A peak-clustering method for MEG group analysis to minimise artefacts due to smoothness

Magnetoencephalography (MEG), a non-invasive technique for characterizing brain electrical activity, is gaining popularity as a tool for assessing group-level differences between experimental conditions. One method for assessing task-condition effects involves beamforming, where a weighted sum of field measurements is used to tune activity on a voxel-by-voxel basis. However, this method has been shown to produce inhomogeneous smoothness differences as a function of signal-to-noise across a volumetric image, which can then produce false positives at the group level. Here we describe a novel method for group-level analysis with MEG beamformer images that utilizes the peak locations within each participant's volumetric image to assess group-level effects. We compared our peak-clustering algorithm with SnPM using simulated data. We found that our method was immune to artefactual group effects that can arise as a result of inhomogeneous smoothness differences across a volumetric image. We also used our peak-clustering algorithm on experimental data and found that regions were identified that corresponded with task-related regions identified in the literature. These findings suggest that our technique is a robust method for group-level analysis with MEG beamformer images.

Synthesis and characterization of silica-supported L-Lysine-based dendritic branches

Two series of novel modified silicas have been prepared in which individual dendritic branches have been attached to aminopropylsilica using standard peptide coupling methodology. The dendritic branches are composed of enantiomerically pure l-lysine building blocks, and hence, the modified silicas have the potential to act as chiral stationary phases in chromatography. In one series of modified silicas, the surface of the dendritic branch consists of Boc carbamate groups, whereas the other has benzoyl amide surface groups. Different coupling reagents have been investigated in order to maximize the loading onto the solid phase. The new supported dendritic materials have been fully characterized with properties of the bulk material determined by elemental analysis, 13C NMR, and IR spectroscopy, whereas XPS provides important information about the surface of the modified silica exposed to the incident X-rays, the key region in which potential chromatographic performance of these materials will take place. Although the bulk analyses indicate that loading of the dendritic branch onto silica decreases with increasing dendritic generation (and consequently steric bulk), XPS indicates that the optimum surface coverage is actually obtained at the second generation of dendritic growth.

Control of pattern formation by time-delay feedback with global and local contributions

We consider the suppression of spatiotemporal chaos in the complex GinzburgLandau equation by a combined global and local time-delay feedback. Feedback terms are implemented as a control scheme, i.e., they are proportional to the difference between the time-delayed state of the system and its current state. We perform a linear stability analysis of uniform oscillations with respect to space-dependent perturbations and compare with numerical simulations. Similarly, for the fixed-point solution that corresponds to amplitude death in the spatially extended system, a linear stability analysis with respect to space-dependent perturbations is performed and complemented by numerical simulations. © 2010 Elsevier B.V. All rights reserved.