Connectivity-informed spatio-temporal MEG source reconstruction: Simulation results using a MAR model

Abstract : 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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Poster communications
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https://hal.inria.fr/hal-02379744
Contributor : Ivana Kojcic <>
Submitted on : Monday, November 25, 2019 - 6:30:07 PM
Last modification on : Wednesday, November 27, 2019 - 1:29:16 AM
Long-term archiving on: Wednesday, February 26, 2020 - 7:56:17 PM

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Ivana Kojčić, Théodore Papadopoulo, Rachid Deriche, Samuel Deslauriers-Gauthier. Connectivity-informed spatio-temporal MEG source reconstruction: Simulation results using a MAR model. Colloque Line Garnero, Oct 2019, Paris, France. ⟨hal-02379744⟩

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