Altered decision-making in multiple sclerosis: a sign of impaired emotional reactivity?

We assessed decision-making capacity and emotional reactivity in 20 patients with multiple sclerosis (MS) and in 16 healthy subjects using the Gambling Task (GT), a model of real-life decision making, and the skin conductance response (SCR). Demographic, neurological, affective, and cognitive parameters were analyzed in MS patients for their effect on decision-making performance. MS patients persisted longer (slope, -3.6%) than the comparison group (slope, -6.4%) in making disadvantageous choices as the GT progressed (p < 0.001), suggesting significant slower learning in MS. Patients with higher Expanded Disability Status Scale scores (EDSS >2.0) showed a different pattern of impairment in the learning process compared with patients with lower functional impairment (EDSS </=2.0). This slower learning was associated with impaired emotional reactivity (anticipatory SCR 3.9 vs 6.1 microSiemens [microS] for patients vs the comparison group, p < 0.0001; post-choice SCR 3.9 vs 6.2 microS, p < 0.0001), but not with executive dysfunction. Impaired emotional dimensions of behavior (assessed using the Dysexecutive Questionnaire, p < 0.002) also correlated with slower learning. Given the considerable consequences that impaired decision making can have on daily life, we suggest that this factor may contribute to handicap and altered quality of life secondary to MS and is dependent on emotional experience. Ann Neurol 2004.

One naive T cell, multiple fates in CD8+ T cell differentiation.

The mechanism by which the immune system produces effector and memory T cells is largely unclear. To allow a large-scale assessment of the development of single naive T cells into different subsets, we have developed a technology that introduces unique genetic tags (barcodes) into naive T cells. By comparing the barcodes present in antigen-specific effector and memory T cell populations in systemic and local infection models, at different anatomical sites, and for TCR-pMHC interactions of different avidities, we demonstrate that under all conditions tested, individual naive T cells yield both effector and memory CD8+ T cell progeny. This indicates that effector and memory fate decisions are not determined by the nature of the priming antigen-presenting cell or the time of T cell priming. Instead, for both low and high avidity T cells, individual naive T cells have multiple fates and can differentiate into effector and memory T cell subsets.

Effect of modafinil on subjective fatigue in multiple sclerosis and stroke patients.

BACKGROUND: Modafinil has anecdotal response to neurological fatigue, but such an effect may depend on the type and location of cerebral impairment. OBJECTIVES: It was the aim of this study to compare fatigue observed in different neurological pathologies, to evaluate the tolerability to modafinil, and to describe changes in subjective fatigue. METHODS: We enrolled 14 brainstem or diencephalic stroke (BDS) patients, 9 cortical stroke (CS) patients and 17 multiple sclerosis (MS) patients. The Fatigue Assessment Instrument severity scale was performed at baseline, after 3 months of modafinil and after 1 month of washout. Cognition, mood and somnolence were assessed. A subgroup of 14 patients underwent activity measures before and during treatment. RESULTS: Thirty-one patients completed the study (10 BDS, 9 CS, 12 MS). The responder profile is more frequent in MS than in CS (p = 0.04), and in BDS than in CS patients (p = 0.04). Actiwatch measures showed no changes in activity during, before and after therapy. CONCLUSION: Modafinil was tolerated in 75% of patients at small doses and seemed to improve the severity of fatigue in the MS and BDS groups but not in the CS group. There was no modification in measured physical activity.

Improved multiple-locus variable-number tandem-repeat assay for Staphylococcus aureus genotyping, providing a highly informative technique together with strong phylogenetic value.

We describe an improved multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for genotyping Staphylococcus aureus. We compare its performance to those of multilocus sequence typing (MLST) and spa typing in a survey of 309 strains. This collection includes 87 epidemic methicillin-resistant S. aureus (MRSA) strains of the Harmony collection, 75 clinical strains representing the major MLST clonal complexes (CCs) (50 methicillin-sensitive S. aureus [MSSA] and 25 MRSA), 135 nasal carriage strains (133 MSSA and 2 MRSA), and 13 published S. aureus genome sequences. The results show excellent concordance between the techniques' results and demonstrate that the discriminatory power of MLVA is higher than those of both MLST and spa typing. Two hundred forty-two genotypes are discriminated with 14 VNTR loci (diversity index, 0.9965; 95% confidence interval, 0.9947 to 0.9984). Using a cutoff value of 45%, 21 clusters are observed, corresponding to the CCs previously defined by MLST. The variability of the different tandem repeats allows epidemiological studies, as well as follow-up of the evolution of CCs and the identification of potential ancestors. The 14 loci can conveniently be analyzed in two steps, based upon a first-line simplified assay comprising a subset of 10 loci (panel 1) and a second subset of 4 loci (panel 2) that provides higher resolution when needed. In conclusion, the MLVA scheme proposed here, in combination with available on-line genotyping databases (including http://mlva.u-psud.fr/), multiplexing, and automatic sizing, can provide a basis for almost-real-time large-scale population monitoring of S. aureus.

Inversion of multiple intersecting high-resolution crosshole GPR profiles for hydrological characterization at the Boise Hydrogeophysical Research Site

The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. In particular, crosshole ground-penetrating radar (GPR) tomography has shown much promise in hydrology because of its ability to provide highly detailed images of subsurface radar wave velocity, which is strongly linked to soil water content. Here, we develop and demonstrate a procedure for inverting together multiple crosshole GPR data sets in order to characterize the spatial distribution of radar wave velocity below the water table at the Boise Hydrogeophysical Research Site (BHRS) near Boise, Idaho, USA. Specifically, we jointly invert 31 intersecting crosshole GPR profiles to obtain a highly resolved and consistent radar velocity model along the various profile directions. The model is found to be strongly correlated with complementary neutron porosity-log data and is further corroborated by larger-scale structural information at the BHRS. This work is an important prerequisite to using crosshole GPR data together with existing hydrological measurements for improved groundwater flow and contaminant transport modeling.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.

An efficient algorithm to perform multiple testing in epistasis screening

Background: Research in epistasis or gene-gene interaction detection for human complex traits has grown over the last few years. It has been marked by promising methodological developments, improved translation efforts of statistical epistasis to biological epistasis and attempts to integrate different omics information sources into the epistasis screening to enhance power. The quest for gene-gene interactions poses severe multiple-testing problems. In this context, the maxT algorithm is one technique to control the false-positive rate. However, the memory needed by this algorithm rises linearly with the amount of hypothesis tests. Gene-gene interaction studies will require a memory proportional to the squared number of SNPs. A genome-wide epistasis search would therefore require terabytes of memory. Hence, cache problems are likely to occur, increasing the computation time. In this work we present a new version of maxT, requiring an amount of memory independent from the number of genetic effects to be investigated. This algorithm was implemented in C++ in our epistasis screening software MBMDR-3.0.3. We evaluate the new implementation in terms of memory efficiency and speed using simulated data. The software is illustrated on real-life data for Crohn’s disease. Results: In the case of a binary (affected/unaffected) trait, the parallel workflow of MBMDR-3.0.3 analyzes all gene-gene interactions with a dataset of 100,000 SNPs typed on 1000 individuals within 4 days and 9 hours, using 999 permutations of the trait to assess statistical significance, on a cluster composed of 10 blades, containing each four Quad-Core AMD Opteron(tm) Processor 2352 2.1 GHz. In the case of a continuous trait, a similar run takes 9 days. Our program found 14 SNP-SNP interactions with a multiple-testing corrected p-value of less than 0.05 on real-life Crohn’s disease (CD) data. Conclusions: Our software is the first implementation of the MB-MDR methodology able to solve large-scale SNP-SNP interactions problems within a few days, without using much memory, while adequately controlling the type I error rates. A new implementation to reach genome-wide epistasis screening is under construction. In the context of Crohn’s disease, MBMDR-3.0.3 could identify epistasis involving regions that are well known in the field and could be explained from a biological point of view. This demonstrates the power of our software to find relevant phenotype-genotype higher-order associations.

Large-scale DNA sequencing in taxonomy and conservation : a case study with the mayfly family Heptageniidae (Ephemeroptera) in the Alps and Madagascar

Les larves aquatiques d'éphémères (Ephemeroptera) colonisent toutes les eaux douces du monde et sont couramment utilisées comme bio-indicateurs de la qualité de l'eau. Le genre Rhithrogena (Heptageniidae) est le deuxième plus diversifié chez les éphémères, et plusieurs espèces européennes ont une distribution restreinte dans des environnements alpins sensibles. Les espèces de Rhithrogena ont été classées en "groupes d'espèces" faciles à identifier. Cependant, malgré leur importance écologique et en terme de conservation, beaucoup d'espèces présentent des différences morphologiques ambiguës, suggérant que lataxonomie actuelle ne refléterait pas correctement leur diversité évolutive. De plus, aucune information sur leurs relations, leur origine, le taux de spéciation ou les mécanismes ayant provoqué leur remarquable diversification dans les Alpes n'est disponible. Nous avons d'abord examiné le statut spécifique d'environ 50% des espèces européennes de Rhithrogena en utilisant un large échantillonnage de populations alpines incluant 22 localités typiques, ainsi qu'une analyse basée sur le modèle général mixte de Yule et de coalescence (GMYC) appliqué à un gène mitochondrial standard (coxl) et à un gène nucléaire développé spécifiquement pour cette étude. Nous avons observé un regroupement significatif des séquences coxl en 31 espèces potentielles, et nos résultats ont fortement suggéré la présence d'espèces cryptiques et de fractionnements taxonomiques excessifs chez les Rhithrogena. Nos analyses phylogénétiques ont démontré la monophylie de quatre des six groupes d'espèces reconnus présents dans notre échantillonnage. La taxonomie ADN développée dans cette étude pose les bases d'une future révision de ce genre important mais cryptique en Europe. Puis nous avons mené une étude phylogénétique multi-gènes entre les espèces européennes de Rhithrogena. Les données provenant de trois gènes nucléaires et de deux gènes mitochondriaux ont été largement concordantes, et les relations entre les espèces bien résolues au sein de la plupart des groupes d'espèces dans une analyse combinant tous les gènes. En l'absence de points de calibration extérieurs tels que des fossiles, nous avons appliqué à nos données mitochondriales une horloge moléculaire standard pour les insectes, suggérant une origine des Rhithrogena alpins à la limite Oligocène / Miocène. Nos résultats ont montré le rôle prépondérant qu'ont joué les glaciations du quaternaire dans leur diversification, favorisant la spéciation d'au moins la moitié des espèces actuelle dans les Alpes. La biodiversité et le taux d'endémisme à Madagascar, notamment au niveau de la faune des eaux douces, sont parmi les plus extraordinaires et les plus menacés au monde. On pense que beaucoup d'espèces d'éphémères sont restreintes à un seul bassin versant (microendémisme) dans les zones forestières, ce qui les rendrait particulièrement sensibles à la réduction et à la dégradation de leur habitat. Mis à part deux espèces décrites, Afronurus matitensis et Compsoneuria josettae, les Heptageniidae sont pratiquement inconnus à Madagascar. Les deux genres ont une distribution discontinue en Afrique, à Madagascar et en Asie du Sud-Est, et leur taxonomie complexe est régulièrement révisée. L'approche standard pour comprendre leur diversité, leur endémisme et leur origine requerrait un échantillonnage étendu sur plusieurs continents et des années de travaux taxonomiques. Pour accélérer le processus, nous avons utilisé des collections de musées ainsi que des individus fraîchement collectés, et appliqué une approche combinant taxonomie ADN et phylogénie. L'analyses GMYC du gène coxl a délimité 14 espèces potentielles à Madagascar, dont 70% vraisemblablement microendémiques. Une analyse phylogénique incluant des espèces africaines et asiatiques portant sur deux gènes mitochondriaux et quatre gènes nucléaires a montré que les Heptageniidae malgaches sont monophylétiques et groupe frère des Compsoneuria africains. L'existence de cette lignée unique, ainsi qu'un taux élevé de microendémisme, mettent en évidence leur importance en terme de conservation. Nos résultats soulignent également le rôle important que peuvent jouer les collections de musées dans les études moléculaires et en conservation. - Aquatic nymphs of mayflies (Ephemeroptera) colonize all types of freshwaters throughout the world and are extensively used as bio-indicators of water quality. Rhithrogena (Heptageniidae) is the second most species-rich genus of mayflies, and several European species have restricted distributions in sensitive Alpine environments and therefore are of conservation interest. The European Rhithrogena species are arranged into "species groups" that are easily identifiable. However, despite their ecological and conservation importance, ambiguous morphological differences among many species suggest that the current taxonomy may not accurately reflect their evolutionary diversity. Moreover, no information about their relationships, origin, timing of speciation and mechanisms promoting their successful diversification in the Alps is available. We first examined the species status of ca. 50% of European Rhithrogena diversity using a widespread sampling scheme of Alpine species that included 22 type localities, general mixed Yule- coalescent (GMYC) model analysis of one standard mitochondrial (coxl) and one newly developed nuclear marker. We observed significant clustering of coxl into 31 GMYC species, and our results strongly suggest the presence of both cryptic diversity and taxonomic oversplitting in Rhithrogena. Phylogenetic analyses recovered four of the six recognized species groups in our samples as monophyletic. The DNA taxonomy developed here lays the groundwork for a future revision of this important but cryptic genus in Europe. Then we conducted a species-level, multiple-gene phylogenetic study of European Rhithrogena. Data from three nuclear and two mitochondrial loci were broadly congruent, and species-level relationships were well resolved within most species groups in a combined analysis. In the absence of external calibration points like fossils, we applied a standard insect molecular clock hypothesis to our mitochondrial data, suggesting an origin of Alpine Rhithrogena in the Oligocene / Miocene boundary. Our results highlighted the preponderant role that quaternary glaciations played in their diversification, promoting speciation of at least half of the current diversity in the Alps. Madagascar's biodiversity and endemism are among the most extraordinary and endangered in the world. This includes the island's freshwater biodiversity, although detailed knowledge of the diversity, endemism, and biogeographic origin of freshwater invertebrates is lacking. Many mayfly species are thought to be restricted to single river basins (microendemic species) in forested areas, making them particularly sensitive to habitat reduction and degradation. The Heptageniidae are practically unknown in Madagascar except for two described species, Afronurus matitensis and Compsoneuria josettae. Both genera have a disjunct distribution in Africa, Madagascar and Southeast Asia, and a complex taxonomic status still in flux. The standard approach to understanding their diversity, endemism, and origin would require extensive field sampling on several continents and years of taxonomic work. Here we circumvent this using museum collections and freshly collected individuals in a combined approach of DNA taxonomy and phylogeny. The cox/-based GMYC analysis revealed 14 putative species on Madagascar, 70% of which potentially microendemics. A phylogenetic analysis that included African and Asian species and data from two mitochondrial and four nuclear loci indicated the Malagasy Heptageniidae are monophyletic and sister to African Compsoneuria. The observed monophyly and high microendemism highlight their conservation importance. Our results also underline the important role that museum collections can play in molecular studies, especially in critically endangered biodiversity hotspots like Madagascar.

Organic matter processing and soil evolution in a braided river system

Traditionally, braided river research has considered flow, sediment transport processes and, recently, vegetation dynamics in relation to river morphodynamics. However, if considering the development of woody vegetated patches over a time scale of decades, we must consider the extent to which soil forming processes, particularly related to soil organic matter, impact the alluvial geomorphic-vegetation system. Here we quantify the soil organic matter processing (humification) that occurs on young alluvial landforms. We sampled different geomorphic units, ranging from the active river channel to established river terraces in a braided river system. For each geomorphic unit, soil pits were used to sample sediment/soil layers that were analysed in terms of grain size (<2mm) and organic matter quantity and quality (RockEval method). A principal components analysis was used to identify patterns in the dataset. Results suggest that during the succession from bare river gravels to a terrace soil, there is a transition from small amounts of external organic matter supply provided by sedimentation processes (e.g. organic matter transported in suspension and deposited on bars), to large amounts of autogenic in situ organic matter production due to plant colonisation. This appears to change the time scale and pathways of alluvial succession (bio-geomorphic succession). However, this process is complicated by: the ongoing possibility of local sedimentation, which can serve to isolate surface layers via aggradation from the exogenic supply; and erosion which tends to create fresh deposits upon which organic matter processing must re-start. The result is a complex pattern of organic matter states as well as a general lack of any clear chronosequence within the active river corridor. This state reflects the continual battle between deposition events that can isolate organic matter from the surface, erosion events that can destroy accumulating organic matter and the early ecosystem processes necessary to assist the co-evolution of soil and vegetation. A key question emerges over the extent to which the fresh organic matter deposited in the active zone is capable of significantly transforming the local geochemical environment sufficiently to accelerate soil development.

In vivo brain macromolecule signals in healthy and glioblastoma mouse models: (1) H magnetic resonance spectroscopy, post-processing and metabolite quantification at 14.1 T.

In (1) H magnetic resonance spectroscopy, macromolecule signals underlay metabolite signals, and knowing their contribution is necessary for reliable metabolite quantification. When macromolecule signals are measured using an inversion-recovery pulse sequence, special care needs to be taken to correctly remove residual metabolite signals to obtain a pure macromolecule spectrum. Furthermore, since a single spectrum is commonly used for quantification in multiple experiments, the impact of potential macromolecule signal variability, because of regional differences or pathologies, on metabolite quantification has to be assessed. In this study, we introduced a novel method to post-process measured macromolecule signals that offers a flexible and robust way of removing residual metabolite signals. This method was applied to investigate regional differences in the mouse brain macromolecule signals that may affect metabolite quantification when not taken into account. However, since no significant differences in metabolite quantification were detected, it was concluded that a single macromolecule spectrum can be generally used for the quantification of healthy mouse brain spectra. Alternatively, the study of a mouse model of human glioma showed several alterations of the macromolecule spectrum, including, but not limited to, increased mobile lipid signals, which had to be taken into account to avoid significant metabolite quantification errors.

Reduced left hemisphere dominance for multiple versus single anagram solutions and its modulation by individuals' schizotypy

Problem solving (including insight, divergent thinking) seems to rely on the right hemisphere (RH). These functions are difficult to assess behaviorally. We propose anagram resolution as a suitable paradigm. University students (n=32) performed three tachistoscopic lateralized visual half-field experiments (stimulus presentation 150ms). In Experiment 1, participants recalled four-letter strings. Subsequently, participants provided solutions for four-letter anagrams (one solution in Experiment 2; two solutions in Experiment 3). Additionally, participants completed a schizotypy questionnaire (O-LIFE). Results showed a right visual field advantage in Experiment 1 and 2, but no visual field advantage in Experiment 3. In Experiment 1, increasing positive schizotypy associated with a RH performance shift. Problem solving seems to require increasingly the RH when facing several rather than one solution. This result supports previous studies on the RH's role in remote associative, metaphor and discourse processing. The more complex language requirements, the less personality traits seem to matter.

Early auditory processing

ABSTRACT (English)An accurate processing of the order between sensory events at the millisecond time scale is crucial for both sensori-motor and cognitive functions. Temporal order judgment (TOJ) tasks, is the ability of discriminating the order of presentation of several stimuli presented in a rapid succession. The aim of the present thesis is to further investigate the spatio-temporal brain mechanisms supporting TOJ. In three studies we focus on the dependency of TOJ accuracy on the brain states preceding the presentation of TOJ stimuli, the neural correlates of accurate vs. inaccurate TOJ and whether and how TOJ performance can be improved with training.In "Pre-stimulus beta oscillations within left posterior sylvian regions impact auditory temporal order judgment accuracy" (Bernasconi et al., 2011), we investigated if the brain activity immediately preceding the presentation of the stimuli modulates TOJ performance. By contrasting the electrophysiological activity before the stimulus presentation as a function of TOJ accuracy we observed a stronger pre-stimulus beta (20Hz) oscillatory activity within the left posterior sylvian region (PSR) before accurate than inaccurate TOJ trials.In "Interhemispheric coupling between the posterior sylvian regions impacts successful auditory temporal order judgment" (Bernasconi et al., 2010a), and "Plastic brain mechanisms for attaining auditory temporal order judgment proficiency" (Bernasconi et al., 2010b), we investigated the spatio-temporal brain dynamics underlying auditory TOJ. In both studies we observed a topographic modulation as a function of TOJ performance at ~40ms after the onset of the first sound, indicating the engagement of distinct configurations of intracranial generators. Source estimations in the first study revealed a bilateral PSR activity for both accurate and inaccurate TOJ trials. Moreover, activity within left, but not right, PSR correlated with TOJ performance. Source estimations in the second study revealed a training-induced left lateralization of the initial bilateral (i.e. PSR) brain response. Moreover, the activity within the left PSR region correlated with TOJ performance.Based on these results, we suggest that a "temporal stamp" is established within left PSR on the first sound within the pair at early stages (i.e. ~40ms) of cortical processes, but is critically modulated by inputs from right PSR (Bernasconi et al., 2010a; b). The "temporal stamp" on the first sound may be established via a sensory gating or prior entry mechanism.Behavioral and brain responses to identical stimuli can vary due to attention modulation, vary with experimental and task parameters or "internal noise". In a fourth experiment (Bernasconi et al., 2011b) we investigated where and when "neural noise" manifest during the stimulus processing. Contrasting the AEPs of identical sound perceived as High vs. Low pitch, a topographic modulation occurred at ca. 100ms after the onset of the sound. Source estimation revealed activity within regions compatible with pitch discrimination. Thus, we provided neurophysiological evidence for the variation in perception induced by "neural noise".ABSTRACT (French)Un traitement précis de l'ordre des événements sensoriels sur une échelle de temps de milliseconde est crucial pour les fonctions sensori-motrices et cognitives. Les tâches de jugement d'ordre temporel (JOT), consistant à présenter plusieurs stimuli en succession rapide, sont traditionnellement employées pour étudier les mécanismes neuronaux soutenant le traitement d'informations sensorielles qui varient rapidement. Le but de cette thèse est d'étudier le mécanisme cérébral soutenant JOT. Dans les trois études présentées nous nous sommes concentrés sur les états du cerveau précédant la présentation des stimuli de JOT, les bases neurales pour un JOT correct vs. incorrect et sur la possibilité et les moyens d'améliorer l'exécution du JOT grâce à un entraînement.Dans "Pre-stimulus beta oscillations within left posterior sylvian regions impact auditory temporal order judgment accuracy" (Bernasconi et al., 2011),, nous nous sommes intéressé à savoir si l'activité oscillatoire du cerveau au pré-stimulus modulait la performance du JOT. Nous avons contrasté l'activité électrophysiologique en fonction de la performance TOJ, mesurant une activité oscillatoire beta au pré-stimulus plus fort dans la région sylvian postérieure gauche (PSR) liée à un JOT correct.Dans "Interhemispheric coupling between the posterior sylvian regions impacts successful auditory temporal order judgment" (Bernasconi et al., 2010a), et "Plastic brain mechanisms for attaining auditory temporal order judgment proficiency" (Bernasconi et al., 2010b), nous avons étudié la dynamique spatio-temporelle dans le cerveau impliqué dans le traitement du JOT auditif. Dans ses deux études, nous avons observé une modulation topographique à ~40ms après le début du premier son, en fonction de la performance JOT, indiquant l'engagement des configurations de générateurs intra- crâniens distincts. La localisation de source dans la première étude indique une activité bilatérale de PSR pour des JOT corrects vs. incorrects. Par ailleurs, l'activité dans PSR gauche, mais pas dans le droit, est corrélée avec la performance du JOT. La localisation de source dans la deuxième étude indiquait une latéralisation gauche induite par l'entraînement d'une réponse initialement bilatérale du cerveau. D'ailleurs, l'activité dans la région PSR gauche corrèlait avec la performance de TOJ.Basé sur ces résultats, nous proposons qu'un « timbre-temporel » soit établi très tôt (c.-à-d. à ~40ms) sur le premier son par le PSR gauche, mais module par l'activité du PSR droite (Bernasconi et al., 2010a ; b). « Le timbre- temporel » sur le premier son peut être établi par le mécanisme neuronal de type « sensory gating » ou « prior entry ».Les réponses comportementales et du cerveau aux stimuli identiques peut varier du à des modulations d'attention ou à des variations dans les paramètres des tâches ou au bruit interne du cerveau. Dans une quatrième expérience (Bernasconi et al. 2011B), nous avons étudié où et quand le »bruit neuronal« se manifeste pendant le traitement des stimuli. En contrastant les AEPs de sons identiques perçus comme aigus vs. grave, nous avons mesuré une modulation topographique à env. 100ms après l'apparition du son. L'estimation de source a révélé une activité dans les régions compatibles avec la discrimination de fréquences. Ainsi, nous avons fourni des preuves neurophysiologiques de la variation de la perception induite par le «bruit neuronal».

Local and Regional Scale Determinants of Biodiversity Patterns in Boreal Agricultural Landscapes

This thesis examines the local and regional scale determinants of biodiversity patterns using existing species and environmental data. The research focuses on agricultural environments that have experienced rapid declines of biodiversity during past decades. Existing digital databases provide vast opportunities for habitat mapping, predictive mapping of species occurrences and richness and understanding the speciesenvironment relationships. The applicability of these databases depends on the required accuracy and quality of the data needed to answer the landscape ecological and biogeographical questions in hand. Patterns of biodiversity arise from confounded effects of different factors, such as climate, land cover and geographical location. Complementary statistical approaches that can show the relative effects of different factors are needed in biodiversity analyses in addition to classical multivariate models. Better understanding of the key factors underlying the variation in diversity requires the analyses of multiple taxonomic groups from different perspectives, such as richness, occurrence, threat status and population trends. The geographical coincidence of species richness of different taxonomic groups can be rather limited. This implies that multiple geographical regions should be taken into account in order to preserve various groups of species. Boreal agricultural biodiversity and in particular, distribution and richness of threatened species is strongly associated with various grasslands. Further, heterogeneous agricultural landscapes characterized by moderate field size, forest patches and non-crop agricultural habitats enhance the biodiversity of rural environments. From the landscape ecological perspective, the major threats to Finnish agricultural biodiversity are the decline of connected grassland habitat networks, and general homogenization of landscape structure resulting from both intensification and marginalization of agriculture. The maintenance of key habitats, such as meadows and pastures is an essential task in conservation of agricultural biodiversity. Furthermore, a larger landscape context should be incorporated in conservation planning and decision making processes in order to respond to the needs of different species and to maintain heterogeneous rural landscapes and viable agricultural diversity in the future.