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tutorials/pipelines/tut_a_con_but/tut_a_con_but.tex

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{Figure examples}
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Example of the displays \fn{Community Structure} with \emph{connectivity data} binarized at fixed thresholds obtained using BRAPH 2.
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Examples of displays of \fn{Community Structure} with connectivity data binarized at fixed thresholds obtained using BRAPH 2.
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\tableofcontents
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tutorials/pipelines/tut_a_fun_bud/tut_a_fun_bud.tex

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\maketitle
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\begin{abstract}
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\noindent
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This tutorial shows how to perform a network analysis using \emph{functional data} (see tutorial \href{https://github.com/braph-software/BRAPH-2/tree/develop/tutorials/general/tut_gr_con}{Group of Subjects with Connectivity Data}), where a functional file containing activation signals for each brain region is available for each subject, as in functional MRI, MEG, or EEG. Step by step, this pipeline guides you to compare the data from two groups of subjects at fixed densities, which correspond, for example, to fixed percentages of strongest connections to be included in the analysis (e.g. fixing the analysis at 10\% allows assessing the 10\% strongest connections in the network). With this tutorial, you will be able to extract and plot differences between two groups. You will also be able to generate publication-quality figures.
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\end{abstract}
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\tableofcontents
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\fig{figure*}
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\fig{marginfigure}
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{fig:01}
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\includegraphics{fig01_01.jpg}
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\includegraphics{fig01_02.jpg}
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{GUI for working with the pipeline to compare two groups of subjects with \emph{functional data} at fixed densities}
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{Figure examples.}
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Example of the graphical user interface to perform group comparisons with \emph{functional data} binarized at fixed densities.
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Examples of displays of \code{Community Structure} with functional data binarized at fixed densities obtained using BRAPH 2.
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}
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\begin{abstract}
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\noindent
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This tutorial shows how to perform a network analysis using \emph{functional data} (see tutorial \href{https://github.com/braph-software/BRAPH-2/tree/develop/tutorials/general/tut_gr_con}{Group of Subjects with Connectivity Data}), where a functional file containing activation signals for each brain region is available for each subject, as in functional MRI, MEG, or EEG. Step by step, this pipeline guides you to compare the data from two groups of subjects at fixed densities, which correspond, for example, to fixed percentages of strongest connections to be included in the analysis (e.g. fixing the analysis at 10\% allows assessing the 10\% strongest connections in the network). With this tutorial, you will be able to extract and plot differences between two groups. You will also be able to generate publication-quality figures.
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\end{abstract}
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\tableofcontents
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\clearpage
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\section{Generate Example Data}
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To obtain the results from the comparisons, select the measures in the \code{COMPARISONS} panel and press \code{Data Selected Comparisons}({\Figref{fig:11}d}), and a new window will open where we can check the value of the difference between groups, the p-values (1-tailed and 2-tailed), as well as the confidence intervals.
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\fig{figure}
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{fig:12}
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\includegraphics{fig12a.jpg}

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