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. Author manuscript; available in PMC: 2022 Jul 1.
Published in final edited form as: Personal Disord. 2020 Jun 25;12(4):339–346. doi: 10.1037/per0000430

Reward Processing and Psychopathic Traits in Children

Yu Gao 1,*, Wei Zhang 2
PMCID: PMC8350845  NIHMSID: NIHMS1729851  PMID: 32584089

Abstract

Growing evidence has suggested that the mechanisms underlying the three dimensions of psychopathic traits, including grandiose-manipulative, callous-unemotional, and daring-impulsive are different. As yet, the neurobiological correlates of each dimension have not been fully understood. In this study, we examined if reward processing deficits were differentially associated with these traits, and whether social adversity moderated these relationships. Pre-ejection period was assessed in children aged 8–10 years from the community (N=340, mean age = 9.06, SD = .60; 48.2% boys) while they were completing a reward task, and the caregivers rated children’s psychopathic traits. Results indicated that (1) high CU traits were associated with less PEP shortening, reflecting reward hypo-responsivity, at low levels of social adversity, and more PEP shortening, indicating hyper-responsivity, at high levels of social adversity, (2) high DI traits were associated with hyper-responsivity at low levels of adversity only, and (3) GM traits were not linked to reward processing deficits. Findings provide further evidence that different etiologies may underlie various dimensions of psychopathic traits, and highlight the important role of psychosocial factors in understanding the neurobiological mechanism of youth psychopathy.

Keywords: pre-ejection period, reward, psychopathic traits, children, biosocial

Psychopathy is characterized by a constellation of traits including glibness, manipulation, lack of empathy and responsibility, shallow emotional response, impulsivity, and aggression (Hare, 2003), and is found to predict a particularly severe and persistent type of antisocial behaviors (Barry et al., 2000). In recent years, research on psychopathy has been extended to children and adolescents (Roose, Bijttebier, Claes, & Lilienfeld, 2011; Salekin, 2016), and a multifaceted structure of youth psychopathy has been conceptualized, including interpersonal (i.e., grandiose-manipulative or GM traits), affective (i.e., callous-unemotional or CU traits) and behavioral (i.e., daring-impulsive or DI traits) (Frick, Bodin, & Barry, 2000; Salekin, 2016). To date research has largely focused on the affective factor (CU), which is often considered the key aspect of psychopathy (Pardini, Lochman, & Frick, 2003), and estimated to affect 2–7% of youths in the general population and 15–50% in the clinical population (Kahn, Frick, Youngstrom, Findling, & Yongstrom, 2012). As a result, the DSM–5 has added the “limited prosocial emotions” (i.e., CU traits) as a new specifier to the diagnosis of conduct disorder (American Psychiatric Association, 2013). Yet, the notion that CU traits are central to psychopathy has not been sufficiently supported by empirical evidence, and that there is no clear definition of the “core” concept of psychopathy (Salekin, 2016). Therefore, it is crucial to capture a broader range of psychopathic traits by including all three dimensions in empirical studies in order to better understand the etiology and developmental courses of psychopathic traits. Based on this idea, the current study investigates distinct associations between psychopathic dimensions and physiological measures of reward processing in children.

Atypical punishment and/or reward processing have been linked to psychopathic traits (Byrd, Loeber, & Pardini, 2014; Murray, Waller, & Hyde, 2018; Reidy et al., 2017). Historically, reward and punishment processing has been conceptualized in terms of the behavioral activation system (BAS) and the behavioral inhibition system (BIS), respectively. The BAS serves to increase activity and initiate goal-directed behavior in response to reward, while the BIS functions to inhibit goal-directed action and avoid adverse outcomes in the presence of aversive stimuli (Gray, 1994). The two systems work together to facilitate the redirection of attention to environmental stimuli and to initiate subsequent behavioral responses, and abnormalities in one or both of these systems have been theorized to link to psychopathic traits and antisocial behavior in general (Blair, 2004; Lykken, 1995). Although an underactive BIS, reflected by lower responses and lack of fear to potential punishments, has been consistently linked to psychopathic traits (e.g., Flor, Birbaumer, Hermann, Ziegler, & Patrick, 2002), a clear link between BAS and psychopathic traits has not been demonstrated.

Many empirical studies have supported a reward-dominant response style in psychopathic individuals by showing that they have difficulty in responding to the changing values of reward/reinforcements in a response modulation paradigm (O’Brien & Frick, 1996; see reviews by Byrd et al., 2014; Murray et al., 2018; Reidy et al., 2017). This reward-dominant style may reflect an overactive BAS that leads to persistent reward-seeking behavior in these individuals (Quay, 1993). These findings in general support Newman and colleagues’ hypothesis that individuals with psychopathic traits have difficulty accommodating the meaning of contextual environmental cues when engaged in a goal-directed activity (Newman, Patterson, Howland, & Nichols, 1990). In contrast, some studies have suggested that an underactive rather than overactive BAS may contribute to an aversive physiological state that in turn facilitates sensation-seeking behaviors in psychopathic individuals (Blair et al., 2006; Mitchell, Richell, Leonard, & Blair, 2006; Rubia et al., 2009; Verona, Patrick, Curtin, Bradley, & Lang, 2004). Yet, others have failed to show associations between reward processing deficits and psychopathic traits (Kimonis, Frick, Fazekas, & Loney, 2006).

Much fewer studies have examined reward processing and psychopathic traits in youth, and findings are also mixed. For example, Roose and colleagues in a sample of community adolescents found that the self-reported BAS Reward-Responsiveness (i.e., positive responses to reward or anticipation of reward) scores were negatively and positively associated with CU traits and GM traits, respectively (Roose et al., 2011; Roose, Bijttebier, Decoene, Claes, & Frick, 2010). Reduced responsivity to reward during a risk-taking task has been associated with higher CU traits in both community and adjudicated samples (Centifanti & Modecki, 2013; Marini & Stickle, 2010). In contrast, increased responsivity to reward during a reward and avoidance learning task has been associated with higher CU traits in a community sample (Loney, Frick, Clements, Ellis, & Kerlin, 2003), and with higher scores on both CU and DI traits in children with emotional and behavioral problems (Fisher & Blair, 1998). Finger and colleagues found that compared to healthy controls, antisocial youth with psychopathic traits showed reduced responsivity in the orbitofrontal cortex to rewarded trials in a passive avoidance task (Finger et al., 2011), but no such differences were found using a response-reversal task (Finger et al., 2008). In a sample of adjudicated adolescents, reduced amygdala responses to reward in a monetary incentive delay task were associated with higher CU traits, while no such associations were found for DI or GM traits (Cohn et al., 2015). More research on differential associations between psychopathy dimensions with reward processing is needed to address the inconsistency between the aforementioned study findings, and to provide a better understanding of their underlying etiology.

It is also important to note that prior studies have used paradigms that typically include aspects of both rewards and punishments (e.g., the Balloon Analogue Risk Task, passive avoidance task, response modulation task), making it difficult to specify the underlying mechanisms, as abnormalities in reward and/or punishment processing may be possible for these effects. Therefore, a task with only rewards is needed to facilitate understanding of the responsivity of the BAS independently from the BIS (Byrd et al., 2014). In the current study, we used a simple reward task in which participants continued to be rewarded for correct responses and no punishment was involved. BAS responsivity was assessed by the measure of pre-ejection period (PEP), an index of the sympathetic nervous system (SNS) linked cardiac activity during the reward task. PEP represents the time interval between the onset of the left ventricular depolarization and the onset of the ejection of blood into the aorta, and has been considered a specific indicator of BAS activation in the conditions of pure reward (Brenner, Beauchaine, & Sylvers, 2005). In general, PEP shortens when SNS is activated during an appetitive response, which increases cardiac output in preparation for approach behavior (Sherwood, Allen, Obrist, & Langer, 1986), so increased PEP shortening during reward tasks reflects increased SNS linked cardiac activity (Beauchaine, Katkin, Strassberg, & Snarr, 2001). Previous studies have demonstrated that in youths with externalizing behavioral problems, such PEP shortening was not observed during reward conditions (e.g., monetary incentive tasks), possibly suggesting an underactive BAS and SNS dysfunction (Brenner & Beauchaine, 2011; Crowell et al., 2006).

In the present study, we sought to examine the relationship between PEP during stimulus conditions of pure reward and psychopathic traits in male and female children from the community. We hypothesized that (1) less PEP shortening to reward, reflecting reward hypo-responsivity and an underactive BAS, would be associated with higher CU traits; (2) more PEP shortening to reward, reflecting reward hyper-responsivity and an overactive BAS, would be associated with higher DI traits, given that more PEP shortening to reward is considered a marker for central dopamine hyperactivity associated with trait impulsivity (Brenner et al., 2005); and (3) no significant association would be observed between PEP reactivity and GM traits, due to the fact that deficiency in reward and punishment processing appears to be less relevant to these traits (Byrd et al., 2014). Finally, there is growing evidence suggesting that the associations between neurobiological risk factors and antisocial/psychopathic behaviors may be moderated by psychosocial factors (Beaver, DeLisi, & Vaughn, 2010; Gao, Baker, Raine, Wu, & Bezdjian, 2009; Gao, Huang, & Li, 2017; Raine, Fung, Portnoy, Choy, & Spring, 2014; Zhang & Gao, 2015). Specifically, it has been proposed that biological factors may play a more critical role when social risk factors are lacking (Raine, 2002). Therefore, we predicted that the association between psychopathic traits and PEP would be stronger in individuals from the benign home background.

Method

Participants

The sample was drawn from a longitudinal study that examined the social and neurobiological risk factors for children and adolescents living in large metropolitan city in the Northeast area. Children with a diagnosed psychiatric disorder, intellectual disabilities, or a pervasive developmental disorder were excluded. The sample consisted of 340 children (48.2% males) (Mean age = 9.06, SD = 0.60), with 11% Hispanic, 21% Caucasian, 52% Black, 2% Asian, and the remaining 14% of mixed/other. A more detailed description of the sample selection procedures and characteristics has been provided elsewhere (hide for peer review). Participants and their primary caregivers were invited to the college for a 2-hour laboratory visit including behavioral interviews, neurocognitive testing, psychophysiological recording, as well as social risk factor assessment. Monetary compensation and transportation reimbursement were provided to the participating families at the end of the visit. The University Institutional Review Board approved all procedures. Parental consent and child assent were obtained from all participants.

Measures

Psychopathic Traits.

The GM and DI traits were assessed using the Antisocial Process Screening Device (APSD) (Frick & Hare, 2001) administered to the caregiver. The GM and DI subscales of the APSD have 7 and 5 items respectively, with each item scored on a 3-point scale: “0” (not at all true), “1” (sometimes true), or “2” (definitely true). The CU traits were assessed using the parent version of the Inventory of Callous-Unemotional Traits (ICU) (Frick, 2004). The ICU was developed from the CU subscale of the APSD to specifically assess CU traits associated with antisocial personality. Items are rated on a 4-point scale from “0” (not true at all) to “3” (very true). Factor analyses have indicated that a modified version of the ICU with 19 items fit the data better than the original 24-item scale (Gao & Zhang, 2016). Coefficient alphas were .70, .60, and .85 for the GM, DI, and CU traits respectively in the current sample.1

Social adversity.

Following prior literature (Gao, Raine, Chen, Venables, & Mednick, 2010; Raine, Yaralian, Reynolds, Venables, & Mednick, 2002), a social adversity index was created via caregiver’s report by adding 1 point for each of the following 10 items: Divorced Parents (single parent family, remarriage, or living with guardians other than parents), Foster Home, Public Housing, Welfare Food Stamps, Parent Ever Arrested (either parent has been arrested at least once), Parents Physically Ill, Parents Mentally Ill, Crowded Home (five or more family members per house room), Teenager Mother (aged 19 years or younger when child was born), and Large Family (sibling order fifth or higher by age 3 years). All items are scored either 0 (no) or 1 (yes), with a higher total score denoting a higher level of social adversity.

The reward task.

In this task, large, single-digit numbers (i.e., 0 to 9) were presented on a computer screen in random order. Participants were required to press one button if the number presented was higher in value than the preceding number, and to press the other button if it was lower. The presentation of the next number was triggered when the correct button was pressed. 10¢ was awarded for each correct response. Throughout all trials, the amount of money earned was displayed on the upper left corner of the screen. The task continued for 2 min. The computer tracked the total number of correct responses completed within the 2 min period. Participants were told to respond quickly and correctly to earn as much monetary reward as possible. This task was chosen because it elicits BAS reactivity purely and involves minimal levels of learning, making it suitable to discern the unique association between simple reward processing (rather than learning) and psychopathic traits.

Psychophysiological Data Acquisition and Reduction

Electrocardiography (ECG) and Impedance cardiography (ICG) signals were recorded continually at 1000 Hz using a Biopac MP150 system (BIOPAC Inc., Goleta, CA) during a 2-min rest before the task, the 2-min reward task, and a final 2-min rest at the end. ECG was recorded using the ECG100C amplifier with two pre-jelled Ag-AgCl disposable vinyl electrodes placed at a modified Lead II configuration. ECG data was set to a band-pass filter of 35 Hz-1.0 Hz. ICG was recorded using the NICO100C amplifier by putting eight spot electrodes on the neck and the torso: two on each side of the upper neck and two on each side of the lower torso, according to the configuration from previous research (Sherwood et al., 1990).

PEP was derived from the ECG and ICG offline with AcqKnowledge 4.2 software with Biopac. Recorded ECG and ICG signals were inspected on a beat-to-beat basis and ensemble-averaged. PEP was measured in milliseconds from the onset of the ECG Q-wave to the B-point of the dZ/dt wave, using an automated scoring algorithm with Biopac (Berntson, Lozano, Chen, & Cacioppo, 2004). Rest PEP was computed as the average PEP of the last 1 min of the two rest periods. Task PEP was the average PEP during the 2-min reward task. PEP reactivity was computed as a difference score (task PEP minus rest PEP), with negative values indicating shortened PEP or increased SNS reactivity to reward, and positive values denoting less PEP shortening or reduced SNS reactivity.

Statistical Analyses

Gender differences in the PEP measures, psychopathic traits, social adversity and behavioral performance were examined using independent samples t-tests. The relationships among main study variables were analyzed by Pearson correlations. To investigate the association between PEP reactivity and psychopathic traits, and the moderating effect of social adversity, hierarchical multiple regressions were conducted. Separate analyses were performed for each psychopathic dimension. In each regression model, the non-focal psychopathic traits and child’s gender were entered in the first step as covariates. Main effects of PEP reactivity and social adversity were included in the second step. The interaction between PEP reactivity and social adversity was entered in the third step. To further examine the nature of moderation effects, the significant interaction was examined using simple slope analyses (Hayes, 2017), and illustrated by plotting the simple regression lines for the high (+1 SD) and low (−1 SD) values of social adversity. All predicting variables were mean centered to avoid multicollinearity and before interaction terms are created.

The logarithmical transformation was applied to the measure of GM traits due to its high skewness (skewness before transformation = 1.71). Outliers were identified and replaced (3 SDs beyond the means) with the next closest value. Missing PEP values (4.1% - 11%) were due to acquisition problems, such as equipment malfunction, extraneous movement, and electrode misplacement or displacement. There was a negligible amount of missing data in social adversity (1.8%), ICU (1.8%), and APSD (2.9%). Little’s MCAR test suggested that data were missing completely at random (Chi square = 28.62, p = .943) (Little & Rubin, 2002). Missing values were imputed through multiple imputations method in SPSS. A total of 10 imputed datasets were created and analyzed in turn for the t-tests, Pearson correlations and hierarchical regression analyses. Results from the imputed datasets were combined and pooled average statistics were reported. All regression analyses were re-run using cases with complete data from the original dataset (available in 289 participants) and the findings remained unchanged. Coefficients and standard errors were reported for the imputed data and the simple slopes were examined based on data without imputations.

Results

Descriptive Statistics

Table 1 presents the descriptive statistics for the primary study variables among the overall sample and for boys and girls separately. Overall, the two gender groups did not differ significantly on all measures. Table 2 presents the zero-order correlations among variables. Rest PEP was marginally positively associated with DI traits (p = .078). No other significant associations between PEP values and psychopathic traits were observed. Social adversity was positively associated with GM (p < .001), CU (p = .037), and DI traits (p < .001).

Table 1.

Descriptive statistics for key study variables and gender differences.

Total Boys Girls
Mean SD Skewness Kurtosis Mean SD Mean SD t-test value p
Rest PEP 83.76 17.04 .12 .53 85.47 17.17 82.10 16.80 1.83 .067
Task PEP 82.78 18.64 −.39 −.11 83.19 18.74 82.38 18.59 .40 .690
PEP reactivity −.98 19.41 .03 .61 −2.27 18.18 0.29 20.50 −1.21 .225
GM traits 1.90 2.09 1.71 3.56 2.05 2.25 1.76 1.92 1.17 .244
CU traits 15.14 7.75 .36 −.28 15.71 7.57 14.58 7.90 1.35 .178
DI traits 2.60 1.73 .33 −.51 2.76 1.77 2.45 1.68 1.64 .100
Social adversity 2.97 2.01 .51 −.40 3.04 2.04 2.90 1.99 0.61 .544
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Note: PEP = pre-ejection period; GM = grandiose-manipulative; CU = callous-unemotional; DI = daring-impulsive. Pooled statistical parameters (e.g., t-test value, p, means) were reported for the imputed data. Skewness and kurtosis were for the original data without imputation. T-tests were re-run using the original dataset and findings remained unchanged.

Table 2.

Correlations among study variables.

1 2 3 4 5 6 7
1. Rest PEP 1
2. Task PEP .41** 1
3. PEP reactivity −.48** .60** 1
4. GM traits .08 .02 .05 1
5. CU traits .08 .04 −.03 .45**
6. DI traits .10† .01 −.08 .59** .47** 1
7. Social adversity .08 .08 .01 .24** .11* .21** 1
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Note: PEP = pre-ejection period; GM = grandiose-manipulative; CU = callous-unemotional; DI = daring-impulsive. Statistics were based on imputed values. Correlations were re-run for the original data set and findings remained unchanged.

†

p < .10

*

p < .05

**

p < .01.

Reward Processing and Psychopathic Traits

GM traits.

Results of hierarchical regression analyses are presented in Table 3. After controlling for CU and DI traits and child’s gender, higher social adversity was associated with greater GM traits (B = .02, t = 2.50, p = .013). No significant main effect was observed for PEP reactivity (p = .884), and the interaction effect between PEP reactivity and social adversity was non-significant (p = .817).

Table 3.

Summary of hierarchical regression for psychopathic traits: The predicting effects of PEP reactivity and social adversity.

GM traits CU traits DI traits
B SE t B SE t B SE t
Step 1 Step 1 Step 1
 CU traits .01 .00 4.20***  GM traits 7.19 1.72 4.18***  GM traits 2.69 .33 8.12***
 DI traits .07 .01 8.54***  DI traits 1.50 .27 5.48***  CU traits .06 .01 5.47***
 Gender −.00 .03 −0.13  Gender −.45 .72 −0.62  Gender −.11 .15 −0.78
Step 2 Step 2 Step 2
 PEP-R .00 .00 −0.15  PEP-R .00 .02 0.10  PEP-R −.004 .004 −0.97
 SA .02 .01 2.50*  SA −.08 .19 −0.42  SA .06 .04 1.66†
Step 3 Step 3 Step 3
 PEP-R × SA .00 .00 0.23  PEP-R × SA −.03 .01 −2.81**  PEP-R × SA .005 .002 2.29*
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Note: PEP = pre-ejection period; PEP-R = PEP reactivity; GM = grandiose-manipulative; CU = callous-unemotional; DI = daring-impulsive; SA = Social adversity. Hierarchical regression analyses were conducted across multiple imputations. Pooled coefficient statistics are given for the imputed data. Analyses were re-run using only cases in the original dataset and findings remained unchanged. The displayed statistics of the variables at Steps 1 and 2 represent the values after interaction terms were included at Step 3 in the final model.

†

p < .10

*

p < .05

**

p < .01

***

p < .001

CU traits.

After controlling for GM and DI traits and child’s gender, no significant main effects were observed for PEP reactivity (p = .919) or social adversity (p = .676). However, the interaction between PEP reactivity and social adversity was significant (B = −.03, t = −2.81, p = .005). Analysis of the simple effect revealed that less PEP shortening was associated with greater CU traits at low levels of social adversity (−1SD; t = 1.99. p = .048), and less CU traits at high levels of social adversity (+1SD; t = −2.22, p = .027). This interaction effect is illustrated in Figure 1.

Figure 1.

Figure 1.

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PEP reactivity by social adversity interaction effect on CU traits. Less PEP shortening was associated with higher CU traits at low levels of social adversity (−1SD), but lower CU traits at high levels of social adversity (+1SD).

DI traits.

After controlling for GM and CU traits and child’s gender, a marginally significant main effect was found for social adversity (B = .06, t = 1.66, p = .068). No significant main effect was observed for PEP reactivity (p = .332). Finally, the interaction between PEP reactivity and social adversity was significant (B = .005, t = 2.29, p = .023). Simple slope analysis indicated that more PEP shortening was associated with greater DI traits at low (−1SD; t = −2.64, p = .009) but not high levels of social adversity (+1SD; t = .76, p = .451). This interaction is illustrated in Figure 2.

Figure 2.

Figure 2.

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PEP reactivity by social adversity interaction effect on DI traits. More PEP shortening was associated with higher DI traits only at the levels of low social adversity, but not high levels of social adversity.

Discussion

In this study, we examined the associations between psychopathic traits and reward processing as measured by pre-ejection period (PEP) reactivity in community children aged 8–10 years. None of the three psychopathy dimensions were associated with rest PEP or PEP reactivity, but regression analyses revealed that after the other two dimensions and gender were controlled for: (1) PEP reactivity was positively associated with CU traits at low levels of social adversity, and negatively associated with CU traits at high social adversity; and (2) PEP reactivity was negatively associated with DI traits at low levels of social adversity only. Both DI and GM were significantly associated with social adversity. Findings provide further evidence that the three dimensions of psychopathy are uniquely associated with physiological and psychosocial measures.

We found that after controlling for relevant covariates, higher CU traits were associated with less PEP shortening during the reward task, reflecting reward hypo-responsivity and an underactive BAS, at low levels of social adversity. This is consistent with our hypothesis, and in parallel with findings from several behavioral and neuroimaging studies (Cohn et al., 2015; Roose et al., 2011; Roose et al., 2010) and the observation that lower positive affect was found in adolescents with high CU traits (Kimonis et al., 2008). An underactive BAS may lead to more reward-seeking behavior in order to achieve satisfying levels of arousal (Cohn et al., 2015; Zuckerman & Kuhlman, 2000). Interestingly, we also found that at high levels of social adversity, higher CU traits were associated with more PEP shortening, reflecting reward hyper-reactivity and an overactive BAS. This finding of an overactive BAS is consistent with past studies showing that children high on CU traits seem to be more sensitive to cues to reward in the avoidance learning task (Barry et al., 2000; Frick, Cornell, Barry, Bodin, & Dane, 2003). In fact, reward hypo-reactivity or an underactive BAS, seems to protect children in the adverse home background from developing CU traits (see Figure 1). It is important to know that in contrast to prior studies that included both punishment and rewards outcomes and that the reward processing is complicated with punishment contingency, our study is the first to use a pure reward task (without punishment component) that supposedly better specifies the mechanism underlying reward processing (Byrd et al., 2014). Future research using similar paradigms is needed to examine if our findings can be replicated.

Taken together, our findings support the notion that CU traits are characterized by abnormal reward processing. This is broadly consistent with the Integrated Emotion Systems (IES) theory postulating that deficiencies in processing positive (and negative) stimuli are associated with higher CU traits (Blair, 2004). Given that cardiac PEP reactivity is considered a proxy for central dopamine responding to incentives (Beauchaine & Gatzke-Kopp, 2012) and marks mesolimbic dopamine reactivity especially during reward responding (Brenner & Beauchaine, 2011; Brenner et al., 2005), our finding also suggests that dopaminergic under- or over- responding to reward is related to CU traits. This abnormality may disrupt the association of reward and contingent behavior while restoring dopamine levels can normalize the ability to form these connections in individuals with conduct problems (borgå Johansen, Sagvolden, Aase, & ann Russell, 2005). Supporting this notion, one study has shown that methylphenidate helps alleviate treatment resistance to behavior therapy in antisocial children with CU traits (Waschbusch, Carrey, Willoughby, King, & Andrade, 2007).

As expected, increased responsivity to reward or an overactive BAS was related to higher DI traits after controlling for CU traits, GM traits, and gender, but only at low levels of social adversity. It partly corroborates the findings linking reward dominance style during risk-taking tasks to psychopathic-impulsivity (Fisher & Blair, 1998) and the notion that central dopamine hyperactivity features trait impulsivity (Beauchaine, 2012; Brenner et al., 2005). These findings are also consistent with Gray’s reinforcement responsivity theory arguing that an overactive BAS is associated with impulsivity (Salekin, 2016).

Consistent with our hypothesis, PEP reactivity was not associated with GM traits. This null finding is in line with prior neuroimaging finding that amygdala activation in response to reward is not linked to GM traits (Cohn et al., 2015), further suggesting that reward processing deficits are less relevant to these interpersonal traits of child psychopathy (Byrd et al., 2014). Finally, we found that social adversity was positively associated with GM and DI traits but not with CU traits, consistent with the literature showing that the latter is in particular primarily influenced by genetic factors (Viding, Blair, Moffitt, & Plomin, 2005; Viding, Jones, Paul, Moffitt, & Plomin, 2008).

A few limitations should be noted. First, the cross-sectional nature of the study prevented us from concluding the causal relationships between reward processing and psychopathic traits. Longitudinal designs are needed to systematically determine the developmental change of these relationships. Second, the psychopathic traits measure in the current study relied on the caregiver’s reports, and the reliability for the daring-impulsive scale is relatively low (.60), possibly due to fewer items (n = 5) included in this scale. Similar reliability values have been reported in other studies (Fung, Gao, & Raine, 2010). Multi-informant measures of psychopathic traits (e.g., parent and teacher report) should be included in future studies. Third, our participants came from the community, so findings may not be generalizable to clinical or incarcerated populations.

In conclusion, our study was innovative to adopt PEP measures to examine the relationships between reward processing deficits and different aspects of psychopathic traits in children. We found that high CU traits are characterized by reward hypo-responsivity at low levels of social adversity and hyper-responsivity at high social adversity. In addition, high DI traits were associated with hyper-responsivity at low levels of adversity. GM traits were not linked to reward processing deficits. Findings provide further evidence that dimensions of psychopathy are differentially associated with psychophysiological measures, and highlight the importance of examining both the neurobiological and psychosocial factors in understanding youth psychopathy.

Acknowledgements:

This work was supported by the National Institute of Health under Award Number SC2HD076044 and SC3GM118233 to the first author. We thank the children and parents who consented to participate in this study. We acknowledge the former research assistants for their contribution in data collection.

Footnotes

1

Analyses were also conducted with the total score from the original 24-item ICU in the correlation and regression models. All results were substantively the same.

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