<html>
<head>
<meta content="text/html; charset=ISO-8859-1"
http-equiv="Content-Type">
</head>
<body bgcolor="#FFFFFF" text="#000000">
Hello all,<br>
<br>
We have perfomed some experiments on the necessary data lenght topic
for ICA. They are described in a paper we have presented at the
Biosignals 2012 conference a month ago (G. Korats et al, "Impact of
window length and decorrelation step on ICA algorithms for EEG blind
source separation"). <br>
<br>
Best,<br>
Radu<br>
<br>
On 18/03/2012 14:55, Scott Makeig wrote:
<blockquote
cite="mid:CAAHbppXjMSiQY5c7icAHrUtYpA+JwzoVXoYHcCviWuAaWivCSA@mail.gmail.com"
type="cite">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!).
<div>
<br>
</div>
<div>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.
<div>
<br>
</div>
<div>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.</div>
<div><br>
</div>
<div>Scott Makeig<br>
<br>
<div class="gmail_quote">On Sat, Mar 17, 2012 at 5:17 PM,
Tarik S Bel-Bahar <span dir="ltr"><<a
moz-do-not-send="true"
href="mailto:tarikbelbahar@gmail.com">tarikbelbahar@gmail.com</a>></span>
wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">
<div>1. not sure if you have to decimate, have seen some
people to do this to better meet requirements for good
ICA decompositions.</div>
<div>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".</div>
<div>3. quote from earlier eeglablist post: "<span>the key
factor is how much data you have (</span><span>timepoints</span><span> / </span><span>channels</span><span>^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)."</span></div>
<div><span>So if below this threshold there is some reason
for adding more time to the protocol, or reducing
channels, or decimation</span></div>
<br>
<br>
<br>
<div class="gmail_quote">
<div>
<div class="h5">On Tue, Mar 13, 2012 at 6:00 AM,
Modestino, Edward J *HS <span dir="ltr"><<a
moz-do-not-send="true"
href="mailto:EJM9F@hscmail.mcc.virginia.edu"
target="_blank">EJM9F@hscmail.mcc.virginia.edu</a>></span>
wrote:<br>
</div>
</div>
<blockquote class="gmail_quote" style="margin:0 0 0
.8ex;border-left:1px #ccc solid;padding-left:1ex">
<div>
<div class="h5">
<div link="blue" vlink="purple" lang="EN-US">
<div>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Dear
EEGLAB experts,</span></p>
<p class="MsoNormal">
<span style="font-family:"Times New
Roman","serif";color:#1f497d"> </span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">(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? <b>Does
one <u>NEED</u> to decimate the data
before running ICA?</b> For instance,
we have a data set recorded at 1,000 Hz.
Do we need to decimate this to
approximately 128 or 256?</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d"> </span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">(2
) According to the formula that Dr. Makeig
gave to determine the optimal amount of
data, <b>#timepoints/(#channels)^2</b>,
it would appear that a <b>higher sampling
rate will give better ICA results</b>.
Is this the case?</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d"> </span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">(3)
Finally, using this formula, <b>#timepoints/(#channels)^2</b>,
is there a <b>threshold or cutoff</b> 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.</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d"> </span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Thanks
for your help,</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Dr.
Modestino</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d"> </span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Edward
Justin Modestino, Ph.D.</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Postdoctoral
Research Associate</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Ray
Westphal Neuroimaging Laboratory</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Division
of Perceptual Studies</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Department
of Psychiatry and Neurobehavioral Sciences
</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">University
of Virginia</span></p>
<p class="MsoNormal"><span
style="font-family:"Times New
Roman","serif";color:#1f497d">Email:
<a moz-do-not-send="true"
href="mailto:ejm9f@virginia.edu"
target="_blank">ejm9f@virginia.edu</a></span></p>
<p class="MsoNormal">
<span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span></p>
<p class="MsoNormal"><span
style="font-size:11.0pt;font-family:"Calibri","sans-serif";color:#1f497d"> </span></p>
</div>
</div>
<br>
</div>
</div>
_______________________________________________<br>
Eeglablist page: <a moz-do-not-send="true"
href="http://sccn.ucsd.edu/eeglab/eeglabmail.html"
target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>
To unsubscribe, send an empty email to <a
moz-do-not-send="true"
href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu"
target="_blank">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>
For digest mode, send an email with the subject "set
digest mime" to <a moz-do-not-send="true"
href="mailto:eeglablist-request@sccn.ucsd.edu"
target="_blank">eeglablist-request@sccn.ucsd.edu</a><br>
</blockquote>
</div>
<br>
<br>
_______________________________________________<br>
Eeglablist page: <a moz-do-not-send="true"
href="http://sccn.ucsd.edu/eeglab/eeglabmail.html"
target="_blank">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a><br>
To unsubscribe, send an empty email to <a
moz-do-not-send="true"
href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu">eeglablist-unsubscribe@sccn.ucsd.edu</a><br>
For digest mode, send an email with the subject "set
digest mime" to <a moz-do-not-send="true"
href="mailto:eeglablist-request@sccn.ucsd.edu">eeglablist-request@sccn.ucsd.edu</a><br>
</blockquote>
</div>
<br>
<br clear="all">
<div><br>
</div>
-- <br>
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, <a
moz-do-not-send="true" href="http://sccn.ucsd.edu/%7Escott"
target="_blank">http://sccn.ucsd.edu/~scott</a><br>
</div>
</div>
<br>
<fieldset class="mimeAttachmentHeader"></fieldset>
<br>
<pre wrap="">_______________________________________________
Eeglablist page: <a class="moz-txt-link-freetext" href="http://sccn.ucsd.edu/eeglab/eeglabmail.html">http://sccn.ucsd.edu/eeglab/eeglabmail.html</a>
To unsubscribe, send an empty email to <a class="moz-txt-link-abbreviated" href="mailto:eeglablist-unsubscribe@sccn.ucsd.edu">eeglablist-unsubscribe@sccn.ucsd.edu</a>
For digest mode, send an email with the subject "set digest mime" to <a class="moz-txt-link-abbreviated" href="mailto:eeglablist-request@sccn.ucsd.edu">eeglablist-request@sccn.ucsd.edu</a></pre>
</blockquote>
</body>
</html>