<p><span style="padding: 3px 10px; border-radius: 5px; color: #ffffff; font-weight: bold; display: inline-block; background-color: #ff0000;"> External Email - Use Caution </span></p><p></p><div dir="ltr"><div>Dear MNE users, <br></div><div>I am new to this field so I am sorry if the answer to my question is obvious.</div><div>I need to do a time-frequency analysis and I am following this tutorial <a href="https://mne.tools/dev/auto_examples/time_frequency/plot_source_label_time_frequency.html#sphx-glr-auto-examples-time-frequency-plot-source-label-time-frequency-py">https://mne.tools/dev/auto_examples/time_frequency/plot_source_label_time_frequency.html#sphx-glr-auto-examples-time-frequency-plot-source-label-time-frequency-py</a> as I am interested in obtaining this sort of maps in certain labels. However, the maps I am getting are definetely not normalized compared to the examples (see my examples attached - lower than 10Hz). <br></div><div>1. What might be the reason for this?Is there something special I need to do when computing inverse solution compared to typical evoked response analysis? (I include only noise covariance there)</div><div>2. What is the recommend parameter here for baseline_mode (percent, logration mean - is there any suggestion on what to use and when?)</div><div>3. In this tutorial and command source_induced_power, what is the method used? Is it Morlet / Multitaper or something else? I found no information on this in contrast to e.g. tfr_morlet commands used elsewhere?</div><div><br></div><div>Thank you in advance.</div><div>Sincerely yours,</div><div>Kirill Elin, PhD<br></div><div>
<pre><a href="https://mne.tools/dev/generated/mne.minimum_norm.source_induced_power.html#mne.minimum_norm.source_induced_power" title="mne.minimum_norm.source_induced_power" class="gmail-sphx-glr-backref-module-mne-minimum_norm gmail-sphx-glr-backref-type-py-function"><span class="gmail-n"><br></span></a></pre>
</div></div>