main-contents.tex

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\begin{document}
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%%  Authorship and Title
\title[TVB]{Integrating neuroinformatics tools in TheVirtualBrain}
\author[Woodman {et~al}]{
        M. Marmaduke Woodman\,$^{1,*}$,  
        Laurent Pezard\,$^{1}$,  
        Lia Domide\,$^{3}$, 
        Stuart Knock\,$^{1}$, 
        Paula Sanz Leon\,$^{1}$, 
        Jochen Mersmann\,$^{2}$,
        Anthony R. McIntosh \,$^{4}$ and  
        Viktor Jirsa\,$^{1}$\footnote{to whom correspondence should be addressed: marmaduke.woodman@univ-amu.fr,
        viktor.jirsa@univ-amu.fr}}

\address{$^{1}$ Institut de Neurosciences des Syst{\`e}mes, Aix-Marseille
    Universit\'e,  27, Bd. Jean Moulin, 13005, Marseille, France.\\
         $^{3}$ Codemart, 13, Petofi Sandor, 400610, Cluj-Napoca, Romania.\\
         $^{2}$ CodeBox GmbH, Hugo Eckener Str. 7, 70184 Stuttgart, Germany.\\
         $^{4}$ Rotman Research Institute at Baycrest, Toronto, M6A 2E1, Ontario, Canada\\
        }

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%##                               ABSTRACT                                   ##%
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\begin{abstract}
\section{}

TheVirtualBrain (TVB) is a neuroinformatics Python package representing the
convergence of clinical, systems, theoretical neuroscience in the integration,
analysis, visualization and modeling of neural dynamics of the human brain as
well as the imaging modalities through which these dynamics are measured.
TVB is composed of a flexible simulator for both neural dynamics
and modalities such as electroencephalography (EEG), magnetoencephalography
(MEG) and functional magnetic resonance imaging (fMRI), common analysis
techniques such as wavelet decomposition and multiscale sample entropy,
interactive visualizers for replaying cortical timeseries on the 3D surface or
editing large-scale connectivity matrices, all accessible via an 
web browser user interface.
A datatype system modeling neuorscientific data ties together these pieces with
persistent data storage, based on a combination of SQL \& HDF5.
 These datatypes combine with adapters
allowing TVB to integrate other algorithms or computational systems,
such as MATLAB, for which support is already provided.
TVB provides infrastructure for multiple projects and
multiple users, possibly participating under multiple roles. For example, a
clinician might import patient data to first identify, based on 
electrophysiological dynamics, several potential lesion point on the patient's 
connectome, as obtained from diffusion spectrum imaging (DSI). 
These lesion points are picked up by a modeler, working on the same project, 
and tested for viability through whole brain simulation, based on the 
patient's connectome, and subsequent analysis of dynamical features.
This workflow is one of several multi-user use cases for which TVB conceived.
TVB also drives research forward: the
simulator itself represents the culmination of several recent yet ad-hoc
simulations in the modeling literature on human resting state. The 
availability of the numerical methods, set of neural mass models and 
forward solutions allows for the construction of a wide range of 
brain-scale simulation scenarios.
TVB is therefore a platform for various tools and disparate expertises, supporting the
analysis and modeling of structural and function data from the human brain.  
We will briefly outline the history and motivation for TVB, describing the 
framework and simulator, giving usage examples in the web UI
and Python scripting.
  
\section{Keywords:} large-scale brain network, simulation,  web platform, Python, virtual
brain, connectivity, connectome, neural mass, time delays

\end{abstract}

%\tableofcontents

\section{Introduction}
\input{motivation.tex}

\section{Architecture}
\input{architecture.tex}

\section{Simulator}
\input{simulator.tex}

\section{User Interaction}
\input{ui.tex}

\section{Future Work}
\input{future.tex}

\section*{Acknowledgments}
Several authors have also participated in the
development of TVB. They are listed in the \texttt{AUTHORS} file 
of the source code and deserve also our warm acknowlegments. LP whishes to thank
specifically Y.~Manhoun for his implication in the conception and development
of the first prototype of the TVB architecture. The research reported herein
was supported by the  Brain Network Recovery Group through the James S.
McDonnell Foundation and the FP7-ICT BrainScales. PSL and MMW received
support by from the French Minist\`{e}re de Recherche and the Fondation
de Recherche Medicale.

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