FieldTrip - Revision history

Vahab: /* Preparing Anatomical and Spatial Information */

2022-09-19T16:16:08Z

Preparing Anatomical and Spatial Information

← Older revision		Revision as of 16:16, 19 September 2022
Line 76:		Line 76:
	=Source Analyses=		=Source Analyses=
	==Preparing Anatomical and Spatial Information==		==Preparing Anatomical and Spatial Information==
	ft_defaults		ft_defaults
	[mri] = ft_read_mri('MPRAGE.nii')		[mri] = ft_read_mri('MPRAGE.nii')

	=Common Issues=		=Common Issues=

Vahab: /* Preparing Anatomical and Spatial Information */

2022-09-19T16:15:56Z

Preparing Anatomical and Spatial Information

← Older revision		Revision as of 16:15, 19 September 2022
Line 76:		Line 76:
	=Source Analyses=		=Source Analyses=
	==Preparing Anatomical and Spatial Information==		==Preparing Anatomical and Spatial Information==
	# ft_defaults		ft_defaults
	# [mri] = ft_read_mri('MPRAGE.nii')		[mri] = ft_read_mri('MPRAGE.nii')

	=Common Issues=		=Common Issues=

Vahab: /* Within Subject Average */

2022-09-19T16:15:32Z

Within Subject Average

← Older revision		Revision as of 16:15, 19 September 2022
Line 55:		Line 55:

	===Within Subject Average ===		===Within Subject Average ===
	cfg = []		cfg = []
	cfg.channel = meg		cfg.channel = meg
	cfg.vartrllength = 1 % Accept variable length trials		cfg.vartrllength = 1 % Accept variable length trials
	tl_run1 = ft_timelockanalysis(cfg, run1.data_clean)		tl_run1 = ft_timelockanalysis(cfg, run1.data_clean)
	tl_run2 = ft_timelockanalysis(cfg, run2.data_clean)		tl_run2 = ft_timelockanalysis(cfg, run2.data_clean)
	cfg = []		cfg = []
	cfg.keepindividual = 'no'		cfg.keepindividual = 'no'
	cfg.channel = meg		cfg.channel = meg
	cfg.method = 'within'		cfg.method = 'within'
	cfg.parameter = 'avg'		cfg.parameter = 'avg'
	[tl_all] = ft_timelockgrandaverage(cfg, tl_run1, tl_run2)		[tl_all] = ft_timelockgrandaverage(cfg, tl_run1, tl_run2)

	===Plotting Averages ===		===Plotting Averages ===

Vahab: /* Within Subject Average */

2022-09-19T16:15:07Z

Within Subject Average

← Older revision		Revision as of 16:15, 19 September 2022
Line 55:		Line 55:

	===Within Subject Average ===		===Within Subject Average ===
	# cfg = []		cfg = []
	# cfg.channel = meg		cfg.channel = meg
	# cfg.vartrllength = 1 % Accept variable length trials		cfg.vartrllength = 1 % Accept variable length trials
	# tl_run1 = ft_timelockanalysis(cfg, run1.data_clean)		tl_run1 = ft_timelockanalysis(cfg, run1.data_clean)
	# tl_run2 = ft_timelockanalysis(cfg, run2.data_clean)		tl_run2 = ft_timelockanalysis(cfg, run2.data_clean)
	# cfg = []		cfg = []
	# cfg.keepindividual = 'no'		cfg.keepindividual = 'no'
	# cfg.channel = meg		cfg.channel = meg
	# cfg.method = 'within'		cfg.method = 'within'
	# cfg.parameter = 'avg'		cfg.parameter = 'avg'
	# [tl_all] = ft_timelockgrandaverage(cfg, tl_run1, tl_run2)		[tl_all] = ft_timelockgrandaverage(cfg, tl_run1, tl_run2)

	===Plotting Averages ===		===Plotting Averages ===

Vahab: /* Plotting Averages */

2022-09-19T16:14:28Z

Plotting Averages

← Older revision		Revision as of 16:14, 19 September 2022
Line 68:		Line 68:

	===Plotting Averages ===		===Plotting Averages ===
	# cfg = []		cfg = []
	# cfg.showoutline = 'yes'		cfg.showoutline = 'yes'
	# cfg.layout = 'neuromag306mag.lay'		cfg.layout = 'neuromag306mag.lay'
	# cfg.xlim = [0.0 0.5] You can edit the time window here		cfg.xlim = [0.0 0.5] You can edit the time window here
	# ft_multiplotER(cfg, tl_all)		ft_multiplotER(cfg, tl_all)


	=Source Analyses=		=Source Analyses=

Vahab: /* Importing Neuromag(.fif) in FieldTrip /

2022-09-19T16:13:22Z

Importing Neuromag(*.fif) in FieldTrip

← Older revision		Revision as of 16:13, 19 September 2022
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	=Importing Neuromag(*.fif) in FieldTrip=		=Importing Neuromag(*.fif) in FieldTrip=

	Fieldtrip can import neuromag data but there is a special way to do this. Follow the following commands to read and import your Neuromag306 data in ~~fieldtrip~~ and work on it as a ~~matlab~~ data structure.		Fieldtrip can import neuromag data but there is a special way to do this. Follow the following commands to read and import your Neuromag306 data in FieldTrip and work on it as a Matlab data structure.

	*hdr = ft_read_header('cu1_AudioRun1_raw.fif')		hdr = ft_read_header('cu1_AudioRun1_raw.fif')
	*dat = ft_read_data('cu1_AudioRun1_raw.fif')		dat = ft_read_data('cu1_AudioRun1_raw.fif')
	*Fevents = ft_read_event('cu1_AudioRun1_raw.fif')		Fevents = ft_read_event('cu1_AudioRun1_raw.fif')
	*cfg.headerfile = 'cu1_AudioRun1_raw.fif'		cfg.headerfile = 'cu1_AudioRun1_raw.fif'
	*cfg.inputfile = 'cu1_AudioRun1_raw.fif'		cfg.inputfile = 'cu1_AudioRun1_raw.fif'
	*cfg.dataset = 'cu1_AudioRun1_raw.fif'		cfg.dataset = 'cu1_AudioRun1_raw.fif'
	*cfg = ft_definetrial(cfg)		cfg = ft_definetrial(cfg)
	*To define the trials		To define the trials
	**F = []		F = []
	**[len, ~] = size(Fevents);		[len, ~] = size(Fevents);
	**for i = 1:len		for i = 1:len
	** %disp(Fevents(i).sample);		%disp(Fevents(i).sample);
	** F = [F, Fevents(i).sample];		F = [F, Fevents(i).sample];
	**end		end
	**F = F';		F = F';
	**endS = F(:,1);		endS = F(:,1);
	**begS = F(:,1);		begS = F(:,1);
	**endS = endS(2:len);		endS = endS(2:len);
	**begS = begS(1:len-1);		begS = begS(1:len-1);
	**offset = zeros(1,len-1)';		offset = zeros(1,len-1)';
	**samples = horzcat(begS, endS, offset)		samples = horzcat(begS, endS, offset)
	*cfg.trl = samples		cfg.trl = samples

	=Artifact Removal=		=Artifact Removal=

Colin: Created page with "=Introduction= FieldTrip is a Free and Open Source MATLAB based toolbox for MEEG analysis. It is developed by the Donders Institute for Brain, Cognition and Behaviour. Field..."

2019-05-24T20:09:28Z

Created page with "=Introduction= FieldTrip is a Free and Open Source MATLAB based toolbox for MEEG analysis. It is developed by the Donders Institute for Brain, Cognition and Behaviour. Field..."

New page

=Introduction=

FieldTrip is a Free and Open Source MATLAB based toolbox for MEEG analysis. It is developed by the Donders Institute for Brain, Cognition and Behaviour. FieldTrip can read and work with all commercial MEG data formats. It can do all parts of analyses, preprocessing, artifact removal, averaging, source analyses and much more.

=Importing Neuromag(*.fif) in FieldTrip=

Fieldtrip can import neuromag data but there is a special way to do this. Follow the following commands to read and import your Neuromag306 data in fieldtrip and work on it as a matlab data structure.

*hdr = ft_read_header('cu1_AudioRun1_raw.fif')
*dat = ft_read_data('cu1_AudioRun1_raw.fif')
*Fevents = ft_read_event('cu1_AudioRun1_raw.fif')
*cfg.headerfile = 'cu1_AudioRun1_raw.fif'
*cfg.inputfile = 'cu1_AudioRun1_raw.fif'
*cfg.dataset = 'cu1_AudioRun1_raw.fif'
*cfg = ft_definetrial(cfg)
*To define the trials
**F = []
**[len, ~] = size(Fevents);
**for i = 1:len
** %disp(Fevents(i).sample);
** F = [F, Fevents(i).sample];
**end
**F = F';
**endS = F(:,1);
**begS = F(:,1);
**endS = endS(2:len);
**begS = begS(1:len-1);
**offset = zeros(1,len-1)';
**samples = horzcat(begS, endS, offset)
*cfg.trl = samples

=Artifact Removal=
==ICA Artifact Removal==
See the [http://fieldtrip.fcdonders.nl/example/use_independent_component_analysis_ica_to_remove_ecg_artifacts ICA for ECG] page for information on how to apply ICA projection on your raw data to remove ECG - heart beat artifact.
<br> Useful mailists answers: http://mailman.science.ru.nl/pipermail/fieldtrip/2012-April/005011.html

=Converting FieldTrip to Neuromag Raw FIFF=
Once you are satisfied with the necessary data processing steps in the FieldTrip environment in MATLAB, you can write the raw data back to the Neuromag FIFF structure that can be read by mne.

== Steps to Follow ==
* Open Matlab
* Have the data struct ready after you are done with FT processing(eg: ft_preprocessing, ft_resampledata etc.,)
* ft_defaults
* fifffile = [pathstr filesep name '.fif'];
* data = ft_checkdata(data, 'datatype', {'raw', 'timelock'}, 'feedback', 'yes');
* info = data.hdr.orig;
* [outfid, cals] = fiff_start_writing_raw(fifffile, info);
* fiff_write_raw_buffer(outfid, data.trial, cals);
**NOTE that the channel data structures must match the buffer and the calibration struc obtained from the data.hdr struct
**Make sure you are writing all the trials into the raw fiff file. For this purpose, you can set one sample to hold the entire time period.
* fiff_finish_writing_raw(outfid);

=Time Lock analysis =
When you have pre-processed your data and have run the ICA analysis to clean the data you are now ready to proceed to the sensor level analysis. This is done by calling the ft_timelockanalysis and ft_timelockgrandaverage commands in FieldTrip. Follow the commands below for computing the average across runs within a subject and for computing the average of a run for a specified trial condition.

===Within Subject Average ===
# cfg = []
# cfg.channel = meg
# cfg.vartrllength = 1 % Accept variable length trials
# tl_run1 = ft_timelockanalysis(cfg, run1.data_clean)
# tl_run2 = ft_timelockanalysis(cfg, run2.data_clean)
# cfg = []
# cfg.keepindividual = 'no'
# cfg.channel = meg
# cfg.method = 'within'
# cfg.parameter = 'avg'
# [tl_all] = ft_timelockgrandaverage(cfg, tl_run1, tl_run2)

===Plotting Averages ===
# cfg = []
# cfg.showoutline = 'yes'
# cfg.layout = 'neuromag306mag.lay'
# cfg.xlim = [0.0 0.5] You can edit the time window here
# ft_multiplotER(cfg, tl_all)

=Source Analyses=
==Preparing Anatomical and Spatial Information==
# ft_defaults
# [mri] = ft_read_mri('MPRAGE.nii')

=Common Issues=
===1) ICA on Neuromag MEG: runica error===
Problem: surf, X, Y, Z, S cant be complex
<br>Solution: Do not include the Reference channel in the cfg or the other option is to specify the components to be 1 less than the number of channels you would like in the component analysis. Read the links below for more detailed info and for commands to included in your script.
<br>http://mailman.science.ru.nl/pipermail/fieldtrip/2013-October/007067.html
<br>http://fieldtrip.fcdonders.nl/faq/why_does_my_ica_output_contain_complex_numbers

===2) fiff_start_file: Permission denied===
See here: http://mailman.science.ru.nl/pipermail/fieldtrip/2014-March/007748.html

FieldTrip - Revision history

Vahab: /* Preparing Anatomical and Spatial Information */

Vahab: /* Preparing Anatomical and Spatial Information */

Vahab: /* Within Subject Average */

Vahab: /* Within Subject Average */

Vahab: /* Plotting Averages */

Vahab: /* Importing Neuromag(*.fif) in FieldTrip */

Colin: Created page with "=Introduction= FieldTrip is a Free and Open Source MATLAB based toolbox for MEEG analysis. It is developed by the Donders Institute for Brain, Cognition and Behaviour. Field..."

Vahab: /* Importing Neuromag(.fif) in FieldTrip /