right: x 5 12, y 5 10, z 5 26; VS left: x 5 210, y 5 8, z 5 24)

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(28). Furthermore, we used a study-specific functional mPFC ROI, defined as the reward feedback one-sample t test cluster, thresholded at pFWE , .01 (4780 mm3), which was similar to previous reports regarding mPFC involvement during the reward feedback condition of the MID task [e.g., (27)]. Second-level analyses were conducted to assess whether DBD-persisters showed aberrant incentive processing, as compared with both other groups, using an a priori t contrast, i.e., (DBD-p vs. [DBD-d and HC]). Additionally, post hoc analyses were performed, comparing the DBD-p group with the other groups individually (DBD-p vs. DBD-d; DBD-p vs. HC) and testing whether DBD-d differed from HC. Multiple regression was used to evaluate the associations of DBD symptoms and psychopathic traits (i.e., callous-unemotional traits, grandiose-manipulative traits, and impulsive-irresponsible traits) with neural responses during incentive processing, using the total sample (except for one participant without YPI data; yielding n 5 127).

RESULTS Clinical Characteristics Subgroups were similar with respect to sociodemographic variables (Table 1; all p $ .31). In addition, all groups showed a similarly low mean IQ (86–92; p 5 .38). DBD-desisters and DBD-persisters scored higher on aggression, psychopathic traits, and internalizing and externalizing problems than healthy control subjects, whereas according to parent reports the DBD-p group was currently more troubled than both other groups.

Task Performance Participants won an average of €2.60 (SD 1.20) during the MID task and were successful on 61% (SD 5%) of the trials, with no effect of trial type (F2,378 5 .1, p 5 .9; see Table 1 for complete performance details). Mean reaction time was shorter for reward and loss trials compared with neutral trials (Welch F2,246 5 26.5, p , .001). DBD-p, DBD-d, and HC did not differ in total earnings or overall or incentivized reaction time (all p . .15). However, DBD-p were slower than DBD-d on neutral trials (F2,65 5 3.2, p 5 .047), while DBD-d had lower mean success rates than HC (F2,65 5 3.6, p 5 .032). Similarly, callous-unemotional and impulsive-irresponsible traits were unrelated to reaction time (r 5 2.00, p 5 .99; r 5 .03; p 5 .74) or earnings (r 5 2.13, p 5 .16; r 5 2.12; p 5 .17) but were both inversely correlated with success rates (r 5 2.20, p 5 .025; r 5 2.19, p 5 .030) due to higher nonresponding rates to targets (r 5 .37, p , .001; r 5 .29, p 5 .001). Grandiose-manipulative traits were unrelated to reaction time (r 5 2.04, p 5 .63), performance (r 5 2.12, p 5 .18), and outcome (r 5 2.08, p 5 .40).

Neural Responses to Incentive Processing We found robust main effects during all phases of incentive processing, including the expected activation in the limbic and frontostriatal neurocircuitry (Table S1 and Figure S2 in Supplement 1).

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Incentive Processing in Relation to Persistence Persistence was unrelated to neural responses during the anticipation phase of incentive processing but was associated with aberrant neural responses during the feedback phase. More specifically, when compared with both other groups, DBD-p youths showed lower responses to reward-feedback (reward hit . miss-contrast) in the right ventral striatum cluster (pFWE , .026; Figure 1), localized ventral to the nucleus accumbens, and higher responses during loss-feedback (loss miss . hit-contrast) in the right amygdala (Figure 2; Table 2). Post hoc analyses confirmed that these results were specific to the persister group, i.e., two-sample t tests for DBD-p versus DBD-d and DBD-p versus HC showed similar significant differences, whereas differences between DBD-d and HC were not significant.

Incentive Processing in Relation to DBD Symptoms and Psychopathic Traits Next, we performed regression analyses to assess the relation of current DBD symptoms and dimensions of psychopathic traits with neural responses during incentive processing. DBD symptoms were not significantly associated with neural responses during incentive processing, but nonsignificant effects were observed in the same direction as in the groupwise comparisons (i.e., lower VS responses during reward feedback: t126 5 23.0; pFWE-small volume correction 5 .056 at [10 6 214]; and higher amygdala responses during loss feedback: t126 5 2.5; pFWE-SVC 5 .14 at [18 0 222]). While Bonferroni-corrected analyses yielded no significant associations between psychopathic traits and incentive processing, callous-unemotional traits were related to lower neural responses in the left amygdala during reward feedback (hit . miss-contrast; Table 2) at a less conservative threshold (pFWE ,.05), whereas grandiose-manipulative and impulsiveirresponsible traits were not significantly related to neural responses during incentive processing.

Post Hoc Analyses The results of these analyses were not confounded by task performance, comorbid mental health problems, or substance use frequency (i.e., tobacco, alcohol, or cannabis use); were not due to outliers; and were similar in persisters with additional high levels of callous-unemotional traits. Including baseline DBD symptoms as a covariate in the persistence analysis reduced results to trend-level significance. Controlling for movement did not alter the significance of the reported findings for DBD subgroup analyses and rendered the association between callous-unemotional traits and lower amygdala responses during gain feedback significant at pFWE-SVC , .026. Additionally, there were trends toward significant associations between callous-unemotional traits and lower ventral striatum and amygdala responses during gain anticipation and higher ventral striatum responses during loss feedback (pFWE-SVC , .05; see Supplement 1 for full details).

DISCUSSION This study investigated the relationships of neural responses during incentive processing with persistence of early-onset

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Table 1. Clinical Characteristics and Performance of Subgroups Characteristics

DBD-p (n 5 22)

DBD-d (n 5 23)

HC (n 5 23)

Other (n 5 60)

Total (n 5 128)

Between-Group Differences (DBD-p vs. DBD-d vs. HC)

Clinical Characteristics Fisher’s exact1 p 5 .49

Male gender, number (%)

16 (73%)

18 (78%)

20 (87%)

55 (92%)

108 (85%)

Low SES neighborhood, number (%)

12 (57%)

13 (57%)

13 (57%)

31 (53%)

69 (54%)

Fisher’s exact1 p 5 1

33 (26%)

Fisher’s exact4 p 5 .59

Non-western ethnicity, number (%)a Age, mean (SD), years

7 (32%)

4 (17%)

9 (39%)

17.9 (1.6)

17.7 (1.6)

F2,65 5 1.4, p 5 .24

17.3 (1.9)

DBD age of onset, mean (SD), years

5.7 (2.7)

5.8 (3.4)

–

–

5.7 (3.0)

t30 5 .09, p 5 .93

Baseline DBD symptoms, mean (SD)

6.9 (3.3)

5.7 (2.2)

1.0 (1.1)

1.0 (1.2)

3.0 (3.2)

Welch2;36.2 5 63.1, p , .001b,c

IQ, nean (SD)

17.9 (1.1)

14 (23%)

17.1 (1.4)

F2,60 5 1.0, p 5 .41

86 (14)

90 (16)

92 (13)

92 (14)

91 (14)

RPQ aggression, mean (SD)

17.1 (8.8)

12.3 (7.3)

4.5 (2.7)

11.2 (5.5)

11.1 (7.1)

Welch2;32.2 5 28.1, p , .001b,c

CBCL internalizing, mean (SD)

61.5 (5.2)

53.7 (12.6)

45.2 (10.0)

49.1 (9.7)

51.3 (11.0)

Welch2;36.6 5 24.2, p , .001c,d

YSR internalizing, mean (SD)

54.1 (8.9)

48.5 (10.4)

39.5 (8.4)

48.2 (8.4)

47.6 (9.8)

F2,65 5 13.9, p , .001b,c

CBCL externalizing, mean (SD)

66.9 (5.8)

57.7 (9.1)

42.2 (6.2)

48.9 (9.3)

52.2 (11.5)

Welch2;39.8 5 93.2, p , .001b,c,d

YSR externalizing, mean (SD)

60.0 (11.1)

55.8 (8.7)

43.3 (5.7)

52.5 (7.9)

52.7 (9.7)

Welch2;38.6 5 28.5, p , .001b,c

ADHD, number (%)

15 (68%)

–

17 (28%)

43 (34%)

DBD, number (%)

22 (100%)

–

–

10 (17%)

32 (25%)

Fisher’s exact1 p , .001b,c

CD, number (%)

10 (46%)

–

–

5 (8%)

15 (12%)

Fisher’s exact1 p # .001b,c

Tobacco use frequency, mean (SD), cigarettes/day

7.6 (8.6)

4.1 (5.7)

3.1 (6.0)

5.9 (7.3)

5.4 (7.1)

Welch2;41.9 5 2.0, p 5 .15

Alcohol use frequency, mean (SD), days/month

3.0 (3.4)

3.4 (5.3)

3.8 (4.2)

4.6 (5.4)

4.0 (4.8)

F2,65 5 .2, p 5 .83

12 (52%)

Fisher’s exact2 p , .001b,c

5 (23%)

4 (19%)

23 (38%)

37 (29%)

Fisher’s exact4 p 5 .98

Cannabis use frequency, mean (SD), days/month

4.9 (9.2)

.1 (.6)

.3 (1.0)

3.1 (7.7)

2.4 (6.7)

Welch2;35.6 5 3.1, p 5 .057

YPI callous-unemotional, mean (SD)

27.4 (10.0)

24.7 (7.6)

20.9 (4.2)

24.4 (6.6)

24.3 (7.3)

Welch2;36.6 5.0, p 5 .012c

YPI grandiose-manipulative, mean (SD)

32.8 (10.1)

33.1 (10.0)

23.3 (2.9)

30.4 (7.5)

30.0 (8.5)

Welch2;31.9 17.3, p , .001b,c

YPI impulsive-irresponsible, mean (SD)

33.0 (7.0)

29.4 (8.7)

21.0 (5.6)

29.1 (6.9)

28.3 (7.9)

Welch2;41.1 20.8, p , .001b,c

YPI total psychopathic traits, mean (SD)

93.2 (23.3)

87.1 (22.8)

65.2 (8.9)

83.8 (16.0)

82.6 (19.7)

Welch2;34.3 19.8, p , .001b,c

Weekly binge drinking (.6 AU), number (%)

5 (24%)

Performance Total earnings, mean (SD), €

2.9 (1.0)

2.3 (1.3)

2.6 (.9)

2.6 (1.4)

2.6 (1.2)

F2,65 2.0, p 5 .15

Reaction time, mean (SD), msec

278 (40)

264 (40)

287 (48)

280 (39)

278 (41)

F2,65 1.6, p 5 .22

Neutral trial reaction time, mean (SD), msec

326 (75)

280 (52)

305 (56)

312 (62)

307 (63)

F2,65 5 3.2, p 5 .047d

Reward trial reaction time, mean (SD), msec

266 (43)

259 (49)

263 (45)

257 (38)

260 (42)

F2,65 5 .1, p 5 .88

Loss trial reaction time, mean (SD), msec

268 (44)

254 (37)

267 (39)

271 (54)

267 (47)

F2,65 5 .8, p 5 .45

Success rate, mean (SD), %

63 (4.2)

59 (5.2)

60 (4.0)

61 (5)

61 (4.8)

F2,65 3.6, p 5 .032

Scan-to-Scan translation, mean (SD), mm

.09 (.04)

.12 (.07)

.18 (.23)

.10 (.06)

.12 (.11)

Welch2;34.2 2.9, p 5 .069

Scan-to-Scan rotation, mean (SD), degree

.08 (.04)

.13 (.09)

.16 (.17)

.09 (.06)

.11 (.09)

Welch2;35.2 3.6, p 5 .037

ADHD, attention-deficit/hyperactivity disorder; AU, arbitrary units; CBCL, Child Behavior Checklist; CD, conduct disorder; DBD, disruptive behavior disorder; DBD-d, desistent DBD subgroup; DBD-p, persistent DBD subgroup; HC, healthy control subjects; RPQ, Reactive Proactive Aggression Questionnaire; SES, socioeconomic status; YPI, Youth Psychopathic Traits Inventory; YSR, Youth Self-Report. a Ethnicity was coded as the country of origin of the participant or parents and was subdivided in Dutch, Western (i.e., other European/North American countries) and non-Western (all other countries). b Significant difference between HC and desisters. c HC versus persisters. d Desisters versus persisters.

antisocial behavior into late adolescence and with psychopathic traits in late adolescence. First, persistence of DBD was associated with lower responses in the ventral striatum during reward feedback and with higher amygdala responses during loss feedback. Second, at a less conservative threshold (i.e., at a typical pFWE , .05), callous-unemotional traits were associated with lower amygdala responses during reward feedback, whereas no associations were found between current DBD symptoms or the other psychopathic traits and neural responses during incentive processing. These findings

suggest a mechanism for the treatment resistance of subgroups of these youth, as well as a potential target for treatment, which may, in turn, optimize sensitivity to behavioral interventions. To our knowledge, this is the first study showing differential neural responses between persistent and desistent subgroups of early-onset antisocial juveniles. While we previously reported higher neural activity during fear conditioning in persistent DBD youths as compared with healthy control subjects, this pattern did not differ between persisters and

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Neural responses during reward feedback in DBD subgroups (y = 6) Healthy controls

DBD desisters

DBD persisters

Ventral striatum responses during reward feedback in DBD subgroups

DBD persisters versus DBD desisters and healthy controls 1

Signal change in [12 6 -14] (%)

0.8

0.6

0.4

HC DBD-d

0.2

DBD-p

0

-0.2

-0.4

Figure 1. Neural responses during reward feedback in disruptive behavior disorder (DBD) subgroups. Statistical parametric maps overlaid on an anatomical template, depicting in the upper frames: main task effects during reward feedback in healthy control subjects (HC) (A), DBD desisters (DBD-d) (B), and DBD persisters (DBD-p) (C). In the lower frames, the statistical parametric map for the contrast [DBD-p , (DBD-d and HC)] is displayed (D), accompanied by a bar graph depicting the mean percent signal change during reward feedback in each subgroup in the peak voxel for this contrast (E).

desisters from the same sample (36). In the current study, incentive processing deficits were uniquely related to DBD persistence. Importantly, we found evidence for deficits in processing both reward and loss outcomes. While neuropsychological studies have not been conclusive on the role of reward processing deficits (i.e., versus punishment processing deficits) in the reward-dominance of antisocial youths [for review, see (14)], our study suggests that such reward processing atypicalities do exist. Cognitive interpretations of these findings are somewhat speculative given the nature of the paradigm employed in the current study, but we feel that several theories should be considered. First, lower responses in the ventral striatum in these youth, compared with control subjects, may signal lower rewardingness of outcomes, which may, in turn, give rise to reward-seeking behavior to achieve satisfying homeostatic levels of reward. A similar theory has been put forward by Zuckerman and Neeb (42), although they hypothesized that it would be aversively low levels of basal

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arousal, rather than phasic reward valuation, that would lead to compensatory sensation seeking. Alternatively, these findings may be interpreted in the light of the theory of Sagvolden et al. (43) (in the context of attention-deficit/hyperactivity disorder, which was prevalent in 68% of DBD persisters but did not explain the current findings; see Supplement 1), stating that dopaminergic underresponding during reward may delay the association of reward and contingent behavior. This suggestion carries relevance, as it suggests that restoring dopamine levels could normalize the apparent inability of DBD persisters to profit from typical conditioning efforts. Indeed, it has been shown that treatment resistance to behavior therapy in children with DBD and high levels of callous-unemotional traits is not present when they additionally receive methylphenidate (44), warranting investigation of its effect on brain function during reward processing in these youth. While our finding of amygdala hyperreactivity during loss outcome in DBD persisters seems to contradict previous findings of amygdala hyporeactivity in youths with DBD

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Neural responses during loss feedback in DBD subgroups (y = 0) Healthy controls

DBD desisters

DBD persistersA.

Amygdala responses during loss feedback in DBD subgroups

DBD persisters versus DBD desisters and healthy controls 0.8

Signal change in [18 0 -22] (%)

0.6

0.4

0.2

HC DBD-d

0

DBD-p

-0.2

-0.4

-0.6

Figure 2. Neural responses during loss feedback in disruptive behavior disorder (DBD) subgroups. Statistical parametric maps overlaid on an anatomical template, depicting in the upper frames: main task effects during loss feedback in healthy control subjects (HC) (A), DBD desisters (DBD-d) (B), and DBD persisters (DBD-p) (C). In the lower frames, the statistical parametric map for the contrast [DBD-p . (DBD-d and HC)] is displayed (D), accompanied by a bar graph depicting the mean percent signal change during loss feedback in each subgroup in the peak voxel for this contrast (E).

(21–23), these were reported in different paradigms (i.e., emotion processing tasks). Furthermore, this finding is consistent with other studies from our own group (36) and from other groups (19,45), adding to accumulating evidence for neurobiological heterogeneity in antisocial youths: limbic hyperreactivity may occur in some of these youths, while there is a pattern of limbic hyporeactivity in others (16,19). These studies converge with the adult literature on persistent antisocial development (46) and emphasize the need to develop personalized interventions. Alternatively, amygdala hyperresponsiveness in DBD persisters can be interpreted as reflecting higher motivational saliency of external feedback cues, because recent studies in adult psychopaths suggest that they rely more on such cues than control subjects do, possibly because they fail to use internal error signals to adapt their behavior (47). Future studies in antisocial youth should use operant learning paradigms, differentiating between internal and external error signaling conditions, to explore this hypothesis.

In the current study, callous-unemotional traits were negatively correlated with amygdala activation during reward feedback. The relation between callous-unemotional traits and amygdala hyporesponsiveness has often been reported (19,21,23), and reward dominance has been found to be most pronounced in children with conduct problems and callousunemotional features (20). Nonetheless, previous fMRI studies using incentive processing paradigms found no relation between neural responses and callous-unemotional traits (24–26). However, two of these studies did not investigate neural responses in subcortical brain regions during reward feedback (24,25), while the other did not investigate amygdala reactivity and used a different paradigm to assess reward processing (26). With respect to impulsive-irresponsible traits, we were surprised not to find any relation with aberrant incentive processing, given previous studies reporting their association with lower ventral striatal responses during reward feedback (26) and anticipation (24,25). While this may be due to type II error, there are alternative explanations, based on

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Table 2. Neural Responses during Incentive Processing in Relation to Persistence and Psychopathic Traits MNI Coordinates Contrast

Brain Region

t Value (z Value)

kE

pFWE

x

y

z

Direction, Post Hoc

DBD-p vs. (DBD-d and HC) (n 5 68; df 5 65) Reward Anticipation

ns

Loss Anticipation

ns

Reward Feedback

VS

3.80 (3.60)

91

.009a

12

6

214

DBD-p , (DBD-d and HC)

Loss Feedback

Amygdala

3.78 (3.58)

271

.011a

18

0

222

DBD-p . (DBD-d and HC)

Post Hoc Contrasts DBD-p vs. DBD-d Reward Anticipation

ns

Loss Anticipation

ns

Reward Feedback

VS

Loss Feedback

Amygdala

23.21 (3.08)

58

.040

14

8

214

DBD-p , DBD-d

3.18 (3.05)

176

.047

18

0

222

DBD-p . DBD-d

DBD-p vs. HC Reward Anticipation

ns

Loss Anticipation

ns

Reward Feedback

VS

Loss Feedback

Amygdala

23.56 (3.39)

99

.018

12

6

214

DBD-p , HC

3.63 (3.45)

252

.016

18

2

220

DBD-p . HC

228

22

220

Negative relation

DBD-d vs. HC Reward Anticipation

ns

Loss Anticipation

ns

Reward Feedback

ns

Loss Feedback

ns

Callous-Unemotional Traits (n 5 127; df 5 125) Reward Anticipation

ns

Loss Anticipation Reward Feedback

ns Amygdala

23.24 (23.17)

Loss Feedback

376

.030 ns

Significance of post hoc tests: 1: DBD-p versus DBD-d, 2: DBD-p versus HC. DBD, disruptive behavior disorder; DBD-d, DBD-desisters; DBD-p, DBD-persisters; HC, healthy control subjects; kE, cluster size; MNI, Montreal Neurological Institute standard space; ns, not significant; pFWE value, family wise error corrected p value; VS, ventral striatum. a Significant at adjusted Bonferroni-corrected family-wise error corrected p , .026.

important study differences. First, the presence of psychopathic traits may be related to multiple underlying (social and biological) mechanisms that differ as a function of sample characteristics and the traits measures (48) that were used. Impulsive and irresponsible behaviors are relatively common in adolescents, as compared with adults, and healthy adolescents show reduced ventral striatal responses during reward anticipation when compared with adults (49), potentially obscuring the relation of such neural responses with trait impulsivity within the psychopathy construct. As such, our results are not necessarily incompatible with those of previous studies but warrant replication in new samples. While this study has several important strengths, such as its large sample size and availability of longitudinal behavioral data, these novel findings should be interpreted with some caution. First, the current study relied on a self-report measure of psychopathic traits. Although the internal consistency of the trait measure in the current study was excellent and the factor structure (50) and construct validity (38,48) of the employed measures have been firmly established, replication using ratings of psychopathic traits by others is recommended (48). Second, similar to most other studies on childhood antisocial behavior, we used DBD to capture a broad range

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of developmental patterns associated with persistent antisocial behavior, an operationalization that does not comply with current diagnostic schemes (i.e., ODD or CD) and is heterogeneous in terms of its clinical and neurobiological characteristics (16). We therefore performed a post hoc analysis showing that differences in neural reactivity were equally related to broad and narrow (DBD-p vs. DBD-p with high levels of callous-unemotional traits) operationalizations of persistent antisocial development (Supplement 1). Third, while we routinely instructed participants to refrain from substance use before the MRI scan and asked if they had (without penalties for positive answers), we did not use breathalyzers or urine drug screens. As such, we cannot completely rule out the possibility of interfering effects of recent substance use on brain function in some participants. Finally, our Institutional Review Board did not allow the use of larger reward magnitudes—as used in other studies [e.g., (9)]—for ethical reasons. As some group differences may only manifest in the presence of larger rewards, we recommend the use of such conditions in future studies. In conclusion, the current findings suggest the presence of clinically relevant incentive processing atypicalities that contribute to the risk of persistent antisocial behavior and may

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help to explain why antisocial youths with high levels of callous-unemotional traits are less responsive to some types of treatment (44,51).

11.

ACKNOWLEDGMENTS AND DISCLOSURES This study was funded by a Netherlands Organisation for Scientific Research Mosaic grant (017.007.022) and by a Netherlands Organisation for Scientific Research Brain and Cognition grant (056-23-010). Funders were not involved in any phase of the study. Preliminary analyses of these data have previously been published as an abstract (Cohn MD, Veltman DJ, Pape LE, van Lith K, Vermeiren RRJM, van den Brink W, Doreleijers TAH, Popma A [2014]: P.3.016 Incentive processing, psychopathic traits and persistent disruptive behavior: Preliminary results of an fMRI study. European Neuropsychopharmacology 24[suppl 1]:S68–S69.) We thank Andrew Trujillo and Brian Knutson for kindly sharing the monetary incentive delay task and Paul Groot for technical assistance. The authors report no biomedical financial interests or potential conflicts of interest.

ARTICLE INFORMATION From the Department of Child and Adolescent Psychiatry (MDC, LEP, KvL, TAHD, AP), VU University Medical Center, Amsterdam; Department of Psychiatry (DJV), VU University Medical Center, Amsterdam; Department of Child and Adolescent Psychiatry (RRJMV), Curium-Leiden University Medical Center, Leiden; Amsterdam Institute for Addiction Research (WvdB), Academic Medical Center, Amsterdam; and Institute of Criminal Law & Criminology (AP), Faculty of Law, Leiden University, Leiden, The Netherlands. Address correspondence to Moran D. Cohn, M.D., VU University Medical Center Amsterdam, Department of Child and Adolescent Psychiatry, Rijksstraatweg 145, PO Box 303, Duivendrecht 1115ZG, Netherlands; E-mail: m. [email protected]. Received Apr 1, 2014; revised Aug 7, 2014; accepted Aug 7, 2014. Supplementary material cited in this article is available online at http:// dx.doi.org/10.1016/j.biopsych.2014.08.017.

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