[Eeglablist] running ICA

[karlo gonzales]

Dear Friends,

I faced a problem with running ICA, that required your expertise and guides. I am simply using:  EEG = pop_runica(EEG,'icatype','runica'); but it seems because of the nature of my data (rank , Gaussian, or ....), ICA algorithm needs to lower learning rate frequently after few steps (please see the below). size of my data is  >> size(EEG.data)       >> ans=  62   4820   159.            

- how do you check rank of your EEG data? (rank(EEG.data)  gives error for 3d matrix )
- what could be wrong here or what i need to check before running ICA?
- May i ask you  that how do you choose your ICA options (e.g., 'pca'  , 'extended1' or ...)?  

Many thanks,
Karlo 

 
 
Input data size [62,766380] = 62 channels, 766380 frames/nFinding 62 ICA components using logistic ICA.
Decomposing 199 frames per ICA weight ((3844)^2 = 766380 weights, Initial learning rate will be 0.001, block size 68.
Learning rate will be multiplied by 0.9 whenever angledelta >= 60 deg.
More than 32 channels: default stopping weight change 1E-7
Training will end when wchange < 1e-007 or after 512 steps.
Online bias adjustment will be used.
Removing mean of each channel ...
Final training data range: -456.566 to 562.934
Computing the sphering matrix...
Starting weights are the identity matrix ...
Sphering the data ...
Beginning ICA training ...
Lowering learning rate to 0.0009 and starting again.
step 1 - lrate 0.000900, wchange 141.51904569, angledelta  0.0 deg
Lowering learning rate to 0.00081 and starting again.
step 1 - lrate 0.000810, wchange 159.49273116, angledelta  0.0 deg
Lowering learning rate to 0.000729 and starting again.
step 1 - lrate 0.000729, wchange 143.22748820, angledelta  0.0 deg
Lowering learning rate to 0.0006561 and starting again.
step 1 - lrate 0.000656, wchange 136.88732118, angledelta  0.0 deg
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