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Neuroimaging findings in disruptive behavior disorders

Published online by Cambridge University Press:  10 April 2015

Rosalind H. Baker ,
Roberta L. Clanton ,
Jack C. Rogers  and
Stéphane A. De Brito
Rosalind H. Baker
Affiliation:
School of Psychology, University of Birmingham, Edgbaston, Birmingham, UK
Roberta L. Clanton
Affiliation:
School of Psychology, University of Birmingham, Edgbaston, Birmingham, UK
Jack C. Rogers
Affiliation:
School of Psychology, University of Birmingham, Edgbaston, Birmingham, UK
Stéphane A. De Brito*
Affiliation:
School of Psychology, University of Birmingham, Edgbaston, Birmingham, UK
*
*Address for correspondence: Stéphane De Brito, School of Psychology, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK. (Email: s.a.debrito@bham.ac.uk)
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Abstract

Decades of research have shown that youths with disruptive behavior disorders (DBD) are a heterogeneous population. Over the past 20 years, researchers have distinguished youths with DBD as those displaying high (DBD/HCU) versus low (DBD/LCU) callous-unemotional (CU) traits. These traits include flat affect and reduced empathy and remorse, and are associated with more severe, varied, and persistent patterns of antisocial behavior and aggression. Conduct problems in youths with HCU and LCU are thought to reflect distinct causal vulnerabilities, with antisocial behavior in youths with DBD/HCU reflecting a predominantly genetic etiology, while antisocial behavior in youths with DBD/LCU is associated primarily with environmental influences. Here we selectively review recent functional (fMRI) and structural (sMRI) magnetic resonance imaging research on DBD, focusing particularly on the role of CU traits. First, fMRI studies examining the neural correlates of affective stimuli, emotional face processing, empathy, theory of mind, morality, and decision-making in DBD are discussed. This is followed by a review of the studies investigating brain structure and structural connectivity in DBD. Next, we highlight the need to further investigate females and the role of sex differences in this population. We conclude the review by identifying potential clinical implications of this research.

Keywords

Antisocial behaviorcallous-unemotional traitsconduct disorderconduct problemsdisruptive behavior disorderssex differencesfMRIvoxel-based morphometrysurface-based morphometrydiffusion tensor imaging

Information

Type
Review Articles
Information
CNS Spectrums , Volume 20 , Special Issue 4: Pediatric Neuroimaging , August 2015 , pp. 369 - 381
Copyright
© Cambridge University Press 2015 

Introduction

Disruptive behavior disorders (DBD), which include conduct disorder/conduct problems and oppositional defiant disorder, are characterized by aggressive and antisocial behavior during childhood and adolescence. 1 These behaviors are among the most common reasons for a childhood referral to mental health and educational services.Reference Scott, Knapp, Henderson and Maughan 2 DBD are associated with problems socially within the school or workplace, which can often lead to legal problems, criminality, and arrest.Reference De Brito and Hodgins 3 As a result, bringing up a child with DBD costs society 10 times more than a child who displays no conduct problems.Reference Scott, Knapp, Henderson and Maughan 2 Crucially, DBD in youths are not only predictive of antisocial and aggressive behaviors in adulthood, but also substance misuse, other mental health problems, and poor physical health.Reference Odgers, Caspi and Broadbent 4

Decades of research have highlighted that youths with DBD are a heterogeneous population that incorporates different subtypes.Reference Frick and Viding 5 Several useful approaches have accounted for this heterogeneity,Reference Frick and Marsee 6 but the approach that distinguishes youths with DBD as those displaying high (DBD/HCU) versus low (DBD/LCU) callous-unemotional (CU) traits has attracted considerable interest over the past 20 years.Reference Frick and Viding 5 CU traits reflect a lack of empathy and guilt, combined with a shallow affect and the callous use of others for one’s own gain. Among antisocial adults, high levels of CU traits characterize adult psychopaths—a particularly severe group of antisocial individuals.Reference Hare 7 While youths cannot be labeled as psychopaths, those with DBD/HCU are thought to be at risk of developing psychopathy in adulthood,Reference Blair 8 , Reference Viding and McCrory 9 and as result have been the focus of intense research. Genetic, behavioral, experimental, and neuroimaging studies have shown that youths with DBD/HCU and those with DBD/LCU are characterized by different vulnerabilities.Reference Frick and Viding 5 This resulted in the recent inclusion of CU traits as the “with Limited Prosocial Emotions” specifier for the diagnosis of conduct disorder in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5 1 ). Twin studies indicate that conduct problems in youths with DBD/HCU are highly heritable, while conduct problems in youths with DBD/LCU are moderately heritable, but largely influenced by environmental factors.Reference Viding, Blair, Moffitt and Plomin 10 Unlike youths with DBD/LCU, youths with DBD/HCU display behaviors akin to adults with psychopathy, notably committing violent crimes at a younger age and displaying a more severe and varied pattern of conduct problems, including instrumental aggression and sadistic acts of violence.Reference Frick and Marsee 6 , Reference Frick, Ray, Thornton and Kahn 11 Youths with DBD/HCU have a preference for novel and dangerous activities, present with a lack of emotional responsiveness to negative emotional stimuli, are impaired at processing others’ fearful and sad facial expressions and vocal tones, and are relatively insensitive to punishment,Reference Blair 8 all of which are consistent with a low fearfulness temperamental style.Reference Frick and Marsee 6 By contrast, youths with DBD/LCU are typically less aggressive, mostly displaying threat-based reactive aggression,Reference Viding and McCrory 9 This most likely reflects a hostile attributional bias in response to real or perceived social threat, such as angry faces or ambiguous neutral faces.Reference Dadds, Perry and Hawes 12 Finally, youths with DBD/LCU have problems regulating their emotions, and display a low frustration tolerance and high levels of anger, impulsivity, and emotional distress.Reference Frick and Marsee 6 , Reference Frick, Ray, Thornton and Kahn 11 They are also more responsive and empathic to the distress of othersReference Jones, Happe, Gilbert, Burnett and Viding 13 and to negative stimuli.Reference Viding and McCrory 9 , Reference Frick, Ray, Thornton and Kahn 11

In addition to distinguishing among subtypes of youths with DBD, there is a growing need to explore the influence of sex, particularly in the context of neuroimaging research.Reference Moffitt, Arseneault and Jaffee 14 Male and female adolescents with DBD may express antisocial behavior in different ways, and show structural differences in the brain and different abnormalities in brain function. However, very little neuroimaging research has investigated females with DBD or directly compared males and females with DBD. While 13.8% of male adolescents present with conduct disorder, only 6.7% of female adolescents show the same presentation.Reference Cohen, Cohen and Kasen 15 Further, males aged 10–17 years are more likely to have been contacted by the police and convicted for a criminal offence than females.Reference Moffitt, Caspi, Rutter and Silva 16 Similarly, the age of onset of antisocial behavior is different between the sexes; while more males are diagnosed with conduct disorder aged 10, with a downward trend after this age, the rate of conduct disorder in females peaks at 16 years.Reference Cohen, Cohen and Kasen 15 One possible reason behind these skewed diagnosis rates could be that the DSM-5 criteria for conduct disorder show a bias towards behaviors more often exhibited by males.Reference Moffitt, Arseneault and Jaffee 14 While males are more likely to show overt behaviors, such as vandalism and aggressive stealing, females are more likely to show covert behaviors, such as lying and sabotaging relationships.Reference Frick and Dickens 17 With the aim of extending research on females with DBD, the FemNAT-CD consortium (http://www.femnat-cd.eu) — a large multisite European study, of which our group is a part—will assess the environmental and neurobiological factors that might underpin sex differences in conduct disorder. For the purposes of this review, the few published neuroimaging studies that have examined females with DBD and considered the influence of sex differences in DBD will be discussed.

In this article, we selectively review recent functional (fMRI) and structural (sMRI) magnetic resonance imaging research on DBD, focusing particularly on the role of CU traits. First, fMRI studies examining the neural correlates of affective stimuli, emotional face processing, empathy, theory of mind, morality, and decision-making in DBD will be discussed (see Table 1). This is followed by a review of the studies investigating brain structure and structural connectivity in DBD (see Table 2). Next, recent studies investigating female samples and the role of sex differences are discussed. We conclude the review by identifying potential clinical implications of this research.

Functional Magnetic Resonance Imaging Evidence

Affective stimuli and emotional face processing

Several fMRI studies have examined the neural correlates of negative affective stimuli (e.g., IAPS stimuliReference Lang, Bradley and Cuthbert 18 ) and face processing in DBD, and have identified an atypical response in this population within a set of cortical and subcortical regions including, among others, the orbitofrontal cortex (OFC), ventromedial prefrontal cortex (VMPFC), anterior cingulate cortex (ACC), insula, temporal lobe, and the amygdala.Reference Rubia 19 , Reference Sterzer and Stadler 20 However, studies that do not take into account individual differences in CU traits have produced a mixed account of the reported amygdala response, with evidence of both amygdala hypo- and hyper-reactivity to negative affective stimuli.Reference Herpertz, Huebner and Marx 21 , Reference Sterzer, Stadler, Krebs, Kleinschmidt and Poustka 22 Given evidence indicating that youths with DBD/HCU and DBD/LCU are characterized by distinct emotional, cognitive, and behavioral responses to affective stimuli and faces,Reference Blair 8 , Reference Frick, Ray, Thornton and Kahn 11 these inconsistent findings may partly result from variations in CU traits across samples.Reference Viding, Sebastian and Dadds 23 Compared to typically developing (TD) youths, youths with DBD/LCU have consistently been found to exhibit hyperactivity in the amygdala when processing both fearful facesReference Viding, Sebastian and Dadds 23 and fearful eyes.Reference Sebastian, McCrory and Dadds 24 These results might partly explain why youths with DBD/LCU have a propensity toward emotion regulation difficulties and reactive aggression when they feel threatened.Reference Frick and Viding 5 By contrast, fMRI studies that have assessed CU traits have consistently shown that youths with DBD/HCU exhibit amygdala hypoactivity during the processing of consciousReference Marsh, Finger and Mitchell 25 , Reference Jones, Laurens, Herba, Barker and Viding 26 (but see Refs. Reference White, Williams and Brislin 27 , Reference Cohn, Popma and van den Brink 28 ) and unconscious fearful faces.Reference Viding, Sebastian and Dadds 23 These findings have been recently extended by White et al,Reference White, Marsh and Fowler 29 who showed that an atypical amygdala response to consciously processed fearful faces in youths with DBD/HCU is not secondary to an attentional deficit (ie, increased top-down control) but is specifically related to the CU component of psychopathic traits. These findings and othersReference Sylvers, Brennan and Lilienfeld 30 are inconsistent with the response modulation hypothesis, which posits that emotional deficits seen in psychopathy stem from a core deficit in selective attention that limits the processing of peripheral information.Reference Newman and Baskin-Sommers 31 In sum, amygdala hypoactivity could partly explain the high propensity for proactive aggression seen in youths with DBD/HCU.Reference Blair 8 In support of this view, a recent study showed that amygdala response to fearful faces in youths with DBD mediated the association between CU traits and proactive aggression.Reference Lozier, Cardinale, Van Meter and Marsh 32

Empathy, theory of mind, and morality

Empathy deficits in relation to DBD have been extensively documented,Reference Frick and Viding 5 with recent fMRI studies examining differences in neural response to perceived pain in others. The experience and observation of perceiving others in pain elicits activation in a network of regions, including the ACC, anterior insula, amygdala, and striatum, which mediate the affective perception of pain, as well as the somatosensory cortex, supplementary motor cortex, and periaqueductal gray, which mediate the perceived somatosensory sensation of pain.Reference Lamm, Decety and Singer 33 Surprisingly, Decety et al Reference Decety, Michalska, Akitsuki and Lahey 34 found that when viewing others in pain, youths with DBD had an increased neural response in regions including the anterior insula, anterior mid-cingulate, dorsal striatum, and amygdala compared to TD youths. This pattern of results was interpreted as reflecting enjoyment in the DBD youths when seeing someone else in pain. However, because CU traits were not measured by Decety et al, it is also possible that the youths with DBD were characterized by low levels of CU traits and associated high emotional reactivity, which could have led to the observed increase in neural response. This hypothesis is supported by two recent studies that include a measure of CU traits.Reference Marsh, Finger and Fowler 35 , Reference Lockwood, Sebastian and McCrory 36 Youths with DBD, as compared to TD youths, showed reduced activation to the perceived pain in others in the ACC, anterior insula, and inferior frontal gyrus.Reference Lockwood, Sebastian and McCrory 36 Crucially, within the DBD group, unique variance associated with callous traits was negatively correlated with the response in the ACC and anterior insula. Consistent with these results, Marsh et al Reference Marsh, Finger and Fowler 35 found that those with DBD/HCU, compared to TD youths, showed reduced response in the ACC and ventral striatum to perceived pain in others. These youths also showed reduced activity in the amygdala and insula in response to others’ pain, but not when imagining that the pain was their own. Importantly, the affective and interpersonal features of measured psychopathy were negatively related to the induced brain response to perceiving pain in others in the amygdala and ACC. Finally, using a more complex affective-processing task including cartoon vignettes, Sebastian et al Reference Sebastian, McCrory and Cecil 37 found that cartoons requiring understanding of distress in others within the context of social situations produced reduced amygdala and anterior insula activity in youths with DBD relative to TD youths. This reduced activation was negatively correlated with the unique variance associated with CU traits. Using the same task, O’Nions et al Reference O’Nions, Sebastian, McCrory, Chantiluke, Happe and Viding 38 found that cartoon scenarios that require the interpretation of others’ intentions did not induce a significantly different brain response in youths with DBD/HCU compared to TD youths. These results dovetail with behavioral and experimental data,Reference Jones, Happe, Gilbert, Burnett and Viding 13 and highlight the fact that youths with DBD/HCU do not have a deficit in understanding the mental states of others, as has been shown for children with autism spectrum disorder.Reference Jones, Happe, Gilbert, Burnett and Viding 13 , Reference O’Nions, Sebastian, McCrory, Chantiluke, Happe and Viding 38 Rather, they show reduced empathic responses to others’ distress cues.Reference Jones, Happe, Gilbert, Burnett and Viding 13

The immoral judgment seen in youths with DBD/HCU may result from impairments in emotional empathy and decision-making (see decision-making section below)—deficits thought to reflect dysfunctions within the amygdala–VMPFC circuitry and striatum.Reference Blair 8 Consistent with this view, a recent study found that compared to TD youths, those with DBD/HCU exhibited reduced amygdala response and reduced amygdala–OFC connectivity during moral judgments about legal actions.Reference Marsh, Finger and Fowler 39

Taken together, these results provide emerging evidence of neural vulnerabilities that might hamper successful socialization of youths with DBD/HCU, putting them at increased risk of displaying severe antisocial behavior and proactive aggression without feeling guilt or empathy for their victims.

Decision-making

Poor and rash decision-making is another central feature of DBD.Reference Viding and Seara-Cardoso 40 A large body of experimental data has identified an association between DBD, CU traits, and impairments in decision-making.Reference Blair 8 , Reference Rubia 19 Neural correlates of these associations have recently been explored within the context of functional neuroimaging studies. For example, compared to TD youths and youths with ADHD, youths with DBD showed a reduced neural response in the OFC during rewarded responses.Reference Rubia, Smith and Halari 41 In another study, when deciding between a low-risk/low-reward or high-risk/high-reward option, youths with DBD and substance use disorders displayed a reduced neural response in a number of regions, including the OFC, ACC, basal ganglia, insula, and amygdala, compared to TD youths.Reference Crowley, Dalwani and Mikulich-Gilbertson 42 In response to wins, DBD youths also had a lower response in the ACC, among other regions, compared to TD youths, but a higher response to losses in the OFC, among other regions.Reference Crowley, Dalwani and Mikulich-Gilbertson 42 However, as these studies did not take the influence of CU traits into account, it is unclear how these atypical responses relate to DBD and/or CU traits. Studies using standard learning (ie, passive avoidance learning) and reversal learning paradigms have also shown that, compared to TD youthsReference Finger, Marsh and Mitchell 43 , Reference Finger, Marsh and Blair 44 and youths with ADHD,Reference Finger, Marsh and Mitchell 43 youths with DBD/HCU exhibit atypical responses to reward and punishment within the OFC/VMPFC and caudate. According to a recent study by White et al,Reference White, Pope and Sinclair 45 these functional differences reflect compromised representations of reinforcement expectancies (ie, the expected value associated with a stimulus/action) within the VMPFC and aberrant prediction error signaling within the caudate (ie, the signal representing the difference between the level of reward/punishment received and the level expected, enabling reinforcement expectancies to be updated). These results are supported by a follow-up study that revealed that during a decision-making task with environmental (eg, threatening images) rather than monetary reinforcers, DBD youths showed reduced modulation of expected value information used to guide decision-making within bilateral caudate regions compared to TD youthsReference White, Fowler and Sinclair 46 (but see also Ref.Reference Crowley, Dalwani and Mikulich-Gilbertson 42 ). Given the lack of association between CU traits and expected value signals in the caudate in these two studies by White et al,Reference White, Pope and Sinclair 45 , Reference White, Fowler and Sinclair 46 one interpretation is that caudate dysfunction may represent a shared impairment in DBD that is not influenced by levels of CU traits. These results fit with behavioral studies that have shown that youths with DBD, irrespective of level of CU traits, display altered decision-making under riskReference Fairchild, Van Goozen, Calder, Stollery and Goodyer 47 and altered temporal discounting of future rewards.Reference White, Clanton and Brislin 48 Taken together, these results provide a potentially important account of why youths with DBD, including those with HCU, persistently engage in antisocial, aggressive, and risk-taking behaviors despite the resulting adverse consequences, such as exclusion from schools and imprisonment.

Table 1

Functional MRI studies of disruptive behaviour disorders in youths

Anatomical abbreviations: ACC – anterior cingulate cortex, DLPFC – dorsolateral prefrontal cortex, OFC – orbitofrontal cortex, PCC – posterior cingulate cortex, PFC – prefrontal cortex, VMPFC – ventromedial prefrontal cortex.

Note: ADHD – Attention-deficit hyperactivity-disorder, APSD – Antisocial Process Screening Device, ASD – antisocial substance dependence, CD – conduct disorder, CP – conduct problems, DBD – disruptive behaviour disorder, HCU – high callous/unemotional traits, ICU – Inventory of Callous-Unemotional Traits, K-SADS – Kiddie Schedule for Affective Disorders and Schizophrenia, LCU – low callous/unemotional traits, ODD – oppositional defiant disorder, PCL-YV – Psychopathy Checklist: Youth Version, TD – typically developing, YPI – Youth Psychopathic Traits Inventory

a CU traits in the Main Results refer to lack of empathy and guilt, and shallow affect. Individual authors may have used a different label, i.e. psychopathic traits, in their paper, but for ease of reading we have used CU traits consistently. The Measures of CU traits column lists the specific measure used.

Table 2

Structural MRI studies of disruptive behaviour disorders in youths

Anatomical abbreviations: ACC – anterior cingulate cortex, DLPFC – dorsolateral prefrontal cortex, OFC – orbitofrontal cortex, PCC – posterior cingulate cortex, PFC – prefrontal cortex, VMPFC – ventromedial prefrontal cortex.

Note: ADHD – Attention-deficit hyperactivity-disorder, APSD – Antisocial Process Screening Device, CD – conduct disorder, CP – conduct problems, DBD – disruptive behaviour disorder, DTI – diffusion tensor imaging, FA – fractional anisotropy, HCU – high callous/unemotional traits, ICU – Inventory of Callous-Unemotional Traits, K-SADS – Kiddie Schedule for Affective Disorders and Schizophrenia, LCU – low callous/unemotional traits, ODD – oppositional defiant disorder, PCL-YV – Psychopathy Checklist: Youth Version, SBM – surface based morphometry, TBSS – tract based spatial statistics, TD – typically developing, VBM – voxel based morphometry, YPI – Youth Psychopathic Traits Inventory.

a CU traits in the Main Results refer to lack of empathy and guilt, and shallow affect. Individual authors may have used a different label, i.e. psychopathic traits, in their paper, but for ease of reading we have used CU traits consistently. The Measures of CU traits column lists the specific measure used.

Structural Magnetic Resonance Imaging Evidence

Atypical neural responses in youths with DBD might be partly underpinned by differences in brain structure and/or connectivity. In this section, we first review sMRI studies on youths with DBD who were not subdivided using measures of CU traits. This is followed by a review of the small number of studies that have used sMRI data to examine the correlates of CU traits using group comparisons and/or parametric analyses.

sMRI studies on youths with DBD commonly report atypical brain structure in regions central to emotion processing and regulation, empathy, morality, and decision-making.Reference Rubia 19 , Reference Sterzer and Stadler 20 The majority of these studies used whole-brain and automated imaging analysis methods, such as voxel-based morphometry (VBM) to examine gray matter volume (GMV) and surface-based morphometry (SBM) to measure cortical thickness and folding. VBM studies consistently observed reduced GMV in fronto-temporal regions, such as the OFC, insula, and amygdala,Reference Fairchild, Hagan, Walsh, Passamonti, Calder and Goodyer 49 – Reference Sterzer, Stadler, Poustka and Kleinschmidt 55 with two studies reporting an overall reduction in GMV in youths with DBD (13%Reference Stevens and Haney-Caron 53 ; 6%Reference Huebner, Vloet and Marx 51 ). Negative correlations were also reported between the volume of the anterior insula and lifetime CD symptomsReference Fairchild, Passamonti and Hurford 54 and aggressive behavior.Reference Sterzer, Stadler, Poustka and Kleinschmidt 55 Studies using SBM have also shown that youths with DBD have thinner cortex or folding irregularities in areas of reduced GM, namely the OFC, insula, and ACC.Reference Fahim, He, Yoon, Chen, Evans and Pérusse 52 , Reference Hyatt, Haney-Caron and Stevens 56 Cortical thinning in more posterior regions, such as the superior temporal cortex and precuneus, was also detected,Reference Hyatt, Haney-Caron and Stevens 56 , Reference Wallace, White and Robustelli 57 as well as reduced volume of the striatum and the amygdala.Reference Wallace, White and Robustelli 57 By contrast, studies using diffusion tensor imaging (DTI) to examine the integrity of white matter tracts have thus far yielded inconsistent results, notably for the uncinate fasciculus, which connects the OFC to the amygdala. While no microstructural differences in this fiber tract have been reported between youths with DBD and TD youths,Reference Haney-Caron, Caprihan and Stevens 58 others do report increased fractional anisotropy (FA).Reference Passamonti, Fairchild and Fornito 59 – Reference Zhang, Gao and Shi 61 Interestingly, reduced FA in the arcuate fasciculusReference Li, Mathews, Wang, Dunn and Kronenberger 62 and increased FA in the corpus callosumReference Zhang, Zhu and Wang 63 in youths with DBD compared to TD youths has also been found. These mixed findings may partly reflect variation in methods of analysis (tract-based spatial statistics [TBSS] vs tractography), different age ranges, and, for some studies, a failure to account for levels of CU traits in the sample (eg,Reference Haney-Caron, Caprihan and Stevens 58 ).

To date, only three sMRI studies (two using VBM) have compared youths with DBD/HCU traits to TD youths. One study showed that a subclinical sample of boys with DBD/HCU traits compared to TD youths presented with increased GM concentration in the medial orbitofrontal and rostral/dorsal anterior cingulate cortices and bilateral temporal lobes—regions that are implicated in decision-making, morality, and empathy.Reference De Brito, Mechelli and Wilke 64 Given evidence of reduction in GM with increasing age in typical development,Reference Gogtay, Giedd and Lusk 65 these results were interpreted as reflecting delayed cortical maturation in the DBD/HCU sample. A follow-up study by De Brito et al Reference De Brito, McCrory and Mechelli 66 using the same sample supports this claim, with decreased white matter concentration observed in boys with DBD/HCU compared to TD youths in frontal, ACC, and temporal regions, consistent with the previous study by De Brito et al.Reference De Brito, Mechelli and Wilke 64 Follow-up analyses on twins revealed that some of the GM differences observed by De Brito et al Reference De Brito, Mechelli and Wilke 64 might represent a potential endophenotype for DBD/HCU.Reference Rijsdijsk, Viding and De Brito 67 Despite evidence of group differences in functional connectivity, Finger et al Reference Finger, Marsh and Blair 68 did not observe differences in structural connectivity within the uncinate fasiculus or other white matter tracts when comparing DBD/HCU youths and TD youths using DTI.

sMRI studies investigating the association between CU traits and VBM, SBM, and DTI metrics have revealed somewhat inconsistent findings. For example, a VBM study using a large sample of male adolescent prisoners with DBD (N=191) revealed negative associations between GM volume and psychopathic traits in the posterior cingulate cortex and OFC, extending into temporal poles and parahippocampal cortex.Reference Ermer, Cope, Nyalakanti, Calhoun and Kiehl 69 This pattern of results was recently replicated in females.Reference Cope, Ermer, Nyalakanti, Calhoun and Kiehl 70 In contrast, Fairchild et al Reference Fairchild, Hagan, Walsh, Passamonti, Calder and Goodyer 49 found that, across DBD and TD females, CU traits were positively correlated with bilateral OFC GM volume, but negatively correlated with anterior insula and striatal GM volume. In a large sample of males with DBD (N=63), Fairchild et al Reference Fairchild, Passamonti and Hurford 54 found no relationship between GM volumes and CU traits. Using SBM, a negative association between CU traits and cortical thickness in the superior temporal cortex has also been reported in youths with DBD.Reference Wallace, White and Robustelli 57 Whilst Finger et al Reference Finger, Marsh and Blair 68 did not find an association between CU traits and DTI metrics, a recent study reported a positive trend between psychopathic traits and FA in the left uncinate fasciculus,Reference Sarkar, Craig and Catani 60 and yet another revealed a negative trend between CU traits and FA values in the left uncinate fasciculus in males with DBD.Reference Zhang, Gao and Shi 61

Neuroimaging Evidence: Sex Matters

Sex differences in DBD are presently overlooked, with most samples in neuroimaging studies of DBD including males only. Thus, it is unclear whether the current evidence base also applies to females.Reference Moffitt, Arseneault and Jaffee 14 Given evidence of sex differences in brain development and brain functioning in TD youths,Reference Lenroot and Giedd 71 it is conceivable that females with DBD might present different impairments from those observed in males with DBD. Yet, to date, only one fMRI study has compared females with DBD to TD females, reporting that those with DBD exhibited reduced medial OFC and increased anterior insula activity to sad, angry, and neutral faces, which is indicative of general face processing impairments.Reference Fairchild, Hagan, Passamonti, Walsh, Goodyer and Calder 72 These results contrast with those observed in males using the same task, whereby males with DBD, compared to TD youths, exhibited increased activity to neutral faces and reduced activity to angry faces, which is indicative of more specific impairments in emotion processing.Reference Passamonti, Fairchild and Goodyer 73

In terms of sMRI studies, Fairchild et al Reference Fairchild, Hagan, Walsh, Passamonti, Calder and Goodyer 49 found that both males and females with CD showed similar reduction in GM volume in the amygdala compared to TD youths, which is consistent with evidence that both males and females with DBD show impaired fear conditioning. Crucially, however, a sex by diagnosis interaction was observed in the bilateral anterior insula: DBD females showed reduced GM volume compared to TD females, with the opposite pattern observed among males. A recent DTI study also reported a sex by diagnosis interaction whereby males with DBD, compared to TD males, had higher FA and lower radial diffusivity of the bilateral uncinate fasciculus, but no group differences were observed between the females with DBD and the TD females. Interestingly, higher FA and lower radial diffusivity in the uncinate fasciculus were found in males with DBD compared to females with DBD.Reference Zhang, Gao and Shi 61

The above results suggest that both males and females with DBD are characterized by functional and structural abnormalities in key regions implicated in affective processing, empathy, and decision-making, but the nature of these deficits within a number of regions varies across sex. Our group is currently investigating the potential origins and implications of these differences within the context of the FemNAT-CD study (http://www.femnat-cd.eu), a large multisite European study examining environmental and neurobiological factors associated with the development of DBD in male and female youths.

Implications for Treatment

The neuroimaging findings reviewed in this article add to the existing body of genetic, behavioral, and experimental evidence by highlighting that youths with DBD/HCU and DBD/LCU are characterized by different neurocognitive vulnerabilities, which are likely to influence intervention implementations and outcomes. Treatments for these subgroups should be tailored to their unique affective, neurocognitive, and motivational styles to maximize their effectiveness.Reference Frick, Ray, Thornton and Kahn 11 Despite evidence that youths with DBD/HCU are less responsive to treatment, and that their antisocial behavior is under strong genetic influence, these youths should not be considered “untreatable.”Reference Viding and McCrory 9 , Reference Frick, Ray, Thornton and Kahn 11 An increasing body of evidence shows that intensive and tailored treatments can reduce antisocial behavior and levels of CU traits in these youths, particularly when their reward-oriented style is primed.Reference Frick, Ray, Thornton and Kahn 11 Neuroimaging evidence suggests that such interventions should seek to increase sensitivity to other’s distress cues, and improve prediction error and expected value signaling during decision-making, possibly through a two-pronged approach that combines behavioral and pharmacological interventions.Reference Blair 8 , Reference Dadds and Rhodes 74 While youths with DBD/LCU might also benefit from behavioral and pharmacological interventions that target decision-making, in contrast to youths with DBD/HCU, they are more likely to respond to interventions that focus on increasing anger control/emotion regulation and reducing harsh and inconsistent parenting, given that these children are more likely to come from dysfunctional families.Reference Frick, Ray, Thornton and Kahn 11 Clearly, any form of intervention should systematically account for the influence of the level of CU traits on treatment response.Reference Lockwood, Sebastian and McCrory 36 , Reference Sebastian, McCrory and Cecil 37

Conclusions

There is increasing recognition among the research and clinical community that youths with DBD are characterized by different patterns of behavioral problems and affective profiles, reflecting different underlying causal mechanisms.Reference Frick, Ray, Thornton and Kahn 11 The evidence base accumulated over the last 20 years has shown that subtyping youths with DBD based on their level of CU traits identifies two subgroups of antisocial youths, who are characterized by different vulnerabilities and behavioral profiles.Reference Viding and McCrory 9 , Reference Frick, Ray, Thornton and Kahn 11 Consistent with experimental data showing high emotional reactivity in DBD/LCU and low emotional reactivity in DBD/HCU, recent fMRI evidence has shown that high levels of CU traits in DBD are associated with hyporesponsivity to affective stimuli and others’ distress in cortical and subcortical regions, such as the anterior insula, ACC, and amygdala. In contrast, low levels of CU traits are associated with heightened response in those regions. No sMRI study has directly compared these two subgroups, and those studies that have examined the associations between CU traits and sMRI indices have produced mixed findings. The paucity of neuroimaging investigations that have focused on females and on the role of sex differences is another important gap in this work. It is hoped that the mounting body of neuroimaging evidence investigating the role of CU traits on brain function and structure could inform the development of tailored treatments for both male and female youths with DBD.

Disclosures

Rosalind Baker and Roberta Clanton have nothing to disclose. Jack Rogers has the following disclosure: University of Birmingham: employee/researcher, salary. Stéphane De Brito has the following disclosures: European Communities Seventh Framework Programme: research, grant; Research Fellowship from the Swiss National Science Foundation: research, grant; Centre for Integrated Molecular Brain Imaging: speaker, speaker’s fee; Child Mental Health Centre, speaker, speaker’s fee.

Footnotes

**

Rosalind H. Baker and Roberta L. Clanton contributed equally to this work.

*

Rosalind Baker, Jack Rogers, and Stéphane De Brito are supported by the European Commission’s Seventh Framework Programme (FP7/2007–2013) under Grant Agreement no. 602407 (FemNAT-CD) (http://ec.europa.eu). Roberta Clanton is supported by a Ph.D. studentship from the College of Life and Environmental Sciences, University of Birmingham. Stéphane A. De Brito was supported by a research fellowship from the Swiss National Science Foundation (SNSF PA00P1_139586). We thank Dr. Graeme Fairchild for his comments on a previous version of the manuscript.

References

1. AmericanPsychiatricAssociation. Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Washington, DC: American Psychiatric Association; 2013.Google Scholar
2. Scott, S, Knapp, M, Henderson, J, Maughan, B. Financial cost of social exclusion: follow up study of antisocial children into adulthood. BMJ. 2001; 323(7306): 191.CrossRefGoogle ScholarPubMed
3. De Brito, SA, Hodgins, S. Antisocial personality disorder. In: McMurran M, Howard R, eds. Personality, Personality Disorder and Violence. Vol. 42. Chichester, UK: Wiley-Blackwell; 2009: 133–153.Google Scholar
4. Odgers, CL, Caspi, A, Broadbent, JM, et al. Prediction of differential adult health burden by conduct problem subtypes in males. Arch Gen Psychiatry. 2007; 64(4): 476–484.CrossRefGoogle ScholarPubMed
5. Frick, PJ, Viding, E. Antisocial behavior from a developmental psychopathology perspective. Dev Psychopathol. 2009; 21(4): 1111–1131.Google Scholar
6. Frick, PJ, Marsee, MA. Psychopathy and developmental pathways to antisocial behavior in youth. In de Haan M, Gunnar MR, eds. Handbook of Psychopathy. New York: Guilford Press; 2006: 353–374.Google Scholar
7. Hare, RD. Manual for the Revised Psychopathy Checklist, 2nd ed. Toronto, ON: Multi-Health Systems; 2003.Google Scholar
8. Blair, RJR. The neurobiology of psychopathic traits in youths. Nat Rev Neurosci. 2013; 14(11): 786–799.CrossRefGoogle ScholarPubMed
9. Viding, E, McCrory, EJ. Genetic and neurocognitive contributions to the development of psychopathy. Dev Psychopathol. 2012; 24(3): 969–983.CrossRefGoogle Scholar
10. Viding, E, Blair, RJR, Moffitt, TE, Plomin, R. Evidence for substantial genetic risk for psychopathy in 7-year-olds. J Child Psychol Psychiatry. 2005; 46(6): 592–597.CrossRefGoogle ScholarPubMed
11. Frick, PJ, Ray, JV, Thornton, LC, Kahn, RE. Can callous-unemotional traits enhance the understanding, diagnosis, and treatment of serious conduct problems in children and adolescents? A comprehensive review. Psychol Bull. 2014; 140(1): 1–57.Google Scholar
12. Dadds, MR, Perry, Y, Hawes, DJ, et al. Attention to the eyes and fear-recognition deficits in child psychopathy. Br J Psychiatry. 2006; 189(3): 280–281.CrossRefGoogle Scholar
13. Jones, AP, Happe, FGE, Gilbert, F, Burnett, S, Viding, E. Feeling, caring, knowing: different types of empathy deficit in boys with psychopathic tendencies and autism spectrum disorder. J Child Psychol Psychiatry. 2010; 51(11): 1188–1197.Google Scholar
14. Moffitt, TE, Arseneault, L, Jaffee, SR, et al. Research review: DSM-V conduct disorder: research needs for an evidence base. J Child Psychol Psychiatry. 2008; 49(1): 3–33.Google Scholar
15. Cohen, P, Cohen, J, Kasen, S, et al. An epidemiologic study of disorders in late childhood and adolescence, 1: age-specific and gender-specific prevalance. J Child Psychol Psychiatry. 1993; 34(6): 851–867.Google Scholar
16. Moffitt, TE, Caspi, A, Rutter, M, Silva, PA. Sex Differences in Antisocial Behaviour: Conduct Disorder, Delinquency and Violence in the Dunedin Longitudinal Study. Cambridge, UK: Cambridge University Press; 2001.Google Scholar
17. Frick, PJ, Dickens, C. Current perspectives on conduct disorder. Curr Psychiatry Rep. 2006; 8(1): 59–72.Google Scholar
18. Lang, PJ, Bradley, MM, Cuthbert, BN. International Affective Picture System (IAPS): Technical Manual and Affective Ratings. Gainesville, FL: The Center for Research in Psychophysiology, University of Florida; 1999.Google Scholar
19. Rubia, K. “Cool” inferior frontostriatal dysfunction in attention-deficit/hyperactivity disorder versus “hot” ventromedial orbitofrontal-limbic dysfunction in conduct disorder: a review. Biol Psychiatry. 2011; 69(12): e69–e87.Google Scholar
20. Sterzer, P, Stadler, C. Neuroimaging of aggressive and violent behaviour in children and adolescents. Front Behav Neurosci. 2009; 3: 35.Google Scholar
21. Herpertz, SC, Huebner, T, Marx, I, et al. Emotional processing in male adolescents with childhood-onset conduct disorder. J Child Psychol Psychiatry. 2008; 49(7): 781–791.Google Scholar
22. Sterzer, P, Stadler, C, Krebs, A, Kleinschmidt, A, Poustka, F. Abnormal neural responses to emotional visual stimuli in adolescents with conduct disorder. Biol Psychiatry. 2005; 57(1): 7–15.CrossRefGoogle ScholarPubMed
23. Viding, E, Sebastian, CL, Dadds, MR, et al. Amygdala response to preattentive masked fear in children with conduct problems: the role of callous-unemotional traits. Am J Psychiatry. 2012; 169(10): 1109–1116.Google Scholar
24. Sebastian, C, McCrory, E, Dadds, M, et al. Neural responses to fearful eyes in children with conduct problems and varying levels of callous–unemotional traits. Psychol Med. 2014; 44(1): 99–109.CrossRefGoogle ScholarPubMed
25. Marsh, AA, Finger, EC, Mitchell, DG, et al. Reduced amygdala response to fearful expressions in children and adolescents with callous-unemotional traits and disruptive behavior disorders. Am J Psychiatry. 2008; 165(6): 712–720.CrossRefGoogle ScholarPubMed
26. Jones, AP, Laurens, KR, Herba, CM, Barker, GJ, Viding, E. Amygdala hypoactivity to fearful faces in boys with conduct problems and callous-unemotional traits. Am J Psychiatry. 2009; 166(1): 95–102.Google Scholar
27. White, SF, Williams, WC, Brislin, SJ, et al. Reduced activity within the dorsal endogenous orienting of attention network to fearful expressions in youth with disruptive behavior disorders and psychopathic traits. Dev Psychopathol. 2012; 24(3): 1105–1116.CrossRefGoogle ScholarPubMed
28. Cohn, MD, Popma, A, van den Brink, W, et al. Fear conditioning, persistence of disruptive behavior and psychopathic traits: an fMRI study. Translational Psychiatry. 2013; 3: e319.Google Scholar
29. White, SF, Marsh, AA, Fowler, KA, et al. Reduced amygdala response in youths with disruptive behavior disorders and psychopathic traits: decreased emotional response versus increased top-down attention to nonemotional features. Am J Psychiatry. 2012; 169(7): 750–758.CrossRefGoogle ScholarPubMed
30. Sylvers, PD, Brennan, PA, Lilienfeld, SO. Psychopathic traits and preattentive threat processing in children: a novel test of the fearlessness hypothesis. Psychol Sci. 2011; 22(10): 1280–1287.CrossRefGoogle ScholarPubMed
31. Newman, JP, Baskin-Sommers, AR. Early selective attention abnormalities in psychopathy: Implications for self-regulation. In: Posner MI, ed. Cogntive Neuroscience of Attention, 2nd ed. New York: Guilford Press; 2011: 421–440.Google Scholar
32. Lozier, LM, Cardinale, EM, Van Meter, JW, Marsh, AA. Mediation of the relationship between callous-unemotional traits and proactive aggression by amygdala response to fear among children with conduct problems. JAMA Psychiatry. 2014; 71(6): 627–636.Google Scholar
33. Lamm, C, Decety, J, Singer, T. Meta-analytic evidence for common and distinct neural networks associated with directly experienced pain and empathy for pain. Neuroimage. 2011; 54(3): 2492–2502.Google Scholar
34. Decety, J, Michalska, KJ, Akitsuki, Y, Lahey, BB. Atypical empathic responses in adolescents with aggressive conduct disorder: a functional MRI investigation. Biol Psychol. 2009; 80(2): 203–211.Google Scholar
35. Marsh, AA, Finger, EC, Fowler, KA, et al. Empathic responsiveness in amygdala and anterior cingulate cortex in youths with psychopathic traits. J Child Psychol Psychiatry. 2013; 54(8): 900–910.CrossRefGoogle ScholarPubMed
36. Lockwood, PL, Sebastian, CL, McCrory, EJ, et al. Association of callous traits with reduced neural response to others’ pain in children with conduct problems. Curr Biol. 2013; 23(10): 901–905.CrossRefGoogle ScholarPubMed
37. Sebastian, CL, McCrory, EJP, Cecil, CAM, et al. Neural responses to affective and cognitive theory of mind in children with conduct problems and varying levels of callous-unemotional traits. Arch Gen Psychiatry. 2012; 69(8): 814–822.CrossRefGoogle ScholarPubMed
38. O’Nions, E, Sebastian, CL, McCrory, E, Chantiluke, K, Happe, F, Viding, E. Neural bases of theory of mind in children with autism spectrum disorders and children with conduct problems and callous-unemotional traits. Dev Sci. 2014; 17(5): 786–796.Google Scholar
39. Marsh, AA, Finger, EC, Fowler, KA, et al. Reduced amygdala-orbitofrontal connectivity during moral judgments in youths with disruptive behavior disorders and psychopathic traits. Psychiatry Res. 2011; 194(3): 279–286.Google Scholar
40. Viding, E, Seara-Cardoso, A. Why do children with disruptive behavior disorders keep making bad choices? Am J Psychiatry. 2013; 170(3): 253–255.CrossRefGoogle ScholarPubMed
41. Rubia, K, Smith, AB, Halari, R, et al. Disorder-specific dissociation of orbitofrontal dysfunction in boys with pure conduct disorder during reward and ventrolateral prefrontal dysfunction in boys with pure ADHD during sustained attention. Am J Psychiatry. 2009; 166(1): 83–94.Google Scholar
42. Crowley, TJ, Dalwani, MS, Mikulich-Gilbertson, SK, et al. Risky decisions and their consequences: Neural processing by boys with antisocial substance disorder. PLoS One. 2010; 5(9): e12835.Google Scholar
43. Finger, EC, Marsh, AA, Mitchell, DG, et al. Abnormal ventromedial prefrontal cortex function in children with psychopathic traits during reversal learning. Arch Gen Psychiatry. 2008; 65(5): 586–594.CrossRefGoogle ScholarPubMed
44. Finger, EC, Marsh, AA, Blair, KS, et al. Disrupted reinforcement signaling in the orbitofrontal cortex and caudate in youths with conduct disorder or oppositional defiant disorder and a high level of psychopathic traits. Am J Psychiatry. 2011; 168(2): 152–162.Google Scholar
45. White, SF, Pope, K, Sinclair, S, et al. Disrupted expected value and prediction error signaling in youths with disruptive behavior disorders during a passive avoidance task. Am J Psychiatry. 2013; 170(3): 315–323.Google Scholar
46. White, SF, Fowler, KA, Sinclair, S, et al. Disrupted expected value signaling in youth with disruptive behavior disorders to environmental reinforcers. J Am Acad Child Adolesc Psychiatry. 2014; 53(5): 579–588.Google Scholar
47. Fairchild, G, Van Goozen, SHM, Calder, AJ, Stollery, SJ, Goodyer, IM. Deficits in facial expression recognition in male adolescents with early-onset or adolescence-onset conduct disorder. J Child Psychol Psychiatry. 2009; 50(5): 627–636.CrossRefGoogle ScholarPubMed
48. White, SF, Clanton, R, Brislin, SJ, et al. Temporal discounting and conduct disorder in adolescents. J Personal Disord. 2014; 28(1): 5–18.Google Scholar
49. Fairchild, G, Hagan, CC, Walsh, ND, Passamonti, L, Calder, AJ, Goodyer, IM. Brain structure abnormalities in adolescent girls with conduct disorder. J Child Psychol Psychiatry. 2013; 54(1): 86–95.Google Scholar
50. Olvera, R, Glahn, D, O’Donnell, L, et al. Cortical volume alterations in conduct disordered adolescents with and without bipolar disorder. Journal of Clinical Medicine. 2014; 3(2): 416–431.Google Scholar
51. Huebner, T, Vloet, TD, Marx, I, et al. Morphometric brain abnormalities in boys with conduct disorder. J Am Acad Child Adolesc Psychiatry. 2008; 47(5): 540–547.Google Scholar
52. Fahim, C, He, Y, Yoon, U, Chen, J, Evans, A, Pérusse, D. Neuroanatomy of childhood disruptive behavior disorders. Aggressive Behavior. 2011; 37(4): 326–337.Google Scholar
53. Stevens, MC, Haney-Caron, E. Comparison of brain volume abnormalities between ADHD and conduct disorder in adolescence. J Psychiatry Neurosci. 2012; 37(6): 389–398.Google Scholar
54. Fairchild, G, Passamonti, L, Hurford, G, et al. Brain structure abnormalities in early-onset and adolescent-onset conduct disorder. Am J Psychiatry. 2011; 168(6): 624–633.Google Scholar
55. Sterzer, P, Stadler, C, Poustka, F, Kleinschmidt, A. A structural neural deficit in adolescents with conduct disorder and its association with lack of empathy. Neuroimage. 2007; 37(1): 335–342.CrossRefGoogle ScholarPubMed
56. Hyatt, CJ, Haney-Caron, E, Stevens, MC. Cortical thickness and folding deficits in conduct-disordered adolescents. Biol Psychiatry. 2012; 72(3): 207–214.Google Scholar
57. Wallace, GL, White, SF, Robustelli, B, et al. Cortical and subcortical abnormalities in youths with conduct disorder and elevated callous-unemotional traits. J Am Acad Child Adolesc Psychiatry. 2014; 53(4): 456–465.Google Scholar
58. Haney-Caron, E, Caprihan, A, Stevens, MC. DTI-measured white matter abnormalities in adolescents with conduct disorder. J Psychiatr Res. 2014; 48(1): 111–120.Google Scholar
59. Passamonti, L, Fairchild, G, Fornito, A, et al. Abnormal anatomical connectivity between the amygdala and orbitofrontal cortex in conduct disorder. PLoS One. 2012; 7(11): e48789.CrossRefGoogle ScholarPubMed
60. Sarkar, S, Craig, MC, Catani, M, et al. Frontotemporal white-matter microstructural abnormalities in adolescents with conduct disorder: a diffusion tensor imaging study. Psychol Med. 2013; 43(2): 401–411.CrossRefGoogle ScholarPubMed
61. Zhang, J, Gao, J, Shi, H, et al. Sex differences of uncinate fasciculus structural connectivity in individuals with conduct disorder. BioMed Research International. 2014; 2014: 673165. http://dx.doi.org/10.1155/2014/673165.Google Scholar
62. Li, TQ, Mathews, VP, Wang, Y, Dunn, D, Kronenberger, W. Adolescents with disruptive behavior disorder investigated using an optimized MR diffusion tensor imaging protocol. Ann N Y Acad Sci. 2005; 1064: 184–192.Google Scholar
63. Zhang, J, Zhu, X, Wang, X, et al. Increased structural connectivity in corpus callosum in adolescent males with conduct disorder. J Am Acad Child Adolesc Psychiatry. 2014; 53(4): 466–475.Google Scholar
64. De Brito, SA, Mechelli, A, Wilke, M, et al. Size matters: increased grey matter in boys with conduct problems and callous-unemotional traits. Brain. 2009; 132(Pt 4): 843–852.CrossRefGoogle ScholarPubMed
65. Gogtay, N, Giedd, JN, Lusk, L, et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci U S A. 2004; 101(21): 8174–8179.Google Scholar
66. De Brito, SA, McCrory, EJ, Mechelli, A, et al. Small, but not perfectly formed: decreased white matter concentration in boys with psychopathic tendencies. Mol Psychiatry. 2011; 16(5): 476–477.Google Scholar
67. Rijsdijsk, FV, Viding, E, De Brito, S, et al. Heritable variations in gray matter concentration as a potential endophenotype for psychopathic traits. Arch Gen Psychiatry. 2010; 67(4): 406–413.Google Scholar
68. Finger, EC, Marsh, A, Blair, KS, et al. Impaired functional but preserved structural connectivity in limbic white matter tracts in youth with conduct disorder or oppositional defiant disorder plus psychopathic traits. Psychiatry Res. 2012; 202(3): 239–244.Google Scholar
69. Ermer, E, Cope, LM, Nyalakanti, PK, Calhoun, VD, Kiehl, KA. Aberrant paralimbic gray matter in incarcerated male adolescents with psychopathic traits. J Am Acad Child Adolesc Psychiatry. 2013; 52(1): 94–103.Google Scholar
70. Cope, LM, Ermer, E, Nyalakanti, PK, Calhoun, VD, Kiehl, KA. Paralimbic gray matter reductions in incarcerated adolescent females with psychopathic traits. J Abnorm Child Psychol. 2014; 42(4): 659–668.CrossRefGoogle ScholarPubMed
71. Lenroot, RK, Giedd, JN. Sex differences in the adolescent brain. Brain Cogn. 2010; 72(1): 46–55.Google Scholar
72. Fairchild, G, Hagan, CC, Passamonti, L, Walsh, ND, Goodyer, IM, Calder, AJ. Atypical neural responses during face processing in female adolescents with conduct disorder. J Am Acad Child Adolesc Psychiatry. 2014; 53(6): 677–687.Google Scholar
73. Passamonti, L, Fairchild, G, Goodyer, IM, et al. Neural abnormalities in early-onset and adolescence-onset conduct disorder. Arch Gen Psychiatry. 2010; 67(7): 729–738.Google Scholar
74. Dadds, MR, Rhodes, T. Aggression in young children with concurrent callous-unemotional traits: can the neurosciences inform progress and innovation in treatment approaches? In: Hodgins S, Viding E, Plodowski A, eds. The Neurobiological Basis of Violence: Science and Rehabilitation. Vol. 363. New York: Oxford University Press; 2008: 85–99.Google Scholar
75. Dalwani, Manish, Sakai, JT, Mikulich-Gilberton, SK, et al. Reduced cortical gray matter volume in male adolescents with substance and conduct problems. Drug and Alcohol Dependence. 2011; 118(2-3): 295–305.Google Scholar
76. White, Stuart, F, Brislin, SJ, Sinclair, S, et al. The relationship between large cavum septum pellucidum and antisocial behavior, callous‐unemotional traits and psychopathy in adolescents. Journal of Child Psychology and Psychiatry. 2013; 54(5): 575–581.Google Scholar
77. Stadler, C, Sterzer, P, Schmeck, K, Krebs, A, Kleinschmidt, A. Reduced anterior cingulate activation in aggressive children and adolescents during affective stimulation: Association with temperament traits. Journal of Psychiatric Research. 2007; 41: 410–417.Google Scholar
Figure 0

Table 1 Functional MRI studies of disruptive behaviour disorders in youths

Figure 1

Table 2 Structural MRI studies of disruptive behaviour disorders in youths