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Update TIPS_and_FAQ.md
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@@ -462,11 +462,33 @@ For multiple-epoch data, the scalp map obtained for the
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different epochs is the same for a particular component. Is this normal
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or is there some mistake that's being done in the analysis?
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**Answer:** Because the ICA algorithm is applied in the electrode space
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domain, the same scalp maps are returned for all epochs. However the
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domain, the same scalp maps are returned for all epochs. However, the
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time course of one ICA component is different for each epoch (if its
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activation value is 0 at a given time, it means that this component is
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not expressed in the data at that particular time).
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### ICA activity warning
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If you re-reference the data after running ICA, or if you remove channels, you might see the warning message:
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```
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ICA activity do not match ICA weights, see ...
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```
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As a rule of thumb, never perform a lossy re-referencing or channel
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removal after running ICA. Instead, remove the channel or re-reference the data, then run ICA again.
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When the data is referenced or if channels are removed, ICA scalp topographies are also referenced, and ICA activity remains unchanged.
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However, the ICA assumptions are broken. In other words, we no longer have ICA_activations = ICA_weights * EEG_data.
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Nevertheless, we believe this type of broken representation is the closest to the one available before re-referencing or removing
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channel(s). The alternative, which consists of recomputing activities, is not ideal because it is no longer an ICA decomposition.
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Importantly, if you save and reload the data, ICA activations are not saved by default, so EEGLAB will recompute them using
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ICA weights and data. This is no longer a standard ICA decomposition. If is important for you to retain the ICA activities, we
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advise that you save the data from the command line using
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```
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save('-mat', 'EEG_dataset_with_ica.set', '-struct', 'EEG');
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```
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Time Frequency
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--------------
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