Development of a computational and neuroinformatics framework for large-scale brain modelling

par Paula Sanz Leon

Thèse de doctorat en Neurosciences

Sous la direction de Viktor K. Jirsa.

Soutenue le 16-10-2014

à Aix-Marseille , dans le cadre de Ecole Doctorale Sciences de la Vie et de la Santé (Marseille) , en partenariat avec UMR 1106 INSERM (laboratoire) .

Le président du jury était Laurent U Perrinet.

Le jury était composé de Viktor K. Jirsa, Laurent U Perrinet, Claus Christian Hilgetag, Gustavo Deco, Andrew Davison.

Les rapporteurs étaient Claus Christian Hilgetag, Gustavo Deco.


  • Résumé

    The central theme of this thesis is the development of both a generalised computational model for large-scale brain networks and the neuroinformatics platform that enables a systematic exploration and analysis of those models. In this thesis we describe the mathematical framework of the computational model at the core of the tool The Virtual brain (TVB), designed to recreate collective whole brain dynamics by virtualising brain structure and function, allowing simultaneous outputs of a number of experimental modalities such as electro- and magnetoencephalography (EEG, MEG) and functional Magnetic Resonance Imaging (fMRI). The implementation allows for a systematic exploration and manipulation of every underlying component of a large-scale brain network model (BNM), such as the neural mass model governing the local dynamics or the structural connectivity constraining the space time structure of the network couplings. We also review previous studies related to brain network models and multimodal neuroimaging integration and detail how they are related to the general model presented in this work. Practical examples describing how to build a minimal *in silico* primate brain model are given. Finally, we explain how the resulting software tool, TVB, facilitates the collaboration between experimentalists and modellers by exposing both a comprehensive simulator for brain dynamics and an integrative framework for the management, analysis, and simulation of structural and functional data in an accessible, web-based interface.


  • Résumé

    The central theme of this thesis is the development of both a generalised computational model for large-scale brain networks and the neuroinformatics platform that enables a systematic exploration and analysis of those models. In this thesis we describe the mathematical framework of the computational model at the core of the tool The Virtual brain (TVB), designed to recreate collective whole brain dynamics by virtualising brain structure and function, allowing simultaneous outputs of a number of experimental modalities such as electro- and magnetoencephalography (EEG, MEG) and functional Magnetic Resonance Imaging (fMRI). The implementation allows for a systematic exploration and manipulation of every underlying component of a large-scale brain network model (BNM), such as the neural mass model governing the local dynamics or the structural connectivity constraining the space time structure of the network couplings. We also review previous studies related to brain network models and multimodal neuroimaging integration and detail how they are related to the general model presented in this work. Practical examples describing how to build a minimal *in silico* primate brain model are given. Finally, we explain how the resulting software tool, TVB, facilitates the collaboration between experimentalists and modellers by exposing both a comprehensive simulator for brain dynamics and an integrative framework for the management, analysis, and simulation of structural and functional data in an accessible, web-based interface.


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Informations

  • Détails : 1 vol.(279 p.)
  • Annexes : Bibliogr. p.249-271

Où se trouve cette thèse ?

  • Bibliothèque : Université d'Aix-Marseille (Marseille. Timone). Service commun de la documentation. Bibliothèque de médecine - odontologie.
  • Disponible pour le PEB
  • Bibliothèque : Université d'Aix-Marseille. Service commun de la documentation. Bibliothèque électronique.
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