binica in fieldtrip

[Stefan Debener]

Dear Sameer,

Try running extended infomax ICA with the PCA option switched on and a
reduction to about 50 components. This should speed up the decomposition
substantially, and return nice eye blink components. If you do not get
dipolar-like component maps, your data may suffer from substantial head
movements. Temporal ICA expects that the sensors-to-source configuration
remains unchanged during recording.

I have not done systematic comparisons myself, but know from others that
fastICA is not necessarily that. It can be even slower that other ICA
algorithms...

Hope this helps,
Stefan


Sameer Walawalkar wrote:

> Hello,
>
> I am running componentanalysis.m within fieldtrip to do ICA in order
> to remove blinks etc. I tried using
>
> cfg.method = 'fastICA'
> cfg.trials = 1:100  (data has 306 channels)
>  but got failure to converge on 19th ica and analysis was aborted.
> Does anyone have any ideas about dealing with this?
>
> I also tried
> cfg.method = 'runica' cfg.trials = 1:100
>
> but it takes a very looooong time.
>
> Any ways around it? I know that one can implement binica in EEGLAB. It
> is supposed to be 12 xs faster and can use smaller memory.
>
> Can I implement cfg.method = 'binica'? in fieldtrip?
>
> thanks,
> sameer
>
>