BESA® Wiki - New pages [en]

Useful batches

2025-07-28T13:34:36Z

Jaehyun: Minor updates to the style of some text and images

{{BESAInfobox
|title = Module information
|module = BESA Research Standard or higher
|version = 7.1 or higher
}}

This page lists a number of useful batches that you can try yourself.

==Download the batch files==
Download and unzip the following files into your folder ''C:\Users\Public\Documents\BESA\Research_7_1\Scripts\Batch\'' (you may need to replace ''C:\Users\Public\Documents\'' with the equivalent Public Documents folder on your computer).

Then move the file ''TenDipBlue.bsa'' to the folder ''C:\Users\Public\Documents\BESA\Research_7_1\Scripts\ColorSchemes\'' (you may need to replace ''C:\Users\Public\Documents\'' with the equivalent Public Documents folder on your computer).

[https://github.com/BESA-GmbH/BESA-Research-Batches/releases/latest/download/BesaResearch_Batches.zip Download batches]

==ECG correction==
===Batch name===
''ECGCorrection.bbat''

===What does it do?===
This batch is used for correcting ECG artifacts. It is particularly useful for MEG data. It should be called before creating an MEG source montage.

===How to use it===
Load a data set that contains an ECG channel, or a clear manifestation of the ECG artifact. Make sure that the channel label of this channel is visible at the left (if not, adjust the montage, or change displayed channel types using the buttons at the top right, until you can see it).
Run the batch. The batch will ask you to set a cursor on the peak of the signal, and mark the channel if possible. It will then mark a number of occurrences and use tag #2 to collect the average ECG signal. This will then be used as an artifact topography for an adaptive artifact correction with minimum distortion of signal of interest.

==Create an MEG source montage==
===Batch name===
''CreateMEGSourceMtg.bbat''

''CreateGRDSourceMtg.bbat''

===What does it do?===
This batch is used for creating an MEG source montage, taking an existing artifact correction for ECG artifacts into account. The batch creates a magnetometer-based [gradiometer-based] source montage with 29 montage channels. Each channel has two orientations. Thus, a maximum of 58 source waveforms will be displayed. The waveforms depict the signal originating from the brain region underlying the head position indicated by the channel label (e.g. F3L will be a brain region underneath the location of the F3 channel from the 10-10 nomenclature).

This batch will enable you to use the MEG review as described in the publications by Benicky et al. (2017)[https://www.sciencedirect.com/science/article/abs/pii/S1388245715007269] and Nenonen et al. (2022) [https://www.mdpi.com/2076-3425/12/1/105/review_report].

===How to use it===
It is recommended to first run ''ECGCorrection.bbat'', or create an ECG artifact topography manually. Then run the batch.
The batch ''CreateMEGSourceMtg'' creates a 29-channel source montage based on magnetometers or axial gradiometers. In case that planar gradiometers should be used, please use the batch ''CreateGRDSourceMtg.bbat''.
After finalization, the number of source waveforms displayed can be adjusted using the button “Opt” – either use Regional Source oriented, or Regional Source all.

==Moving dipole fit==
===Batch name===
''MovingDipole11Dips_Minus20ToPeak.bbat''

Additional file: ''TenDipBlue.bsa''

===What does it do?===
This batch is intended to be used on epileptic spike averages. It performs a single dipole fit for each time point between 20 ms before the spike peak to the peak, in 2 ms steps. It displays the result in the 3D MRI view of the subject.

===How to use it===
As a pre-requisite, the associated solution file ''TenDipBlue.bsa'' needs to be copied to the folder ''C:\Users\Public\Documents\BESA\Research_7_1\Scripts\ColorSchemes''.

An averaged segment containing an epileptic spike should be loaded. It is assumed that the spike maximum lies at the zero latency point of the segment (indicated by a dotted line in the review display).

Before running the batch, check the filter settings: For epileptic spikes, we recommend setting a low cutoff of 3 Hz forward filter with 6dB, and a high cutoff of 35 Hz zero-phase with 24 dB.

Run the batch and follow the instructions when prompted. The result is automatically saved in a solution file (file basename followed by ''_MovDip_minus20_to_peak.bsa'').

==Dipole cluster fit==
===Batch name===
''ClusterDipoleFit.bbat''

===What does it do?===
For a number of segments of single events, the batch performs a dipole fit in each segment, and displays the result as a cluster in the 3D MRI view of the subject.

===How to use it===
As a prerequisite, you will need a segmented file that contains segments of single events of equal size. In order to get this, you can use the menu “''File / Export''”, then select “''Epochs around triggers''”, then press the button “''Triggers''” where you can define which trigger(s) to use (you can also use conditions that you defined in the ERP module).

The interval can be adjusted with the “Interval” button. The batch will expect at least 100 ms before and more than 100 ms after the event time point.

[[File:ExportMask.png]]

Run the export, and re-load the exported file.

Before running the batch, check the filter settings: For epileptic spikes, we recommend setting a low cutoff of 3 Hz forward filter with 6dB, and a high cutoff of 35 Hz zero-phase with 24 dB.
Also, in case you have both MEG and EEG data in your file, select the general modality you want to fit (EEG or MEG) using the button at the top right of the review window.

Now, start the batch. You will be asked to supply the latency at which the fit should be performed. Then, all segments will be processed (up to a maximum of 50 segments).

==Create discrete solution from source image==
===Batch name===
''CreateSourcesFromImageEEG.bbat''

''CreateSourcesFromImageMEG.bbat''

===What does it do?===
After a source image has been computed, this batch (with EEG in the name for an EEG image, or with MEG in the name for an MEG image) will create a new discrete solution, add the sources from the maxima of the source image, and fit their orientation within the current fit interval.

===How to use it===
As a prerequisite, you will need to compute a source image in the Source Analysis window.
The batch should then be called directly from the BESA Source Analysis window, using the menu Fit / Run Batch.
It will ask for the number of maxima in the image, which you can read from the title bar of the 3D window. Then it will create the solution and ensure that orientations are fitted correctly.

<div><ul>
<li style="display: inline-block;"> [[File:2025_11_Sesame1.png|thumb|800px]] </li>
<li style="display: inline-block;"> [[File:2025_11_Sesame2.png|thumb|800px]] </li>
</ul></div>

[[Category:Batches]]

How to Use BrainVision Analyzer with BESA Connectivity

2023-11-13T20:37:01Z

Harald:

{{BESAInfobox
|title = Module information
|module = BESA Connectivity
|version = BESA Connectivity 1.0 or higher
}}

== Note and general remarks==
To transform data from BrainVision Analyzer to BESA Connectivity, you need to convert it using MATLAB. We assume that you have it already installed on your PC and BrainVision Analyzer is configured to work with it. You will also need this script from our Github page:

https://github.com/BESA-GmbH/BESA-MATLAB-Scripts/blob/main/Additional_utilities/BESAConnectivityScripts/Analyzer_to_BESAConnectivity.m
You will also need these toolboxes:
https://github.com/BESA-GmbH/BESA-MATLAB-Scripts/tree/main/MATLAB2BESA

Please ensure that the MATLAB2BESA toolbox is in the MATLAB path.

== What to do in BrainVision Analyzer==
You need to prepare data that is in segments - but not averaged! You can of course apply any filtering and data processing beforehand. Then you export segments to MATLAB using the Brain Vision Analyzer to MATLAB interface.
Please make sure to use the following options when exporting:
- Type "desktop" in the first dialog
- Check boxes for "Export data in EEGLab format", "Raise EEGLab" and "Markers" in the second dialog.
- In the third dialog, select all EEG channels that have coordinates (but not channels which do not have coordinates in Brain Vision Analyzer, like A1, A2)

[[File:Analyzer Export Options.png|1200px]]

== Adapt the script ==
The script Analyzer_to_BESAConnectivity.m needs to be adapted. The following lines should be changed:
*In line after "%% Add toolboxes" provide full path to MATLAB2BESA toolbox
*You may adapt where the resulting file will be saved by changing the line "FilePathName = [pwd '\BAtoBESA.generic'];"
*There may be a different convention for x-axis values in the EEGLab representation. If electrodes like F4, P4, etc. appear on the left, then adjust the script such that in section ''Channel labels and units'' of the script, the line
: <code>EEG.chanlocs(ChanIdx).Y,... </code> is replaced by
: <code>-EEG.chanlocs(ChanIdx).Y,... </code>

== Finalization ==
You just need to run the script just by either pressing Run in matlab toolbar or by calling "Analyzer_to_BESAConnectivity" command.
In BESA Connectivity you then start a Time-Frequency workflow and open the newly created file.

[[Category:Connectivity]] [[Category:Time-Frequency]] [[Category:Data Import/Export]]

Freezing issue when using the Chinese or Japanese keyboard setting

2023-08-08T10:13:18Z

Harald:

{{BESAInfobox
|title = Module information
|module = BESA Research Basic or higher
|version = 6.1 or higher
}}

== Problem ==

BESA Research may freeze on Windows 10 after pressing a key with a Chinese or Japanese keyboard setting on "Batch Processing" or "Combine Conditions, Channels, Find Peaks" dialog.<br>
This is a known issue related to the Microsoft input method editor.

== Solution ==

The workarounds are:

1) Use an English keyboard setting or

2) Turn on the option to use the previous version of Microsoft Input Method Editor in Windows Settings:
# Open the '''Windows Settings''', then select '''Time & Language'''.
# Select '''Language''' on the left side menu, then select your language (e.g. '''Chinese'''), and click '''Options'''.
# Select a keyboard (e.g. '''Microsoft Pinyin'''), then click '''Options'''.
# Select '''General''', then turn on the Compatibility option, '''Use previous version of Microsoft Pinyin'''.
[[File:Use previous version of Microsoft IME 01.png|1000px]]

[[Category:Troubleshooting]]

Problems with switching to individual head model

2023-07-06T10:34:45Z

Harald:

{{BESAInfobox
|title = Module information
|module = BESA Research Standard or higher
|version = 7.1 or higher
}}

This Wiki page provides solutions for common issues when trying to activate the individual head model in BESA Source Analysis.

== I get an error message when selecting the individual EEG BEM or FEM model in Source Analysis ==
=== Reference electrode ===
A possible reason is that a reference electrode is defined, but was not digitized. In that case:
# Close BESA Source Analysis.
# In BESA Research, select "Edit / Channel Configuration...". In the channel configuration, switch off the reference electrode.
# After accepting with OK, re-start BESA Source Analysis. Now it should work as expected.
#: [[File:Channel_Config_Ref.png|400px]]

=== Electrodes were placed by BESA MRI but not all electrode labels conform to 10-10 standard ===
In this scenario, there are no digitized electrode positions; instead, standard electrode labels were used by BESA MRI for placing them onto the re-constructed head surface.<br>
If not all electrodes conform to the 10-10 standard, then the leadfields cannot be created for these electrodes. The way forward here is to:
# set the channels that do not have 10-10 labels to bad
# change the montage to "Original Average Reference"
#: [[File:Org_Av_Ref.png|500px]]
# export the data using the option "Current Montage"
#: [[File:Export_currMtgpng.png|500px]]
# open the exported data file. Now follow the workflow for placing 10-10 electrodes in BESA MRI, and computing the BEM / FEM for these electrodes.

== I have bad channels in my data ==
This is not a problem. The BEM or FEM is computed with the full electrode set. You can set them to bad afterwards in BESA Research, or before. Both scenarios work.

== Some of my EEG electrodes are not used in the co-registration, and show as transparent spheres during computation of the BEM or FEM ==
This is not a problem. The BEM or FEM will still be computed for these electrodes. However, you should be aware that the leadfield computation accuracy may suffer for these electrodes, since the volume conduction model is less accurate in the low parts of the face. It may an idea to set these electrodes to bad for source localization.

== I don't have digitized coordinates for my 10-10 electrodes ==
In BESA MRI, you can use the option "Place 10-10 electrode system" for the co-registration. This will work also for BEM / FEM computation, unless some of the electrodes do not conform to the 10-10 standard. In this case, please follow the instructions above.

Importing Digitized Points Measured by Polhemus Fastrak

2022-06-10T15:25:03Z

Jaehyun:

{{BESAInfobox
|title = Importing Digitized Points Measured by Polhemus Fastrak
|module = BESA Research Basic or higher
|version = BESA Research 5.2 or higher
}}

When head surface points and/or EEG sensor locations are measured using [https://polhemus.com/scanning-digitizing/digitizing-products/ Polhemus Fastrak] device together with [https://cortechsolutions.com/products/emse/locator/ '''Locator'''] software or [https://neuroimage.usc.edu/brainstorm/Tutorials/TutDigitize '''Digitize GUI of Brainstorm'''], the digitized points can be exported to a file format compatible with BESA Research (e.g. surface point coordinate file, [http://wiki.besa.de/index.php?title=Working_With_Additional_Files#sfp_.28surface_point_coordinate.29_file *.sfp]).

On the other hand, if you are using '''PiMgr''' software (Polhemus tracker management application), you need to reorganize the digitized surface points to fit the file format BESA Research requires. For example, a .sfp file should be prepared as the screenshot below using labels and cartesian coordinates (x, y, z) values. You can find more detailed information on how to reorganize digitized surface points for BESA Research in the following wiki article: [http://wiki.besa.de/index.php?title=Electrodes_and_Surface_Locations#Polhemus_Digitizer_Data Electrodes and Surface Locations | Polhemus Digitizer Data].

[[File:ST addfiles (2).gif]]

After the reorganization, digitized surface points can be imported into BESA Research using the ''Channel and digitized head surface point information'' dialog (''File → Head Surface Points and Sensors → Load Coordinate Files...'', keyboard shortcut: CTRL + L). See also the following wiki article: [http://wiki.besa.de/index.php?title=Importing_Digitized_Coordinates Importing Digitized Coordinates].

[[File:Import surface points 01.png|800px]]

The imported digitized surface points can be inspected in a 3D view using the menu ''File → Head Surface Points and Sensors → View'' (keyboard shortcut: V).

[[File:Surface points window 01.png|left|frame|Gray cubes: surface points, purple cubes: fiducials, red disks: electrodes, gray disks: HPI coils for MEG]]

[[Category:Data Import/Export‏‎]]

Issues related to the language setting of Windows

2022-01-27T15:48:38Z

Jaehyun: Created page with "== Problem == One of the Unicode related options on Windows 10 causes some issues listed below: * BESA Research shows the following error message when starting MRI coregistr..."

== Problem ==

One of the Unicode related options on Windows 10 causes some issues listed below:

* BESA Research shows the following error message when starting MRI coregistration.
** <code>MRI program could not be started.</code>
* BESA Research displays wrong special characters (see [[Wrong characters in BESA software]]).

== Solution ==

To solve the issues, you should change the "Language for non-Unicode programs" setting.

# In '''Windows Settings''', select '''Time & Language'''.
# Select '''Region''' at the left side menu.
# Select '''Additional data, time & regional settings'''.
# In "Clock and Region" dialog, select '''Region'''.
#: [[File:WindowsRegionSetting_01.png|1300px]]
# Move to '''Administrative''' tab in the "Region" dialog
# Click '''Change system locale...'''.
# Change the "Current system locale" to '''English (United States)'''.
# Uncheck the checkbox '''Beta: Use Unicode UTF-8 for worldwide language support'''.
# Restart Windows.
#: [[File:WindowsRegionSetting_02.png|800px]]

[[Category:Troubleshooting]]

Export Surface Images as the GIfTI File Format using MATLAB

2021-05-25T14:27:00Z

Jaehyun:

{{BESAInfobox
|title = Module information
|module = BESA Research Standard or higher
|version = BESA Research 6.1 or higher
}}

[https://www.nitrc.org/projects/gifti/ GIfTI] (Geometry format under the Neuroimaging Informatics Technology Initiative) is a file format for surface-based neuroimaging data and many surface-based brain mapping applications support to read this file format.

Although BESA Research does not have a feature to export surface image results ([[Source_Analysis_3D_Imaging#Cortical_LORETA |cortical LORETA]], [[Source_Analysis_3D_Imaging#Cortical_CLARA | cortical CLARA]], and [[Source_Analysis_3D_Imaging#Surface_Minimum_Norm_Image | minimum norm]]) in the GIfTI file format directly, imaging results on co-registered MRI surfaces exported from BESA Research to MATLAB can be exported in the GIfTI file format (*.gii) using [https://github.com/BESA-GmbH/BESA-MATLAB-Scripts/releases/latest/download/BESA2MATLAB.zip BESA2MATLAB] (BESA MATLAB Readers) and [https://www.artefact.tk/software/matlab/gifti/ GIfTI library for MATLAB].

[[File:ExportToGIfTI 01.png|700px]]

== Procedure ==

# Export surface image results to MATLAB using the '''Send to MATLAB''' dialog in the Source Analysis window of BESA Research (''File → Send to MATLAB...'').
#* Select the "3D image", "Current image", and "Voxel amplitude" options in the '''Send to MATLAB''' dialog if the options are not selected.
# After finishing the data exporting process, type <code>desktop</code> in the MATLAB window to open the MATLAB desktop window.
#* In the <code>besa_image</code> data structure, exported surface image results can be found.
# Export surface image results in GIfTI file format: refer to the MATLAB script shown below.
#* It is required to download the [https://github.com/BESA-GmbH/BESA-MATLAB-Scripts/releases/latest/download/BESA2MATLAB.zip BESA2MATLAB] (BESA MATLAB Readers) and [https://www.artefact.tk/software/matlab/gifti/ GIfTI library for MATLAB] if you do not have these toolboxes yet.
#* Please modify the example script below to add the '''BESA MATLAB Readers''' and '''GIfTI library for MATLAB''' folders to the search path for MATLAB and to set the file path of the ''sfh'' file used in BESA Research.

<source lang="matlab">
% Export surface image values to GIfTI (.gii)

% -------------------------------------------------------------------------
% Add paths: BESA2MATLAB (BESA MATLAB Readers) and GIfTI library for MATLAB
% -------------------------------------------------------------------------

%addpath('xxx'); % add BESA2MATLAB
%addpath('xxx'); % add GIfTI library for MATLAB

% -------------------------------------------------------------------------
% Set the file path of the sfh file used in BESA Research
% -------------------------------------------------------------------------

%fileSfh = 'xxx\xxx.sfh';

% -------------------------------------------------------------------------
% Prepare white matter surface
% -------------------------------------------------------------------------

% Read BESA coregistration information from a .sfh file
sfh = readBESAsfh(fileSfh);

% Read a reduced white matter surface (in Talairach space)
% ex: xxx\MRIFiles\SurfaceFiles\MRISeg_MRI_T1_TAL_WM_RED.srf
BrainSurfaceReduced = [sfh.Talairach.TalBrainSurfacePath(1:end-4) '_RED.srf'];
wm = readBESAsrf(BrainSurfaceReduced);
% Read an original white matter surface (in Talairach space) if you want to use it.
%wm = readBESAsrf(sfh.Talairach.TalBrainSurfacePath);

% NOTE: The wm.CoordsVertices is in the BrainVoyager coordinate system.
val_shift = 128;
surface = [];
surface.faces = wm.Triangles + 1; % In MATLAB, an index starts from 1.
surface.vertices = ...
[ wm.CoordsVertices(:,3) - val_shift, ...
-(wm.CoordsVertices(:,1) - val_shift),...
-(wm.CoordsVertices(:,2) - val_shift)];
% Flip x axis
surface.vertices(:,1) = -surface.vertices(:,1);

% -------------------------------------------------------------------------
% Interpolate the surface image values
% -------------------------------------------------------------------------

value = griddata(...
besa_image.xcoordinates, besa_image.ycoordinates, besa_image.zcoordinates, ...
besa_image.data,...
surface.vertices(:,1), surface.vertices(:,2), surface.vertices(:,3), 'nearest');

value(isnan(value)) = 0;

% -------------------------------------------------------------------------
% Prepare GIfTI objects
% -------------------------------------------------------------------------

% White matter surface
gSurface = gifti(surface);

% Intepolated surface image values
gSurfaceImage = [];
gSurfaceImage.cdata = value;
gSurfaceImage = gifti(gSurfaceImage);

% Plot the white matter surface
%figure; plot(gSurface);
% Plot the white matter surface with surface image values
%figure; plot(gSurface, gSurfaceImage);

% -------------------------------------------------------------------------
% Save as the GIfTI file format (*.gii)
% -------------------------------------------------------------------------

save(gSurface, 'surface.gii', 'Base64Binary');
save(gSurfaceImage, 'surfaceImage.gii', 'Base64Binary');

</source>

== See also ==

* [[MATLAB Interface]]
* [[Integration_with_MRI_and_fMRI#The_Coregistration_File_.28.2A.sfh.29 | The Coregistration File (*.sfh)]]

[[Category:Data Import/Export‏‎]]

Export Data to Brainstorm

2021-05-21T16:11:34Z

Jaehyun:

{{BESAInfobox
|title = Module information
|module = BESA Research Standard or higher
|version = BESA Research 6.1 or higher
}}

BESA Research can export EEG or MEG data to MATLAB in a structure data type named <code>besa_channels</code>. The exported data structure can be also imported to [https://neuroimage.usc.edu/brainstorm/Introduction Brainstorm] for further analysis using the <code>besa2brainstorm</code> MATLAB function included in the [https://github.com/BESA-GmbH/BESA-MATLAB-Scripts/releases/latest/download/BESA2MATLAB.zip BESA2MATLAB] (BESA MATLAB Readers).

[[File:ExportDataToBrainstorm01.png|700px]]

== Procedure ==

# Export EEG or MEG data to MATLAB in BESA Research using the [[Export#Export_Dialog | '''Export data''']] dialog (''File → Send to MATLAB...'').
# After finishing the data exporting process, type <code>desktop</code> in the MATLAB window to open the MATLAB desktop window.
# Add the '''BESA MATLAB Readers''' and '''Brainstorm''' folders to the search path for MATLAB.
# Run Brainstorm and then create a '''Protocol''' and '''Subject'''. Protocols and subjects already created in Brainstorm can be also used instead of creating new ones.
# Import the <code>besa_channels</code> structure to Brainstorm using the <code>besa2brainstorm</code> function. For an example, refer to the MATLAB script below.

An example MATLAB script for importing the <code>besa_channels</code> structure to Brainstorm:

<source lang="matlab">
% Add paths: BESA2MATLAB (BESA MATLAB Readers) and Brainstorm
%addpath('xxx');
%addpath('xxx');

% Create a protocol and a subject in Brainstorm
% ex) Protocol name: Protocol01; Subject name: Subject01

% Import the besa_channels structure to Brainstorm
bstVar = [];
bstVar.ProtocolName = 'Protocol01';
bstVar.SubjectName = 'Subject01';
bstVar.StudyName = 'test_S1_EpochedData';
besa2brainstorm(besa_channels, bstVar, true);
</source>

== See also ==

* [[MATLAB Interface]]
* [[Export]]
* [[Export Single Trial Data]]

[[Category:Data Import/Export‏‎]]

Discrete Sources

2021-05-04T12:11:50Z

Dominik:

{{BESAInfobox
|title = Module information
|module = BESA Research Standard or higher
|version = 6.1 or higher
}}

== Overview ==

A source is used to model the electro-magnetic activity caused by patches of simultaneously active neurons. There are three types of sources in BESA:

* [[Image:singleDipole.png|40px]] [[#Single Dipole | single dipoles]],
* [[Image:regionalSource.png|40px]] [[#Regional Source | regional sources]],
* [[Image:spatialComponent.png|40px]] [[#Spatial Component | spatial components]].

In case of MRI-coregistered datasets the [[#Confidence Ellipsoid and Error Rim | confidence ellipsoid and error rim]] can be displayed for single dipoles and regional sources.

== Single Dipole ==

[[Image:singleDipole.png|40px]] A single dipole source (abbreviation: ''SD'' or ''Dip'') can be regarded as an electric current dipole, which is used for the physical modeling of the physiological activity. It is described by a location and an orientation, and the source waveform describes its amplitude over time.

'''Selected Source'''

A source is selected by clicking onto the source plot in the head box or by clicking onto the source waveform in the source box. It is deselected by selecting another source or by clicking beneath any source plot in the head box.

The selected source is marked with a circle around its source plots in the head box, with a golden halo in the 3D window and a colored rectangle around its On/Off and Fit/No fit button in the source box. If a source is selected its parameters are displayed in the parameter box.

== Regional Source ==

[[Image:regionalSource.png|40px]] A regional source (abbreviation: ''RS'') is a source which describes all activity originating in the vicinity of its location. It can be regarded as a source with three (MEG spherical head models: two) [[#Single Dipole| single dipoles]] (called components) at the same location but with orthogonal orientations.

[[Image:orientedRegionalSource.png|40px]] A regional source can be rotated such that one of the single orientations of its components explains a maximum of activity at a specified sample. If a regional source has been rotated, the orientation of each component is displayed in the [[Source_Analysis_Functions_of_the_Window#Head_Box | head box]], otherwise only the source body is displayed.

== Spatial Component ==

[[Image:spatialComponent.png|40px]] A spatial component (abbreviation: ''SpC'') is a source represented by a principal vector. This principal vector results from a Principal Component Analysis (PCA) or Independent Component Analysis (ICA) of the covariance data matrix, from the RAP-Music algorithm, or from the measured data at the cursor sample. It describes the contribution of the source at the sensors. The topography of a spatial component need not be of dipolar nature.

If the spatial component results from a PCA, ICA, or the cursor sample, its location is reconstructed by an approximation. Spatial components created by RAP-Music have exactly defined location and orientation but can consist of two components (with one resulting principal vector).

== Confidence Ellipsoid and Error Rim ==
''(requires BESA Research 7.1 or higher)''

For [[#DSingle Dipole | dipole solutions]] and [[#Regional Source | oriented regional sources]], confidence limits are calculated, displayed, and stored. The last fit interval used for a source is relevant for computing the confidence limit, as well as the baseline interval. These intervals are also stored with the solution. In case of multi-dipole solutions or solutions which include spatial components, the full source model is taken into account for computation. Confidence limits are written to solution files if the coordinate system for export is set to Talairach. For these solutions, an import and display of the solution in BESA MRI is possible (BESA MRI 3.0 or higher). The limit that is computed corresponds to the 95% confidence limit. Computation follows the approach of M. Hämäläinen (Interpretation of neuromagnetic measurements: modeling and statistical considerations, PhD thesis at Helsinki University of Technology 1987, pp 27 ff).

* Note: Confidence limit display in the MRI window is only active if an individual MRI was co-registered.
* Also note that the confidence limit computed requires a baseline interval that is well defined. The baseline interval can be adjusted by clicking on the baseline indicator bar at the top left of the Source Analysis window.
* Confidence limits depend on many factors including the number of active sources, the signal-to-noise ratio, and the fit interval. In particular, the confidence limit does not account for other errors, e.g. head model errors, co-registration errors, or influence of artifacts on the solution. They should be regarded as a guideline and serve as a lower limit to the confidence of the solution, not as an upper limit.

'''The confidence ellipsoid radii are computed as follows:'''

First the data predicted by the model (b) is computed using fitting time point i or the fitting interval, and predicted source strength from the inverse operator applied to measured data.

ji is calculated for the time point. Then the Jabobian J can be defined as change in b when moving the dipole in the three main axes of the ellipsoid, e.g. for the first axis (depicted as x axis here):

[[Image:confidenceEllipsoid_eq01.png]]

where h is sufficiently small.

Then compute the C matrix (3x3) from which radii (∆x,∆y,∆z) for a 95% confidence interval can be defined:

[[Image:confidenceEllipsoid_eq02.png]]

[[Image:confidenceEllipsoid_eq03.png]]

'''References'''

* Hämäläinen, M., 1987. Interpretation of neuromagnetic measurements : modeling and statistical considerations. Helsinki University of Technology.

{{BESAManualNav}}

Filtering scope

2021-02-02T16:14:49Z

Harald:

{{BESAInfobox
|title = Module information
|module = BESA Research
|version = 6.1 or higher
}}
==Overview==
In EEG/MEG data analysis frequency filtering is one of the most basic and at the same time important operations. In BESA Research filtering is implemented as a linear operation so it is interchangeable in the processing pipeline - it can be changed at every processing step in almost all situations. There are however some situations where filtering cannot be applied in a strictly linear manner - e.g. averaging in the presence of slow drifts. In general, due to the linear nature of filtering we recommend not to apply filtering in the pre-averaging processing stage (apart from high pass to reduce drifts) as it can still be applied afterwards. You will be prompted by the application if you encounter this type of situation in data analysis:

[[File:Filter_notification.jpg]]

Also at some stages of the data processing, filtering is of major importance, therefore we made it more accessible and you can easily redefine it. Please have a look at the table below:
{| class="wikitable" style="text-align:center;"
! style="font-weight: bold;" | Filter type
! style="font-weight: bold;" | Review window
! style="font-weight: bold;" | Search Average View
! style="font-weight: bold;" | Averaged buffer
! style="font-weight: bold;" | FFT
! style="font-weight: bold;" | lienear correlation / regression
! style="font-weight: bold;" | Combine Conditions
! style="font-weight: bold;" | ERP
! style="font-weight: bold;" | Coherence
! style="font-weight: bold;" | Time Frequency plot<br>(single click)
! style="font-weight: bold;" | TopViewer
! style="font-weight: bold;" | Source Analysis
|-
| style="font-weight: bold;" | Low/High pass
| style="background: #F2D16B" |Main
| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px, #BA9588 10px, #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
| style="background: #BA9588" |as used during buffer creation
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| None
| style="background: #6BCFF2" |ERP
| style="background: #6BCFF2" |ERP
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #CFF26B" |SA
|-
| style="font-weight: bold;" | Notch
| style="background: #F2D16B" |Main
| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px, #BA9588 10px, #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
| style="background: #BA9588" |as used during buffer creation
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| None
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
|-
| style="font-weight: bold;" | Bandpass
| style="background: #F2D16B" |Main
| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px, #BA9588 10px, #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
| style="background: #BA9588" |as used during buffer creation
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| None
| style="background: #6BCFF2" |ERP
| style="background: #6BCFF2" |ERP
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
|-
| style="font-weight: bold;" | Polygraphic
| style="background: #F2D16B" |Main*
| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px, #BA9588 10px, #BA9588 20px);"| Main* / can be redefined to default values(2-35Hz)
| style="background: #BA9588" |as used during buffer creation
| style="background: #F2D16B" |Main*
| style="background: #F2D16B" |Main*
| None
| style="background: #F2D16B" |Main*
| style="background: #F2D16B" |Main*
| style="background: #F2D16B" |Main*
| style="background: #F2D16B" |Main*
| n.a.
|-
| style="font-weight: bold;" | artifact correction
| style="background: #F2D16B" |Main
| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px, #BA9588 10px, #BA9588 20px);"| Main / can be redefined to default values(2-35Hz)
| style="background: #BA9588" |as used during buffer creation
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: #6BCFF2" |ERP
| style="background: #6BCFF2" |ERP
| style="background: #F2D16B" |Main
| style="background: #F2D16B" |Main
| style="background: repeating-linear-gradient(45deg, #F2D16B,#F2D16B 10px, #CFF26B 10px,#CFF26B 20px);"| Main/SA
|}

==Main settings==
The main setting for artifact correction can be set using '''EdF''' or menu entry '''Filters/Edit Filter Settings'''...

[[File:filter_main.jpg]]

==Specific ERP settings==
The ERP filter settings can be set during paradigm definition. Note that there are two different settings - for artifact scan and for averaging.

[[File:filter_ERP.jpg]]

==Specific Source Analysis settings==
For source analysis (SA), if you press the '''ESI/MSI''' button on the toolbar ribbon ''Main'' filter settings will be used. Filters for SA can be set during sending a block of data to Source Analysis (right-click on the highlighted block and select '''Source Analysis''').

[[File:filter_SA.jpg]]

In case of enabled artifact correction, you will be prompted just before averaging if you want to average artifact corrected data or not. The detailed description of difference in both approaches can be found [[Using BESA to correct blink and EKG artifacts in MEG data#Averaging the raw data|here]].

==Notch filter==
Note that because of its generic nature - power line artifact removal - the notch filter is treated differently. The notch filter value populates from ''Main'' setting to all subsequent applications.

==Bandpass filter==
The bandpass filter is complementary to the high/low pass filter combination. For convenience, it is treated differently (it also has different filter characteristics) and also populates to all subsequent applications from ''Main'' setting.

==Polygraphic filter==
Polygraphic channels are filtered using Main settings. Note that there are additional settings that can be applied to the polygraphic filter accessible via '''Filters/Polygraphic/Additional Chans...'''

[[File:filter_poly.jpg]]

==See also==
*[[Review#Filtering|Filtering]]
*[[Using BESA to correct blink and EKG artifacts in MEG data]]
*[[Pipeline for simultaneous EEG-fMRI recording]]

[[Category:Preprocessing]]