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getting_started:neuromag [2016/12/21 12:41] 134.151.16.108 [Frequently Asked Questions] |
getting_started:neuromag [2017/08/17 11:21] (current) 127.0.0.1 external edit |
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| * 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. | * 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. | ||
| - | ===== Frequently Asked Questions ===== | + | ===== Frequently Asked Questions ===== |
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| - | ---- | + | |
| - Can I do source reconstruction with combined planar and magnetometer channels? | - Can I do source reconstruction with combined planar and magnetometer channels? | ||
| *Yes, by specifying cfg.coilaccuracy=1 or 2 during ft_preprocessing | *Yes, by specifying cfg.coilaccuracy=1 or 2 during ft_preprocessing | ||
| - Can I do source reconstruction with combined MEG and EEG channels? | - Can I do source reconstruction with combined MEG and EEG channels? | ||
| * Almost! | * Almost! | ||
| - | - How can I visialize planar gradient data? | + | - How can I visualize planar gradient data? |
| *After combining, but also by pulling them apart in side-by-side layouts | *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 gradiomaters? | + | - 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 | * After combining, or using some smart (still to be defined) neighbourhood definition | ||
| - Can I do stats with clustering on combined planar and data? | - Can I do stats with clustering on combined planar and data? | ||
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| *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. | *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? | - Should I use or avoid using MaxFilter? | ||
| - | *It depends | + | *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 |
134.151.16.108
