Differences

This shows you the differences between two versions of the page.

--- getting_started:neuromag [2014/10/02 10:41]
62.159.73.150 [Special issues]
+++ getting_started:neuromag [2018/10/21 15:07]
42.49.180.224 [Introduction]
@@ Line 1: / Line 1: @@
 {{tag>elekta neuromag dataformat meg}}
-====== Getting started with Elekta-Neuromag data ======
+====== Getting started with Elekta/Neuromag data ======
 ===== Introduction =====
@@ Line 7: / Line 7: @@
 All data in Neuromag is stored in *.fif files, where the files can contain different data objects. The following data objects can be read and used in FieldTrip: MEG data, EEG data, gradiometer positions, single sphere models, BEM models (using the MEG-CALC toolbox). FieldTrip reads Neuromag fif files using low-level Matlab functions from the MNE toolbox from Matti Hamalainen, see [[http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/MNE_register/index.php|MNE software]]. This will work on any platform, as it is based on open-source m-files. To load the data into Matlab you need the MNE toolbox from Matti Hämäläinen, see [[http://www.nmr.mgh.harvard.edu/martinos/userInfo/data/MNE_register/index.php|MNE software]].
-Alternative support for Neuromag data is implemented by calling the mex files from [[http://www.kolumbus.fi/kuutela/programs/meg-pd/|Kimmo Uutela's MEG-PD toolbox]]. The files in the MEG-PD toolbox are not included with FieldTrip, but you can download them[[http://www.kolumbus.fi/kuutela/programs/meg-pd/|here]]. Extract the toolbox and put it on your matlab path, or copy the files into the "fieldtrip/private" directory. This is used if you select the file format as "neuromag_fif".
+Alternative support for Neuromag data is implemented by calling the mex files from [[http://www.kolumbus.fi/kuutela/programs/meg-pd/|Kimmo Uutela's MEG-PD toolbox]]. The files in the MEG-PD toolbox are not included with FieldTrip, but you can download them[[http://www.kolumbus.fi/kuutela/programs/meg-pd/|here]]. Extract the toolbox and put it on your matlab path, or copy the files into the &quot;fieldtrip/private&quot; directory. This is used if you select the file format as &quot;neuromag_fif&quot;.
-Note that the MEG-PD toolbox will only function on 32-bit machines, and requires either a Linux or HP-UX system to run. As the mex files are compiled code, it is not possible to modify these to run on 64-bit machines (which are becoming increasingly common), at present.
+Note that the MEG-PD toolbox will only function on 32-bit machines, and requires either a Linux or HP-UX system to run. As the mex files are compiled code, it is not possible to modify these to run on 64-bit machines (which are becoming increasingly common), at present.
 ===== Set Path =====
 \\
@@ Line 57: / Line 56: @@
 ===== Special issues =====
+  * if you have STI001 up to STI008, the TTL values (single bits) in those channels will be combined into an event of type 'Trigger' with an integer value between 0 and 255.
   * Reading .fif mri-data with fieldtrip and making a single shell headmodel (example script can be found [[example/read_neuromag_mri_and_create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space|here]]).
-Not yet documented or fixed but encountered:
+  * The default behavior of ft_read_event is that it assumes that event values below 5 are noise. However, in the new systems (Elekta Neuromag VectorView or Triux (306 channels both) this is seldom the case.
-  * read_trigger, this function assumes that event_values below 5 are noise. In the new system (Elekta Neuromag VectorView 306) this is seldom the case.
+===== Frequently Asked Questions =====
+\\
+    - Can I do source reconstruction with combined planar and magnetometer channels?
+        *Yes, by specifying cfg.coilaccuracy=1 or 2 during ft_preprocessing
+    - Can I do source reconstruction with combined MEG and EEG channels?
+        * Almost!
+    - How can I visualize planar gradient data?
+        *After combining, but also by pulling them apart in side-by-side layouts
+    - How can I do stats with clustering on data from the planar gradiometers?
+        * After combining, or using some smart (still to be defined) neighbourhood definition
+    - Can I do stats with clustering on combined planar and data?
+        *Yes, using two (non-neighbouring) concatenated neighbourhood definitions
+    - Can I combine multiple runs of an experiment (over multiple files)?
+       *Yes, by using ft_appenddata...but see next question
+    - How can I deal with rank-deficient maxfiltered data from multiple datasets/runs?
+        *After combining data from separate runs using ft_appenddata, you can run PCA using ft_componentanalysis followed by ft_rejectcomponent such that the rank of your covariance matrix is a number less than 64.
+    - Should I use or avoid using MaxFilter?
+        *It depends on several factors, including the level of noise in your recording, the presence of artefacts from outside the helmet and large amounts of head movement. Optimising source-localisation for Maxfiltered data is still under development. N.B. If you used Internal Active Shielding (IAS) running Maxfilter is obligatory