Papers by Theodore Papadopoulo
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2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)
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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific r... more HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Rank-1 CNN for mental workload classification from EEG Sara Sedlar, Johann Benerradi, Côme Le Breton, Rachid Deriche, Théodore Papadopoulo, Max Wilson
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Recovering brain activity from M/EEG measurements is an ill-posed problem and prior constraints n... more Recovering brain activity from M/EEG measurements is an ill-posed problem and prior constraints need to be introduced in order to obtain unique solution. The majority of the methods use spatial and/or temporal constraints, without taking account of long-range connectivity. In this work, we propose a new connectivity-informed spatio-temporal approach to constrain the inverse problem using supplementary information coming from diffusion MRI. We present results based on simulated brain activity using a Multivariate Autoregressive Model, with realistic subject anatomy obtained from Human Connectome Project dataset.
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We aimed to validate structural connectivity measures based on diffusion MRI with Electrical Stim... more We aimed to validate structural connectivity measures based on diffusion MRI with Electrical Stimulation (ES) of the human brain cortex. For this, we combined white matter fiber tractography with propagation of Cortico-Cortical Evoked Potentials (CCEPs) induced by in-trasurgical ES in the language system of brain tumor patients. Our results showed high correlation (Pearson's coefficient 0.5-0.9) between delays of CCEPs and pathways connecting stimulation sites with recording electrodes. Our approach outperformed earlier study based on Diffusion Tensor Imaging. This potentially indicates that probabilistic tractogra-phy is an effective tool to quantify cortico-cortical communication non-invasively.
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Recovering brain activity from M/EEG measurements is an ill-posed problem and prior constraints n... more Recovering brain activity from M/EEG measurements is an ill-posed problem and prior constraints need to be introduced in order to obtain unique solution. The majority of the methods use spatial and/or temporal constraints, without taking account of long-range connectivity. In this work, we propose a new connectivity-informed spatio-temporal approach to constrain the inverse problem using supplementary information coming from difusion MRI. We present results based on simulated brain activity obtained with realistic subject anatomy from Human Connectome Project dataset.
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Lecture Notes in Computer Science, 2014
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Artificial and Biological Vision Systems, 1992
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2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012
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NeuroImage, 2004
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Computational Intelligence and Neuroscience, 2011
To recover the sources giving rise to electro- and magnetoencephalography in individual measureme... more To recover the sources giving rise to electro- and magnetoencephalography in individual measurements, realistic physiological modeling is required, and accurate numerical solutions must be computed. We present OpenMEEG, which solves the electromagnetic forward problem in the quasistatic regime, for head models with piecewise constant conductivity. The core of OpenMEEG consists of the symmetric Boundary Element Method, which is based on an extended Green Representation theorem. OpenMEEG is able to provide lead fields for four different electromagnetic forward problems: Electroencephalography (EEG), Magnetoencephalography (MEG), Electrical Impedance Tomography (EIT), and intracranial electric potentials (IPs). OpenMEEG is open source and multiplatform. It can be used from Python and Matlab in conjunction with toolboxes that solve the inverse problem; its integration within FieldTrip is operational since release 2.0.
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Papers by Theodore Papadopoulo