<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">Thanks Denis.</div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Jul 31, 2019 at 12:09 PM Denis A. Engemann <<a href="mailto:denis-alexander.engemann@inria.fr" target="_blank">denis-alexander.engemann@inria.fr</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"> External Email - Use Caution <br>
<br>
Hi Vivek,<br>
<br>
No this is not convenient as the PSD function gives you a power spectrum and not a time course.<br>
<br>
You really want to use apply_inverse_epochs: <a href="https://mne.tools/dev/generated/mne.minimum_norm.apply_inverse_epochs.html#mne.minimum_norm.apply_inverse_epochs" rel="noreferrer" target="_blank">https://mne.tools/dev/generated/mne.minimum_norm.apply_inverse_epochs.html#mne.minimum_norm.apply_inverse_epochs</a><br>
<br>
We then compute the analytic signal <a href="https://en.wikipedia.org/wiki/Analytic_signal#Envelope_and_instantaneous_phase" rel="noreferrer" target="_blank">https://en.wikipedia.org/wiki/Analytic_signal#Envelope_and_instantaneous_phase</a> using the Hilbert transform.<br>
<br>
If you do not do that by hand, the envelope_correlation function will take care of it internally as in this example:<br>
<a href="https://mne.tools/dev/auto_examples/connectivity/plot_mne_inverse_envelope_correlation.html#sphx-glr-auto-examples-connectivity-plot-mne-inverse-envelope-correlation-py" rel="noreferrer" target="_blank">https://mne.tools/dev/auto_examples/connectivity/plot_mne_inverse_envelope_correlation.html#sphx-glr-auto-examples-connectivity-plot-mne-inverse-envelope-correlation-py</a><br>
<br>
Best regards,<br>
Denis<br>
<br>
> On Jul 31, 2019, at 8:24 AM, Vivek Sharma <<a href="mailto:vivek.sharma1510@gmail.com" target="_blank">vivek.sharma1510@gmail.com</a>> wrote:<br>
> <br>
> External Email - Use Caution <br>
> <br>
> <br>
> Hi,<br>
> Can we compute envelope correlation using source data obtained from using mne.minimum_norm.compute_source_psd function.<br>
> <br>
> On Tue, Jul 16, 2019 at 10:32 PM Vivek Sharma <<a href="mailto:vivek.sharma1510@gmail.com" target="_blank">vivek.sharma1510@gmail.com</a>> wrote:<br>
> I mean how can I have this.<br>
> If I have sources calculated using "<a href="https://martinos.org/mne/stable/auto_examples/datasets/plot_opm_rest_data.html#sphx-glr-auto-examples-datasets-plot-opm-rest-data-py" rel="noreferrer" target="_blank">https://martinos.org/mne/stable/auto_examples/datasets/plot_opm_rest_data.html#sphx-glr-auto-examples-datasets-plot-opm-rest-data-py</a>" this example. So how should I proceed to compute envelope correlation in this calculated source space.<br>
> <br>
> On Tue, Jul 16, 2019 at 9:47 PM Alexandre Gramfort <<a href="mailto:alexandre.gramfort@inria.fr" target="_blank">alexandre.gramfort@inria.fr</a>> wrote:<br>
> External Email - Use Caution <br>
> <br>
> then you have your answer. It is written:<br>
> <br>
> data: array_like, shape=(n_epochs, n_signals, n_times)<br>
> <br>
> so you miss one dimension<br>
> <br>
> A<br>
> <br>
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> <br>
> <br>
> -- <br>
> Vivek Sharma<br>
> <br>
> <br>
> -- <br>
> Vivek Sharma<br>
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</blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail-m_7267281975957124895gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><span style="font-size:12.8px">Vivek Sharma</span></div></div></div></div></div></div></div></div></div></div></div></div></div></div>