François Laurent

Classification methods for ongoing EEG and MEG signals

Classification algorithms help predict the qualitative properties of a subjects mental state by extracting useful information from the highly multivariate non-invasive recordings of his brain activity. In particular, applying them to Magneto-encephalography (MEG) and electro-encephalography (EEG) is a challenging and promising task with prominent practical applications to e.g. Brain Computer Interface (BCI). In this paper, we first review the principles of the major classification techniques and discuss their application to MEG and EEG data classification. Next, we investigate the behavior of classification methods using real data recorded during a MEG visuomotor experiment. In particular, we study the influence of the classification algorithm, of the quantitative functional variables used in this classifier, and of the validation method. In addition, our findings suggest that by investigating the distribution of classifier coefficients, it is possible to infer knowledge and construct functional interpretations of the underlying neural mechanisms of the performed tasks. Finally, the promising results reported here (up to 97% classification accuracy on 1-second time windows) reflect the considerable potential of MEG for the continuous classification of mental states.

Prediction of performance level during a cognitive task from ongoing EEG oscillatory activities

OBJECTIVEnTracking the level of performance in cognitive tasks may be useful in environments, such as aircraft, in which the awareness of the pilots is critical for security. In this paper, the usefulness of EEG for the prediction of performance is investigated.nnnMETHODSnWe present a new methodology that combines various ongoing EEG measurements to predict performance level during a cognitive task. We propose a voting approach that combines the outputs of elementary support vector machine (SVM) classifiers derived from various sets of EEG parameters in different frequency bands. The spectral power and phase synchrony of the oscillatory activities are used to classify the periods of rapid reaction time (RT) versus the slow RT responses of each subject.nnnRESULTSnThe voting algorithm significantly outperforms classical SVM and gives a good average classification accuracy across 12 subjects (71%) and an average information transfer rate (ITR) of 0.49bit/min. The main discriminating activities are laterally distributed theta power and anterio-posterior alpha synchronies, possibly reflecting the role of a visual-attentional network in performance.nnnCONCLUSIONSnPower and synchrony measurements enable the discrimination between periods of high average reaction time versus periods of low average reaction time in a same subject. Moreover, the proposed approach is easy to interpret as it combines various types of measurements for classification, emphasizing the most informative.nnnSIGNIFICANCEnOngoing EEG recordings can predict the level of performance during a cognitive task. This can lead to real-time EEG monitoring devices for the anticipation of human mistakes.

New organometallic route to vanadium carbonitride thin films

Chloroimidovanadium compounds Cl3VNR [R = CH3(1), C6H5CH3(2) and t-C4H9(3)] have been prepared, studied by thermal analysis and evaluated as molecular precursors to vanadium nitride by chemical vapour deposition (CVD). The decomposition mechanism of 1 and 2 is complex and depends on the nature of the carrier gas, but in both cases the temperature at which decomposition ends (ca. 900°C) is too high for their practical use in low-temperature CVD processes. Compound 3 is volatile and decomposes at quite low temperatures (<250°C), and has been used as a precursor to vanadium nitride in a hot-wall CVD reactor. Shiny, black metal-like thin films have been obtained that have been characterized as vanadium carbonitride by X-ray powder patterns and XPS analysis.

Nitrate pollution risk assessment : from the model to the indicator

The diffuse nature of nitrate pollution makes it difficult to evaluate existing or planned measures to reduce it. Tools have therefore been developed to assess this pollution, ranging from simple indicators to complex models. The aim of this paper is to compare indicators and models by analysing results obtained from their individual application to the same area. The pros and cons of each approach are evaluated in terms of both the conditions of their implementation and the results obtained. This comparison helps to guide the choice of a methodology. Rules governing that choice are set in relation to the nature of the diagnosis to perform and the characteristics of the area under study.

Source reconstruction and synchrony measurements for revealing functional brain networks and classifying mental states.

We classified performance-related mental states from EEG-derived measurements. We investigated the usefulness of massively distributed source reconstruction, comparing scalp and cortical scales. This approach provides a more detailed picture of the functional brain networks underlying the changes related to the mental state of interest. Local and distant synchrony measurements (coherence, phase locking value) were used for both scalp measurements and cortical current density sources, and were fed into a SVM-based classifier. We designed two simulations where classification scores increased when our 60-electrode scalp measurements were reconstructed on 60 sources and on a 500-source cortex. Source reconstruction appeared to be most useful in these simulations, in particular, when distant synchronies were involved and local synchronies did not prevail. Despite the simplicity of the model used, certain flaws in accuracy were observed in the localization of informative activities, due to the relationship between amplitude and phase for mixed signals. Our results with real EEG data suggested that the phenomenon of interest was characterized merely by modulations in local amplitudes, but also in strength of distant couplings. After source reconstruction, classification rates also increased for real EEG data when seeking distant phase-related couplings. When reconstructing a large number of sources, the regularization coefficient should be carefully selected on a subject-by-subject basis. We showed that training classifiers using such high-dimension data is useful for localizing discriminating patterns of activity.

PHYTOREMEDIATION OF PERSISTENT ORGANIC POLLUTANTS

Rural economy in Croatia with your small sized sector of peasant enterprises still stays in the shadow of restructuring of large industrial sector. The slow leading process of privatization, the wandering in the claim the best solution in agricultural development, absence of consensus about key development priorities, as well as common indicators of backwardness, are only part of gray scale of problems which dented the continue pauperization of wide rural area in Croatia. The Croatian government administration late with implementation of new rural policy measures, which are recommended by Council Regulation (EC) No 1257/1999. This act emphasis the balanced development of the countryside alongside the market support measures in the lights of the social and territorial cohesion. It is based on the following principles: recognising the multifunctional role of agriculture, improving competitiveness, ensuring that environmental issues are taken into account, diversifying economic activity, and conserving rural heritage. In the past time new rural policy in Croatia is considered below local and regional development programs, where the LEADER approach take important role. This is result of pre-accession process to EU and new possibilities of using considerable financial support in IPA subsidy program 2007- 2113.

Modelling water flow in a complex watershed in humid a tropical area using swat: a case study of Taabo watershed in Ivory Coast

ABSTRACT Understanding the water balance of a basin is the most important aspect in water resources development and management programmes. The objective of this study was to implement an agro-hydrological model (SWAT) to model water flow transport within the river network with a perspective to reduce the sedimentation and eutrophication of lakes in Ivory Coast. The daily simulation of SWAT model carried out in the period from 1979 to 1990 has been divided into warm-up (1979–1981), calibration (1982–1986) and validation (1987–1990). For calibrating the model, a preliminary sensitivity and uncertainty analysis in the SUFI-2 algorithm was performed based on 19 hydrologic parameters. The model has given good results of performance and robustness. All statistical parameters (Nash-Sutcliffe coefficient (NS) and the coefficient of determination (R2)) used to achieve the model performance of above 0.7 for the calibration period and around 0.6 for the validation period. As for the uncertainty criteria (P-factor and R-factor), the observation data are very good in general because more than 80% are bracketed by the 95PPU both for calibration and validation periods. Graphically, the streamflow predictions match well with actual measurements. Water transfers between the soil, surface water, groundwater and atmosphere are largely conditioned by the uneven spatial distribution of pedology, land use and climate.

Molecular precursors for OMCVD preparation of TiN, VN, TiC and VC thin-film ceramic materials*

Twenty-two organometallic molecular compounds have been prepared and tested for use as precursors for the OMCVD preparation of TiN, VN, TiC and VC thin-film ceramic materials. Methodologies and main results on thermal analyses and deposit characterization are described.

Towards a Meta-Social-Ecological System Perspective: A Response to Gounand et al.

The meta-ecosystem approach has significantly advanced ecosystem science and landscape ecology by explicitly addressing the flow of elements (live organisms, biotic and abiotic materials) among ecosystems at different temporal and spatial scales [1,2]. Gounand et al. [3] recently argued that the conciliation of theoretical and empirical studies on meta-ecosystems needs better quantification of spatial flows in terms of movements (dispersal, foraging, life-cycle, and migration), feedbacks, and resources.

Gérer les forêts dégradées, une nouvelle priorité en Amazonie brésilienne

En Amazonie bresilienne, les forets degradees dominent les paysages des fronts pionniers. Un grand defi attend desormais cette region : stopper la degradation et gerer durablement ces forets. Les forets degradees representent aujourd’hui une categorie de foret a part entiere. Elles peuvent neanmoins jouer un role majeur pour lutter contre le changement climatique. Elles peuvent aussi contribuer a un meilleur fonctionnement ecologique des territoires. Developper des politiques publiques visant le double objectif de reduire la degradation et de valoriser ces forets implique un appui fort de la recherche. Dans ce Perspective, nous mettons l’accent sur quatre priorites de recherche : developper des methodes de caracterisation et de suivi des forets degradees, elaborer des plans d’amenagement specifiques, comprendre le role joue par tous les acteurs sociaux et accompagner les politiques a l’echelle territoriale.