Using the GUI

Main Window

To start the GUI, navigate to the folder that contains the files and type NLA_GUI in the command section of the MATLAB window. Or, in the file browser section of the MATLAB window, right click on NLA_GUI.mlapp and select Run.

_images/main_gui2.png

Main windows of Network Level Analysis program

  1. Edge-level test dropdown selector (See Edge-level Statistical Tests)

  2. Edge-level test pane

    This pane will list all of the options and inputs needed for each test that’s currently selected. Usually there are selectors for functional connectivity, network atlas, and behavior files. There may also be other options depending on the test. If “Precalculated data” is selected, there will be selectors for data instead. (See: Precalculated data loader)

  3. Behavior table

    This will display the table when the behavior file is loaded. The table is used to select the behvaior to test, co-variates used (optional), and permutation groupings (optional). (See: Behavior Table)

  4. Network-level test pane

    Selection of network-level test(s). One can be selected, or multiple with Ctrl/Shift + left click. See Network-level tests

  5. Run options

    Checkboxes to select test method(s). If within network pair is selected, full connectome will also be selected. Note: Chi-Squared and Hypergeometric tests are incompatible with the within newtork pair method. Quality control (See: Quality Control) button launches the quality control menu. Permutation count is how many permutations to run. More permutations will take more time, but will produce more precise results. Run will run the edge level test and open the results window.

Loading Results

If previous data was saved (See saving results) there is an option to load it here. Click the File menu in the upper left-hand corner and select Load Previous Results. Depending on the size of the saved data, this could take a bit of time.

Results Window

_images/test_results_gui.png

Results windown with results for Network Level Analysis program

After Run is pressed in the main window, the results window will open. Initially, most of it bill be bank except for a View button to view the result of the (non-permuted) edge-level test along with another Run button. Pressing this run button will begin running all the permutations of the edge-level and network-level test(s).

After all the permutations of the tests are run, the window will change.

  1. Edge test results display

  2. Network level test results. Grouped by test method. The list can be changed to group by test by pushing the Flip Nesting button.

  3. Open TriMatrix Plot. This opens an interactive plot of the statistics. (See TriMatrix Plot)

  4. Open Diagnostic Plots. These three plots

Saving Results

To save results for use later (See loading results), click the File menu in the upper left-hand corner and select save. This may take a bit of time depending on how large the dataset is and how many permutations were run. The results will be saved as:

  1. a ResultPool object using models and classes from the NLA codebase. This can only be used if the NLA is in MATLAB’s current path.

  2. a nested structure of data that can be used without the NLA code. The structures are in the same ordering as the ResultPool, but there are no built-in classes and orderings.

Lower Triangle Network-Level Results Window

_images/trimatrix_plot.png

TriMatrix (lower triangular area) of p-values and display options

  1. TriMatrix plot of p-values for selected test.

  2. Options. After changing options, the Apply button must be pushed to take effect. Chord plots, convergence plots, and brain plots will not update after their generation.

    Plot Scale: allows for linear, log, and -log10 scaling of results. Colormap: change the colormap of results using built-in MATLAB colormaps.

    Plot Value: plot p-values or statistics. Upper and Lower Limit: set limits for color scale. p-value threshold: set threshold for significance, defaults to 0.05.

    Multiple Comparisons Correction: select correction type from a drop down list. Options include, none, Bonferroni, Benjamini-Hochberg, Benjamini-Yekutieli, Holm-Bonferroni, Freedman-Lane, and Westfall-Young. Legend Visible: turn on/off the legend containing networks and their colors.

    Edge Chord Plot Type: visualization options for edge-level chord plots. Chords can be visualized according to p-value or coefficient. Coefficient-based visualization can be split according to positive and negative edges, and they can be visualized in basic format, hardcoded with [-0.3,0.3] limits, unless the Sandwich estimator is used [-3, 3] for that case. Non-basic format colors chords with respect to the standard deviation of the data. There are buttons to visualize edge- and network-level chord plots. There are no visualization options for network-level chord plots.

    Convergence Plot Color: colormap for convergence plot, requires the selection of multiple network-level results in the Results Window (See Results Window).

    Brain Plot Type: visualizes edge-level results as sticks between ROI centroids visualized as spheres on the brain. There are two options, magnitude and direction. Magnitude colors the sticks based on the magnitude of the correlation. Direction colors the sticks red if the correlation is positive and blue if the correlation is negative. There is a checkbox to show or hide the ROI centroids on brain plots.