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«by Amy Lynn Byrd, Ph.D. B.S. in Psychology, College of Charleston, 2006 M.S. in Clinical Psychology, University of Pittsburgh, 2010 Submitted to the ...»

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Regulatory Regions Also contrary to hypotheses, no group differences were detected in response to punishment within regulatory regions (e.g., ACC, mPFC, OFC). While there was some evidence to suggest reduced activation across reward and punishment conditions within the mPFC, this was specific to CP youth with low levels of CU and was not consistent across analyses. Prior work in this area has demonstrated abnormalities in the ACC (Gatzke-Kopp, et al., 2009), mPFC (Bjork, et al., 2010; Finger, et al., 2008) and OFC (Finger, et al., 2011; Rubia, et al., 2009) among youth with CP; however, the direction of these findings has varied (i.e., increased versus decreased activation among CP youth relative to HC) and this may be attributable to variation in task and analysis design. For example, while Rubia et al. (2009) utilized a rewarded continuous performance and compared responsivity to rewarded responses relative to responses without reward, Finger and colleagues (2008) used a response-reversal task and examined reactivity to punished errors versus rewarded responses. Along these lines, the current dissertation separately examined responsivity to the initial encoding of unpredictable reward and punishment within the context of a card guessing task. Because this task does not require learning to modify a previously rewarded response or set-shifting, it may be less likely to highlight potential group differences in regulatory regions like the ACC or OFC that are noted for their involvement in error monitoring and contingency learning (e.g., Rogers, et al., 2004). Conversely, it may be that prior to the transition to adolescence, differences in regulatory function are less pronounced.

Specifically, risk-taking behaviors in adolescence are believed to arise due to an imbalance between more rapidly developing subcortical regions (i.e., striatum, amygdala) and protracted

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Steinberg, 2008). This dual-process is at its height during adolescence, with more recent suggestion that differences in the development of these systems are particularly pronounced among youth with CP (Bjork & Pardini, 2014). Thus, we may expect evidence of aberrant processing within regulatory regions to be more prominent in adolescence.

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While the current dissertation failed to find associations between individual differences in reward/punishment processing and response to intervention, results reiterate findings from Burke and Loeber (2014) and confirm the effectiveness of SNAP, a multimodal, empirically-supported intervention. Specifically, youth with CP who were assigned to SNAP experienced a significant reduction in level of externalizing behavior over time relative to CP youth experiencing treatment as usual. Importantly, It should also be noted that within the larger treatment sample, CU traits failed to moderate treatment effectiveness, further emphasizing the utility of this intervention among youth with CP and CU (Pardini, Byrd, Kimonis, Burke, & Loeber, in preparation). While moderation analyses were exploratory in nature given the small sample size, results emphasize the utility of this intervention in youth with early-onset CP despite abnormalities in reward and punishment processing.

While these results are promising, intervention efforts typically boast effect sizes that are still small to moderate (e.g., Matthys, et al., 2012b; McCart, Priester, Davies, & Azen, 2006).

This may be related to the ‘one size fits all’ approach and a failure to assess and treat childspecific deficits at an individual level. Given the noted heterogeneity that exists among youth

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effectiveness of social learning-based interventions. Some researchers have proposed assessing children with CP for potential deficits in reward/punishment processing prior to treatment initiation, in order to modify or individualize the treatment approach (see Matthys, et al., 2012b).

For example, treatment for youth with deficits in punishment processing may focus on increasing the use of praise and reward systems that facilitate the reinforcement of positive, prosocial behaviors (see Dadds and Salmon 2003). Evan as the current dissertation failed to identify an association between reward/punishment processing and responsiveness to intervention, this avenue of research may warrant continued investigation. Moreover, an examination of how treatment induced changes in specific parenting behaviors serve to interact with identified deficits in reward and/or punishment processing may help to further elucidate more complex moderation mechanisms and ultimately, amplify treatment effectiveness.

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The current study offers additional insights into the characterization of abnormalities in reward/punishment processing in CP youth and is the first known investigation to examine these mechanisms among subgroups of CP youth with and without CU traits relative to matched HC.

Moreover, it is one of the only studies to explore how individual differences in responsivity to reward/punishment may influence responsiveness to treatment. Nonetheless, findings from the current dissertation should be considered in the context of several limitations. First and foremost, it is important to reiterate that the sample size in the current dissertation is notably small. While primary comparisons at baseline utilized a sample size almost double that of prior imaging

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resulted in relatively small group sizes and could undermine attempts to detect significant effects. Moreover, analyses examining associations between reward/punishment processing and treatment responsiveness were notably exploratory in nature given the small number of CP youth who completed both an fMRI scan and treatment. This combined with significant variability in responsivity to reward/punishment within groups necessitates continued investigation and attempted replication in larger samples.

Second, it should be noted that CU traits and psychopathic features were measured using the APSD, a measure that while consistently used in the literature, has been noted for its lack of internal consistency (Munoz & Frick, 2007; Poythress, et al., 2006). This scale was used with the intention to examine the new DSM-5 specifier ‘lack of prosocial emotions’ as an indicator of the presence CU traits (American Psychiatric Association, 2013). While this represents an important advancement in the literature, future studies may want to utilize alternative measures and/or create a composite that takes advantage of different measures and informants. Along these lines, while parent- and child-report were combined in the current study to make use of multiple informants, the addition of teacher-report would be ideal so as to provide important information about these features in an alternative setting. Finally, the current investigation is one of the only studies to examine potential differences in groups characterized by CU versus psychopathic features. A comparison of results based these classification criteria revealed minimal differences, though the only variation between subgroups was specific to the presence of CU traits. Thus, as future research continues to investigate potential differences in these subgroups, it will be important to explicitly delineate these classifications as they are often used interchangeably throughout the literature.

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sample of boys with severe CP in late-childhood, limiting the degree to which these results can be generalized to community samples, girls and/or adolescents. As such, future research is needed to examine the extent to which potential abnormalities are characteristic of youth with mild to moderate CP as well as samples of girls. Moreover, given the noted changes in neural function that occur during the transition to adolescence (Bjork & Pardini, 2014; Steinberg, 2008), it will be important to investigate neural processing in comparable samples of adolescents. Along these lines, it is unclear whether the abnormalities documented in the current investigation are stable and/or reliably predict risk for the persistence of CP. Very few studies have examined within individual change in neural functioning over time and how this relates to future CP. Thus, little is known about whether abnormalities associated with CP in late childhood reflect preexisting, stable functional abnormalities or slower developmental maturation that may resolve over time. More importantly, it remains unclear how stability versus change in aberrant neural responses is associated with the persistence or desistance of CP over time. Prospective longitudinal studies that incorporate the assessment of neural function over time are needed to address these limitations.

It is also important to note that while the current dissertation identified group based functional differences in distinct regions associated with reward and punishment processing, these regions are merely ‘one piece of the puzzle’ and should be considered within the context of a broader, interconnected circuitry. Recent meta-analytic findings emphasize the importance of conceptualizing behavioral constructs (e.g., risk-taking, emotional experience) as arising from aberrant processing throughout general brain networks. This was found to be superior to a ‘locationist’ approach focused on direct links between deficits in any one region and relevant

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identification of group based differences in amygdala responsivity to punishment or striatal reactivity to reward in the current dissertation represent vulnerabilities or probabilistic associations that are believed to increase risk for CP. That is to say, the association between reduced amygdala activation to punishment and CP does not represent a direct causal relationship but instead operates as a part of a structurally and functionally interconnected neural network. Accordingly, deterministic interpretations should be cautioned against. Instead, current results highlight potential risk factors that comprise one piece of a more complex mosaic that we are still working to better delineate and understand (see Hyde, et al., 2013 for further discussion).

Along these lines, the current dissertation did not consider the role of important contextual influences and how they may interact with deficits in reward/punishment processing to increase risk for CP. For example, harsh and inconsistent parenting is thought to inadvertently reinforce CP (Patterson et al. 1992) and may also contribute to the development of CU traits or psychopathic features (Waller et al. 2013). This type of parenting combined with an insensitivity to punishment and difficulties inhibiting a reward-dominant response style may be particularly detrimental. Moreover, research suggests that parent–child interactions are bidirectional and as such, have cascading effects that serve to further entrain aberrant reward and punishment processing (Dodge and Pettit 2003; Pardini et al. 2008; Sameroff 2000). The examination of these interactive processes is particularly important to consider as we seek to further understand the development and persistence of CP. In addition, the evaluation of interactions between intervention driven changes in parenting and child specific deficits in reward/punishment processing may also help to shed light on variability in the success of intervention for these youth. Lastly, youth with deficits in reward/punishment processing may be particularly

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to reward in the presence of peers (Centifanti and Modecki 2013). As such, further investigation of the role of peers, particularly during the transition to adolescence may be particularly informative.

In sum, the current dissertation demonstrates consistent deficits in punishment processing among boys with high levels of CP in late childhood. This was most robust within the amygdala and not specific to youth with CU traits or psychopathic features. Additionally, there was initial evidence of distinct reward processing mechanisms among CP youth with high versus low levels of CU traits, though it is unclear whether this is attributable to CU traits or other confounding variables (e.g., internalizing problems). Finally, although random assignment to SNAP resulted in significant reductions in CP at 3-month follow-up, individual differences in responsivity to reward and punishment were unrelated to post-treatment levels of CP and failed to moderate the effectiveness of the SNAP intervention. Future research should seek to replicate these results and build on this basic understanding of aberrant reward/punishment processing by examining reward/punishment processing within the context of learning. Moreover, gaining a better understanding the development of reward/punishment processing over time and the potential interaction between these mechanisms and relevant contextual influences (e.g., parenting) will be particularly important. As our knowledge about these mechanisms increase, this information should be used to refine and individualize prevention and intervention efforts.

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Achenbach, T. M. (1991). Manual for Child Behavior Checklist/ 4-18 and 1991 profile:

Burlington, VT: University of Vermont, Department of Psychiatry.

Amaral, D. G., Price, J. L., Pitkanen, A., & Carmichael, S. T. (1992). Anatomical organization of

the primate amygdaloid complex. In J. P. Aggleton (Ed.), The Amygdala:

Neurobiological Aspects of Emotion, Memory, and Mental Dysfunction (pp. 1–66). New York: Wiley-Liss.

American Psychiatric Association. (2013). The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Arlington, VA.

Augimeri, L., Farrington, D. P., Koegl, C., & Day, D. (2007). The SNAP™ Under 12 Outreach Project: Effects of a community based program for children with conduct problems.

Journal of Child and Family Studies, 16(6), 799-807. 10.1007/s10826-006-9126-x Balleine, B. W., Delgado, M. R., & Hikosaka, O. (2007). The role of the dorsal striatum in reward and decision-making. The Journal of Neuroscience, 27(31), 8161-8165.

Balleine, B. W., & Killcross, S. (2006). Parallel incentive processing: An integrated view of amygdala function. Trends in Neurosciences, 29(5), 272-279. 10.1016/j.tins.2006.03.002 Balsam, P. D., Drew, M. R., & Gallistel, C. R. (2010). Time and Associative Learning. Comp Cogn Behav Rev, 5, 1-22.

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