User Reference:EEGLabImport - Revision history

Swiftj: /* Using EEGLabImport */

2021-03-02T17:15:27Z

Using EEGLabImport

← Older revision		Revision as of 17:15, 2 March 2021
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	Begin a Matlab session, and start EEGLAB by typing ''eeglab'' at the command prompt. EEGLabImport is		Begin a Matlab session, and start EEGLAB by typing ''eeglab'' at the command prompt. EEGLabImport is
	detected and added to the menus automatically.		detected and added to the menus automatically.
	Go to File->Import ~~Data~~->BCI2000 ~~Data~~ to start the data import program. A file-select		Go to File->Import data->Using EEGLAB functions and plugins->From BCI2000 .DAT file to start the data import program. A file-select
	dialog is presented, in which multiple BCI2000 data files can be selected (see figure below). The default file extension		dialog is presented, in which multiple BCI2000 data files can be selected (see figure below). The default file extension
	for BCI2000 data files is *.dat. Select one or more files from the desired folder, and press Open.		for BCI2000 data files is *.dat. Select one or more files from the desired folder, and press Open.

Swiftj: /* Installing EEGLabImport */

2021-03-02T17:09:07Z

Installing EEGLabImport

← Older revision		Revision as of 17:09, 2 March 2021
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	#Copy the folder <tt>BCI2000/tools/EEGLabImport</tt> to the EEGLab plugin folder, located at <tt>eeglab/plugins</tt>.		#Copy the folder <tt>BCI2000/tools/EEGLabImport</tt> to the EEGLab plugin folder, located at <tt>eeglab/plugins</tt>.

	If you do not have a downloaded version of BCI2000 with the appropriate tools installed, or you are using an operating system other than Windows, the contents of the <tt>BCI2000/Tools/mex</tt> can be downloaded HERE and the contents of the <tt>BCI2000/Tools/EEGlabImport<tt> folder can be downloaded HERE.		If you do not have a downloaded version of BCI2000 with the appropriate tools installed, or you are using an operating system other than Windows, the contents of the <tt>BCI2000/Tools/mex</tt> can be downloaded HERE and the contents of the <tt>BCI2000/Tools/EEGlabImport</tt> folder can be downloaded HERE.

	When EEGLAB is started, the plugin will be automatically detected and installed.		When EEGLAB is started, the plugin will be automatically detected and installed.

Swiftj: /* Installing EEGLabImport */

2021-03-02T17:08:47Z

Installing EEGLabImport

← Older revision		Revision as of 17:08, 2 March 2021
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	Installation of the plugin is straightforward, but may require compiling the <tt>load_bcidat</tt> MEX function for your platform.		Installation of the plugin is straightforward, but may require compiling the <tt>load_bcidat</tt> MEX function for your platform.

	#If you are using a 32-bit version ~~ofWindows~~, <tt>load_bcidat.mexw32</tt> is likely already compiled for your platform, and can be located in the <tt>BCI2000/tools/mex/</tt> folder. Copy ~~this file~~ to the <tt>BCI2000/tools/EEGLabImport</tt> folder, and skip to 5.		#If you are using a 32-bit version of Windows, <tt>load_bcidat.mexw32</tt> is likely already compiled for your platform, and can be located in the <tt>BCI2000/tools/mex/</tt> folder. Copy the entire mex folder to the <tt>BCI2000/tools/EEGLabImport</tt> folder, and skip to 5.
	#If you are using a platform for which a version of <tt>load_bcidat</tt> does not exist in the <tt>/tools/mex</tt> folder, the <tt>load_bcidat</tt> MEX file must be compiled.		#If you are using a platform for which a version of <tt>load_bcidat</tt> does not exist in the <tt>/tools/mex</tt> folder, the <tt>load_bcidat</tt> MEX file must be compiled.
	#Open Matlab, and navigate to <tt>BCI2000/src/core/Tools/mex/</tt>. Type <tt>buildmex</tt> at the command line; this will build the BCI2000 MEX functions for your platform.		#Open Matlab, and navigate to <tt>BCI2000/src/core/Tools/mex/</tt>. Type <tt>buildmex</tt> at the command line; this will build the BCI2000 MEX functions for your platform.
	#Once the build process is complete, locate the <tt>~~load_bcidat~~</tt> ~~file for your platform based on its extension (see the Matlab MEX documentation for more details)~~, and copy it to <tt>BCI2000/tools/EEGLabImport</tt>.		#Once the build process is complete, locate the <tt>BCI2000/Tools/mex</tt> folder, and copy it to <tt>BCI2000/tools/EEGLabImport</tt>.
	#Copy the folder <tt>BCI2000/tools/EEGLabImport</tt> to the EEGLab plugin folder, located at <tt>eeglab/plugins</tt>.		#Copy the folder <tt>BCI2000/tools/EEGLabImport</tt> to the EEGLab plugin folder, located at <tt>eeglab/plugins</tt>.

			If you do not have a downloaded version of BCI2000 with the appropriate tools installed, or you are using an operating system other than Windows, the contents of the <tt>BCI2000/Tools/mex</tt> can be downloaded HERE and the contents of the <tt>BCI2000/Tools/EEGlabImport<tt> folder can be downloaded HERE.

	When EEGLAB is started, the plugin will be automatically detected and installed.		When EEGLAB is started, the plugin will be automatically detected and installed.

Mellinger: /* Using EEGLabImport */

2012-11-12T14:19:01Z

Using EEGLabImport

← Older revision		Revision as of 14:19, 12 November 2012
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	described below.		described below.

	*'''TargetCode''' – This state gives the target number that was displayed to the subject during each trial. In cases where only 2 targets are presented, this will have a value of either 1 or 2. EEGLAB stores ~~the~~ TargetCode as a single event~~, and does not discriminate between different values. Therefore, once~~ the ~~data is imported, it is necessary~~ to ~~create new~~, ~~separate events for each TargetCode value in EEGLAB using~~ the ~~Edit->Select Epochs/Events menu. Refer~~ to the ~~EEGLAB documentation for more information~~.		*'''TargetCode''' – This state gives the target number that was displayed to the subject during each trial. In cases where only 2 targets are presented, this will have a value of either 1 or 2. EEGLAB stores each change in TargetCode as a single event with the event's type field set to "TargetCode", and the event's position field set to the actual value of "TargetCode".
	*'''ResultCode''' – This is related to the TargetCode state, but tells how the user actually performed on the task. If the user was able to move the cursor to the correct Target, then the ResultCode is the same as the TargetCode for that trial. Otherwise, it will be different. This is useful if you only want to select trials that result in a hit.		*'''ResultCode''' – This is related to the TargetCode state, but tells how the user actually performed on the task. If the user was able to move the cursor to the correct Target, then the ResultCode is the same as the TargetCode for that trial. Otherwise, it will be different. This is useful if you only want to select trials that result in a hit.
	*'''Feedback''' – This event gives the time at which the user is first presented with visual feedback of the cursor. This often does not coincide with the appearance of the target, and you may want to average on the Feedback state instead of TargetCode.		*'''Feedback''' – This event gives the time at which the user is first presented with visual feedback of the cursor. This often does not coincide with the appearance of the target, and you may want to average on the Feedback state instead of TargetCode.

Mellinger: /* Installing EEGLabImport */

2010-03-05T19:36:59Z

Installing EEGLabImport

← Older revision		Revision as of 19:36, 5 March 2010
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	==Installing EEGLabImport==		==Installing EEGLabImport==
	Installation of the plugin is straightforward.		Installation of the plugin is straightforward, but may require compiling the <tt>load_bcidat</tt> MEX function for your platform.
	Copy the <tt>BCI2000/tools/EEGLabImport</tt> folder to the <tt>eeglab/plugins</tt> ~~folder~~. ~~In either case, when~~ EEGLAB is started,
	the plugin will be automatically detected and installed.		#If you are using a 32-bit version ofWindows, <tt>load_bcidat.mexw32</tt> is likely already compiled for your platform, and can be located in the <tt>BCI2000/tools/mex/</tt> folder. Copy this file to the <tt>BCI2000/tools/EEGLabImport</tt> folder, and skip to 5.
			#If you are using a platform for which a version of <tt>load_bcidat</tt> does not exist in the <tt>/tools/mex</tt> folder, the <tt>load_bcidat</tt> MEX file must be compiled.
			#Open Matlab, and navigate to <tt>BCI2000/src/core/Tools/mex/</tt>. Type <tt>buildmex</tt> at the command line; this will build the BCI2000 MEX functions for your platform.
			#Once the build process is complete, locate the <tt>load_bcidat</tt> file for your platform based on its extension (see the Matlab MEX documentation for more details), and copy it to <tt>BCI2000/tools/EEGLabImport</tt>.
			#Copy the folder <tt>BCI2000/tools/EEGLabImport</tt> to the EEGLab plugin folder, located at <tt>eeglab/plugins</tt>.

			When EEGLAB is started, the plugin will be automatically detected and installed.

	==Using EEGLabImport==		==Using EEGLabImport==
	Begin a Matlab session, and start EEGLAB by typing ''eeglab'' at the command prompt. EEGLabImport is		Begin a Matlab session, and start EEGLAB by typing ''eeglab'' at the command prompt. EEGLabImport is

Mellinger: /* Analyzing the Data */

2008-08-19T17:27:34Z

Analyzing the Data

← Older revision		Revision as of 17:27, 19 August 2008
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	produced:		produced:

	[[Image:EEGLabImport8.PNG\|~~width=200~~\|Spectral plot and maps for all channels for TargetCode = 1]]		[[Image:EEGLabImport8.PNG\|400px\|Spectral plot and maps for all channels for TargetCode = 1]]

	Note that in this figure, the scalp maps are '''not''' normalized to each other; the red in the 10 Hz figure is much		Note that in this figure, the scalp maps are '''not''' normalized to each other; the red in the 10 Hz figure is much
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	clicking on the scalp map, which will open a new figure:		clicking on the scalp map, which will open a new figure:

	[[Image:EEGLabImport9.PNG\|~~width=200~~\|Spectral map for 10 Hz]]		[[Image:EEGLabImport9.PNG\|400px\|Spectral map for 10 Hz]]

	Press the Colorbar button (under the Window and Help menus) to find out what the range is in this figure (it is about -25 to +25).		Press the Colorbar button (under the Window and Help menus) to find out what the range is in this figure (it is about -25 to +25).
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	‘electrodes’,’on’, add ‘maplimits’,[-25 25]:		‘electrodes’,’on’, add ‘maplimits’,[-25 25]:

	[[Image:EEGLabImport10.PNG~~\|width=200~~\|Normalized Spectral Maps]]		[[Image:EEGLabImport10.PNG\|Normalized Spectral Maps]]

	Press OK, and the new normalized figure is produced:		Press OK, and the new normalized figure is produced:

	[[Image:EEGLabImport11.PNG\|~~width=200~~\|Normalized Spectral Maps]]		[[Image:EEGLabImport11.PNG\|400px\|Normalized Spectral Maps]]

	One method of comparing between the two conditions would be look at the TargetCode 2 dataset using the		One method of comparing between the two conditions would be look at the TargetCode 2 dataset using the
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	The dataset4 was selected and analyzed exactly the same as before:		The dataset4 was selected and analyzed exactly the same as before:

	[[Image:EEGLabImport12.PNG\|~~width=200~~\|Normalized spectral map for TargetCode = 2]]		[[Image:EEGLabImport12.PNG\|400px\|Normalized spectral map for TargetCode = 2]]

	Notice that the 10 Hz activation is much weaker for TargetCode = 2 than for TargetCode = 1.		Notice that the 10 Hz activation is much weaker for TargetCode = 2 than for TargetCode = 1.
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	Spectrum box, and 1250 for the Mark Times box. Press OK, and the following figure is produced:		Spectrum box, and 1250 for the Mark Times box. Press OK, and the following figure is produced:

	[[Image:EEGLabImport14.PNG\|ERP Image for TargetCode = 1]]		[[Image:EEGLabImport14.PNG\|400px\|ERP Image for TargetCode = 1]]

	This shows the amplitude for each trial, the mean response, the ERSP (event-related spectral power), and the		This shows the amplitude for each trial, the mean response, the ERSP (event-related spectral power), and the
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	dataset to #4, and enter the same parameters for the analysis in the ERP Image) as in this figure:		dataset to #4, and enter the same parameters for the analysis in the ERP Image) as in this figure:

	[[Image:EEGLabImport15.PNG\|ERP Image for TargetCode = 2]]		[[Image:EEGLabImport15.PNG\|400px\|ERP Image for TargetCode = 2]]

	There is a very noticeable change in signal amplitude for each condition after the baseline condition, when the cursor appears		There is a very noticeable change in signal amplitude for each condition after the baseline condition, when the cursor appears

Mellinger: /* Channel Spectra and Maps */

2008-08-19T17:23:45Z

Channel Spectra and Maps

← Older revision		Revision as of 17:23, 19 August 2008
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	end time the same; the omits the baseline activity before the cursor appears. Since this is a small dataset, set		end time the same; the omits the baseline activity before the cursor appears. Since this is a small dataset, set
	Percent data to sample to 100. Set the Frequencies to plot as scalp maps to '6 10 22' (this will become more		Percent data to sample to 100. Set the Frequencies to plot as scalp maps to '6 10 22' (this will become more
	clear shortly). Finally, in the last box, change the ‘electrodes’ option to ‘on.’ Press Ok. The following plot is		clear shortly). Finally, in the last box, change the ‘electrodes’ option to ‘on.’ Press OK. The following plot is
	produced:		produced:

	[[Image:EEGLabImport8.PNG\|Spectral plot and maps for all channels for TargetCode = 1]]		[[Image:EEGLabImport8.PNG\|width=200\|Spectral plot and maps for all channels for TargetCode = 1]]

	Note that in this figure, the scalp maps are '''not''' normalized to each other; the red in the 10 Hz figure is much		Note that in this figure, the scalp maps are '''not''' normalized to each other; the red in the 10 Hz figure is much
Line 156:		Line 156:
	clicking on the scalp map, which will open a new figure:		clicking on the scalp map, which will open a new figure:

	[[Image:EEGLabImport9.PNG\|Spectral map for 10 Hz]]		[[Image:EEGLabImport9.PNG\|width=200\|Spectral map for 10 Hz]]

	Press the Colorbar button (under the Window and Help menus) to find out what the range is in this figure (it is about -25 to +25).		Press the Colorbar button (under the Window and Help menus) to find out what the range is in this figure (it is about -25 to +25).
Line 162:		Line 162:
	‘electrodes’,’on’, add ‘maplimits’,[-25 25]:		‘electrodes’,’on’, add ‘maplimits’,[-25 25]:

	[[Image:EEGLabImport10.PNG\|Normalized Spectral Maps]]		[[Image:EEGLabImport10.PNG\|width=200\|Normalized Spectral Maps]]

	Press OK, and the new normalized figure is produced:		Press OK, and the new normalized figure is produced:

	[[Image:EEGLabImport11.PNG\|Normalized Spectral Maps]]		[[Image:EEGLabImport11.PNG\|width=200\|Normalized Spectral Maps]]

	One method of comparing between the two conditions would be look at the TargetCode 2 dataset using the		One method of comparing between the two conditions would be look at the TargetCode 2 dataset using the
Line 172:		Line 172:
	The dataset4 was selected and analyzed exactly the same as before:		The dataset4 was selected and analyzed exactly the same as before:

	[[Image:EEGLabImport12.PNG\|Normalized spectral map for TargetCode = 2]]		[[Image:EEGLabImport12.PNG\|width=200\|Normalized spectral map for TargetCode = 2]]

	Notice that the 10 Hz activation is much weaker for TargetCode = 2 than for TargetCode = 1.		Notice that the 10 Hz activation is much weaker for TargetCode = 2 than for TargetCode = 1.

Mellinger: /* Channel Spectra and Maps */

2008-08-19T15:25:36Z

Channel Spectra and Maps

← Older revision		Revision as of 15:25, 19 August 2008
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	One method of comparing between the two conditions would be look at the TargetCode 2 dataset using the		One method of comparing between the two conditions would be look at the TargetCode 2 dataset using the
	same analysis and the same range (-25 to +25) as before, and seeing how the activation strength compares.		same analysis and the same range (-25 to +25) as before, and seeing how the activation strength compares.
	The dataset4 was selected and analyzed exactly the same as before~~, producing Figure 12. Notice that the 10-~~		The dataset4 was selected and analyzed exactly the same as before:
	~~Hz activation is much weaker for TargetCode = 2 than for TargetCode = 1.~~

	[[Image:EEGLabImport12.PNG\|Normalized spectral map for TargetCode = 2]]		[[Image:EEGLabImport12.PNG\|Normalized spectral map for TargetCode = 2]]

			Notice that the 10 Hz activation is much weaker for TargetCode = 2 than for TargetCode = 1.

	====Channel ERP Analysis====		====Channel ERP Analysis====

Mellinger: /* Channel ERP Analysis */

2008-08-19T15:24:47Z

Channel ERP Analysis

← Older revision		Revision as of 15:24, 19 August 2008
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	This shows the amplitude for each trial, the mean response, the ERSP (event-related spectral power), and the		This shows the amplitude for each trial, the mean response, the ERSP (event-related spectral power), and the
	inter-trial coherence for the condition that the TargetCode = 1. Compare this to TargetCode = 2 (change the		inter-trial coherence for the condition that the TargetCode = 1. Compare this to TargetCode = 2 (change the
	dataset to #4, and enter the same parameters for the analysis in the ERP Image) in ~~Figure 15. There is a very~~		dataset to #4, and enter the same parameters for the analysis in the ERP Image) as in this figure:
	~~noticeable change in signal amplitude for each condition after the baseline condition, when the cursor appears~~
	~~and the control phase of the task begins.~~

	[[Image:EEGLabImport15.PNG\|ERP Image for TargetCode = 2]]		[[Image:EEGLabImport15.PNG\|ERP Image for TargetCode = 2]]

			There is a very noticeable change in signal amplitude for each condition after the baseline condition, when the cursor appears
			and the control phase of the task begins.

	===Further Information===		===Further Information===
	This tutorial aimed at getting you started using EEGLAB for analyzing BCI2000 data.		This tutorial aimed at getting you started using EEGLAB for analyzing BCI2000 data.

Mellinger: /* Channel Spectra and Maps */

2008-08-19T15:23:40Z

Channel Spectra and Maps

← Older revision		Revision as of 15:23, 19 August 2008
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	Because we are interested in what happened during the trial, change the start time to 1250 ms, and leave the		Because we are interested in what happened during the trial, change the start time to 1250 ms, and leave the
	end time the same; the omits the baseline activity before the cursor appears. Since this is a small dataset, set		end time the same; the omits the baseline activity before the cursor appears. Since this is a small dataset, set
	Percent data to sample to 100. Set the Frequencies to plot as scalp maps to 6 10 22 (this will become more		Percent data to sample to 100. Set the Frequencies to plot as scalp maps to '6 10 22' (this will become more
	clear shortly). Finally, in the last box, change the ‘electrodes’ option to ‘on.’ Press Ok. The following plot is		clear shortly). Finally, in the last box, change the ‘electrodes’ option to ‘on.’ Press Ok. The following plot is
	produced:		produced:
Line 154:		Line 154:
	Note that in this figure, the scalp maps are '''not''' normalized to each other; the red in the 10 Hz figure is much		Note that in this figure, the scalp maps are '''not''' normalized to each other; the red in the 10 Hz figure is much
	larger than the red in the other two figures. To compensate for this, find out what the maximum range is by		larger than the red in the other two figures. To compensate for this, find out what the maximum range is by
	clicking on the scalp map, which will open a new figure ~~(Figure 9). Press the Colorbar button (under the~~		clicking on the scalp map, which will open a new figure:
	~~Window and Help menus) to find out what the range is in this figure. It is about -25 to +25.~~

	[[Image:EEGLabImport9.PNG\|Spectral map for 10 Hz]]		[[Image:EEGLabImport9.PNG\|Spectral map for 10 Hz]]

			Press the Colorbar button (under the Window and Help menus) to find out what the range is in this figure (it is about -25 to +25).
	Now, go to Plot->Channel Spectra and Maps again, and enter the same options as before. Now, next to		Now, go to Plot->Channel Spectra and Maps again, and enter the same options as before. Now, next to
	‘electrodes’,’on’, add ‘maplimits’,[-25 25]:		‘electrodes’,’on’, add ‘maplimits’,[-25 25]: