MatMef

Matlab wrapper for MEF 3.0 library

This project provides Matlab (mex) functions to read and write MEF 3.0 data using the MEF 3.0 library

Using pre-compiled mex files

1. Clone or download (and extract) the matmef repository
2. Use the functions (as illustrated in the examples below)

Building from source

1. Clone the matmef repository using: git clone https://github.com/MaxvandenBoom/matmef.git
2. Start matlab and set the matmef folder as your working directory

3. To compile the .mex files, run the following lines in matlab:

   • mex read_mef_session_metadata.c matmef_mapping.c mex_utils.c matmef_dataconverter.c
   • mex read_mef_ts_data.c matmef_read.c mex_utils.c matmef_dataconverter.c
   • mex init_mef_struct.c matmef_mapping.c mex_utils.c matmef_dataconverter.c
   • mex write_mef_segment_metadata.c matmef_write.c mex_utils.c matmef_utils.c matmef_mapping.c matmef_dataconverter.c
   • mex write_mef_ts_segment_data.c matmef_write.c mex_utils.c matmef_utils.c matmef_mapping.c matmef_dataconverter.c

Matlab usage examples

%  
% High-level  
%  

% metadata only  
[metadata] = readMef3('./mefSessionData/');

% two channels  
[metadata, signaldata] = readMef3('./mefSessionData/', [], {'Ch02', 'Ch07'});  

% all channels, samples 0-1000  
[metadata, signaldata] = readMef3('./mefSessionData/', [], [], 'samples', 0, 1000);  

% two channels, samples 0-1000  
[metadata, signaldata] = readMef3('./mefSessionData/', [], {'Ch02', 'Ch07'}, 'samples', 0, 1000);  

% all channels, multiple ranges/epochs
ranges = [[0,    1000]; ...
          [1000, 2000]; ...
          [5000, 6000]];
[metadata, signaldata] = readMef3('./mefSessionData/', [], [], 'samples', ranges);

%  
% Low-level  
%  

session = read_mef_session_metadata('./mefSessionData/', [], 1);  
data = read_mef_ts_data('./mefSessionData/channelPath/');  
data = read_mef_ts_data('./mefSessionData/channelPath/', [], 'samples', int64(0), int64(1000));
data = read_mef_ts_data('./mefSessionData/channelPath/', [], 'time', int64(1578715810000000), int64(1578715832000000));

Acknowledgements

• Written by Max van den Boom (Multimodal Neuroimaging Lab, Mayo Clinic, Rochester MN)

• Adapted from PyMef (by Jan Cimbalnik, Matt Stead, Ben Brinkmann, and Dan Crepeau)

• EEGLAB plugin code by Arnaud Delorme

• Contributors: Richard J. Cui, Dan Crepeau

• This project was funded by the National Institute Of Mental Health of the National Institutes of Health Award Number R01MH122258 to Dora Hermes