Intergenerational transmission of child maltreatment using a multi-informant multi-generation family design.

In the current study a three-generational design was used to investigate intergenerational transmission of child maltreatment (ITCM) using multiple sources of information on child maltreatment: mothers, fathers and children. A total of 395 individuals from 63 families reported on maltreatment. Principal Component Analysis (PCA) was used to combine data from mother, father and child about maltreatment that the child had experienced. This established components reflecting the convergent as well as the unique reports of father, mother and child on the occurrence of maltreatment. Next, we tested ITCM using the multi-informant approach and compared the results to those of two more common approaches: ITCM based on one reporter and ITCM based on different reporters from each generation. Results of our multi-informant approach showed that a component reflecting convergence between mother, father, and child reports explained most of the variance in experienced maltreatment. For abuse, intergenerational transmission was consistently found across approaches. In contrast, intergenerational transmission of neglect was only found using the perspective of a single reporter, indicating that transmission of neglect might be driven by reporter effects. In conclusion, the present results suggest that including multiple informants may be necessary to obtain more valid estimates of ITCM

Interpretation of ambiguous situations: evidence for a dissociation between social and physical threat in Williams syndrome

There is increasing evidence that Williams syndrome (WS) is associated with elevated anxiety that is non-social in nature, including generalised anxiety and fears. To date very little research has examined the cognitive processes associated with this anxiety. In the present research, attentional bias for non-social threatening images in WS was examined using a dot-probe paradigm. Participants were 16 individuals with WS aged between 13 and 34 years and two groups of typically developing controls matched to the WS group on chronological age and attentional control ability respectively. The WS group exhibited a significant attention bias towards threatening images. In contrast, no bias was found for group matched on attentional control and a slight bias away from threat was found in the chronological age matched group. The results are contrasted with recent findings suggesting that individuals with WS do not show an attention bias for threatening faces and discussed in relation to neuroimaging research showing elevated amygdala activation in response to threatening non-social scenes in WS

Genetics of callous-unemotional behavior in children

Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU

Subanesthetic ketamine treatment promotes abnormal interactions between neural subsystems and alters the properties of functional brain networks

Acute treatment with subanesthetic ketamine, a non-competitive N-methyl-D-aspartic acid (NMDA) receptor antagonist, is widely utilized as a translational model for schizophrenia. However, how acute NMDA receptor blockade impacts on brain functioning at a systems level, to elicit translationally relevant symptomatology and behavioral deficits, has not yet been determined. Here, for the first time, we apply established and recently validated topological measures from network science to brain imaging data gained from ketamine-treated mice to elucidate how acute NMDA receptor blockade impacts on the properties of functional brain networks. We show that the effects of acute ketamine treatment on the global properties of these networks are divergent from those widely reported in schizophrenia. Where acute NMDA receptor blockade promotes hyperconnectivity in functional brain networks, pronounced dysconnectivity is found in schizophrenia. We also show that acute ketamine treatment increases the connectivity and importance of prefrontal and thalamic brain regions in brain networks, a finding also divergent to alterations seen in schizophrenia. In addition, we characterize how ketamine impacts on bipartite functional interactions between neural subsystems. A key feature includes the enhancement of prefrontal cortex (PFC)-neuromodulatory subsystem connectivity in ketamine-treated animals, a finding consistent with the known effects of ketamine on PFC neurotransmitter levels. Overall, our data suggest that, at a systems level, acute ketamine-induced alterations in brain network connectivity do not parallel those seen in chronic schizophrenia. Hence, the mechanisms through which acute ketamine treatment induces translationally relevant symptomatology may differ from those in chronic schizophrenia. Future effort should therefore be dedicated to resolve the conflicting observations between this putative translational model and schizophrenia

Research on the relation of EEG signal chaos characteristics with high-level intelligence activity of human brain

Using phase space reconstruct technique from one-dimensional and multi-dimensional time series and the quantitative criterion rule of system chaos, and combining the neural network; analyses, computations and sort are conducted on electroencephalogram (EEG) signals of five kinds of human consciousness activities (relaxation, mental arithmetic of multiplication, mental composition of a letter, visualizing a 3-dimensional object being revolved about an axis, and visualizing numbers being written or erased on a blackboard). Through comparative studies on the determinacy, the phase graph, the power spectra, the approximate entropy, the correlation dimension and the Lyapunov exponent of EEG signals of 5 kinds of consciousness activities, the following conclusions are shown: (1) The statistic results of the deterministic computation indicate that chaos characteristic may lie in human consciousness activities, and central tendency measure (CTM) is consistent with phase graph, so it can be used as a division way of EEG attractor. (2) The analyses of power spectra show that ideology of single subject is almost identical but the frequency channels of different consciousness activities have slight difference. (3) The approximate entropy between different subjects exist discrepancy. Under the same conditions, the larger the approximate entropy of subject is, the better the subject's innovation is. (4) The results of the correlation dimension and the Lyapunov exponent indicate that activities of human brain exist in attractors with fractional dimensions. (5) Nonlinear quantitative criterion rule, which unites the neural network, can classify different kinds of consciousness activities well. In this paper, the results of classification indicate that the consciousness activity of arithmetic has better differentiation degree than that of abstract

Stochastic Gravity: Theory and Applications

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel.In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime: we compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a quasi-static black hole.Comment: 75 pages, no figures, submitted to Living Reviews in Relativit

Association of limbic system-associated membrane protein (LSAMP) to male completed suicide

<p>Abstract</p> <p>Background</p> <p>Neuroimaging studies have demonstrated volumetric abnormalities in limbic structures of suicide victims. The morphological changes might be caused by some inherited neurodevelopmental defect, such as failure to form proper axonal connections due to genetically determined dysfunction of neurite guidance molecules. Limbic system-associated membrane protein (LSAMP) is a neuronal adhesive molecule, preferentially expressed in developing limbic system neuronal dendrites and somata. Some evidence for the association between LSAMP gene and behavior has come from both animal as well as human studies but further investigation is required. In current study, polymorphic loci in human LSAMP gene were examined in order to reveal any associations between genetic variation in <it>LSAMP </it>and suicidal behaviour.</p> <p>Methods</p> <p>DNA was obtained from 288 male suicide victims and 327 healthy male volunteers. Thirty SNPs from LSAMP gene and adjacent region were selected by Tagger algorithm implemented in Haploview 3.32. Genotyping was performed using the SNPlex™ (Applied Biosystems) platform. Data was analyzed by Genemapper 3.7, Haploview 3.32 and SPSS 13.0.</p> <p>Results</p> <p>Chi square test revealed four allelic variants (rs2918215, rs2918213, rs9874470 and rs4821129) located in the intronic region of the gene to be associated with suicide, major alleles being overrepresented in suicide group. However, the associations did not survive multiple correction test. Defining the haplotype blocks using confidence interval algorithm implemented in Haploview 3.32, we failed to detect any associated haplotypes.</p> <p>Conclusion</p> <p>Despite a considerable amount of investigation on the nature of suicidal behaviour, its aetiology and pathogenesis remain unknown. This study examined the variability in LSAMP gene in relation to completed suicide. Our results indicate that LSAMP might play a role in pathoaetiology of suicidal behaviour but further studies are needed to understand its exact contribution.</p

Stochastic Gravity: Theory and Applications

Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime, compute the two-point correlation functions of these perturbations and prove that Minkowski spacetime is a stable solution of semiclassical gravity. Second, we discuss structure formation from the stochastic gravity viewpoint. Third, we discuss the backreaction of Hawking radiation in the gravitational background of a black hole and describe the metric fluctuations near the event horizon of an evaporating black holeComment: 100 pages, no figures; an update of the 2003 review in Living Reviews in Relativity gr-qc/0307032 ; it includes new sections on the Validity of Semiclassical Gravity, the Stability of Minkowski Spacetime, and the Metric Fluctuations of an Evaporating Black Hol