Reproducibility of graph metrics of human brain structural networks

Recent interest in human brain connectivity has led to the application of graph theoretical analysis to human brain structural networks, in particular white matter connectivity inferred from diffusion imaging and fiber tractography. While these methods have been used to study a variety of patient populations, there has been less examination of the reproducibility of these methods. A number of tractography algorithms exist and many of these are known to be sensitive to user-selected parameters. The methods used to derive a connectivity matrix from fiber tractography output may also influence the resulting graph metrics. Here we examine how these algorithm and parameter choices influence the reproducibility of proposed graph metrics on a publicly available test-retest dataset consisting of 21 healthy adults. The dice coefficient is used to examine topological similarity of constant density subgraphs both within and between subjects. Seven graph metrics are examined here: mean clustering coefficient, characteristic path length, largest connected component size, assortativity, global efficiency, local efficiency, and rich club coefficient. These reproducibility of these network summary measures is examined using the intraclass correlation coefficient (ICC). Graph curves are created by treating the graph metrics as functions of a parameter such as graph density. Functional data analysis techniques are usedto examine differences in graph measures that result from the choice of fiber tracking algorithm. The graph metrics consistently showed good levels of reproducibility as measured with ICC, with the exception of some instability at low graph density levels. The global and local efficiency measures were the most robust to the choice of fiber tracking algorithm

Magnetic circular dichroism in X-ray fluorescence of Heusler alloys at threshold excitation

The results of fluorescence measurements of magnetic circular dichroism (MCD) in Mn L_2,L_3 X-ray emission and absorption for Heusler alloys NiMnSb and Co2MnSb are presented. Very intense resonance Mn L_3 emission is found at the Mn 2p_3/2 threshold and is attributed to a peculiarity of the threshold excitation in materials with the half-metallic character of the electronic structure. A theoretical model for the description of resonance scattering of polarized x-rays is suggested.Comment: 3 pages, 2 figures. Discussed at conferences, submitting process in progres

One, four or 100 genera? A new classification of the cone snails

International audienc

Adaptive query-based sampling of distributed collections

As part of a Distributed Information Retrieval system a de-scription of each remote information resource, archive or repository is usually stored centrally in order to facilitate resource selection. The ac-quisition ofprecise resourcedescriptionsistherefore animportantphase in Distributed Information Retrieval, as the quality of such represen-tations will impact on selection accuracy, and ultimately retrieval per-formance. While Query-Based Sampling is currently used for content discovery of uncooperative resources, the application of this technique is dependent upon heuristic guidelines to determine when a sufficiently accurate representation of each remote resource has been obtained. In this paper we address this shortcoming by using the Predictive Likelihood to provide both an indication of thequality of an acquired resource description estimate, and when a sufficiently good representation of a resource hasbeen obtained during Query-Based Sampling

Multivariate Normalization with Symmetric Diffeomorphisms for Multivariate Studies

Current clinical and research neuroimaging protocols acquire images using multiple modalities, for instance, T1, T2, diffusion tensor and cerebral blood flow magnetic resonance images (MRI). These multivariate datasets provide unique and often complementary anatomical and physiological information about the subject of interest. We present a method that uses fused multiple modality (scalar and tensor) datasets to perform intersubject spatial normalization. Our multivariate approach has the potential to eliminate inconsistencies that occur when normalization is performed on each modality separately. Furthermore, the multivariate approach uses a much richer anatomical and physiological image signature to infer image correspondences and perform multivariate statistical tests. In this initial study, we develop the theory for Multivariate Symmetric Normalization (MVSyN), establish its feasibility and discuss preliminary results on a multivariate statistical study of 22q deletion syndrome

Surface Grafting of Poly(L-glutamates). 2. Helix Orientation

In this paper the average helix orientation of surface-grafted poly(γ-benzyl L-glutamate) (PBLG), poly(γ-methyl L-glutamate) (PMLG), and poly(γ-methyl L-glutamate)-co-(γ-n-stearyl L-glutamate) (PMLGSLG 70/30) was investigated by means of FT-IR transmission spectroscopy. The theoretical relation between the average tilt angle (θ) and the absorption peak areas of three different backbone amide bands could be calculated because their transition dipole moment directions with respect to the helix axis were known. From the normalized absorptions, the average tilt angles of grafted helices of PBLG, PMLG, and PMLGSLG 70/30 were determined. The somewhat larger average angle of PMLG helices of 35 ± 5° with respect to the substrate compared to the value of 32 ± 5° of PBLG was due to the higher grafting density of PMLG. Because of the smaller helix diameter as a result of the smaller size of the methyl side group, more PMLG helices grew on the same surface area. Sterical hindrance and unfavorable polar interactions between unidirectional aligned helices forced the PMLG helices in a more upright arrangement. The even more perpendicular orientation of PMLGSLG 70/30 (48 ± 6°) could be the result of incorporation of mainly γ-methyl L-glutamate N-carboxyanhydride (MLG-NCA) monomers during the initiation step. Incorporation of the much larger γ-n-stearyl L-glutamate N-carboxyanhydride (SLG-NCA) monomers afterward lead to enlarged angles with respect to the substrate. Due to swelling, a pronounced change in helix orientation of grafted PMLGSLG 70/30 in n-hexadecane was observed, resulting in an almost perpendicular helix orientation.

Two-Spinon and Orbital Excitations of the Spin-Peierls System TiOCl

We combine high-resolution resonant inelastic x-ray scattering with cluster calculations utilizing a recently derived effective magnetic scattering operator to analyze the polarization, excitation energy, and momentum dependent excitation spectrum of the low-dimensional quantum magnet TiOCl in the range expected for orbital and magnetic excitations (0 - 2.5 eV). Ti 3d orbital excitations yield complete information on the temperature-dependent crystal-field splitting. In the spin-Peierls phase we observe a dispersive two-spinon excitation and estimate the inter- and intra-dimer magnetic exchange coupling from a comparison to cluster calculations

Mining of Topographic Feature from Heterogeneous Imagery and Its Application to Lunar Craters

Abstract. In this study, a crater detection system for a large-scale image database is proposed. The original images are grouped according to spatial frequency patterns and both optimized parameter sets and noise reduction techniques used to identify candidate craters. False candidates are excluded using a self-organizing map (SOM) approach. The results show that despite the fact that a accurate classification is achievable using the proposed technique, future improvements in detection process of the system are needed.

Phase transitions in optimal unsupervised learning

We determine the optimal performance of learning the orientation of the symmetry axis of a set of P = alpha N points that are uniformly distributed in all the directions but one on the N-dimensional sphere. The components along the symmetry breaking direction, of unitary vector B, are sampled from a mixture of two gaussians of variable separation and width. The typical optimal performance is measured through the overlap Ropt=B.J* where J* is the optimal guess of the symmetry breaking direction. Within this general scenario, the learning curves Ropt(alpha) may present first order transitions if the clusters are narrow enough. Close to these transitions, high performance states can be obtained through the minimization of the corresponding optimal potential, although these solutions are metastable, and therefore not learnable, within the usual bayesian scenario.Comment: 9 pages, 8 figures, submitted to PRE, This new version of the paper contains one new section, Bayesian versus optimal solutions, where we explain in detail the results supporting our claim that bayesian learning may not be optimal. Figures 4 of the first submission was difficult to understand. We replaced it by two new figures (Figs. 4 and 5 in this new version) containing more detail