binica in fieldtrip

Christian Hesse c.hesse at FCDONDERS.RU.NL
Mon Feb 12 09:51:07 CET 2007

Hi Sameer,

when using any ICA algorithm in Fiieldtrip, you must, of course,
specify and pass the usual algorithm control parameters, since the
componentanalysis funcntion is only a wrapper.

As I mentioned in a previous email, you need to do model order
selection (i.e. choose the number of ICs) and often reduce the
dimension of your data (usually the same as the number of ICs). For
FastICA you probably also want to specify the nonlinearity and
whether the components are to be estimated one by one or all
together. Please see the relevant documentation in the FastICA Matlab

With the appropriate data dimension reduction, the performance of
FastICA (tanh nonlinearity and symmetric approach) and Infomax should
be essentially the same, so I suggest you pick whichever method you
can get to work. You may also want to try the JADE algorithm (fine if
you reduce data dimension).

Hope that helps,

On 9 Feb 2007, at 23:28, 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

Christian Hesse, PhD, MIEEE

F.C. Donders Centre for Cognitive Neuroimaging
P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Tel.: +31 (0)24 36 68293
Fax: +31 (0)24 36 10989

Email: c.hesse at

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