Anomalous pattern based clustering of mental tasks with subject independent learning – some preliminary results

In this paper we describe a new method for EEG signal classification in which the classification of one subject’s EEG signals is based on features learnt from another subject. This method applies to the power spectrum density data and assigns class-dependent information weights to individual features. The informative features appear to be rather similar among different subjects, thus supporting the view that there are subject independent general brain patterns for the same mental task. Classification is done via clustering using the intelligent k-means algorithm with the most informative features from a different subject. We experimentally compare our method with others.</jats:p

Wavelet Lifting over Information-Based EEG Graphs for Motor Imagery Data Classification

The imagination of limb movements offers an intuitive paradigm for the control of electronic devices via brain computer interfacing (BCI). The analysis of electroencephalographic (EEG) data related to motor imagery potentials has proved to be a difficult task. EEG readings are noisy, and the elicited patterns occur in different parts of the scalp, at different instants and at different frequencies. Wavelet transform has been widely used in the BCI field as it offers temporal and spectral capabilities, although it lacks spatial information. In this study we propose a tailored second generation wavelet to extract features from these three domains. This transform is applied over a graph representation of motor imaginary trials, which encodes temporal and spatial information. This graph is enhanced using per-subject knowledge in order to optimise the spatial relationships among the electrodes, and to improve the filter design. This method improves the performance of classifying different imaginary limb movements maintaining the low computational resources required by the lifting transform over graphs. By using an online dataset we were able to positively assess the feasibility of using the novel method in an online BCI context

Positive exchange bias in ferromagnetic La0.67Sr0.33MnO3 / SrRuO3 bilayers

Epitaxial La0.67Sr0.33MnO3 (LSMO)/ SrRuO3 (SRO) ferromagnetic bilayers have been grown on (001) SrTiO3 (STO) substrates by pulsed laser deposition with atomic layer control. We observe a shift in the magnetic hysteresis loop of the LSMO layer in the same direction as the applied biasing field (positive exchange bias). The effect is not present above the Curie temperature of the SRO layer (), and its magnitude increases rapidly as the temperature is lowered below . The direction of the shift is consistent with an antiferromagnetic exchange coupling between the ferromagnetic LSMO layer and the ferromagnetic SRO layer. We propose that atomic layer charge transfer modifies the electronic state at the interface, resulting in the observed antiferromagnetic interfacial exchange coupling.Comment: accepted to Applied Physics Letter

Morphological evolution of a 3D CME cloud reconstructed from three viewpoints

The propagation properties of coronal mass ejections (CMEs) are crucial to predict its geomagnetic effect. A newly developed three dimensional (3D) mask fitting reconstruction method using coronagraph images from three viewpoints has been described and applied to the CME ejected on August 7, 2010. The CME's 3D localisation, real shape and morphological evolution are presented. Due to its interaction with the ambient solar wind, the morphology of this CME changed significantly in the early phase of evolution. Two hours after its initiation, it was expanding almost self-similarly. CME's 3D localisation is quite helpful to link remote sensing observations to in situ measurements. The investigated CME was propagating to Venus with its flank just touching STEREO B. Its corresponding ICME in the interplanetary space shows a possible signature of a magnetic cloud with a preceding shock in VEX observations, while from STEREO B only a shock is observed. We have calculated three principle axes for the reconstructed 3D CME cloud. The orientation of the major axis is in general consistent with the orientation of a filament (polarity inversion line) observed by SDO/AIA and SDO/HMI. The flux rope axis derived by the MVA analysis from VEX indicates a radial-directed axis orientation. It might be that locally only the leg of the flux rope passed through VEX. The height and speed profiles from the Sun to Venus are obtained. We find that the CME speed possibly had been adjusted to the speed of the ambient solar wind flow after leaving COR2 field of view and before arriving Venus. A southward deflection of the CME from the source region is found from the trajectory of the CME geometric center. We attribute it to the influence of the coronal hole where the fast solar wind emanated from.Comment: ApJ, accepte