You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: tutorial_frontiers2018_group.m
    path of file: ./repos/brainstorm3/toolbox/script
    
    the code of the file until where you have to start completion: function tutorial_frontiers2018_group(ProtocolName, reports_dir)
% TUTORIAL_FRONTIERS2018_GROUP: Runs the Brainstorm/SPM group analysis pipeline (group analysis) - FRONTIERS ARTICLE VERSION
%
% ONLINE TUTORIALS: 
%    - https://neuroimage.usc.edu/brainstorm/Tutorials/VisualSingle
%    - https://neuroimage.usc.edu/brainstorm/Tutorials/VisualGroup
%
% INPUTS:
%    - ProtocolName : Name of the protocol in which the recordings for the 16 subjects have been imported (Frontiers2018Single or Frontiers2018Group)
%                     This folder must include: the run-level averages (recordings and time-frequency) and the source kernels for each run
%    - reports_dir  : If defined, exports all the reports as HTML to this folder

% @=============================================================================
% This function is part of the Brainstorm software:
% https://neuroimage.usc.edu/brainstorm
% 
% Copyright (c) Universit
    
function for screen captures
function DataScreenCapture(sFiles, isMEG, isEEG, Comment)
    if isMEG
        % Process: Snapshot: Recordings time series
        bst_process('CallProcess', 'process_snapshot', sFiles, [], ...
            'target',         5, ...  % Recordings time series
            'modality',       3, ...  % MEG (Magnetometers)
            'time',           0.1055, ...
            'Comment',        ['MEG MAG: ' Comment]);
        % Process: Snapshot: Recordings topography (contact sheet)
        bst_process('CallProcess', 'process_snapshot', sFiles, [], ...
            'target',         7, ...  % Recordings topography (contact sheet)
            'modality',       3, ...  % MEG (Magnetometers)
            'contact_time',   [0.050, 0.300], ...
            'contact_nimage', 6, ...
            'Comment',        ['MEG MAG: ' Comment]);
    end
    if isEEG
        % Process: Snapshot: Recordings time series
        bst_process('CallProcess', 'process_snapshot', sFiles, [], ...
            'target',         5, ...  % Recordings time series
            'modality',       4, ...  % EEG
            'time',           0.1055, ...
            'Comment',        ['EEG: ' Comment]);
        % Process: Snapshot: Recordings topography (contact sheet)
        bst_process('CallProcess', 'process_snapshot', sFiles, [], ...
            'target',         7, ...  % Recordings topography (contact sheet)
            'modality',       4, ...  % EEG
            'contact_time',   [0.050, 0.300], ...
            'contact_nimage', 6, ...
            'Comment',        ['EEG: ' Comment]);
    end
end

% ===== FACES-SCRAMBLED: MEAN DIFF =====
% Process: Select data files in: */DirIntra/"Avg: Faces | "
sSubjAvgFacesData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname',   'All', ...
    'condition',     DirIntra, ...
    'tag',           'Avg: Faces | ', ...
    'includeintra',  1);
% Process: Select data files in: */DirIntra/"WAvg: Avg: Scrambled (6 files)"
sSubjAvgScrambledData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname',   'All', ...
    'condition',     DirIntra, ...
    'tag',           'WAvg: Avg: Scrambled (6 files)', ...
    'includeintra',  1);
% Process: Difference of means [mean]
sDiffFacesData = bst_process('CallProcess', 'process_diff_mean', sSubjAvgFacesData, sSubjAvgScrambledData, ...
    'avg_func', 1, ...  % Arithmetic average mean(A) - mean(B)
    'weighted', 0);
% Process: Set comment
sDiffFacesData = bst_process('CallProcess', 'process_set_comment', sDiffFacesData, [], ...
    'tag',     'Faces - Scrambled', ...
    'isindex', 0);
% Take screen captures
DataScreenCapture(sDiffFacesData, 1, 1, sDiffFacesData.Comment);

% ===== FACES-SCRAMBLED: PARAMETRIC T-TEST =====
% Process: Select data files in: */DirIntra/"Avg: Faces | "
sSubjAvgFacesData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname',   'All', ...
    'condition',     DirIntra, ...
    'tag',           'Avg: Faces | ', ...
    'includeintra',  1);
% Process: Select data files in: */DirIntra/"WAvg: Avg: Scrambled (6 files)"
sSubjAvgScrambledData = bst_process('CallProcess', 'process_select_files_data', [], [], ...
    'subjectname',   'All', ...
    'condition',     DirIntra, ...
    'tag',           'WAvg: Avg: Scrambled (6 files)', ...
    'includeintra',  1);
% Process: t-test paired [ALL]          H0:(A=B), H1:(A<>B)
sStatParamFacesData = bst_process('CallProcess', 'process_test_parametric2p', sSubjAvgFacesData, sSubjAvgScrambledData, ...
    'timewindow',    [], ...
    'sensortypes',   '', ...
    'isabs',         0, ...
    'avgtime',       0, ...
    'avgrow',        0, ...
    'Comment',       '', ...
    'test_type',     'ttest_paired', ...  % Paired Student's t-test        (A-B)~N(m,v)t = mean(A-B) / std(A-B) * sqrt(n)      df=n-1
    'tail',          'two');  % Two-tailed
% Process: Set comment
sStatParamFacesData = bst_process('CallProcess', 'process_set_comment', sStatParamFacesData, [], ...
    'tag',     'Faces - Scrambled: Parametric t-test', ...
    'isindex', 0);
% Take screen captures
DataScreenCapture(sStatParamFacesData, 1, 1, sStatParamFacesData.Comment);

% ===== FACES-SCRAMBLED: NON-PARAMETRIC T-TEST =====
% Process: Perm t-test paired [All]          H0:(A=B), H1:(A<>B)
sStatPermFacesData = bst_process('CallProcess', 'process_test_permutation2p', sSubjAvgFacesData, sSubjAvgScrambledData, ...
    'timewindow',     [], ...
    'sensortypes',    '', ...
    'isabs',          0, ...
    'avgtime',        0, ...
    'avgrow',         0, ...
    'iszerobad',      0, ...
    'Comment',        '', ...
    'test_type',      'ttest_paired', ...  % Paired Student's t-test T = mean(A-B) / std(A-B) * sqrt(n)
    'randomizations', 1000, ...
    'tail',           'two');  % Two-tailed
% Process: Set comment
sStatPermFacesData = bst_process('CallProcess', 'process_set_comment', sStatPermFacesData, [], ...
    'tag',     'Faces - Scrambled: Permutation t-test', ...
    'isindex', 0);
% Take screen captures
DataScreenCapture(sStatPermFacesData, 1, 1, sStatPermFacesData.Comment);

% ===== FACES-SCRAMBLED: CLUSTER T-TEST =====
% Process: FT t-test paired cluster [all EEG]          H0:(A=B), H1:(A<>B)
sStatClustFacesData = bst_process('CallProcess', 'process_ft_timelockstatistics', sSubjAvgFacesData, sSubjAvgScrambledData, ...
    'sensortypes',    'EEG', ...
    'timewindow',     [], ...
    'isabs',          0, ...
    'avgtime',        0, ...
    'avgchan',        0, ...
    'randomizations', 1000, ...
    'statistictype',  2, ...  % Paired t-test
    'tail',           'two', ...  % Two-tailed
    'correctiontype', 2, ...  % cluster
    'minnbchan',      0, ...
    'clusteralpha',   0.05);
% If FieldTrip is available and results were returned
if ~isempty(sStatClustFacesData)
    % Process: Set comment
    sStatClustFacesData = bst_process('CallProcess', 'process_set_comment', sStatClustFacesData, [], ...
        'tag',     'Faces - Scrambled: Cluster t-test EEG', ...
        'isindex', 0);
    % Take screen captures
    DataScreenCapture(sStatClustFacesData, 0, 1, sStatClustFacesData.Comment);
end