Analysis code for Bonaiuto, et al "Laminar-specific cortical dynamics in human visual and sensorimotor cortices"

https://www.biorxiv.org/content/early/2017/11/30/226274

https://elifesciences.org/articles/33977

Requirements:

• RMAOV2: https://uk.mathworks.com/matlabcentral/fileexchange/5578-rmaov2
• shadedErrorBar: https://fr.mathworks.com/matlabcentral/fileexchange/26311-raacampbell-shadederrorbar?
• barwitherr: https://fr.mathworks.com/matlabcentral/fileexchange/30639-barwitherr-errors-varargin-?focused=3845794&tab=function
• dict: http://uk.mathworks.com/matlabcentral/fileexchange/19381-lookuptable
• MEGSurfer: https://github.com/jbonaiuto/MEGsurfer

% To run analysis

% Create subject structure

subjects=create_subject_structure();

% Create contrast structure

contrasts=create_contrast_structure();

%%% Analyze subject behavior

subjects_behavior(subjects);

%%% Reproducibility

% Extract fiducial coil coordinates

extract_fiducials(subjects);

% Analyze fiducial coil movement

analyze_fiducials(subjects);

% Sensor cluster TF

run_tfs(subjects(3));
extract_tfs(subjects(3));
plot_tfs(subjects(3));

% ERPs

plot_erps(subjects(3));

% Field maps

plot_field_maps(subjects(3));

%%% Laminar analysis

% Run inversions

for idx=1:length(subjects)
    for session_num=1:length(subjects(idx).sessions)
        run_all_session(subjects(idx), session_num, contrasts);
    end
    run_all_subject(subjects(idx), contrasts);
end

% Plot example subjects

for idx=1:length(contrasts)
    plot_classification_results_subject(subjects, contrasts(idx), 'thresh_percentile', 0, 'whole_brain', true, 'plot_ext', 'global_');
    plot_classification_results_subject(subjects, contrasts(idx), 'thresh_percentile', 80, 'whole_brain', true, 'plot_ext', 'func_');
    plot_classification_results_subject(subjects, contrasts(idx), 'thresh_percentile', 80, 'whole_brain', false, 'plot_ext', 'anat_');
end

% Plot subject-level results

for idx=1:length(contrasts)
    plot_classification_results_subjects(subjects, contrasts(idx));
end

% Shuffled control

for idx=1:length(subjects)
    for session_num=1:length(subjects(idx).sessions)
        run_all_session_shuffled(subjects(idx), session_num, contrasts);
    end
    run_all_subject_shuffled(subjects(idx), contrasts);
end
for idx=1:length(contrasts)
    plot_classification_results_subjects_shuffled(subjects, contrasts(idx));
end

% Co-registration error control

for idx=1:length(subjects)
    for session_num=1:length(subjects(idx).sessions)
        run_all_session_coregerr(subjects(idx), session_num, contrasts);
    end
    run_all_subject_coregerr(subjects(idx), contrasts);
end
for idx=1:length(contrasts)
    plot_classification_results_subjects_coregerr(subjects, contrasts(idx));
end

% SNR control

run_all_session_noise(subjects, contrasts);

%%% Condition comparison

for idx=1:length(contrasts)
    plot_subjects_condition_power(subjects, contrasts(idx));
end