#EROs, PLI, & DPLI Analyzer ##Authors:
- Vlastimil Koudelka
- Grygoriy Tsenov
This is for rodents, for human version switch to "human" branch, please.
This software is a result of the research funded by the project Nr. LO1611 with a financial support from the MEYS under the NPU I program.
##Experimental code for Event Related Oscillation detection. Developed software calculates advanced time-frequency quantities addressing evoked and induced EEG events. The software is designed to analyze both animal and human EEG data in order to provide translation between the observed phenomena. The analyzer is based on MATLAB platform and accepts LabChart and EDF data formats. More specifically, Event Related Oscillations are calculated to address induced oscillations. Phase Locking Index evaluates evoked oscillations over the trials and Phase Difference Locking Index measures functional connections between selected electrodes. The main outputs of the analyzer are the time-frequency characteristics of the quantities mentioned above.
##How to use EROS RODENTS
There are two executable scripts (in MATLAB) in repository:
EROS_RODENTS.m
and
PDLI_RODENTS.m
Both scripts accept .mat files structure exported by LabCart software. For EDF support, switch to the "human" branch.
####EROS_RODENTS.m
Calculates, visualizes, and stores Event Related Oscillations (ERO), Phase Locking Index (PLI), and Event Related Potential (ERP). Additional output is Averaged Event Related Oscillations (AVG_ERO), which is the ERO obtained from ERP.
####PDLI_RODENTS.m
Calculates, visualizes, and stores Phase Locking Index as a functional connectivity measure between electrodes. All combinations of electrodes are provided.
###Workflow
####Configure parallel computation: For optimal performance set a number of parallel workers: Prallel->Manage Cluster Profiles->Cluster Profile->Edit->NumWorkers
For older MATLAB versions execute "matlabpool open" before calculation.
####Open your dataset:
####Visualize:
####Store your results:
Output data from EROS_RODENTS.m is the following array of subjects:
subject(i)
ans =
n_ch: 2 %number of channels
chan_label: {{1x1 cell} {1x1 cell}} %channel names
f_name: 'P2_NT4T880 28MAY2014_2chan.mat' %source file
f_path: 'D:\Grisa\DPLI\' %source path
triggers: [320x3 double] %event list
ERO: {2x2 cell} %rows - channels
AVG_ERO: {2x2 cell} %columns - events
ERP: {2x2 cell} %(1,2,3...)
PLI: {2x2 cell} %according to event list
Output data from DPLI_RODENTS.m is the following array of subjects:
subject(1)
ans =
n_ch: 2
raw_data: {[1x5974400 double] [1x5974400 double]}
chan_label: {{1x1 cell} {1x1 cell}}
Fs_raw: 4000
f_name: 'P2_NT4T880 28MAY2014_2chan.mat'
f_path: 'D:\Grisa\DPLI\'
triggers: [320x2 double]
A_PDLI: {2x1 cell} %DPLI for event A
B_PDLI: {2x1 cell} %DPLI for event B
t: [1x326 double]
f: [1x92 double]