Neuroplasticity of inhibitory control

Executive control refers to a set of abilities enabling us to plan, control and implement our behavior to rapidly and flexibly adapt to environmental requirements. These adaptations notably involve the suppression of intended or ongoing cognitive or motor processes, a skill referred to as "inhibitory control". To implement efficient executive control of behavior, one must monitor our performance following errors to adjust our behavior accordingly. Deficits in inhibitory control have been associated with the emergènce of a wide range of psychiatric disorders, ranging from drug addiction to attention deficit/hyperactivity disorders. Inhibitory control deficits could, however, be remediated- The brain has indeed the amazing possibility to reorganize following training to allow for behavioral improvements. This mechanism is referred to as neural and behavioral plasticity. Here, our aim is to investigate training-induced plasticity in inhibitory control and propose a model of inhibitory control explaining the spatio- temporal brain mechanisms supporting inhibitory control processes and their plasticity. In the two studies entitled "Brain dynamics underlying training-induced improvement in suppressing inappropriate action" (Manuel et al., 2010) and "Training-induced neuroplastic reinforcement óf top-down inhibitory control" (Manuel et al., 2012c), we investigated the neurophysiological and behavioral changes induced by inhibitory control training with two different tasks and populations of healthy participants. We report that different inhibitory control training developed either automatic/bottom-up inhibition in parietal areas or reinforced controlled/top-down inhibitory control in frontal brain regions. We discuss the results of both studies in the light of a model of fronto-basal inhibition processes. In "Spatio-temporal brain dynamics mediating post-error behavioral adjustments" (Manuel et al., 2012a), we investigated how error detection modulates the processing of following stimuli and in turn impact behavior. We showed that during early integration of stimuli, the activity of prefrontal and parietal areas is modulated according to previous performance and impacts the post-error behavioral adjustments. We discuss these results in terms of a shift from an automatic to a controlled form of inhibition induced by the detection of errors, which in turn influenced response speed. In "Inter- and intra-hemispheric dissociations in ideomotor apraxia: a large-scale lesion- symptom mapping study in subacute brain-damaged patients" (Manuel et al., 2012b), we investigated ideomotor apraxia, a deficit in performing pantomime gestures of object use, and identified the anatomical correlates of distinct ideomotor apraxia error types in 150 subacute brain-damaged patients. Our results reveal a left intra-hemispheric dissociation for different pantomime error types, but with an unspecific role for inferior frontal areas. Les fonctions exécutives désignent un ensemble de processus nous permettant de planifier et contrôler notre comportement afin de nous adapter de manière rapide et flexible à l'environnement. L'une des manières de s'adapter consiste à arrêter un processus cognitif ou moteur en cours ; le contrôle de l'inhibition. Afin que le contrôle exécutif soit optimal il est nécessaire d'ajuster notre comportement après avoir fait des erreurs. Les déficits du contrôle de l'inhibition sont à l'origine de divers troubles psychiatriques tels que l'addiction à la drogue ou les déficits d'attention et d'hyperactivité. De tels déficits pourraient être réhabilités. En effet, le cerveau a l'incroyable capacité de se réorganiser après un entraînement et ainsi engendrer des améliorations comportementales. Ce mécanisme s'appelle la plasticité neuronale et comportementale. Ici, notre but èst d'étudier la plasticité du contrôle de l'inhibition après un bref entraînement et de proposer un modèle du contrôle de l'inhibition qui permette d'expliquer les mécanismes cérébraux spatiaux-temporels sous-tendant l'amélioration du contrôle de l'inhibition et de leur plasticité. Dans les deux études intitulées "Brain dynamics underlying training-induced improvement in suppressing inappropriate action" (Manuel et al., 2010) et "Training-induced neuroplastic reinforcement of top-down inhibitory control" (Manuel et al., 2012c), nous nous sommes intéressés aux changements neurophysiologiques et comportementaux liés à un entraînement du contrôle de l'inhibition. Pour ce faire, nous avons étudié l'inhibition à l'aide de deux différentes tâches et deux populations de sujets sains. Nous avons démontré que différents entraînements pouvaient soit développer une inhibition automatique/bottom-up dans les aires pariétales soit renforcer une inhibition contrôlée/top-down dans les aires frontales. Nous discutons ces résultats dans le contexte du modèle fronto-basal du contrôle de l'inhibition. Dans "Spatio-temporal brain dynamics mediating post-error behavioral adjustments" (Manuel et al., 2012a), nous avons investigué comment la détection d'erreurs influençait le traitement du prochain stimulus et comment elle agissait sur le comportement post-erreur. Nous avons montré que pendant l'intégration précoce des stimuli, l'activité des aires préfrontales et pariétales était modulée en fonction de la performance précédente et avait un impact sur les ajustements post-erreur. Nous proposons que la détection d'erreur ait induit un « shift » d'un mode d'inhibition automatique à un mode contrôlé qui a à son tour influencé le temps de réponse. Dans "Inter- and intra-hemispheric dissociations in ideomotor apraxia: a large-scale lesion-symptom mapping study in subacute brain-damaged patients" (Manuel et al., 2012b), nous avons examiné l'apraxie idémotrice, une incapacité à exécuter des gestes d'utilisation d'objets, chez 150 patients cérébro-lésés. Nous avons mis en avant une dissociation intra-hémisphérique pour différents types d'erreurs avec un rôle non spécifique pour les aires frontales inférieures.

Visual functions in the healthy and schizophrenic brain : from stimulus control to illusory perceptions using electrical neuroimaging

ABSTRACT (FRENCH)Ce travail de thèse basé sur le système visuel chez les sujets sains et chez les patients schizophrènes, s'articule autour de trois articles scientifiques publiés ou en cours de publication. Ces articles traitent des sujets suivants : le premier article présente une nouvelle méthode de traitement des composantes physiques des stimuli (luminance et fréquence spatiale). Le second article montre, à l'aide d'analyses de données EEG, un déficit de la voie magnocellulaire dans le traitement visuel des illusions chez les patients schizophrènes. Ceci est démontré par l'absence de modulation de la composante PI chez les patients schizophrènes contrairement aux sujets sains. Cette absence est induite par des stimuli de type illusion Kanizsa de différentes excentricités. Finalement, le troisième article, également à l'aide de méthodes de neuroimagerie électrique (EEG), montre que le traitement des contours illusoires se trouve dans le complexe latéro-occipital (LOC), à l'aide d'illusion « misaligned gratings ». De plus il révèle que les activités démontrées précédemment dans les aires visuelles primaires sont dues à des inférences « top- down ».Afin de permettre la compréhension de ces trois articles, l'introduction de ce manuscrit présente les concepts essentiels. De plus des méthodes d'analyses de temps-fréquence sont présentées. L'introduction est divisée en quatre parties : la première présente le système visuel depuis les cellules retino-corticales aux deux voix du traitement de l'information en passant par les régions composant le système visuel. La deuxième partie présente la schizophrénie par son diagnostic, ces déficits de bas niveau de traitement des stimuli visuel et ces déficits cognitifs. La troisième partie présente le traitement des contours illusoires et les trois modèles utilisés dans le dernier article. Finalement, les méthodes de traitement des données EEG seront explicitées, y compris les méthodes de temps-fréquences.Les résultats des trois articles sont présentés dans le chapitre éponyme (du même nom). De plus ce chapitre comprendra les résultats obtenus à l'aide des méthodes de temps-fréquenceFinalement, la discussion sera orientée selon trois axes : les méthodes de temps-fréquence ainsi qu'une proposition de traitement de ces données par une méthode statistique indépendante de la référence. La discussion du premier article en montrera la qualité du traitement de ces stimuli. La discussion des deux articles neurophysiologiques, proposera de nouvelles d'expériences afin d'affiner les résultats actuels sur les déficits des schizophrènes. Ceci pourrait permettre d'établir un marqueur biologique fiable de la schizophrénie.ABSTRACT (ENGLISH)This thesis focuses on the visual system in healthy subjects and schizophrenic patients. To address this research, advanced methods of analysis of electroencephalographic (EEG) data were used and developed. This manuscript is comprised of three scientific articles. The first article showed a novel method to control the physical features of visual stimuli (luminance and spatial frequencies). The second article showed, using electrical neuroimaging of EEG, a deficit in spatial processing associated with the dorsal pathway in chronic schizophrenic patients. This deficit was elicited by an absent modulation of the PI component in terms of response strength and topography as well as source estimations. This deficit was orthogonal to the preserved ability to process Kanizsa-type illusory contours. Finally, the third article resolved ongoing debates concerning the neural mechanism mediating illusory contour sensitivity by using electrical neuroimaging to show that the first differentiation of illusory contour presence vs. absence is localized within the lateral occipital complex. This effect was subsequent to modulations due to the orientation of misaligned grating stimuli. Collectively, these results support a model where effects in V1/V2 are mediated by "top-down" modulation from the LOC.To understand these three articles, the Introduction of this thesis presents the major concepts used in these articles. Additionally, a section is devoted to time-frequency analysis methods not presented in the articles themselves. The introduction is divided in four parts. The first part presents three aspects of the visual system: cellular, regional, and its functional interactions. The second part presents an overview of schizophrenia and its sensoiy-cognitive deficits. The third part presents an overview of illusory contour processing and the three models examined in the third article. Finally, advanced analysis methods for EEG are presented, including time- frequency methodology.The Introduction is followed by a synopsis of the main results in the articles as well as those obtained from the time-frequency analyses.Finally, the Discussion chapter is divided along three axes. The first axis discusses the time frequency analysis and proposes a novel statistical approach that is independent of the reference. The second axis contextualizes the first article and discusses the quality of the stimulus control and direction for further improvements. Finally, both neurophysiologic articles are contextualized by proposing future experiments and hypotheses that may serve to improve our understanding of schizophrenia on the one hand and visual functions more generally.

Adaptive strategy for the statistical analysis of connectomes.

We study an adaptive statistical approach to analyze brain networks represented by brain connection matrices of interregional connectivity (connectomes). Our approach is at a middle level between a global analysis and single connections analysis by considering subnetworks of the global brain network. These subnetworks represent either the inter-connectivity between two brain anatomical regions or by the intra-connectivity within the same brain anatomical region. An appropriate summary statistic, that characterizes a meaningful feature of the subnetwork, is evaluated. Based on this summary statistic, a statistical test is performed to derive the corresponding p-value. The reformulation of the problem in this way reduces the number of statistical tests in an orderly fashion based on our understanding of the problem. Considering the global testing problem, the p-values are corrected to control the rate of false discoveries. Finally, the procedure is followed by a local investigation within the significant subnetworks. We contrast this strategy with the one based on the individual measures in terms of power. We show that this strategy has a great potential, in particular in cases where the subnetworks are well defined and the summary statistics are properly chosen. As an application example, we compare structural brain connection matrices of two groups of subjects with a 22q11.2 deletion syndrome, distinguished by their IQ scores.

An Automatic Approach for Learning and Tuning Gaussian Interval Type-2 Fuzzy Membership Functions Applied to Lung CAD Classification System

The potential of type-2 fuzzy sets for managing high levels of uncertainty in the subjective knowledge of experts or of numerical information has focused on control and pattern classification systems in recent years. One of the main challenges in designing a type-2 fuzzy logic system is how to estimate the parameters of type-2 fuzzy membership function (T2MF) and the Footprint of Uncertainty (FOU) from imperfect and noisy datasets. This paper presents an automatic approach for learning and tuning Gaussian interval type-2 membership functions (IT2MFs) with application to multi-dimensional pattern classification problems. T2MFs and their FOUs are tuned according to the uncertainties in the training dataset by a combination of genetic algorithm (GA) and crossvalidation techniques. In our GA-based approach, the structure of the chromosome has fewer genes than other GA methods and chromosome initialization is more precise. The proposed approach addresses the application of the interval type-2 fuzzy logic system (IT2FLS) for the problem of nodule classification in a lung Computer Aided Detection (CAD) system. The designed IT2FLS is compared with its type-1 fuzzy logic system (T1FLS) counterpart. The results demonstrate that the IT2FLS outperforms the T1FLS by more than 30% in terms of classification accuracy.

Early attentional processes distinguish selective from global motor inhibitory control : An electrical neuroimaging study

The rapid stopping of specific parts of movements is frequently required in daily life. Yet, whether selective inhibitory control of movements is mediated by a specific neural pathway or by the combination between a global stopping of all ongoing motor activity followed by the re-initiation of task-relevant movements remains unclear. To address this question, we applied time-wise statistical analyses of the topography, global field power and electrical sources of the event-related potentials to the global vs selective inhibition stimuli presented during a Go/NoGo task. Participants (n = 18) had to respond as fast as possible with their two hands to Go stimuli and to withhold the response from the two hands (global inhibition condition, GNG) or from only one hand (selective inhibition condition, SNG) when specific NoGo stimuli were presented. Behaviorally, we replicated previous evidence for slower response times in the SNG than in the Go condition. Electrophysiologically, there were two distinct phases of event-related potentials modulations between the GNG and the SNG conditions. At 110âeuro"150 ms post-stimulus onset, there was a difference in the strength of the electric field without concomitant topographic modulation, indicating the differential engagement of statistically indistinguishable configurations of neural generators for selective and global inhibitory control. At 150âeuro"200 ms, there was topographic modulation, indicating the engagement of distinct brain networks. Source estimations localized these effects within bilateral temporo-parieto-occipital and within parieto-central networks, respectively. Our results suggest that while both types of motor inhibitory control depend on global stopping mechanisms, selective and global inhibition still differ quantitatively at early attention-related processing phases.

Regulation of innate and adaptive immunity by Notch.

Coordinated function of the innate and adaptive arms of the immune system in vertebrates is essential to promote protective immunity and to avoid immunopathology. The Notch signalling pathway, which was originally identified as a pleiotropic mediator of cell fate in invertebrates, has recently emerged as an important regulator of immune cell development and function. Notch was initially shown to be a key determinant of cell-lineage commitment in developing lymphocytes, but it is now known to control the homeostasis of several innate cell populations. Moreover, the roles of Notch in adaptive immunity have expanded to include the regulation of T cell differentiation and function. The aim of this Review is to summarize the current status of immune regulation by Notch. A better understanding of Notch function in both innate and adaptive immunity will hopefully provide multiple avenues for therapeutic intervention in disease.

Adaptive frequency tracking of the baseline ECG identifies the site of atrial fibrillation termination by catheter ablation

Multiple organization indices have been used to predict the outcome of stepwise catheter ablation in long-standing persistent atrial fibrillation (AF), however with limited success. Our study aims at developinginnovative organization indices from baseline ECG (i.e. during the procedure, before ablation) in orderto identify the site of AF termination by catheter ablation. Seventeen consecutive male patients (age60 ± 5 years, AF duration 7 ± 5 years) underwent a stepwise catheter ablation. Chest lead V6 was placedin the back (V6b). QRST cancelation was performed from chest leads V1 to V6b. Using an innovativeadaptive harmonic frequency tracking, two measures of AF organization were computed to quantify theharmonics components of ECG activity: (1) the adaptive phase difference variance (APD) between theAF harmonic components as a measure of AF regularity, and (2) and adaptive organization index (AOI)evaluating the cyclicity of the AF oscillations. Both adaptive indices were compared to indices computedusing a time-invariant approach: (1) ECG AF cycle length (AFCL), (2) the spectrum based organizationindex (OI), and (3) the time-invariant phase difference TIPD. Long-standing persistent AF was terminatedinto sinus rhythm or atrial tachycardia in 13/17 patients during stepwise ablation, 11 during left atriumablation (left terminated patients - LT), 2 during the right atrium ablation (right terminated patients -RT), and 4 were non terminated (NT) and required electrical cardioversion. Our findings showed that LTpatients were best separated from RT/NT before ablation by the duration of sustained AF and by AOI onchest lead V1 and APD from the dorsal lead V6b as compared to ECG AFCL, OI and TIPD, respectively. Ourresults suggest that adaptive measures of AF organization computed before ablation perform better thantime-invariant based indices for identifying patients whose AF will terminate during ablation within theleft atrium. These findings are indicative of a higher baseline organization in these patients that could beused to select candidates for the termination of AF by stepwise catheter ablation.© 2013 Elsevier Ltd. All rights reserved.

Control of mitochondrial pH by uncoupling protein 4 in astrocytes promotes neuronal survival.

Brain activity is energetically costly and requires a steady and highly regulated flow of energy equivalents between neural cells. It is believed that a substantial share of cerebral glucose, the major source of energy of the brain, will preferentially be metabolized in astrocytes via aerobic glycolysis. The aim of this study was to evaluate whether uncoupling proteins (UCPs), located in the inner membrane of mitochondria, play a role in setting up the metabolic response pattern of astrocytes. UCPs are believed to mediate the transmembrane transfer of protons, resulting in the uncoupling of oxidative phosphorylation from ATP production. UCPs are therefore potentially important regulators of energy fluxes. The main UCP isoforms expressed in the brain are UCP2, UCP4, and UCP5. We examined in particular the role of UCP4 in neuron-astrocyte metabolic coupling and measured a range of functional metabolic parameters including mitochondrial electrical potential and pH, reactive oxygen species production, NAD/NADH ratio, ATP/ADP ratio, CO2 and lactate production, and oxygen consumption rate. In brief, we found that UCP4 regulates the intramitochondrial pH of astrocytes, which acidifies as a consequence of glutamate uptake, with the main consequence of reducing efficiency of mitochondrial ATP production. The diminished ATP production is effectively compensated by enhancement of glycolysis. This nonoxidative production of energy is not associated with deleterious H2O2 production. We show that astrocytes expressing more UCP4 produced more lactate, which is used as an energy source by neurons, and had the ability to enhance neuronal survival.

Electroencephalogram paroxysmal theta characterizes cataplexy in mice and children.

Astute control of brain activity states is critical for adaptive behaviours and survival. In mammals and birds, electroencephalographic recordings reveal alternating states of wakefulness, slow wave sleep and paradoxical sleep (or rapid eye movement sleep). This control is profoundly impaired in narcolepsy with cataplexy, a disease resulting from the loss of orexin/hypocretin neurotransmitter signalling in the brain. Narcolepsy with cataplexy is characterized by irresistible bouts of sleep during the day, sleep fragmentation during the night and episodes of cataplexy, a sudden loss of muscle tone while awake and experiencing emotions. The neural mechanisms underlying cataplexy are unknown, but commonly thought to involve those of rapid eye movement-sleep atonia, and cataplexy typically is considered as a rapid eye movement sleep disorder. Here we reassess cataplexy in hypocretin (Hcrt, also known as orexin) gene knockout mice. Using a novel video/electroencephalogram double-blind scoring method, we show that cataplexy is not a state per se, as believed previously, but a dynamic, multi-phased process involving a reproducible progression of states. A knockout-specific state and a stereotypical paroxysmal event were introduced to account for signals and electroencephalogram spectral characteristics not seen in wild-type littermates. Cataplexy almost invariably started with a brief phase of wake-like electroencephalogram, followed by a phase featuring high-amplitude irregular theta oscillations, defining an activity profile distinct from paradoxical sleep, referred to as cataplexy-associated state and in the course of which 1.5-2 s high-amplitude, highly regular, hypersynchronous paroxysmal theta bursts (∼7 Hz) occurred. In contrast to cataplexy onset, exit from cataplexy did not show a predictable sequence of activities. Altogether, these data contradict the hypothesis that cataplexy is a state similar to paradoxical sleep, even if long cataplexies may evolve into paradoxical sleep. Although not exclusive to overt cataplexy, cataplexy-associated state and hypersynchronous paroxysmal theta activities are highly enriched during cataplexy in hypocretin/orexin knockout mice. Their occurrence in an independent narcolepsy mouse model, the orexin/ataxin 3 transgenic mouse, undergoing loss of orexin neurons, was confirmed. Importantly, we document for the first time similar paroxysmal theta hypersynchronies (∼4 Hz) during cataplexy in narcoleptic children. Lastly, we show by deep recordings in mice that the cataplexy-associated state and hypersynchronous paroxysmal theta activities are independent of hippocampal theta and involve the frontal cortex. Cataplexy hypersynchronous paroxysmal theta bursts may represent medial prefrontal activity, associated in humans and rodents with reward-driven motor impulse, planning and conflict monitoring.

Contribution of the gap junction proteins Connexin40 and Connexin43 to the control of blood pressure

Summary Cells in tissues and organs coordinate their activities by communicating with each other through intercellular channels named gap junctions. These channels are conduits between the cytoplasmic compartments of adjacent cells, allowing the exchange of small molecules which may be crucial for hormone secretion. Renin is normally secreted in a regulated manner by specific cells of the juxtaglomerular apparatus located within the renal cortex. Gap junctional communication may be requisite to maintain an accurate functioning in coordination of renin-producing cells, more especially as renin is of paramount importance for the control of blood pressure. Connexin43 (Cx43) and Cx40 form gap junctions that link in vivo the cells of the juxtaglomerular apparatus. Cx43 links the endothelial cells, whereas gap junctions made of Cx40 connect the endothelial cells, the renin secreting cells, as well as the endothelial cells of to the renin-secreting cells of the afferent arteriole. The observation that loss of Cx40 results in chronic hypertension associated with altered vasomotion and signal conduction along arterioles, has lead us to suggest that connexins may contribute to control blood pressure by participating to the integration of various mechanical, osmotic and electrochemical stimuli involved in the control of renin secretion and by mediating the adaptive changes of the vascular wall induced by elevated blood pressure and mechanical stress. We therefore postulated that the absence of Cx40 could have deleterious effects on the coordinated functioning of the renin-containing cells, hence accounting for hypertension. In the first part of my thesis, we reported that Cx40-deficient mice (Cx40) are hypertensive due to increased plasma renin levels and numbers of renin-producing cells. Besides, we demonstrated that prostaglandins and nitric oxide, which are possible mediators in the regulation of renin secretion by the macula densa, exert a critical role in the mechanisms controlling blood pressure ín Cx40 knockout hypertensive mice. In view of previous studies that stated avessel-specifc increase in the expression of Cx43 during renin-dependent hypertension, we hypothesized that Cx43 channels are particularly well-matched to integrate the response of cells constituting the vascular wall to hypertensive conditions. Using transgenic mice in which Cx43 was replaced by Cx32, we revealed that the replacement of Cx43 by Cx32 is associated with decreased expression and secretion of renin and prevent the renin-dependent hypertension which is normally induced in the 2K1C model. To gain insights into the regulation of connexins in two separate tissues exposed to the same fluid pressure, the second part of my thesis work was dedicated to the study of the impact of chronic hypertension and related hypertrophy on the expression of the cardiovascular connexins (Cx40, Cx37, Cx43 and Cx45) in mouse aorta and heart. Our results documented that the expression of connexins is differentially regulated in mouse aorta. according to the models of hypertension. Thus, blood pressure induces mechanical forces that differentially alter the expression of vascular connexins in order to respond to an adaptation of the aortic wall observed under pathological conditions. Altogether these data provide the first evidences that intercellular communication mediated by gap junctions is required for a proper renin secretion from the juxtaglomerular apparatus in order to control blood pressure.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Neural regulation of pancreatic islet cell mass and function.

Intracellular glucose signalling pathways control the secretion of glucagon and insulin by pancreatic islet α- and β-cells, respectively. However, glucose also indirectly controls the secretion of these hormones through regulation of the autonomic nervous system that richly innervates this endocrine organ. Both parasympathetic and sympathetic nervous systems also impact endocrine pancreas postnatal development and plasticity in adult animals. Defects in these autonomic regulations impair β-cell mass expansion during the weaning period and β-cell mass adaptation in adult life. Both branches of the autonomic nervous system also regulate glucagon secretion. In type 2 diabetes, impaired glucose-dependent autonomic activity causes the loss of cephalic and first phases of insulin secretion, and impaired suppression of glucagon secretion in the postabsorptive phase; in diabetic patients treated with insulin, it causes a progressive failure of hypoglycaemia to trigger the secretion of glucagon and other counterregulatory hormones. Therefore, identification of the glucose-sensing cells that control the autonomic innervation of the endocrine pancreatic and insulin and glucagon secretion is an important goal of research. This is required for a better understanding of the physiological control of glucose homeostasis and its deregulation in diabetes. This review will discuss recent advances in this field of investigation.

Accurate and efficient simulation of multiphase flow in a heterogeneous reservoir by using error estimate and control in the multiscale finite-volume framework

The multiscale finite-volume (MSFV) method is designed to reduce the computational cost of elliptic and parabolic problems with highly heterogeneous anisotropic coefficients. The reduction is achieved by splitting the original global problem into a set of local problems (with approximate local boundary conditions) coupled by a coarse global problem. It has been shown recently that the numerical errors in MSFV results can be reduced systematically with an iterative procedure that provides a conservative velocity field after any iteration step. The iterative MSFV (i-MSFV) method can be obtained with an improved (smoothed) multiscale solution to enhance the localization conditions, with a Krylov subspace method [e.g., the generalized-minimal-residual (GMRES) algorithm] preconditioned by the MSFV system, or with a combination of both. In a multiphase-flow system, a balance between accuracy and computational efficiency should be achieved by finding a minimum number of i-MSFV iterations (on pressure), which is necessary to achieve the desired accuracy in the saturation solution. In this work, we extend the i-MSFV method to sequential implicit simulation of time-dependent problems. To control the error of the coupled saturation/pressure system, we analyze the transport error caused by an approximate velocity field. We then propose an error-control strategy on the basis of the residual of the pressure equation. At the beginning of simulation, the pressure solution is iterated until a specified accuracy is achieved. To minimize the number of iterations in a multiphase-flow problem, the solution at the previous timestep is used to improve the localization assumption at the current timestep. Additional iterations are used only when the residual becomes larger than a specified threshold value. Numerical results show that only a few iterations on average are necessary to improve the MSFV results significantly, even for very challenging problems. Therefore, the proposed adaptive strategy yields efficient and accurate simulation of multiphase flow in heterogeneous porous media.

Adaptive tracking of EEG oscillations.

Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception. However, measuring this activity and its influence requires precise extraction of frequency components. This processing is not straightforward. Particularly, difficulties with extracting oscillations arise due to their time-varying characteristics. Moreover, when phase information is needed, it is of the utmost importance to extract narrow-band signals. This paper presents a novel method using adaptive filters for tracking and extracting these time-varying oscillations. This scheme is designed to maximize the oscillatory behavior at the output of the adaptive filter. It is then capable of tracking an oscillation and describing its temporal evolution even during low amplitude time segments. Moreover, this method can be extended in order to track several oscillations simultaneously and to use multiple signals. These two extensions are particularly relevant in the framework of EEG data processing, where oscillations are active at the same time in different frequency bands and signals are recorded with multiple sensors. The presented tracking scheme is first tested with synthetic signals in order to highlight its capabilities. Then it is applied to data recorded during a visual shape discrimination experiment for assessing its usefulness during EEG processing and in detecting functionally relevant changes. This method is an interesting additional processing step for providing alternative information compared to classical time-frequency analyses and for improving the detection and analysis of cross-frequency couplings.

An adaptive multiscale method for density-driven instabilities

Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.