[Eeglablist] Decimation prior to ICA and related things

[Scott Makeig]

The data_length/channels^2 = k > 30 heuristic was based on observing our
256-channel data decompositions. For fewer channels, I don't think this (k
> 30) may be necessary (though a small k will very likely prove a
problem!).

But for small numbers of channels, data length is not so much an obstacle
-- for example, decomposing 32 channels with k=30 would require only
30*32^2= 32K data points: At a sampling rate of (say) 256 Hz, this would be
~2 minutes of data. With 128 channels, the equivalent heuristic would be
~32 minutes.

I hope one of us will be able to do a proper study, decomposing data
subsets of various lengths and measuring mutual information reduction and
dipolarity (see Delorme et al., PLoS One 2012). Also, Jason Palmer has been
working on theoretic lower bounds on ICA accuracy at given data lengths and
channel numbers. I'll summarize result with him when possible.

Scott Makeig

On Sat, Mar 17, 2012 at 5:17 PM, Tarik S Bel-Bahar
<tarikbelbahar at gmail.com>wrote:

> 1. not sure if you have to decimate, have seen some people to do this to
> better meet requirements for good ICA decompositions.
> 2. don't think higher sampling rate will give you better ICA. I think it's
> more of a matter that ICA is fed data that gives an accurate and lengthy
> representation of the whole "Data space".
> 3. quote from earlier eeglablist post: "the key factor is how much data
> you have  (timepoints / channels^2). If this is > 30 (or near to it),
> then we find it preferable to return all possible components (since pca
> does a rather poor job of separating sources)."
> So if below this threshold there is some reason for adding more time to
> the protocol, or reducing channels, or  decimation
>
>
>
> On Tue, Mar 13, 2012 at 6:00 AM, Modestino, Edward J *HS <
> EJM9F at hscmail.mcc.virginia.edu> wrote:
>
>> Dear EEGLAB experts,****
>>
>> ** **
>>
>> (1) Is it true that  ICA must be subject, like all the model-based
>> spectral analysis methods, to a recommendation that one decimate to the
>> lowest frequency capable of representing the actual signal content of the
>> data without alienation effects?  *Does one NEED to decimate the data
>> before running ICA?*  For instance, we have a data set recorded at 1,000
>> Hz.  Do we need to decimate this to approximately 128 or 256?****
>>
>> ** **
>>
>> (2 ) According to the formula that Dr. Makeig gave to determine the
>> optimal amount of data,  *#timepoints/(#channels)^2*, it would appear
>> that a *higher sampling rate will give better ICA results*.  Is this the
>> case?****
>>
>> ** **
>>
>> (3) Finally, using this formula, *#timepoints/(#channels)^2*, is there a
>> *threshold or cutoff* one needs to be exceeded to have the optimal
>> amount of data to run ICA. Simply doing the equation without any way to
>> interpret the output is not helpful.****
>>
>> ** **
>>
>> Thanks for your help,****
>>
>> Dr. Modestino****
>>
>> ** **
>>
>> Edward Justin Modestino, Ph.D.****
>>
>> Postdoctoral Research Associate****
>>
>> Ray Westphal Neuroimaging Laboratory****
>>
>> Division of Perceptual Studies****
>>
>> Department of Psychiatry and Neurobehavioral Sciences ****
>>
>> University of Virginia****
>>
>> Email: ejm9f at virginia.edu****
>>
>> ** **
>>
>> ** **
>>
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>
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-- 
Scott Makeig, Research Scientist and Director, Swartz Center for
Computational Neuroscience, Institute for Neural Computation; Prof. of
Neurosciences (Adj.), University of California San Diego, La Jolla CA
92093-0559, http://sccn.ucsd.edu/~scott
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