Associations between childhood adversity, cognitive schemas and attenuated psychotic symptoms

Aim: Childhood Adversity (CA) is strongly linked to psychotic-like symptoms across the clinical spectrum, though the mechanisms underlying these associations remain poorly understood. Negative cognitive schemas are associated with both CA exposure and psychotic symptoms, highlighting the possibility that cognitive schemas may be a key risk pathway. The purpose of this study was to determine whether negative cognitive schemas mediate the association between CA and specific attenuated psychotic symptoms in a large sample of clinical-high risk youth. Given the variability in experiences that encompass CA (eg, abuse, neglect and poverty) and attenuated psychotic symptoms (eg, suspiciousness and perceptual abnormalities), we also tested whether these associations differ by CA type (threat vs deprivation) and attenuated positive psychotic symptom domain. Methods: Data were collected from 531 clinical-high risk youth between 12 and 35 years of age (mean = 18.80, SD = 4.21) who completed a clinical assessment that included the Structured Interview of Prodromal Syndromes (SIPS), Childhood Trauma and Abuse scale and questionnaires on cognitive schemas and depressive symptoms. Results: No direct effects of threat or deprivation exposure on any of the psychotic symptom domains were found. However, there was a unique indirect effect of threat, but not deprivation, on delusional thinking and suspiciousness through negative cognitive schemas about others. Conclusion: Cognitive vulnerability in the form of negative schemas about others may be one mechanism linking childhood threat experiences and attenuated psychotic symptoms. The results underscore the importance of targeting negative schemas in interventions to mitigate psychosis risk

The genetic architecture of the human cerebral cortex

INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When considered together, these results support the radial unit hypothesis that different developmental mechanisms promote surface area expansion and increases in thickness. To identify specific genetic influences on individual cortical regions, we controlled for global measures (total surface area or average thickness) in the regional analyses. After multiple testing correction, we identified 175 loci that influence regional surface area and 10 that influence regional thickness. Loci that affect regional surface area cluster near genes involved in the Wnt signaling pathway, which is known to influence areal identity. We observed significant positive genetic correlations and evidence of bidirectional causation of total surface area with both general cognitive functioning and educational attainment. We found additional positive genetic correlations between total surface area and Parkinson’s disease but did not find evidence of causation. Negative genetic correlations were evident between total surface area and insomnia, attention deficit hyperactivity disorder, depressive symptoms, major depressive disorder, and neuroticism. CONCLUSION This large-scale collaborative work enhances our understanding of the genetic architecture of the human cerebral cortex and its regional patterning. The highly polygenic architecture of the cortex suggests that distinct genes are involved in the development of specific cortical areas. Moreover, we find evidence that brain structure is a key phenotype along the causal pathway that leads from genetic variation to differences in general cognitive function

Linear filtering applied to Monte Carlo criticality calculations

A significant improvement in the acceleration of the convergence of the eigenvalue computed by Monte Carlo techniques has been developed by applying linear filtering theory to Monte Carlo calculations for multiplying systems. A Kalman filter was applied to a KENO Monte Carlo calculation of an experimental critical system consisting of eight interacting units of fissile material. A comparison of the filter estimate and the Monte Carlo realization was made. The Kalman filter converged in five iterations to 0.9977. After 95 iterations, the average k-eff from the Monte Carlo calculation was 0.9981. This demonstrates that the Kalman filter has the potential of reducing the calculational effort of multiplying systems. Other examples and results are discussed. (auth

Applications of Kalman Filtering to nuclear material control. [Kalman filtering and linear smoothing for detecting nuclear material losses]

The feasibility of using modern state estimation techniques (specifically Kalman Filtering and Linear Smoothing) to detect losses of material from material balance areas is evaluated. It is shown that state estimation techniques are not only feasible but in most situations are superior to existing methods of analysis. The various techniques compared include Kalman Filtering, linear smoothing, standard control charts, and average cumulative summation (CUSUM) charts. Analysis results indicated that the standard control chart is the least effective method for detecting regularly occurring losses. An improvement in the detection capability over the standard control chart can be realized by use of the CUSUM chart. Even more sensitivity in the ability to detect losses can be realized by use of the Kalman Filter and the linear smoother. It was found that the error-covariance matrix can be used to establish limits of error for state estimates. It is shown that state estimation techniques represent a feasible and desirable method of theft detection. The technique is usually more sensitive than the CUSUM chart in detecting losses. One kind of loss which is difficult to detect using state estimation techniques is a single isolated loss. State estimation procedures are predicated on dynamic models and are well-suited for detecting losses which occur regularly over several accounting periods. A single isolated loss does not conform to this basic assumption and is more difficult to detect

Technique for detecting a small magnitude loss of special nuclear material

The detection of losses of special nuclear materials has been the subject of much research in recent years. The standard industry practice using ID/LEID will detect large magnitude losses. Time series techniques such as the Kalman Filter or CUSUM methods will detect small magnitude losses if they occur regularly over a sustained period of time. To date no technique has been proposed which adequately addresses the problem of detecting a small magnitude loss occurring in a single period. This paper proposes a method for detecting a small magnitude loss. The approach makes use of the influence function of Hempel. The influence function measures the effect of a single inventory difference on a group of statistics. An inventory difference for a period in which a loss occurs can be expected to produce an abnormality in the calculated statistics. This abnormality is measurable by the influence function. It is shown that a one period loss smaller in magnitude than the LEID can be detected using this approach

Enhancement of kalman filter single loss detection capability

A new technique to significantly increase the sensitivity of the Kalman filter to detect one-time losses for nuclear marterial accountability and control has been developed. The technique uses the innovations sequence obtained from a Kalman filter analysis of a material balance area. The innovations are distributed as zero mean independent Gaussion random variables with known variance. This property enables an estimator to be formed with enhanced one time loss detection capabilities. Simulation studies of a material balance area indicate the new estimator greatly enhances the one time loss detection capability of the Kalman filter

Operating experience with a near-real-time inventory balance in a nuclear fuel cycle plant

The principal objective of the ORNL Integrated Safeguards Program (ISP) is to provide enhanced material accountability, improved process control, and greater security for nuclear fuel cycle facilities. With the improved instrumentation and computer interfacing currently installed, the ORNL /sup 233/U Pilot Plant has demonstrated capability of a near-real-time liquid-volume balance in both the solvent-extraction and ion-exchange systems. Future developments should include the near-real-time mass balancing of special nuclear materials as both a static, in-tank summation and a dynamic, in-line determination. In addition, the aspects of site security and physical protection can be incorporated into the computer monitoring

Operating experience with a near-real-time inventory balance in a nuclear-fuel-cycle plant

The principal objective of the ORNL Integrated Safeguards Program (ISP) is to provide enhanced material accountability, improved process control, and greater security for nuclear fuel cycle facilities. With the improved instrumentation and computer interfacing currently installed, the ORNL /sup 233/U Pilot Plant has demonstrated capability of a near-real-time liquid-volume balance in both the solvent-extraction and ion-exchange systems. Future developments should include the near-real-time mass balancing of special nuclear materials as both a static, in-tank summation and a dynamic, in-line determination. In addition, the aspects of site security and physical protection can be incorporated into the computer monitoring