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John,<br class="">
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<div class="">The answer is 'yes'. </div>
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<div class="">For epoched data, EEG.data typically has shape [channel x sample x epoch], so, for epoch ‘e'</div>
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<div class=""><font face="Courier" class=""><span class="Apple-tab-span" style="white-space:pre"></span>EEG.icaact(:,:,e) = (EEG.icaweights*EEG.icasphere)*EEG.data(</font><span style="font-family: Courier;" class="">EEG.icachansind</span><span style="font-family: Courier;" class="">,:,e)</span></div>
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<div class="">The ICA solution does not vary with time, so the same unmixing solution is applied to every time point.</div>
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<div class="">If you want to get into it, look through e.g. eeg_checkset.m, which shows how EEG.data is reshaped into a 2-d matrix [channel x (samples*epochs)] for saving:</div>
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<span class="Apple-tab-span" style="white-space:pre"></span>reshape(EEG.data, EEG.nbchan, EEG.pnts*EEG.trials);</div>
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<div class="">and then when reloaded, ICA activations are recomputed on this 2-d matrix, and then put back into [channel x sample x epoch] shape:</div>
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<span class="Apple-tab-span" style="white-space:pre"></span>EEG.icaact = (EEG.icaweights*EEG.icasphere)*EEG.data(EEG.icachansind,:);
<span style="color: rgb(37, 153, 45);" class="">% automatically does single or double</span></div>
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<span class="Apple-tab-span" style="white-space:pre"></span>EEG.icaact = reshape( EEG.icaact, size(EEG.icaact,1), EEG.pnts, EEG.trials);</div>
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<div class="">John</div>
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<div style="orphans: 2; widows: 2;" class="">John R. Iversen, PhD</div>
<div style="orphans: 2; widows: 2;" class="">University of California, San Diego</div>
<div style="orphans: 2; widows: 2;" class="">Swartz Center for Computational Neuroscience</div>
<div style="orphans: 2; widows: 2;" class="">Institute for Neural Computation</div>
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<div style="orphans: auto; widows: auto;" class="">9500 Gilman Dr #0559</div>
<div style="orphans: auto; widows: auto;" class="">La Jolla, CA 92093</div>
<div style="orphans: auto; widows: auto;" class=""><a href="mailto:jiversen@ucsd.edu" class="">jiversen@ucsd.edu</a></div>
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<div class="">On Aug 1, 2018, at 9:18 AM, John Myers <<a href="mailto:john.myers@my.utsa.edu" class="">john.myers@my.utsa.edu</a>> wrote:</div>
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<div class="">Hello Everyone!</div>
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<div class="">I'm writing to ask how to generate ICA component activations (EEG.icaact) for single trials using the data structures in EEGLAB. </div>
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<div class="">I know that EEG.icaact = (EEG.icaweights*EEG.icasphere)*EEG.data. I'm wondering if this formula can be used to transform a single trial of EEG data into component activations. </div>
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<div class="">Concretely, my quesiton is, "C<span style="background-color: transparent; font-family: Arial; font-size: 11pt; white-space: pre-wrap;" class="">an I compute an IC activation for a single trial using the (EEG.icaweights*EEG.icasphere)*EEG.(single
trial data)? If not, how can I do this using EEGLAB's structures. </span></div>
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Best wishes,
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<div dir="ltr" class=""><span style="font-size:12.8px" class="">John Myers, M.S.</span>
<div style="font-size:12.8px" class="">PhD Student</div>
<div style="font-size:12.8px" class="">Cognitive Neuroscience Lab</div>
<div style="font-size:12.8px" class="">UTSA</div>
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