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Equipe de recherche ODYSSEE

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Odysséehas been created in 2002. Until late 2008, Odysséefocused on computational neuroscience and some of its applications to try to unveil the principles that govern the functioning of neurons and assemblies thereof, to understand the relations between the anatomy of the human brain and its functions and to bridge the gap between biological and computational vision. The research activity has been conducted in the following four main areas:

Modeling and simulating single and assemblies of neurons.

Measuring and modeling the human brain anatomical connectivity using Diffusion Magnetic Resonance Imaging (D-MRI).

Measuring and modeling the functioning of the human brain through its electrical activity using Magneto- and Electroencephalography (M/EEG).

Computational and biological vision.

Research within Axes 1 and 4 is now the main focus of the project-team NeuroMatchCompwhile Research directions 2 and 3 have been the main focus of Odysséein 2009. Details about directions 1 and 4 are available in the NeuroMatchCompscientific activity report.

The main objective of our research is to develop rigorous mathematical models and computational tools for analyzing and modeling the complex Central Nervous System (brain and spinal cord) anatomy and function. These models and tools will help to better understand the architecture and the functioning of human Central Nervous System (CNS) and address pressing and challenging clinical and neuroscience questions. Exploring new directions to solve these challenging problems will push forward the state-of-the-art in Anatomical and Functional Computational Imaging of the CNS.

The relationship between CNS structure and function is fundamental in neuroscience. Developing computational models and techniques that recover the anatomical connectivity and the function of the CNS in vivo is thus of utmost importance: it will definitely improve the understanding of the CNS and its mechanisms. On the basis of our expertise and contributions to the field of computational CNS Imaging and in order to have an impact on this field, our research focusses mainly on the Anatomical and Functional Computational Imaging of the CNS with a particular emphasis on signal and image recording from Diffusion Magnetic Resonance Imaging (D-MRI), Magneto-Encephalography (MEG) and Electro-Encephalography (EEG).

In order to further increase the impact of our research, we also aim to push our contributions towards some applications related to CNS diseases with characteristic abnormalities in the micro-structure of brain tissues that are not apparent and cannot be revealed reliably by standard imaging techniques. Diffusion MRI, a recent imaging modality based on the measurement of the random thermal movement (diffusion) of water molecules within samples can make visible these co-lateral damages to the fibers of the CNS white matter that connect different brain regions. This is why in our research, Diffusion MRI is the major anatomical imaging modality that will be considered to recover the CNS connectivity.

Connectivity represents the network infrastructure of the CNS. Electric activity corresponds to communications over this network. MEG and EEG (jointly as M/EEG) reveal part of the cortical electric activity. M/EEG are also instrumental in diagnosing diseases linked to anomalous brain function - that in some cases anatomical or functional MR images do not reveal. In some CNS injuries (medullar injuries, strokes, AMS), the peripheral nervous system may not be able to execute commands that are issued by the brain. Brain Computer Interfaces (BCI) is an application of EEG that has been proposed as a means to translate in real-time the electrical activity of the brain in commands to control devices. While BCI had been advocated as a means to communicate and help restore mobility or autonomy for very severe cases of disabled patients, it is more realistically a tool for a new interactive probing and training of the human brain.

These considerations support the need to make research on new models and computational tools to analyse CNS signals and imaging data with the goal of pushing forward the state-of-the-art to help address pressing and challenging clinical and neuroscience questions. This is our main objective within this research. This will help to better understand the architecture and function of the CNS and allow the development of biomarkers to better understand the progression of certain types of neurodegenerative diseases. Such an understanding will also help improving BCI systems with the above goal of better interactive probing and training of the human brain. These long term and ambitious applications, if successful, will help us make true our dream to effectively contribute reducing the number of people suffering from CNS diseases.

In order to tackle these challenging objectives, our strategy is based on the following road map:

Develop rigorous mathematical and computational tools for the analysis and interpretation of Diffusion MRI and M/EEG data.

Improve acquisition and processing techniques and push forward the state-of-the-art in Computational CNS imaging.

Use our expertise to address with collaborators clinical and neuroscience questions.

This will be implemented through:

Publications in international conferences and journals dedicated to promoting advances in computational methods for Diffusion MRI and M/EEG analysis and/or use of Diffusion MRI and M/EEG in clinical and neuroscience applications.

Building of a dense network of collaborations with national as well as international neuroimaging laboratories through which we will access equipment and data and with whom we will jointly contribute to solve common crucial problems of interest.

Development of software packages that will be used in a first stage by our national and international collaborators and then made available to other partners.

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