Some of the resources shared by the Simon Group:
Sqdproject
Description: Shantanu Ray's Matlab routines to read and write MEG160 files with demo file
New version:
README
gzip: sqdproject2.1.1beta.tar.gz
Windows: sqdproject2.1.1beta.exe
This is a beta version. So if you run into any errors, please let me know.
Old version:
gzip: Sqdproject.tar.gz
Windows: Sqdproject.exe
Nayef Ahmar's MEG code
sqd2mat.m - To port Squid files into Matlab
mat2sqd.m - To port Matlab files into Squid
adapt_noise_supp.m - Frequency domain least mean square method. Suppress environmental noise using 3 reference channels. Revised 12/05--do not use older versions.
adapt_noise_supp_mref.m - Frequency domain least mean square method. Suppress environmental and or artifact noise using any number of reference channels
FH_sig_tests.m - F and Hotelling's significance test
visual_filt_epoch_2s.m - Contrast raw and filtered data for one stimulus
Nayef Ahmar's adaptive filtering/noise suppression requires Sqdproject.
These functions read in a raw .sqd file and writes out a cleaned .sqd file. It is conceptually similar to MEG160's noise reduction ("CALM") but much more effective. The adaptive filtering method used is "Block LMS".
It takes some time to run, e.g. processing an 800 MB sqd file takes:
35 minutes on a 2.8 GHz Xeon with 2 GB RAM
45 minutes on a 1.5 GHz G4 with 2 GB RAM
2.5 hours on a 450 MHz Sun Ultra 10 with 1 GB RAM
Note that one of the input paramters trades memory use for time, so it will work with less memory but take more time (change it to a value smaller than the default of 1), if memory is an issue.
Yadong Wang's code
This set of codes will read data from sqd file directly (by sqdread)and perform noise reduction like CALM and output the epoch data according to triggers into MATLAB format.
The main file is: read_epochs_noise_reduction.m
Usage:
Read epochs from SQD file, given trigger, and epoch start and end time and perform multi-channel-noise-reduction.
It will generate two directories:
a. 'matdata' contains a set of matlab .mat file for each trigger. These are original data, without noise reduction
b. 'matdata_nr' contains one .mat file for each trigger, after noise reduction.
Other files:
find_trigger.m
multi_reference_adaptive_filter.m
optimum_noise_canceler_multi_ref.m
Huan Luo's code
readingMEGfile.m
writingMEGfile.m
Using readingMEG & WritingMEG instructions
wavelettransform.m
example.m