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Section: Partnerships and Cooperations
National Initiatives
ANR
ANR CO-ADAPT
Participants : Maureen Clerc [coordinator] , Dieter Devlaminck, Sebastian Hitziger, Loïc Mahé, Théodore Papadopoulo, Eoin Thomas, Romain Trachel.
Duration: December 2009 to April 2014
The partners of this project were the INSERM U1028 laboratory of Bron, the "laboratoire de Neurologie de la cognition" UMR6155 CNRS of Marseille, the Inria Lille Sequel project-team and the "Laboratoire d'Analyse Topologie et Probabilités” UMR6632/CNRS of Université de Provence, Marseille.
Brain Computer Interfaces (BCI) provide a direct communication channel from the brain to a computer, bypassing traditional interfaces such as keyboard or mouse, and also providing a feedback to the user, through a sensory modality (visual, auditory or haptic). A target application of BCI is to restore mobility or autonomy to severely disabled patients, but more generally BCI opens up many new opportunities for better understanding the brain at work, for enhancing Human Computer Interaction, and for developing new therapies for mental illnesses.
In BCI, new modes of perception and interaction come into play, and a new user must learn to operate a BCI, as an infant learns to explore his/her sensorimotor system. Central to BCI operation are the notions of feedback and of reward, which we believe should hold a more central position in BCI research.
The goal of this project was to study the co-adaptation between a user and a BCI system in the course of training and operation. The quality of the interface was judged according to several criteria (reliability, learning curve, error correction, bit rate). BCI were considered under a joint perspective: the user's and the system's. From the user's brain activity, features must be extracted, and translated into commands to drive the BCI system. Feature extraction from data, and classification issues, are very active research topics in BCI. However, additional markers may also be extracted to modulate the system's behavior. It is for instance possible to monitor the brain's reaction to the BCI outcome, compared to the user's expectations. This type of information we refer to as meta-data because it is not directly related to the command, and it may be qualitative rather than quantitative.
The aim of CO-ADAPT was to propose new directions for BCI design, by modeling explicitly the co-adaptation taking place between the user and the system (web site http://coadapt.inria.fr ).
This project has led to many concrete realizations, e.g. an international BCI Challenge on detecting Error Potentials, and software (CoAdapt P300 stimulator).
ANR Mosifah
Participants : Rachid Deriche, Maureen Clerc, Théodore Papadopoulo, Gonzalo Sanguinetti.
Duration: October 2013 to September 2017
This ANR Numerical Models 2013 project is about multimodal and multiscale modelling and simulation of the fiber architecture of the human heart. It started on October 2013 and involves three partners : Creatis Team, INSA, Lyon (I. Magnin, Y. Zhu); TIMC-IMAG, CNRS, Grenoble (Y. Uson) and the Athena project team.
It consists in modelling and simulating the ex vivo and in vivo 3D fiber architectures at various scales using multiphysical data from different imaging modalities working at different spatial resolutions. To this end, the myocardium of the human heart will be imaged using respectively Polarized Light Imaging (PLI) and dMRI.
Appropriate diffusion models will be explored including second and fourth order DTI models as well as HARDI models such as the single shell Q-Ball Imaging (QBI). These various types of images will be processed within the right Riemannian mathematical framework to provide tensor as well as Ensemble Average Propagator (EAP) and Orientation Distribution Function (ODF) fields. Virtual cardiac fiber structure (VCFS) will then be modelled using myocardial fiber information derived from each of these imaging modalities. Finally, diffusion behavior of water molecules in these VCFSs will be simulated by means of quantum spin theory, which allows computing ex vivo and in vivo virtual diffusion magnetic resonance (MR) images at various scales ranging from a few microns to a few millimeters. From the obtained virtual diffusion MR images, multiscale and probabilistic atlas describing the 3D fiber architecture of the heart ex vivo and in vivo will be constructed. Meanwhile, the simulation involving a large number of water molecules, grid computing will be used to cope with huge computation resource requirement.
We expect to construct a complete database containing a very wide range of simulated (noise and artifact-free) diffusion images that can be used as benchmarks or ground-truth for evaluating or validating diffusion image processing algorithms and create new virtual fiber models allowing mimicking and better understanding the heart muscle structures. Ultimately, the proposed research can open a completely novel way to approach the whole field of heart diseases including the fundamental understanding of heart physiology and pathology, and new diagnosis, monitoring and treatment of patients.
ANR MULTIMODEL
Participants : Théodore Papadopoulo, Maureen Clerc, Sebastian Hitziger, Emmanuel Olivi.
Duration: December 2010 to May 2014
The MULTIMODEL project stems from a conjoint INSERM-Inria scientific initiative launched in December 2008 and ended in 2010. It involves 5 partners (Inserm U751 in Marseille, U678 in Paris, U836 in Grenoble, U642 in Rennes and Inria Athena project-team).
The general objectives of the MULTIMODEL project were :
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To develop computational models at the level of neuronal systems that will help interpreting neuroimaging data in terms of excitation-, inhibition- and synchronization-related processes.
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To acquire multimodal datasets, obtained in rats and humans under physiological and epileptogenic conditions, which will be used to develop the biophysical models and to test their face validity and predictability.
Specifically, the following questions were dealt with:
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How can models be integrated in order to link data from different modalities (electro/magneto-encephalography, optical imaging, functional MRI)?
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What is the influence of hidden parameters on the observed signals (e.g. ratio of excitation/inhibition and synchronization degree across regions)?
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To what extent can biophysical modelling bring valuable insights on physiological and pathological brain activity ?
We operated at the level of population of cells, i.e. at a scale compatible with the resolution of neuroimaging tools (at the level of the mm). A novel model structure was investigated, which includes astrocytes at this “mesoscopic” level and operates in networks of connected regions. Moreover, models in physiological and pathological conditions were compared, which is a step towards a better understanding of mechanisms underlying epileptic condition.
ANR VIBRATIONS
Participants : Théodore Papadopoulo, Maureen Clerc, Rachid Deriche, Demian Wassermann.
Duration: Early 2014 to early 2018
This Translational ANR project has just been been accepted.
Computational modeling, under the form of a “virtual brain” is a powerful tool to investigate the impact of different configurations of the sources on the measures, in a well-controlled environment.
The VIBRATIONS project proposes to simulate in a biologically realistic way MEG and EEG fields produced by different configurations of brain sources, which will differ in terms of spatial and dynamic characteristics. The research hypothesis is that computational and biophysical models can bring crucial information to clinically interpret the signals measured by MEG and EEG. In particular, they can help to efficiently address some complementary questions faced by epileptologists when analyzing electrophysiological data.
The project follows a three-fold strategy:
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construct virtual brain models with both dynamic aspects (reproducing both hyperexcitability and hypersynchronisation alterations observed in the epileptic brain) and a realistic geometry based on actual tractography measures performed in patients
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explore the parameter space though large-scale simulations of source configurations, using parallel computing implemented on a computer cluster.
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confront the results of these simulations to simultaneous recordings of EEG, MEG and intracerebral EEG (stereotactic EEG, SEEG). The models will be tuned on SEEG signals, and tested versus the surface signals in order to validate the ability of the models to represent real MEG and EEG signals.
The project constitutes a translational effort from theoretical neuroscience and mathematics towards clinical investigation. A first output of the project will be a database of simulations, which will permit in a given situation to assess the number of configurations that could have given rise to the observed signals in EEG, MEG and SEEG. A second – and major - output of the project will be to give the clinician access to a software platform which will allow for testing possible configurations of hyperexcitable regions in a user-friendly way. Moreover, representative examples will be made available to the community through a website, which will permit its use in future studies aimed at confronting the results of different signal processing methods on the same ‘ground truth’ data.
ADT
ADT BOLIS
Participants : Théodore Papadopoulo, Juliette Leblond [APICS] , Jean-Paul Marmorat [APICS] .
Duration:December 2014 to December 2016 ADT BOLIS aims to build a sofware platform dedicated to inverse source localisation, building upon the elements of software found in FindSources3D. The platform will be modular, ergonomic, accessible and interactive. It will offer a detailed visualisation of the processing steps and the results.
ADT OpenViBE-X
Participants : Théodore Papadopoulo, Maureen Clerc, Nathanaël Foy.
Duration: October 2014 to October 2016
The OpenViBE-X ADT addresses the OpenViBE Brain Computer Interfaces (BCI) platform, in order to:
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enrich the interaction with multimodal biosignals (eye gaze, heart-rate)
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implement methods for auto-calibration and online adaptation of the classification
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provide support, maintenance and dissemination for this software.
The OpenViBE platform is a central element to BCI research at Inria, and in the international community.
ADT OpenViBE-NT
Participants : Théodore Papadopoulo, Maureen Clerc, Loïc Mahé.
Duration: October 2012 to December 2014
OpenViBE is an opensource software which development started in 2005 with the goal of offering an open research tool for BCI and for supporting disabled people. Since its release in 2009, this software has received a lot of success (+10.000 downloads). But since 2005, new use have appeared as well as some limitations. The current software thus lacks of some features that limit its use, deployment and perennity. The goal of this ADT is to solve these problems, to improve and to extend OpenViBe One main goal was to improve the usability and the attractivity of the software and to retain a large community of users so as to ensure its sustainability. This ADT also supported the research made in four Inria teams (Athena , Hybrid , Neurosys and Potioc ) on hot topics such as adaptive or hybrid BCIs. In September 2014, the partners of this ADT organized a workshop on OpenViBE at the 6th international conference on Brain Computer Interfaces in Graz.
ADT MedInria-NT
Participants : Jaime Garcia Guevara, Loïc Cadour, Théodore Papadopoulo, Maureen Clerc, Rachid Deriche.
Duration: December 2010 to December 2012, prolongated to December 2014
The goal of this technical project, funded by Inria for 2 years, is to introduce some tools developed at Athena into the medInria platform. There are basically two such facilities: