The familial basis of facial emotion recognition deficits in adolescents with conduct disorder and their unaffected relatives

Background. There is accumulating evidence of impairments in facial emotion recognition in adolescents with conduct disorder (CD). However, the majority of studies in this area have only been able to demonstrate an association, rather than a causal link, between emotion recognition deficits and CD. To move closer towards understanding the causal pathways linking emotion recognition problems with CD, we studied emotion recognition in the unaffected first-degree relatives of CD probands, as well as those with a diagnosis of CD. Method. Using a family-based design, we investigated facial emotion recognition in probands with CD (n = 43), their unaffected relatives (n = 21), and healthy controls (n = 38). We used the Emotion Hexagon task, an alternative forced-choice task using morphed facial expressions depicting the six primary emotions, to assess facial emotion recognition accuracy. Results. Relative to controls, the CD group showed impaired recognition of anger, fear, happiness, sadness and surprise (all p < 0.005). Similar to probands with CD, unaffected relatives showed deficits in anger and happiness recognition relative to controls (all p < 0.008), with a trend toward a deficit in fear recognition. There were no significant differences in performance between the CD probands and the unaffected relatives following correction for multiple comparisons. Conclusions. These results suggest that facial emotion recognition deficits are present in adolescents who are at increased familial risk for developing antisocial behaviour, as well as those who have already developed CD. Consequently, impaired emotion recognition appears to be a viable familial risk marker or candidate endophenotype for CD

Mapping the structural organization of the brain in conduct disorder: replication of findings in two independent samples.

BACKGROUND: Neuroimaging methods that allow researchers to investigate structural covariance between brain regions are increasingly being used to study psychiatric disorders. Structural covariance analyses are particularly well suited for studying disorders with putative neurodevelopmental origins as they appear sensitive to changes in the synchronized maturation of different brain regions. We assessed interregional correlations in cortical thickness as a measure of structural covariance, and applied this method to investigate the coordinated development of different brain regions in conduct disorder (CD). We also assessed whether structural covariance measures could differentiate between the childhood-onset (CO-CD) and adolescence-onset (AO-CD) subtypes of CD, which may differ in terms of etiology and adult outcomes. METHODS: We examined interregional correlations in cortical thickness in male youths with CO-CD or AO-CD relative to healthy controls (HCs) in two independent datasets. The age range in the Cambridge sample was 16-21 years (mean: 18.0), whereas the age range of the Southampton sample was 13-18 years (mean: 16.7). We used FreeSurfer to perform segmentations and applied structural covariance methods to the resulting parcellations. RESULTS: In both samples, CO-CD participants displayed a strikingly higher number of significant cross-cortical correlations compared to HC or AO-CD participants, whereas AO-CD participants presented fewer significant correlations than HCs. Group differences in the strength of the interregional correlations were observed in both samples, and each set of results remained significant when controlling for IQ and comorbid attention-deficit/hyperactivity disorder symptoms. CONCLUSIONS: This study provides new evidence for quantitative differences in structural brain organization between the CO-CD and AO-CD subtypes, and supports the hypothesis that both subtypes of CD have neurodevelopmental origins.This research was funded by Wellcome Trust grant 083140 (Fairchild, Goodyer), Medical Research Council project U.1055.02.001.00001.01 (Calder), an Adventure in Research grant from Southampton University (Fairchild), a PhD studentship from Southampton University (Sully), and the Betty Behrens Research Fellowship at Clare Hall, Cambridge University (Passamonti).This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1111/jcpp.1258

Reduced Default Mode Connectivity in Adolescents With Conduct Disorder

Objective: conduct disorder (CD) is characterized by impulsive, aggressive, and antisocial behaviors that may be related to deficits in empathy and moral reasoning. The brain’s default mode network (DMN) has been implicated in self-referential cognitive processes of this kind.Method: we examined connectivity between key nodes of the DMN in 29 male adolescents with CD and 29 age- and sex-matched typically-developing adolescents. We ensured that group differences in DMN connectivity were not explained by comorbidity with other disorders by systematically controlling for the effects of substance use disorders (SUDs), attention-deficit/hyperactivity disorder (ADHD) symptoms, psychopathic traits, and other common mental health problems.Results: only after adjusting for co-occurring ADHD symptoms, the group with CD showed hypo-connectivity between core DMN regions relative to typically-developing controls. ADHD symptoms themselves were associated with DMN hyperconnectivity. There was no effect of psychopathic traits on DMN connectivity in the group with CD, and the key results were unchanged when controlling for SUDs and other common mental health problems.Conclusion: future research should directly investigate the possibility that the aberrant DMN connectivity observed in the current study contributes to CD-related deficits in empathy and moral reasoning, and examine self-referential cognitive processes in CD more generall

Improving Site-Specific Radiological Performance Assessments -13431

ABSTRACT An improved approach is presented for conducting complete and defensible radiological site-specific performance assessments (PAs) to support radioactive waste disposal decisions. The basic tenets of PA were initiated some thirty years ago, focusing on geologic disposals and evaluating compliance with regulations. Some of these regulations were inherently probabilistic (i.e., addressing uncertainty in a quantitative fashion), such as the containment requirements of the U.S. Environmental Protection Agency&apos;s (EPA&apos;s) 40 CFR 191, Environmental Radiation Protection Standards for Management and Disposal of Spent Nuclear Fuel, §191.13 [1]. Methods of analysis were developed to meet those requirements, but at their core early PAs used &quot;conservative&quot; parameter values and modeling approaches. This limited the utility of such PAs to compliance evaluation, and did little to inform decisions about optimizing disposal, closure and long-term monitoring and maintenance, or, in general, maintaining doses &quot;as low as reasonably achievable&quot; (ALARA). This basic approach to PA development in the United States was employed essentially unchanged through the end of the 20 th century, principally by the U.S. Department of Energy (DOE). Performance assessments developed in support of private radioactive waste disposal operations, regulated by the U.S. Nuclear Regulatory Commission (NRC) and its agreement states, were typically not as sophisticated. Discussion of new approaches to PA is timely, since at the time of this writing, the DOE is in the midst of revising its Order 435.1, Radioactive Waste Management Over the previous decade, theoretical developments and improved computational technology have provided the foundation for integrating decision analysis (DA) concepts and objective-focused thinking, plus a Bayesian approach to probabilistic modeling and risk analysis, to guide improvements in PA. This decision-making approach, The full DA approach to PA is described, from explicitly incorporating societal values through stakeholder involvement to model building. Model building involves scoping by considering features, events, processes, and exposure scenarios (FEPSs), development of a conceptual site model (CSM), translation into numerical models and subsequent computation, and model evaluation. These are implemented in a cycle of uncertainty analysis, sensitivity analysis and value of information analysis so that uncertainty can be reduced until sufficient confidence is gained in the decisions to be made. This includes the traditional focus on hydrogeological processes, but also places emphasis on other FEPSs such as biotically-induced transport and human exposure phenomena. The significance of human exposure scenarios is emphasized by modifying the traditional acronym &quot;FEPs&quot; to include them, hence &quot;FEPSs&quot;. WM2013 Conference, February 24 -28, 2013, Phoenix, Arizona, USA. 2 The radioactive waste community is also recognizing that disposal sites are to be considered a national (or even global) resource. As such, there is a pressing need to optimize their utility within the constraints of protecting human health and the environment. Failing to do so will result in the need for additional sites or options for storing radioactive waste temporarily, assuming a continued need for radioactive waste disposal. Optimization should be performed using DA, including economic analysis, invoked if necessary through the ALARA process. The economic analysis must recognize the cost of implementation (disposal design, closure, maintenance, etc.), and intra-and inter-generational equity in order to ensure that the best possible radioactive waste management decisions are made for the protection of both current and future generations. In most cases this requires consideration of population or collective risk