Computing Results of Inverse Solution

Presets

You can quickly set the most important parameters according to some predefined scenarios. You are then free to fine-tune any parameter, of course.

(1) Groups of EEG Files

Use this preset to specify how Cartool has to understand each group of files that you give it:

• All Subjects, One Condition: a group of files holds all subjects at once, for 1 condition only
• 1 Subject, All Conditions: a group of files holds only 1 subvject, and all conditions together
• 1 Subject, All Epochs and All Conditions: drop all epochs, all conditions for a single subject

You can still change the preset even after the files have been dropped in.

Add New Group of Files

Enter a new group EEG or Frequency files.

Cartool will check that the new group of files is compatible with the existing ones, and will complain if needed...

Remove Last Group

Does what it says.

Clear All Groups

Clear out all the groups at once.

Read Lists from File

You can direclty retrieve the lists of groups previously (see below).

See also Drag & Drop.

Write Lists to File

You can save the lists of current groups into a file, in case you want to re-use them (much recommended!).

See the file formats available.

(List of current groups of files)

For your entertainment and great pleasure, you can here contemplate your life and a summary of all the groups of files you already added to this sub-box.

Number of Subjects:

Number of conditions:

A summary of what Cartool understands in terms of subjects and conditions.

(2) EEG Preprocessing

EEG Spatial Filter, using XYZ file:

If this option is selected, then the EEG data will be preprocessed with a Spatial Filter .

This filter takes care of any remaining outliers, while also smoothing out the data . This really improves the Results of Inverse Solution, as outliers are definitely a no-no.

Cartool will check that electrodes coordinates is compatible with the other files, and will complain if needed...

(3) Inverse Processing

Inverse Matrix File:

This one input is mandatory, so give one of the inverse matrix generated here.

Cartool will check that inverse matrix is compatible with the other files, and will complain if needed...

Results Type:

The type of results to be actually saved.

Inverse solutions produces dipoles for each solution points, each dipole therefor coding for both orientation and power. You can specify what to do with these vecotrial information.

Norm

Only the norm of each dipole will be saved.

This is what you need 99% of the time.

Vectorial

The complete vector of each dipole will be saved.

Not recommended unless you know what you are doing. Also, it takes more space on the disk.

Inverse Regularization:

Regularization is a kind of smoothing that accounts for noise in the data.

Apply more regularization for noisier data, and less for cleaner data.

Don't over-do regularization, as makes the localization more blurry and less precise.

Auto

Data is tested against all available regularizations. Then the optimal one is picked: the lowest regularization factor that doesn't change much the results.

This is the recommended option .

Fixed

Or you can set a specific regularization factor, ranging from 0 (none) to 12 (max), 4 being the default value.

(4) Inverse Postprocessing

Standardize Solution Points (in Time):

This will normalize the time course of each solution point by its background activity (noise). The real activities, the highest values, are not taken into account in the formula, as this would be counter-productive by 'neutralizing' them.

This option is highly recommened for optimal results!

See the relevant discussion here.

Compute Z-Score

Compute the Z-Scores every time.

Load Z-Score factors files

Try to reload the Z-Score factors from existing files. Files should match the inverse name and regularization, and of course, subjects' names.

Templatize (per Map):

Apply some sort of normalization to output only templates of activations , stripping the power component out.

Ranking

Each sample's results will be ranked, for each sample independently . Hence values will be between (0..1]

Envelope (Gap Bridging, in Time):

Apply an Envelope method ("Gap Bridging") to the norms of results. This goes faster than Hilbert transform, and gives more or less consistent results.

Lowest Band-Pass Frequency:

Provide here the lowest frequency to account for for the envelope.

ROIs (per Map):

If the option is selected, you have to provide the ROIs file that matches the current inverse matrix.

This is useful to reduce the results'size. It is of course applied for each sample at a time.

ROIs results are computed using a Median, not a Mean, of all points belonging to a given region.

Cartool will check that ROIs are compatible with the other files, and will complain if needed...

(4) Output Options

Optional Base File Name Prefix:

Specify here an optional prefix for all the output file names.

Saving Files:

A few options to tailor how you want to overflow your disk with files...

Each input file will have a one-to-one corresponding output .ris file.

All Epochs will have a corresponding  .ris file, which means, that could be huge.

This option, usually associated with ERP experiments, will gracefully compute the average .ris of each condition .

It will work correctly only if all the files have exactly the same lengths, across all conditions and all subjects.

This option is tailored for clusters of data (from the Fitting f.ex.). It will compute the mean template across each cluster of data. This might be even the only results of interest in that specific case...

Save the Z-Score factors to file. This could be handy in case of re-computation by just reloading them - these factors take a bit of time to compute...

Process

Runs the computation.

This button remains disabled until all the parameter dialogs have received enough (and consistent) informations .

Cancel

Quit the dialog.

Help

Launch the Help to the right page (should be here...).