Pipeline for simultaneous EEG-fMRI recording - Revision history

Mateusz at 09:34, 10 March 2022

2022-03-10T09:34:04Z

Show changes

Mateusz: /* Pipeline overview */

2022-03-10T08:24:07Z

‎Pipeline overview

Harald: /* Good practice */

2021-05-04T14:21:36Z

‎Good practice

Harald: /* Final data processing */

2021-05-04T14:18:09Z

‎Final data processing

Harald: /* BCG artifact correction */

2021-05-04T14:09:22Z

‎BCG artifact correction

Harald: /* fMRI gradient removal */

2021-05-04T13:59:30Z

‎fMRI gradient removal

Mateusz at 10:14, 28 February 2020

2020-02-28T10:14:29Z

Mateusz at 09:33, 12 September 2019

2019-09-12T09:33:37Z

Jamie: /* fMRI gradient removal */

2019-04-08T10:29:44Z

‎fMRI gradient removal

Harald at 07:17, 28 May 2018

2018-05-28T07:17:45Z

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 ==Pipeline overview==
-The recommended pipeline of processing EEG data registered during fMRI session looks as follows:
+The recommended pipeline <ref>{{harvtxt|Rusiniak et al.|2022}}</ref> of processing EEG data registered during fMRI session looks as follows:
 [[File:EEG-fMRI pipeline.png]]

@@ Line 109: / Line 109: @@
 ==Good practice==
 Please keep in mind that simultaneous EEG-fMRI recording is a difficult yet powerful technique. The following rules could help one to perform a successful experiment:
-* Remember that proper '''EEG and MRI hardware clock syncrhonization''' is esential for fMRI gradient artifact removal. BESA Research internaly perform checks if the synchronizaiton is sufficient however it is user responsibility to maintain hardware configuraiton. Under any circumstances '''do not change EEG data sampling rate''' prior fMRI gradient removal procedure.
+* Remember that proper '''EEG and MRI hardware clock synchronization''' is essential for fMRI gradient artifact removal. BESA Research internally performs checks if the synchronization is sufficient however it is the user's responsibility to maintain the hardware configuration. Under any circumstances '''do not change EEG data sampling rate''' prior to the fMRI gradient removal procedure.
 * For an ERP experiment remember to introduce temporal '''jitter between trials''' (e.g. a random value in the range of ±200 ms). Also, applying a pure EEG or a pure fMRI paradigm will probably have the effect that one of the modalities will not show satisfying results. Proper paradigm preparation is essential for success. Some further guidelines can be found here: (Rusiniak et al., 2013a).
 * Inform your subject how important it is '''not to move'''.
 * Keep electrode to skin '''impedance as low as possible'''.
-* The EEG-fMRI recording session should be long enough to allow for proper artifact creation. Usually the experiment should '''last at least 6 minutes'''.
+* The EEG-fMRI recording session should be long enough to allow for appropriate artifact template creation. Usually the experiment should '''last at least 6 minutes'''.
 * At the same time try to '''limit the time of experiment to a minimum''' and preferably perform EEG-fMRI registration before other sequences to limit movement due to an inconvenient supine position.
-* From the standard position, move the '''subject about 4 cm towards caudal direction''' to reduce artifacts: The MRI laser crosshair should be not in the Nasion position but in the middle of forehead (Mullinger et al., 2011).
+* From the standard position, move the '''subject about 4 cm towards the caudal direction''' to reduce artifacts: The MRI laser crosshair should be not in the Nasion position but in the middle of the forehead (Mullinger et al., 2011).
 * Especially for the first few registrations '''repeat the experiment outside of the MR bore''' to compare results.
 ==References==
 * Abreu, R., Leal, A., Figueiredo, P., 2018. EEG-Informed fMRI: A Review of Data Analysis Methods. Front. Hum. Neurosci. 12, 29. https://doi.org/10.3389/fnhum.2018.00029

@@ Line 98: / Line 98: @@
 ==Final data processing==
-If you need you can perform also blink artifact correction using similar approach to the EKG reduction (but select only one component at the final stage, since it is very well established artifact).
+If needed you can also perform blink artifact correction using an approach similar to the EKG reduction (but select only one component at the final stage, since it is a very well-established artifact).
-Now you can proceed with further data processing. There are some minor differences in comparison with general BESA pipeline:
+Now you can proceed with further data processing. There are some minor differences in comparison with the general BESA pipeline:
-* if you want to perform averaging you will be similarly asked if you want to turn off artifact correction. Please do so, by pressing '''<span style="color:#3366ff;">Yes</span>''' button. The artifact correction should be turned on again just after averaging. When averaged file is open go to menu '''<span style="color:#3366ff;">Artifact/Load...</span>''' and select file with exact name of your data file but with extension <span style="color:#ff9c00;">.atf</span>. When artifact coefficient file is loaded go to menu '''<span style="color:#3366ff;">Artifact\Options</span>''' and change method of brain activity modeling to Surrogate. Please verify if selected number of artifact components used for reduction can be lowered.
+* if you want to perform averaging you will be similarly asked if you want to turn off artifact correction. Please do so, by pressing '''<span style="color:#3366ff;">Yes</span>''' button. The artifact correction should be turned on again just after averaging. When the averaged file is open go to menu '''<span style="color:#3366ff;">Artifact/Load...</span>''' and select the file with the exact name of your data file but with extension <span style="color:#ff9c00;">.atf</span>. Once the artifact coefficient file is loaded, go to menu '''<span style="color:#3366ff;">Artifact\Options</span>''' and change the method of brain activity modeling to ''Surrogate''. Please verify if the selected number of artifact components used for reduction can be lowered.
 * As you might noticed we recommend performing source localization while artifact correction is off, and load artifact coefficients directly to the source analysis module. For EEG-fMRI data however it is acceptable to use artifact corrected data as input to the source analysis module.
-* if you want to perform '''Time-domain beamformer''' accessed from ERP module (average tab) you will be prompted if artifact correction should be turned off. We recommend to perform beamformer with artifact correction off, but for EEG-fMRI data set please keep it on (press '''<span style="color:#3366ff;">No</span>''' button), since big BCG artifact will affect results.
+=== Source analysis (requires BESA Research Standard or higher ===
 ==Good practice==
 Please keep in mind that simultaneous EEG-fMRI recording is a difficult yet powerful technique. The following rules could help one to perform a successful experiment:

@@ Line 51: / Line 51: @@
 ==BCG artifact correction==
-First scroll through data and mark bad electrodes and bad blocks of data. Note that especially at the beginning of the recording there might be fragments of data still contaminated with fMRI gradient artifact, as shown below. It is correct behavior since MRI machine use so-called dummy scans that are not for data collection but magnetization stabilization. These volumes are also not usually bound with triggers in the data. If you use paradigm it should start after these scans. The most typical approach is to start stimuli presentation after fMRI session starts (experiment should be triggered by MRI scanner)
+First scroll through the data and mark bad electrodes and bad blocks of data. Note that especially at the beginning of the recording there might be fragments of data still contaminated with an fMRI gradient artifact, as shown below. This is the correct behavior since the MRI machine use so-called dummy scans that are not for data collection but intended for magnetization stabilization. These volumes are also not usually associated with triggers in the data. If you use a paradigm it should start after these scans. The most typical approach is to start stimuli presentation after the fMRI session starts (experiment should be triggered by MRI scanner).
 [[File:FMRI dummy.PNG|800px]]
 ===Recommendation for artifact template creation===
-For BCG artifact removal we recommend using PCA based template creation. ICA approach is a bit difficult for this matter since BCG artifact is a complex signal distortion (constituted usually from more than three components). Also the main assumption of ICA is violated - components are dependent. Keep in mind that BCG artifact is induced by, Hall effect, pulsating skin and head movement. All of described phenomena are related to the heart beat. On top of it the part related to the movement can consist of up to six components in the worst scenario (head movement and head rotation, both possible in three dimensions).
+For BCG artifact removal we recommend using the PCA based template creation. The ICA approach is a bit difficult for this matter since the BCG artifact is a complex signal distortion (constituted usually from more than three components). Also the main assumption of ICA is violated - components are dependent rather than independent. Keep in mind that the BCG artifact is induced by Hall effect, pulsating skin, and head movement. All of these phenomena are related to the heart beat. On top of that, the part related to movement can consist of up to six components in the worst scenario (head movement and head rotation, both possible in three dimensions).
-===How to create template===
+===How to create the template===
-Before attempting artifact creation, it is wise to set filtration to match artifact frequency. For BCG following filter settings should be sufficient:
+Before attempting to create the artifact template, it is wise to set a filter to match the artifact frequency. For BCG, the following filter settings should be sufficient:
 {| class="wikitable"
 ! style="font-weight: bold;" | Filter
@@ Line 77: / Line 77: @@
 |}
-Mark a block of data where BCG is clearly noticeable. you can either use EKG channel or just all channels as the BCG is very prominent (check example below). If you decide to use EKG channel rembmer that BCG artifact starts around 200-300 ms after QRS complex visible in EKG.
+Mark a block of data where BCG is clearly noticeable. You can either use an EKG channel or just all channels as the BCG is very prominent (check the example below). If you decide to use an EKG channel remember that the BCG artifact starts around 200-300 ms after the QRS complex visible in EKG.
 [[File:Fmri BCG.PNG|800px]]
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 Go to menu '''<span style="color:#3366ff;">Search</span>''' and verify if '''<span style="color:#3366ff;">Search, Average, View</span>''' option is checked. If not, please enable it.
-Press '''<span style="color:#3366ff;">SaV</span>''' button in toolbar to start creation of artifact template. In the displayed dialog use settings as below to perform searching for artifact occurrences similar to the selected block, using all channels with criterion for similarity of 65% correlation, after applying predefined filters. When you press OK search will start.
+Press the '''<span style="color:#3366ff;">SAV</span>''' button in the toolbar to start creation of the artifact template. In the displayed dialog use settings as below to perform searching for artifact occurrences similar to the selected block, using all channels with a criterion for similarity of 65% correlation, after applying predefined filters. When you press OK, the search will start.
 [[File:FMRI SaV.PNG]]
-When search is finished you will see averaged artifact in buffor on left side of the data window, as shown below. If you start scrolling through data the averaged block disappear. You can switch it on at anytime by menu '''<span style="color:#3366ff;">View/Averaged Buffers</span>'''. Note that you have blue vertical lines (if you selected to assign BCG artifacts to pattern 1) in trigger line at the bottom of screen. For good artifact correction they should cover almost whole file. Also at the bottom of averaged buffer you can see the number of averages (277 for example).  Make sure that this number is relatively big to be sure the artifact template is correctly created.
+When the search is finished you will see the averaged artifact in a buffer on the left side of the data window, as shown below. If you start scrolling through data the averaged block disappear. You can switch it on at any time using the menu entry '''<span style="color:#3366ff;">View/Averaged Buffers</span>'''. Note that you have blue vertical lines (if you selected to assign the BCG artifacts to pattern 1) in the event bar at the bottom of screen. For good artifact correction they should cover almost the whole file. Also, at the bottom of the averaged buffer display you can see the number of averages (277 for example).  Make sure that this number is relatively large to be sure the artifact template is correctly created.
 [[File:FMRI BCG averaged.PNG|800px]]
-===How to select proper number of components for artifact correction===
+===How to select the correct number of components for artifact correction===
-Finally click right mouse button over the averaged buffer and select '''<span style="color:#3366ff;">Whole Segment</span>'''. Click with right mouse button over yellow tinted area and select '''<span style="color:#3366ff;">Define Artifact Topography</span>'''. A new window will popup. Check EKG box and select number of components used for artifact correction. The component number is followed by the number how much signal variability is explained by the component, expressed in percentage. A question without answer is how many components should be reduced, since it really depends on the data. As a good starting point you may select all components that explain more than 1% of BCG variance (so basically select number  with variance lower than 1% - as in example below 5(0.68)). Note that data will be automatically updated to the current settings. You can adjust this number at any further stage of data processing.
+Finally click the right mouse button over the averaged buffer and select '''<span style="color:#3366ff;">Whole Segment</span>'''. Click again with the right mouse button over the yellow marked area and select '''<span style="color:#3366ff;">Define Artifact Topography</span>'''. A new dialog will pop up. Check the EKG box and select the number of components used for artifact correction. The component number is followed by a number indicating how much signal variability is explained by the component, expressed in percentage. A question without answer is how many components should be reduced, since it really depends on the data. As a good starting point you may select all components that explain more than 1% of the BCG variance (so basically select the first number with variance lower than 1% - as in the example below 5(0.68)). Note that data will be automatically updated to the current settings. You can adjust this number at any further stage of data processing.
 [[File:FMRI components.PNG]]

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 * fMRI trigger code - code in the EEG recording provided by MR scanner.
 * Delay between marker and start of volume acquisition - a delay between marker in EEG provided by MR scanner and real start of fMRI volume acquisition.  This value can be also used if sparse acquistion is used and scanning starts with some delays
-* Number of scans to skip - if dummy scans (MR volumes acquired to stabilize magnetization) have corresponding markers in EEG data adjust this value to match number of real volumes used for fMRI analysis.
+* Number of scans to skip - if dummy scans (MR volumes acquired to stabilize magnetization) have corresponding markers in EEG data adjust this value to match the number of real volumes used for fMRI analysis.
 * Realignment file - direct output file from first step of fMRI analysis (realignment). We support native realignment file as generated by SPM, FSL, AFNI and Brainvoyager.
 Other parameters should be carefully selected depending on the data:
-* Number of artifact occurrence averages - The default value is 16. That means that 8 preceding and 8 proceeding artifact occurrences are used to create averaged template. Note that if odd number is used (ie. 17) the signal from volume that is being currently corrected is also used for averaging. If a larger number is selected then the artifact is more stable and more differentiated from EEG data. However if there is a lot of movement during the recording session the artifact template will be incorrect. A smaller number of artifact occurrences for averaging or more advanced methods of artifact removal should be selected in such situation.
+* Number of artifact occurrence averages - The default value is 16. That means that 8 preceding and 8 proceeding artifact occurrences are used to create the averaged template. Note that if an odd number is used (ie. 17) the signal from the volume that is being currently corrected is also used for averaging. If a larger number is selected then the artifact is more stable and more differentiated from EEG data. However if there is a lot of movement during the recording session the artifact template will be incorrect. A smaller number of artifact occurrences for averaging or more advanced methods of artifact removal should be selected in such situations.
-* Movement threshold - this parameter is only used for two advanced methods: ''Allen et al. 2000 Modified'' and ''Mossmann et al. 2009''. When changing this value check how the template creation matrix looks. If you note that matrix is very segmented (as below) you might consider increasing the threshold value.
+* Movement threshold - this parameter is only used for two advanced methods: ''Allen et al. 2000 Modified'' and ''Moosmann et al. 2009''. When changing this value check how the template creation matrix looks. If you note that the matrix is highly segmented (as in the below example) you might consider increasing the threshold value.
 [[File:FMRI_distorted_matrix.PNG]]
-If you wish  you can downsample data and export file with fMRI artifact gradient removed after using aforementioned tool by pressing '''<span style="color:#3366ff;">WrS</span>''' button:
+If you wish you can downsample data and export file with fMRI artifact gradient removed after using the aforementioned tool by pressing the '''<span style="color:#3366ff;">WrS</span>''' button:
 [[file:FMRI export.PNG]]

← Older revision		Revision as of 10:14, 28 February 2020
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	* Rusiniak, M., Lewandowska, M., Wolak, T., Pluta, A., Milner, R., Ganc, M., Włodarczyk, A., Senderski, A., Śliwa, L., Skarżyński, H., 2013a. A modified oddball paradigm for investigation of neural correlates of attention: a simultaneous ERP–fMRI study. Magn. Reson. Mater. Phys. Biol. Med. 26, 511–526. https://doi.org/10.1007/s10334-013-0374-7		* Rusiniak, M., Lewandowska, M., Wolak, T., Pluta, A., Milner, R., Ganc, M., Włodarczyk, A., Senderski, A., Śliwa, L., Skarżyński, H., 2013a. A modified oddball paradigm for investigation of neural correlates of attention: a simultaneous ERP–fMRI study. Magn. Reson. Mater. Phys. Biol. Med. 26, 511–526. https://doi.org/10.1007/s10334-013-0374-7
	* Rusiniak, M., Wolak, T., Lewandowska, M., Cieśla, K., Skarzynski, H., 2013b. The relation between EPI sequence parameters and electroencephalographic data during simultaneus EEG-fMRI registration: an initial report., in: ESMRMB 2013 Congress, Book of Abstracts, Saturday. Presented at the ESMRMB, Springer, Toulouse, p. 661. https://doi.org/10.1007/s10334-013-0384-5		* Rusiniak, M., Wolak, T., Lewandowska, M., Cieśla, K., Skarzynski, H., 2013b. The relation between EPI sequence parameters and electroencephalographic data during simultaneus EEG-fMRI registration: an initial report., in: ESMRMB 2013 Congress, Book of Abstracts, Saturday. Presented at the ESMRMB, Springer, Toulouse, p. 661. https://doi.org/10.1007/s10334-013-0384-5
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		+
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		+	[[Category:ERP/ERF]] [[Category:Preprocessing]] [[Category:Source Analysis]] [[Category: MRI]]

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 * Abreu, R., Leal, A., Figueiredo, P., 2018. EEG-Informed fMRI: A Review of Data Analysis Methods. Front. Hum. Neurosci. 12, 29. https://doi.org/10.3389/fnhum.2018.00029
 * Allen, P.J., Josephs, O., Turner, R., 2000. A Method for Removing Imaging Artifact from Continuous EEG Recorded during Functional MRI. NeuroImage 12, 230–239. https://doi.org/10.1006/nimg.2000.0599
-* Moosmann, M., Schönfelder, V.H., Specht, K., Scheeringa, R., Nordby, H., Hugdahl, K., 2009. Realignment parameter-informed artefact correction for simultaneous EEG–fMRI recordings. NeuroImage 45, 1144–1150. https://doi.org/10.1016/j.neuroimage.2009.01.024BESA® Research 7.0
+* Moosmann, M., Schönfelder, V.H., Specht, K., Scheeringa, R., Nordby, H., Hugdahl, K., 2009. Realignment parameter-informed artefact correction for simultaneous EEG–fMRI recordings. NeuroImage 45, 1144–1150. https://doi.org/10.1016/j.neuroimage.2009.01.024
 * Mullinger, K.J., Yan, W.X., Bowtell, R., 2011. Reducing the gradient artefact in simultaneous EEG-fMRI by adjusting the subject’s axial position. NeuroImage 54, 1942–1950.
 * Rusiniak, M., Lewandowska, M., Wolak, T., Pluta, A., Milner, R., Ganc, M., Włodarczyk, A., Senderski, A., Śliwa, L., Skarżyński, H., 2013a. A modified oddball paradigm for investigation of neural correlates of attention: a simultaneous ERP–fMRI study. Magn. Reson. Mater. Phys. Biol. Med. 26, 511–526. https://doi.org/10.1007/s10334-013-0374-7
 * Rusiniak, M., Wolak, T., Lewandowska, M., Cieśla, K., Skarzynski, H., 2013b. The relation between EPI sequence parameters and electroencephalographic data during simultaneus EEG-fMRI registration: an initial report., in: ESMRMB 2013 Congress, Book of Abstracts, Saturday. Presented at the ESMRMB, Springer, Toulouse, p. 661. https://doi.org/10.1007/s10334-013-0384-5

@@ Line 11: / Line 11: @@
 * Be sure that you have jitter between trials in ERP experiment (i.e. random value of ±200ms). Some further guidelines about paradigm creation can be found here: (Rusiniak et al., 2013a).
 * Try to limit subject movement to minimum.
-* Make electrode to skin impedance is as low as possible.
+* Make sure electrode to skin impedance is as low as possible.
-* Design EEG-fMRI recording session to be long enough for proper artifact creation. Usually experiment should last at least 6 minutes.
+* Design EEG-fMRI recording session to be long enough for proper artifact creation. Usually the experiment should last at least 6 minutes.
-* Especially for first few registrations repeat the experiment outside of the bore to compare results.
+* Especially for the first few registrations repeat the experiment outside of the bore to compare results.
 ==Pipeline overview==
@@ Line 21: / Line 21: @@
 '''Please note that some steps are grouped with colors:'''
-* orange color indicate steps that are part of typical processing of ERP data.
+* orange color indicates steps that are part of typical processing of ERP data.
-* blue color indicate optional, yet strongly recommended EEG-MRI data co-registration.
+* blue color indicates optional, yet strongly recommended EEG-MRI data co-registration.
 * yellow color marks the steps related to fMRI gradient artifact removal
 * green steps are reserved for BCG (and blink) artifact correction
-* violet color indicate steps for time frequency analysis. Here also information about rejected epochs is provided for averaging purpose.
+* violet color indicates steps for time-frequency analysis. Here also information about rejected epochs is provided for averaging purpose.
 ==fMRI gradient removal==
-Please note that you need hardware clock synchronization between EEG equipment and MRI scanner before removing fMRI gradient artifact. Do not perform any sampling rate change (especially do not downsample data!) before performing this preprocessing step. Clock synchronization assures alignment between triggers present in EEG data and start of fMRI volume acquisition as well as consistent span between samples containing artifact. That mean that every epoch containing fMRI induced artifact is identical.
+Please note that you need hardware clock synchronization between EEG equipment and MRI scanner before removing fMRI gradient artifact. Do not perform any sampling rate change (especially do not downsample data!) before performing this preprocessing step. Clock synchronization assures alignment between triggers present in EEG data and start of fMRI volume acquisition as well as consistent span between samples containing artifact. That means that every epoch containing fMRI induced artifact is identical.
-To remove fMRI gradient select menu entry '''<span style="color:#3366ff;">Artifact\fMRI artifact...</span>'''. Following dialog box will appear:
+To remove fMRI gradient select the menu entry '''<span style="color:#3366ff;">Artifact\fMRI artifact...</span>'''. The following dialog box will appear:
 [[File:FMRI_dialogbox.PNG]]