The dissociative subtype of posttraumatic stress disorder is associated with subcortical white matter network alterations

Posttraumatic stress disorder (PTSD) is characterized by intrusions, avoidance, and hyperarousal while patients of the dissociative subtype (PTSD-D) experience additional dissociative symptoms. A neurobiological model proposes hyper-inhibition of limbic structures mediated by prefrontal cortices to underlie dissociation in PTSD. Here, we tested whether functional alterations in fronto-limbic circuits are underpinned by white matter network abnormalities on a network level. 23 women with PTSD-D and 19 women with classic PTSD participated. We employed deterministic diffusion tractography and graph theoretical analyses. Mean fractional anisotropy (FA) was chosen as a network weight and group differences assessed using network-based statistics. No significant white matter network alterations comprising both frontal and limbic structures in PTSD-D relative to classic PTSD were found. A subsequent whole brain exploratory analysis revealed relative FA alterations in PTSD-D in two subcortical networks, comprising connections between the left amygdala, hippocampus, and thalamus as well as links between the left ventral diencephalon, putamen, and pallidum, respectively. Dissociative symptom severity in the PTSD-D group correlated with FA values within both networks. Our findings suggest fronto-limbic inhibition in PTSD-D may present a dynamic neural process, which is not hard-wired via white matter tracts. Our exploratory results point towards altered fiber tract communication in a limbic-thalamic circuit, which may underlie (a) an initial strong emotional reaction to trauma reminders before conscious regulatory processes are enabled and (b) deficits in early sensory processing. In addition, aberrant structural connectivity in low-level motor regions may present neural correlates for dissociation as a passive threat-response

Neural correlates of acute post-traumatic dissociation:a functional neuroimaging script-driven imagery study

Background: Current neurobiological models of post-traumatic stress disorder (PTSD) assume excessive medial frontal activation and hypoactivation of cortico-limbic regions as neural markers of post-traumatic dissociation. Script-driven imagery is an established experimental paradigm that is used to study acute dissociative reactions during trauma exposure. However, there is a scarcity of experimental research investigating neural markers of dissociation; findings from existing script-driven neuroimaging studies are inconsistent and based on small sample sizes. Aims: The current aim was to identify the neural correlates of acute post-traumatic dissociation by employing the script-driven imagery paradigm in combination with functional magnetic resonance imaging. Method: Functional neuroimaging data was acquired in 51 female patients with PTSD with a history of interpersonal childhood trauma. Blood-oxygen-level-dependent response during the traumatic (versus neutral) autobiographical memory recall was analysed, and the derived activation clusters were correlated with dissociation measures. Results: During trauma recall, enhanced activation in the cerebellum, occipital gyri, supramarginal gyrus and amygdala was identified. None of the derived clusters correlated significantly with dissociative symptoms, although patients reported increased levels of acute dissociation following the paradigm. Conclusions: The present study is one of the largest functional magnetic resonance imaging investigations of dissociative neural biomarkers in patients with PTSD undergoing experimentally induced trauma confrontation to elicit symptom-specific brain reactivity. In light of the current reproducibility crisis prominent in neuroimaging research owing to costly and time-consuming data acquisition, the current (null) findings highlight the difficulty of extracting reliable neurobiological biomarkers for complex subjective experiences such as dissociation

Multiple sequence alignment based on set covers

We introduce a new heuristic for the multiple alignment of a set of sequences. The heuristic is based on a set cover of the residue alphabet of the sequences, and also on the determination of a significant set of blocks comprising subsequences of the sequences to be aligned. These blocks are obtained with the aid of a new data structure, called a suffix-set tree, which is constructed from the input sequences with the guidance of the residue-alphabet set cover and generalizes the well-known suffix tree of the sequence set. We provide performance results on selected BAliBASE amino-acid sequences and compare them with those yielded by some prominent approaches

Random Shortest Paths: {Non-Euclidean} Instances for Metric Optimization Problems

Probabilistic analysis for metric optimization problems has mostly been conducted on random Euclidean instances, but little is known about metric instances drawn from distributions other than the Euclidean. This motivates our study of random metric instances for optimization problems obtained as follows: Every edge of a complete graph gets a weight drawn independently at random. The distance between two nodes is then the length of a shortest path (with respect to the weights drawn) that connects these nodes. We prove structural properties of the random shortest path metrics generated in this way. Our main structural contribution is the construction of a good clustering. Then we apply these findings to analyze the approximation ratios of heuristics for matching, the traveling salesman problem (TSP), and the k-median problem, as well as the running-time of the 2-opt heuristic for the TSP. The bounds that we obtain are considerably better than the respective worst-case bounds. This suggests that random shortest path metrics are easy instances, similar to random Euclidean instances, albeit for completely different structural reasons

Electronic properties of LaO1-xFxFeAs in the normal state probed by nmr/nqr

We report 139La, 57Fe and 75As nuclear magnetic resonance (NMR) and nuclear quadrupole resonance (NQR) measurements on powders of the new LaO1−xFxFeAs superconductor for x=0 and 0.1 at temperatures up to 480 K, and compare our measured NQR spectra with local density approximation (LDA) calculations. For all three nuclei in the x=0.1 material, it is found that the local Knight shift increases monotonically with an increase in temperature, and scales with the macroscopic susceptibility, suggesting a single magnetic degree of freedom. Surprisingly, the spin lattice relaxation rates for all nuclei also scale with one another, despite the fact that the form factors for each site sample different regions of q-space. This result suggests a lack of any q-space structure in the dynamical spin susceptibility that might be expected in the presence of antiferromagnetic correlations. Rather, our results are more compatible with simple quasi-particle scattering. Furthermore, we find that the increase in the electric field gradient at the As cannot be accounted for by LDA calculations, suggesting that structural changes, in particular the position of the As in the unit cell, dominate the NQR response

Nanoscale Electronic Order in Iron Pnictides

The charge distribution in RFeAs (R=La, Sm) iron pnictides is probed using As NQR. Whereas undoped and optimally-doped/overdoped compounds feature a single charge environment, two charge environments are detected in the underdoped region. Spin- lattice relaxation measurements show their coexistence at the nanoscale. Together with the quantitative variations of the spectra with doping, they point at a local electronic order in the iron layers, where low- and high-doping-like regions would coexist. Implications for the interplay of static magnetism and superconductivity are discussed

MaxPre : An Extended MaxSAT Preprocessor

We describe MaxPre, an open-source preprocessor for (weighted partial) maximum satisfiability (MaxSAT). MaxPre implements both SAT-based and MaxSAT-specific preprocessing techniques, and offers solution reconstruction, cardinality constraint encoding, and an API for tight integration into SAT-based MaxSAT solvers.Peer reviewe