<div dir="ltr">Hi Gustavo,<br><div class="gmail_extra"><br><div class="gmail_quote">2015-01-23 22:14 GMT+01:00 Gustavo Sudre <span dir="ltr"><<a href="mailto:gsudre@gmail.com" target="_blank">gsudre@gmail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Dennis,<div><br></div><div>If I understand you correctly, you suggested that we should not apply SSP projections to the data before ICA (i.e. fit ICA to data before projections) and, if necessary, apply it afterwards. Is that correct?</div><div><br></div></div></blockquote><div><br></div><div>I did not say it like that. I said there are clear trade-offs. If you can reject bad epochs, have many trials, and are studying averaged time-locked responses, there won't be too much to gain by using ICA. If you want to use as much as possible of your data, e.g. for single trial analysis or continous recordings, ICA can be a great.</div><div>Independently, empty room projections might improve ICA results by denoising inputs.</div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div></div><div>My question is actually about the CTF compensation. It looks like the compensators are applied to the data similarly to SSP operators, with a dot product as in Raw._read_segment. Would you then suggest that we should apply the compensators only after ICA as well? </div></div></blockquote><div><br></div><div>Good question, I think intuitiely I would fit the ICA on the compensated data. I don't think the results will look better on CTF raw data.</div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>If yes, is setting info.['comp'] to None the easiest way to do that, since comp=False is not as common as proj=False?</div><div><br></div></div></blockquote><div><br></div><div>I thiknk there's a misunderstanding. Proj=True makes sense if projs are empty room vectors, or SSS, or CTF compensation. ICA does not handle Gaussian noise.</div><div>You then need to make sure that you apply all projections (ICA is also just a projection) in the right order. But normally you'd never look at uncompenated data at any stage, would you?</div><div><br></div><div>Hope this helps,</div><div>Denis</div><div> </div><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div></div><div>Thanks a bunch!</div><span class="HOEnZb"><font color="#888888"><div><br></div><div>Gustavo</div><div> </div></font></span></div><div class="gmail_extra"><br><div class="gmail_quote"><div><div class="h5">On Mon, Nov 3, 2014 at 2:43 PM, Denis-Alexander Engemann <span dir="ltr"><<a href="mailto:denis.engemann@gmail.com" target="_blank">denis.engemann@gmail.com</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 dir="ltr">Hi Yuhan,<br><br>I include the mailing list in this part of our conversation because this might be interesting for other people as well.<br><br><br>2014-11-03 20:30 GMT+01:00 Chen, Yu-han <<a href="mailto:CHENY4@email.chop.edu" target="_blank">CHENY4@email.chop.edu</a>>:<br>><br>> Hi Dennis, <br>><br>> I (...) figured out that the SSP was turned on during epoching. Our original problem is that when we tried to epoch raw data, ICA cleaned data, ECG signal, the averaged ECG epoch is flat (zeros across the entire epoch). When we set proj = False for mne.Epoch, the problem is resolved. Is it true that by default, Epoch.py will set the SSP on? <br>><br><br>Yes, you need to take care of this. Anyways I'm surprised you're getting flat signals. What kind of SSPs did you include? <br> <br>><br>> The data I feed in is the Elekta data with maxfiltered tsss and movement correction applied. <br>><br><br>Normally you have SSPS included in the raws if you don't use maxfilter. But think there's no point in using those if you have maxfiltered your data.<br>If you aim to identify biological artifacts using ICA there is no point in having ECG/EOG projections.<br>When using maxfilter and ICA, you should not necessarily use SSP in addition.<br>FYI I'd recommend to look up the number of dimensions estimated by maxfilter from the log or recover it by estimating the rank of the data and using this as input to ICA(n_components).<br><br>HTH,<br>Denis<br><br>PS: what about the performance metric, still interested in contributing it? ;-)<br><br>> Thanks!<br>> Yuhan </div>
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