Studies of the mechanisms in the brain that allow complex neuronal activity to arise in a coordinated fashion have produced some of the most spectacular discoveries in neuroscience, and still promise huge potential understanding as novel technological and especially methodological tools are developped. Neurophysiology has allowed to understand small-scale networks of neurons, and the study of brain lesions has identified local brain areas specifically associated with a certain function. Non-invasive brain imaging techniques, such as electro- or magneto-encephalography (EEG and MEG) and functional magnetic resonance imaging (fMRI) have brought brain research an incredible amount of a novel type of data, that is, multivariate time series representing local dynamics at each of multiple sites or sources throughout the whole human brain while functioning. These data have already demonstrated that neurophysiological processes typically have long memory or fractal scaling properties at a univariate level of analysis and demonstrate complex network topological organization at a multivariate level of analysis using wavelet correlations. Compared to estimators employed previously, this wavelet correlation is well-behaved for long memory and nonstationary processes. These findings suggest that brain dynamics and networks may have important statistical properties in common with other, substantively diverse, complex systems that are currently the focus of exciting activity in the general field of statistical physics. This project is focusing on the study of consciousness disorders (a medical state that follows coma) for which understanding the disconnexion process of the brain is crucial to improve everyday management for these patients. Consciousness disorders is a major concern in public health. Due to the progress in intensive care, more and more patients will survive severe acute brain damage. Disorders of consciousness can be acute and reversible or they can be irreversible and permanent. In the context of consciousness disorders, the aim of this project is to characterize multivariate neurophysiological datasets to elucidate the biological basis for information processing and propragation in the human brain. Neuroimagery provides us with time series, associated with either voxels or sensors, which correspond to the information processed by a brain area in time. These data have brought to light the dynamic nature of the brain, which follows complex time patterns, a subject which has been at the center of neuroscience for a century; but so far, the space-time patterns have remained nearly unexplored. This is why the revolution of understanding that they can bring is yet to come, as what they reveal of the circulation of the information in the brain and its dynamics has not been yet successfully analysed. Participating in this novel understanding, this project will open up new directions to help clinicians for the diagnosis and to give better predictions concerning the possible recovery of these patients. This will also bring new opportunities to understand the spontaneous fluctuations in brain activity observed on resting state healthy volunteers and the nature of consciousness. More generally, after Geschwind's pioneer work in neurology and psychiatry, pathologies could be described in terms of disconnection syndromes. Thus, the approach described here might be extended to other pathologies such as multiple sclerosis, epilepsy, stroke, Alzheimer disease, schizophrenia. This project requires a very broad skillset, comprising statistical signal processing, complex network analysis and visualization, and systems neuroscience. Thus, the team is composed of experts in medical applications (S. Krémer), neurosciences (C. Delon-Martin), statistics (S. Achard and J.-F. Coeurjolly) and signal processing (V. Noblet).

TOTS stands for Tomographie OcÈanique en zone peu profonde : nouvelles perspectives en Traitement du Signal (Shallow water tomography: new trends in array signal processing) and addresses 3 different tomography problems: - Classical tomography providing the spatio-temporal sound speed structure of a ocean portion, - Detection-localization of a target in shallow water, performed using an impedance tomography - Surface tomography. These problems, usually considered separately, are studied jointly in the project as most of the methods developed for one of them can be used (if adapted) for the others. Performing tomography in shallow water, which is still an almost unknown environment, is particularly interesting as its knowledge could help scientists to better understand streams, tides, human influence and pollution in coastal areas. Consequently, they need the precise knowledge of the spatial-temporal distribution of ocean temperature. Moreover, performing the other tomographies to localize an underwater source and to estimate the surface height is also very interesting as these problems have many applications (acoustic barrier in harbors for example) which are not solved yet. As written by Munk et al, "The problem of acoustic tomography is to infer, from precise measurement of travel time, or of other properties of acoustic propagation, the state of the ocean traversed by the sound field". The first task to perform Ocean Acoustic Tomography is then to choose the best acoustic observables and to measure them as accurately as possible. Then, once the acoustic observables are extracted, the second step consists in building a forward model linking acoustic observables to ocean physical parameters. Finally, the last step of the tomographic process is to invert for ocean physical parameters such as for example, the spatial-temporal temperature distribution in the ocean. The principal limitation is that tomography needs the separation and identification of the different arrivals in the signal which is a difficult task in a multipath recorded signal. One of the goals of our project is to overtake this limitation in shallow water configuration taking profit of source-receive array configuration. This will be done developing and using different approaches: double beamforming, adaptive double beamforming, high resolution methods. The other main difficulty to perform shallow water tomography is to establish a link between acoustic observables and physical parameters we invert for. Classical tomography uses ray modelization of the propagation to perform this task but this model does not take into account acoustic diffraction. As a result, the way to include it in tomography inversion is to deal with Sensitivity Kernels that have been widely used in seismic tomography. Studying Sensitivity Kernels and their use in high-resolution shallow water tomography will be very useful to develop more accurate tomography methods. Finally, all these methods will be validated on real data. We will have access to the existing FAF03 and FAF05 data set provided by the Marine Physical Laboratory (San Diego). We will also perform laboratory experiments in a more controlled environment. They will be performed in an ultrasonic tank developed by P. Roux at the Laboratoire de GÈophysique Interne et Tectonophysique (LGIT) in Grenoble. This project is thus a multidisciplinary project, carried by researchers from different scientific fields, which deals with two main tasks: development of the methods (from the extraction of acoustic observables to inversion) and application of these methods on real data (at-sea and tank data) to perform high-resolution shallow water tomography. Through this project, we aim at gathering, around Barbara Nicolas, a junior CNRS research scientist at Gipsa-lab, a work force in Grenoble devoted to research on shallow water tomography. The two laboratories involved in this project are GIPSA-lab and LGIT-Grenoble.

Mono- and digalactosyldiacylglycerol (MGDG and DGDG) are the most abundant lipids of photosynthetic membranes in chloroplasts of algae and plant cells. These galactolipids constitute therefore the most profuse lipid class on earth. Due to their high levels in food of plant origin, they are a primary source of galactose and fatty acids in human diet. Galactolipids have long been considered to be strictly localized in plastids (a plant specific organelle), where they constitute 80% of membrane lipids, in contrast with the endomembrane system and mitochondria which are phospholipid-rich. However, DGDG can relocate outside plastids to replace phospholipids in response to phosphate (Pi) deficiency. Galactolipid and phospholipid metabolisms are thus coupled, although the respective biosynthetic pathways are in distinct organelles, i.e. the plastid envelope for galactolipids and endoplasmic reticulum for phospholipids. The question addressed here is to understand how MGDG synthesis can be controlled by a molecular tuning of MGD enzymes, in relation with the phospholipid metabolism. The proposed project falls in the scope of the SVSE5 axis of the call (enzymology, structural biology, membrane systems, biomimetic systems). In Arabidopsis, a multigenic family of MGDG synthases (MGD1, 2, 3) can catalyze the galactosylation of diacylglycerol (DAG). MGD1 is the most abundant, localized in the inner envelope membrane of chloroplasts and is essential for the expansion of thylakoids. Expression of MGD2 and 3 increases in response to Pi shortage, indicating that the lipid-remodelling observed in this condition implies MGD2 and 3 isoforms in a genetic regulation. Partners 1 and 2 have recently examined the possible role of phosphatidic acid (PA) in a metabolic regulation since PA is known to act as a signalling molecule, is a precursor of phospholipids and a product of phospholipid breakdown by phospholipases D. PA was shown to be a strong and specific activator of MGD1 and could be a key regulator in the galactolipid vs phospholipid dialogue. Possible mechanisms for tuning MGD1 activity could imply the binding of effectors, conformational changes, modulation of MGD1 association to membranes, etc. No microsystem is currently available to allow a correlation between MGD1 activity, its association to lipids and its activation or inhibition. The ReGal project aims at dissecting the molecular mechanisms of MGD1 regulation based (1) on structural analyses of MGD1 interaction with effectors, (2) on mechanistic studies of MGD1 activation and inhibition in a biomimetic membrane and (3) on the monitoring of MGD1 substrate (DAG) and activator (PA) in the chloroplast of Arabidopsis cells in relevant physiological contexts and genetic backgrounds. Two models of effectors have been selected. Model of activator is PA. Model of inhibitor is a synthetic molecule named galvestine, obtained by Partner 1 following a high throughput screening and chemical optimization program. Galvestine competes with the binding of DAG to MGD1, 2 and 3 in vitro, and allows a dose-dependent control of MGDG level in planta. Partner 2 has improved the purification of MGD1 in such manner that it is now feasible to attempt crystallographic resolution and functional analyses in reconstituted membranes. Membrane systems will be reconstituted by assembly of lipids including MGDG, DGDG, and lipid effectors like PA, forming Langmuir monolayers, a technology mastered by Partner 3. Living cell dynamics of DAG and PA in chloroplasts, monitored by fluorescent indicators, should allow to correlate information gained from structural and functional studies with cellular measurements in various physiological and environmental contexts. Analyses in Arabidopsis mutated at the level of PLDz and/or NPC phospholipases will be carried out to integrate the deduced metabolic regulation model with knowledge on the genetic regulation, in the context of Pi deficiency.

Interplay between strong correlations and frustrated geometry offers a generic recipe for experimentalists and theorists searching for materials exhibiting exotic ground-states and unconventional phase transitions which might lead to unsuspected applications. The project describes in details several promising routes to achieve the double goal of i) understanding the novel physical concepts at play and ii) providing a quantitative understanding of the related microscopic models hence opening the way to material design. The project focuses more explicitly on frustrated quantum magnets, itinerant correlated particles (electrons or bosons) on frustrated geometries and on systems with emerging excitations carrying non-abelian statistics (as in some novel fractional Quantum Hall states). One common feature of such systems is the potential emergence of exotic topological properties of its ground-state (useful e.g. to build a "quantum computor") due to its constrained nature linked to very strong correlations.

The proposed fundamental research will develop an integrated experimental and meso-scale simulation approach to design porous electrochemical ceramics with multifunctional design requirements. It will focus on the development of a framework for the analysis and optimization of the microstructure of this important class of materials. The competing requirements on the microstructure, for optimum electrochemical performance on one hand and mechanical performance and thermo-mechanical stability on the other, will be studied. Using this understanding to design optimal microstructures, to process them and characterize their performance is the central element of this integrated experimental and theoretical investigation. The principal aimed application is concerned with the porous electrodes of Solid Oxide Fuel Cells (SOFCs). The project application is within the call of collaborative projects in materials research, "MATERIALS WORLD NETWORK" of the National Science Foundation (NSF).