<html><head><meta http-equiv="content-type" content="text/html; charset=utf-8"></head><body dir="auto"><div>Hi Elena,</div><div> The 'zlogratio' option may be somewhat informative as it gives you the z-score of the power relative to baseline (<span style="background-color: rgba(255, 255, 255, 0);">after converting to log scale) </span>where the baseline variance is estimated across the time samples in the baseline period (not across trials). </div><div><br></div><div>However, if you want a proper statistical analysis, it account for the topology of the time-frequency data (i.e., correct for multiple comparisons in a suitable way) and perhaps use the across trial variability information.. These are however, not implemented so far. </div><div><br></div><div>What kind of stats would be most useful?</div><div><br></div><div>Hari</div><div><br></div><div><br></div><div>Hari Bharadwaj<div>Research Fellow,</div><div>Martinos Center for Biomedical Imaging,</div><div>Massachusetts General Hospital</div><div>Charlestown, MA 02129</div><div><br></div><div><a href="mailto:hari@nmr.mgh.harvard.edu">hari@nmr.mgh.harvard.edu</a></div><div><a href="http://www.haribharadwaj.com">www.haribharadwaj.com</a></div><div>Ph: 734-883-5954</div></div><div><br>On Jul 16, 2015, at 9:29 AM, Elena Orekhova <<a href="mailto:orekhova.elena.v@gmail.com">orekhova.elena.v@gmail.com</a>> wrote:<br><br></div><blockquote type="cite"><div><div dir="ltr"><div><div><div>Alex, thank you for the explanation.<br><br></div>What would be the easiest way to know if the single subject power changes relative to the baseline are significant?<br></div>I used tfr_multitaper, but it only outputs the average, not the single trials.<br><br></div>Elena<br></div><div class="gmail_extra"><br><div class="gmail_quote">On 16 July 2015 at 14:58, Alexandre Gramfort <span dir="ltr"><<a href="mailto:alexandre.gramfort@telecom-paristech.fr" target="_blank">alexandre.gramfort@telecom-paristech.fr</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex">hi Elena,<br>
<br>
see:<br>
<br>
<a href="https://github.com/mne-tools/mne-python/blob/master/mne/baseline.py#L76" rel="noreferrer" target="_blank">https://github.com/mne-tools/mne-python/blob/master/mne/baseline.py#L76</a><br>
<br>
HTH<br>
Alex<br>
<div><div class="h5"><br>
On Thu, Jul 16, 2015 at 2:53 PM, Elena Orekhova<br>
<<a href="mailto:orekhova.elena.v@gmail.com">orekhova.elena.v@gmail.com</a>> wrote:<br>
> Hi,<br>
><br>
> I wonder how the 'logratio' option works for the power normalization?<br>
><br>
> Is it<br>
> 1. log10(signal/baseline)<br>
> 2. ln(signal/baseline)<br>
> or<br>
> 3. in dB?<br>
><br>
> Thanks,<br>
> Elena<br>
><br>
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