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+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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diff --git a/dev/_modules/mne_connectivity/base.html b/dev/_modules/mne_connectivity/base.html
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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diff --git a/dev/_modules/mne_connectivity/effective.html b/dev/_modules/mne_connectivity/effective.html
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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diff --git a/dev/_modules/mne_connectivity/envelope.html b/dev/_modules/mne_connectivity/envelope.html
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
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+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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diff --git a/dev/auto_examples/dpli_wpli_pli.html b/dev/auto_examples/dpli_wpli_pli.html
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+++ b/dev/auto_examples/dpli_wpli_pli.html
@@ -2576,7 +2576,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
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@@ -2669,7 +2669,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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diff --git a/dev/auto_examples/dynamic/index.html b/dev/auto_examples/dynamic/index.html
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+++ b/dev/auto_examples/dynamic/index.html
@@ -509,7 +509,7 @@
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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diff --git a/dev/auto_examples/dynamic/mne_var_connectivity.html b/dev/auto_examples/dynamic/mne_var_connectivity.html
index 17ab47eb..b3f94830 100644
--- a/dev/auto_examples/dynamic/mne_var_connectivity.html
+++ b/dev/auto_examples/dynamic/mne_var_connectivity.html
@@ -501,117 +501,21 @@ <h2>Load the data<a class="headerlink" href="#load-the-data" title="Permalink to
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-Download complete in 15s (84.1 MB)
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 /home/circleci/project/examples/dynamic/mne_var_connectivity.py:42: FutureWarning: extension should start with a period &quot;.&quot;, but got: &quot;vhdr&quot;. Prepending &quot;.&quot; to form: &quot;.vhdr&quot;. This will raise an exception starting with MNE-BIDS 0.12.
   bids_path = BIDSPath(root=bids_root, subject=&#39;pt1&#39;, session=&#39;presurgery&#39;,
 /home/circleci/project/examples/dynamic/mne_var_connectivity.py:48: RuntimeWarning: The unit for channel(s) $G11, $G12, DC01, DC09, DC10, DC11, DC12, EKG1, EKG2 has changed from V to NA.
@@ -639,8 +543,8 @@ <h2>Load the data<a class="headerlink" href="#load-the-data" title="Permalink to
 - Upper transition bandwidth: 0.50 Hz (-6 dB cutoff frequency: 60.90 Hz)
 - Filter length: 6601 samples (6.601 s)
 
-[Parallel(n_jobs=1)]: Done  17 tasks      | elapsed:    0.1s
-[Parallel(n_jobs=1)]: Done  71 tasks      | elapsed:    0.6s
+[Parallel(n_jobs=1)]: Done  17 tasks      | elapsed:    0.2s
+[Parallel(n_jobs=1)]: Done  71 tasks      | elapsed:    0.7s
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 &lt;EpochConnectivity | n_epochs : 302, , nave : 302, nodes, n_estimated : 84, 7056, ~16.3 MB&gt;
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@@ -1211,7 +1118,7 @@ <h2>Evaluate the VAR model fit<a class="headerlink" href="#evaluate-the-var-mode
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 Using data from preloaded Raw for 302 events and 500 original time points ...
 
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@@ -1278,10 +1185,10 @@ <h2>Evaluate model fit again<a class="headerlink" href="#evaluate-model-fit-agai
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 Using data from preloaded Raw for 302 events and 500 original time points ...
 
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 <p><a class="reference download internal" download="" href="../../_downloads/42721ed4a42770a074be546dbbd7c6b1/mne_var_connectivity.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">mne_var_connectivity.ipynb</span></code></a></p>
@@ -1366,7 +1273,7 @@ <h2>Evaluate model fit again<a class="headerlink" href="#evaluate-model-fit-agai
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
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diff --git a/dev/auto_examples/dynamic/sg_execution_times.html b/dev/auto_examples/dynamic/sg_execution_times.html
index e5bf3507..f13e69d4 100644
--- a/dev/auto_examples/dynamic/sg_execution_times.html
+++ b/dev/auto_examples/dynamic/sg_execution_times.html
@@ -401,7 +401,7 @@
                   
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-dynamic-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1>
-<p><strong>00:59.424</strong> total execution time for 1 file <strong>from auto_examples/dynamic</strong>:</p>
+<p><strong>00:50.157</strong> total execution time for 1 file <strong>from auto_examples/dynamic</strong>:</p>
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 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="mne_var_connectivity.html#sphx-glr-auto-examples-dynamic-mne-var-connectivity-py"><span class="std std-ref">Compute vector autoregressive model (linear system)</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_var_connectivity.py</span></code>)</p></td>
-<td><p>00:59.424</p></td>
+<td><p>00:50.157</p></td>
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@@ -479,7 +479,7 @@
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/auto_examples/granger_causality.html b/dev/auto_examples/granger_causality.html
index 9462e43f..1b5e1eaa 100644
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+++ b/dev/auto_examples/granger_causality.html
@@ -568,66 +568,52 @@ <h2>Background<a class="headerlink" href="#background" title="Permalink to this
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 - Upper transition bandwidth: 0.50 Hz (-6 dB cutoff frequency: 50.88 Hz)
 - Filter length: 7921 samples (6.601 s)
 
-[Parallel(n_jobs=1)]: Done  17 tasks      | elapsed:    0.0s
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 [Connectivity computation done]
 Replacing existing metadata with 3 columns
 Connectivity computation...
@@ -967,11 +956,10 @@ <h2>Improving the robustness of connectivity estimates with time-reversal<a clas
 Computing GC time-reversed for connection 1 of 1
 
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 [Connectivity computation done]
 </pre></div>
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@@ -1064,34 +1052,34 @@ <h2>Controlling spectral smoothing with the number of lags<a class="headerlink"
 Computing GC for connection 1 of 1
 
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 [Connectivity computation done]
 
 Text(0.5, 0.98, &#39;GC: [A =&gt; B]&#39;)
@@ -1178,7 +1166,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
 </dd>
 </dl>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 20.736 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 19.132 seconds)</p>
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 <p><a class="reference download internal" download="" href="../_downloads/bc4fcabe78bb61cbb3c5dd027303b4da/granger_causality.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">granger_causality.ipynb</span></code></a></p>
@@ -1271,7 +1259,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/auto_examples/handling_ragged_arrays.html b/dev/auto_examples/handling_ragged_arrays.html
index 1aa247d1..5274d8ce 100644
--- a/dev/auto_examples/handling_ragged_arrays.html
+++ b/dev/auto_examples/handling_ragged_arrays.html
@@ -585,7 +585,7 @@ <h2>Background<a class="headerlink" href="#background" title="Permalink to this
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Assertions completed successfully!
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.473 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 0.373 seconds)</p>
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 <p><a class="reference download internal" download="" href="../_downloads/627c6a640d649eb934528032e8142ffb/handling_ragged_arrays.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">handling_ragged_arrays.ipynb</span></code></a></p>
@@ -673,7 +673,7 @@ <h2>Background<a class="headerlink" href="#background" title="Permalink to this
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/auto_examples/index.html b/dev/auto_examples/index.html
index 3af7eb36..8c5be51e 100644
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+++ b/dev/auto_examples/index.html
@@ -586,7 +586,7 @@ <h1>Dynamic Connectivity Examples<a class="headerlink" href="#dynamic-connectivi
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/auto_examples/mic_mim.html b/dev/auto_examples/mic_mim.html
index 2e75def2..9c8d588b 100644
--- a/dev/auto_examples/mic_mim.html
+++ b/dev/auto_examples/mic_mim.html
@@ -536,7 +536,7 @@ <h2>Background<a class="headerlink" href="#background" title="Permalink to this
 - Upper transition bandwidth: 0.50 Hz (-6 dB cutoff frequency: 50.88 Hz)
 - Filter length: 7921 samples (6.601 s)
 
-[Parallel(n_jobs=1)]: Done  17 tasks      | elapsed:    0.0s
+[Parallel(n_jobs=1)]: Done  17 tasks      | elapsed:    0.1s
 [Parallel(n_jobs=1)]: Done  71 tasks      | elapsed:    0.2s
 Not setting metadata
 30 matching events found
@@ -614,113 +614,113 @@ <h2>Background<a class="headerlink" href="#background" title="Permalink to this
 Computing MIC for connection 1 of 1
 
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 [Connectivity computation done]
 Replacing existing metadata with 3 columns
 Connectivity computation...
@@ -1050,52 +1050,56 @@ <h2>Handling high-dimensional data<a class="headerlink" href="#handling-high-dim
 Computing MIC for connection 1 of 1
 
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 Computing MIM for connection 1 of 1
 
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 [Connectivity computation done]
 </pre></div>
 </div>
@@ -1156,7 +1160,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
 </dd>
 </dl>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 35.493 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 37.640 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-mic-mim-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/799bb176de53e03eae2c7f13f6e52594/mic_mim.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">mic_mim.ipynb</span></code></a></p>
@@ -1249,7 +1253,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/auto_examples/mixed_source_space_connectivity.html b/dev/auto_examples/mixed_source_space_connectivity.html
index c8741c6c..847ceeb8 100644
--- a/dev/auto_examples/mixed_source_space_connectivity.html
+++ b/dev/auto_examples/mixed_source_space_connectivity.html
@@ -672,7 +672,7 @@
     Found 1275/2615 points outside using surface Qhull
     Found   97/1340 points outside using solid angles
     Total 1589/2961 points inside the surface
-Interior check completed in 1543.4 ms
+Interior check completed in 1651.9 ms
     1372 source space points omitted because they are outside the inner skull surface.
     283 source space points omitted because of the    5.0-mm distance limit.
 1306 sources remaining after excluding the sources outside the surface and less than    5.0 mm inside.
@@ -762,7 +762,7 @@
     Found    0/ 815 points outside using surface Qhull
     Found    0/ 815 points outside using solid angles
     Total 1026/1026 points inside the surface
-Interior check completed in 1160.4 ms
+Interior check completed in 1200.1 ms
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 Checking surface interior status for 1026 points...
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     Total 1026/1026 points inside the surface
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     84 source space point omitted because of the    5.0-mm distance limit.
 Checking surface interior status for 2 points...
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     Total 2/2 points inside the surface
-Interior check completed in 199.6 ms
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 Checking surface interior status for 9 points...
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     Found 0/0 points outside using solid angles
     Total 9/9 points inside the surface
-Interior check completed in 213.6 ms
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 Checking surface interior status for 33 points...
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     Found  0/32 points outside using solid angles
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-Interior check completed in 323.6 ms
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 Checking surface interior status for 21 points...
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     Found  0/13 points outside using solid angles
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 Checking surface interior status for 1 point ...
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 Checking surface interior status for 7 points...
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     Found 0/0 points outside using surface Qhull
     Found 0/0 points outside using solid angles
     Total 7/7 points inside the surface
-Interior check completed in 341.5 ms
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 Checking surface interior status for 44 points...
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     Found  0/43 points outside using solid angles
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 Checking surface interior status for 305 points...
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@@ -828,7 +828,7 @@
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     Found   0/  0 points outside using solid angles
     Total 0/305 points inside the surface
-Interior check completed in 335.2 ms
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 Composing the field computation matrix...
 Computing MEG at 2001 source locations (free orientations)...
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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--- a/dev/auto_examples/mne_inverse_coherence_epochs.html
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         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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diff --git a/dev/auto_examples/mne_inverse_envelope_correlation.html b/dev/auto_examples/mne_inverse_envelope_correlation.html
index 4c5bdf4d..7dcb1434 100644
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-Interior check completed in 2939.1 ms
+Interior check completed in 3209.8 ms
 Checking surface interior status for 4098 points...
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     Found    0/2863 points outside using solid angles
     Total 4098/4098 points inside the surface
-Interior check completed in 2897.9 ms
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 Checking surface interior status for 298 points...
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@@ -729,7 +729,7 @@ <h2>Compute the forward and inverse<a class="headerlink" href="#compute-the-forw
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     Found   0/  0 points outside using solid angles
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-Interior check completed in 198.6 ms
+Interior check completed in 217.4 ms
 
 Composing the field computation matrix...
 Computing MEG at 8196 source locations (free orientations)...
@@ -908,7 +908,7 @@ <h2>Do pairwise-orthogonalized envelope correlation<a class="headerlink" href="#
 
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         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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+++ b/dev/auto_examples/mne_inverse_envelope_correlation_volume.html
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     Found  761/1214 points outside using surface Qhull
     Found   30/ 453 points outside using solid angles
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-Interior check completed in 704.4 ms
+Interior check completed in 749.4 ms
     791 source space points omitted because they are outside the inner skull surface.
     94 source space points omitted because of the    5.0-mm distance limit.
 479 sources remaining after excluding the sources outside the surface and less than    5.0 mm inside.
@@ -766,7 +766,7 @@ <h2>Compute the forward and inverse<a class="headerlink" href="#compute-the-forw
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     Found   0/329 points outside using solid angles
     Total 479/479 points inside the surface
-Interior check completed in 610.2 ms
+Interior check completed in 689.2 ms
 
 Checking surface interior status for 298 points...
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@@ -774,7 +774,7 @@ <h2>Compute the forward and inverse<a class="headerlink" href="#compute-the-forw
     Found  15/ 15 points outside using surface Qhull
     Found   0/  0 points outside using solid angles
     Total 0/298 points inside the surface
-Interior check completed in 193.2 ms
+Interior check completed in 223.2 ms
 
 Composing the field computation matrix...
 Computing MEG at 479 source locations (free orientations)...
@@ -858,7 +858,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
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@@ -949,7 +949,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
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         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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@@ -849,7 +849,7 @@ <h2>References<a class="headerlink" href="#references" title="Permalink to this
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
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diff --git a/dev/auto_examples/sensor_connectivity.html b/dev/auto_examples/sensor_connectivity.html
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     assembling connectivity matrix
 [Connectivity computation done]
 
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@@ -679,7 +679,7 @@
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   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
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diff --git a/dev/auto_examples/sg_execution_times.html b/dev/auto_examples/sg_execution_times.html
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-<p><strong>04:01.923</strong> total execution time for 15 files <strong>from auto_examples</strong>:</p>
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 </thead>
 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="mne_inverse_envelope_correlation.html#sphx-glr-auto-examples-mne-inverse-envelope-correlation-py"><span class="std std-ref">Compute envelope correlations in source space</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_envelope_correlation.py</span></code>)</p></td>
-<td><p>00:47.029</p></td>
+<td><p>00:54.104</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="mic_mim.html#sphx-glr-auto-examples-mic-mim-py"><span class="std std-ref">Compute multivariate measures of the imaginary part of coherency</span></a> (<code class="docutils literal notranslate"><span class="pre">mic_mim.py</span></code>)</p></td>
-<td><p>00:35.493</p></td>
+<td><p>00:37.640</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="mne_inverse_envelope_correlation_volume.html#sphx-glr-auto-examples-mne-inverse-envelope-correlation-volume-py"><span class="std std-ref">Compute envelope correlations in volume source space</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_envelope_correlation_volume.py</span></code>)</p></td>
-<td><p>00:25.201</p></td>
+<td><p>00:32.233</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="connectivity_classes.html#sphx-glr-auto-examples-connectivity-classes-py"><span class="std std-ref">Using the connectivity classes</span></a> (<code class="docutils literal notranslate"><span class="pre">connectivity_classes.py</span></code>)</p></td>
-<td><p>00:20.813</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="compare_connectivity_over_time_over_trial.html#sphx-glr-auto-examples-compare-connectivity-over-time-over-trial-py"><span class="std std-ref">Comparing spectral connectivity computed over time or over trials</span></a> (<code class="docutils literal notranslate"><span class="pre">compare_connectivity_over_time_over_trial.py</span></code>)</p></td>
+<td><p>00:20.825</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="granger_causality.html#sphx-glr-auto-examples-granger-causality-py"><span class="std std-ref">Compute directionality of connectivity with multivariate Granger causality</span></a> (<code class="docutils literal notranslate"><span class="pre">granger_causality.py</span></code>)</p></td>
-<td><p>00:20.736</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="connectivity_classes.html#sphx-glr-auto-examples-connectivity-classes-py"><span class="std std-ref">Using the connectivity classes</span></a> (<code class="docutils literal notranslate"><span class="pre">connectivity_classes.py</span></code>)</p></td>
+<td><p>00:19.945</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="compare_connectivity_over_time_over_trial.html#sphx-glr-auto-examples-compare-connectivity-over-time-over-trial-py"><span class="std std-ref">Comparing spectral connectivity computed over time or over trials</span></a> (<code class="docutils literal notranslate"><span class="pre">compare_connectivity_over_time_over_trial.py</span></code>)</p></td>
-<td><p>00:19.062</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="granger_causality.html#sphx-glr-auto-examples-granger-causality-py"><span class="std std-ref">Compute directionality of connectivity with multivariate Granger causality</span></a> (<code class="docutils literal notranslate"><span class="pre">granger_causality.py</span></code>)</p></td>
+<td><p>00:19.132</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="mixed_source_space_connectivity.html#sphx-glr-auto-examples-mixed-source-space-connectivity-py"><span class="std std-ref">Compute mixed source space connectivity and visualize it using a circular graph</span></a> (<code class="docutils literal notranslate"><span class="pre">mixed_source_space_connectivity.py</span></code>)</p></td>
-<td><p>00:18.905</p></td>
+<td><p>00:17.1000</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="dpli_wpli_pli.html#sphx-glr-auto-examples-dpli-wpli-pli-py"><span class="std std-ref">Comparing PLI, wPLI, and dPLI</span></a> (<code class="docutils literal notranslate"><span class="pre">dpli_wpli_pli.py</span></code>)</p></td>
-<td><p>00:14.631</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="mne_inverse_psi_visual.html#sphx-glr-auto-examples-mne-inverse-psi-visual-py"><span class="std std-ref">Compute Phase Slope Index (PSI) in source space for a visual stimulus</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_psi_visual.py</span></code>)</p></td>
+<td><p>00:14.531</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="mne_inverse_psi_visual.html#sphx-glr-auto-examples-mne-inverse-psi-visual-py"><span class="std std-ref">Compute Phase Slope Index (PSI) in source space for a visual stimulus</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_psi_visual.py</span></code>)</p></td>
-<td><p>00:12.927</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="dpli_wpli_pli.html#sphx-glr-auto-examples-dpli-wpli-pli-py"><span class="std std-ref">Comparing PLI, wPLI, and dPLI</span></a> (<code class="docutils literal notranslate"><span class="pre">dpli_wpli_pli.py</span></code>)</p></td>
+<td><p>00:14.372</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="mne_inverse_coherence_epochs.html#sphx-glr-auto-examples-mne-inverse-coherence-epochs-py"><span class="std std-ref">Compute coherence in source space using a MNE inverse solution</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_coherence_epochs.py</span></code>)</p></td>
-<td><p>00:11.015</p></td>
+<td><p>00:12.429</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="mne_inverse_label_connectivity.html#sphx-glr-auto-examples-mne-inverse-label-connectivity-py"><span class="std std-ref">Compute source space connectivity and visualize it using a circular graph</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_label_connectivity.py</span></code>)</p></td>
-<td><p>00:06.678</p></td>
+<td><p>00:05.722</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="cwt_sensor_connectivity.html#sphx-glr-auto-examples-cwt-sensor-connectivity-py"><span class="std std-ref">Compute seed-based time-frequency connectivity in sensor space</span></a> (<code class="docutils literal notranslate"><span class="pre">cwt_sensor_connectivity.py</span></code>)</p></td>
-<td><p>00:04.236</p></td>
+<td><p>00:04.358</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="sensor_connectivity.html#sphx-glr-auto-examples-sensor-connectivity-py"><span class="std std-ref">Compute all-to-all connectivity in sensor space</span></a> (<code class="docutils literal notranslate"><span class="pre">sensor_connectivity.py</span></code>)</p></td>
-<td><p>00:02.372</p></td>
+<td><p>00:02.531</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="mne_inverse_connectivity_spectrum.html#sphx-glr-auto-examples-mne-inverse-connectivity-spectrum-py"><span class="std std-ref">Compute full spectrum source space connectivity between labels</span></a> (<code class="docutils literal notranslate"><span class="pre">mne_inverse_connectivity_spectrum.py</span></code>)</p></td>
-<td><p>00:02.350</p></td>
+<td><p>00:02.398</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="handling_ragged_arrays.html#sphx-glr-auto-examples-handling-ragged-arrays-py"><span class="std std-ref">Working with ragged indices for multivariate connectivity</span></a> (<code class="docutils literal notranslate"><span class="pre">handling_ragged_arrays.py</span></code>)</p></td>
-<td><p>00:00.473</p></td>
+<td><p>00:00.373</p></td>
 <td><p>0.0</p></td>
 </tr>
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diff --git a/dev/generated/mne_connectivity.Connectivity.html b/dev/generated/mne_connectivity.Connectivity.html
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diff --git a/dev/generated/mne_connectivity.EpochTemporalConnectivity.html b/dev/generated/mne_connectivity.EpochTemporalConnectivity.html
index 3611c777..c74bb2bc 100644
--- a/dev/generated/mne_connectivity.EpochTemporalConnectivity.html
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diff --git a/dev/generated/mne_connectivity.SpectralConnectivity.html b/dev/generated/mne_connectivity.SpectralConnectivity.html
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diff --git a/dev/generated/mne_connectivity.SpectroTemporalConnectivity.html b/dev/generated/mne_connectivity.SpectroTemporalConnectivity.html
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diff --git a/dev/generated/mne_connectivity.TemporalConnectivity.html b/dev/generated/mne_connectivity.TemporalConnectivity.html
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diff --git a/dev/generated/mne_connectivity.check_indices.html b/dev/generated/mne_connectivity.check_indices.html
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diff --git a/dev/generated/mne_connectivity.degree.html b/dev/generated/mne_connectivity.degree.html
index ead132f2..042e8d06 100644
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diff --git a/dev/generated/mne_connectivity.envelope_correlation.html b/dev/generated/mne_connectivity.envelope_correlation.html
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diff --git a/dev/generated/mne_connectivity.phase_slope_index.html b/dev/generated/mne_connectivity.phase_slope_index.html
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diff --git a/dev/generated/mne_connectivity.read_connectivity.html b/dev/generated/mne_connectivity.read_connectivity.html
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diff --git a/dev/generated/mne_connectivity.seed_target_indices.html b/dev/generated/mne_connectivity.seed_target_indices.html
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diff --git a/dev/generated/mne_connectivity.seed_target_multivariate_indices.html b/dev/generated/mne_connectivity.seed_target_multivariate_indices.html
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diff --git a/dev/generated/mne_connectivity.select_order.html b/dev/generated/mne_connectivity.select_order.html
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diff --git a/dev/generated/mne_connectivity.spectral_connectivity_epochs.html b/dev/generated/mne_connectivity.spectral_connectivity_epochs.html
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diff --git a/dev/generated/mne_connectivity.spectral_connectivity_time.html b/dev/generated/mne_connectivity.spectral_connectivity_time.html
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diff --git a/dev/generated/mne_connectivity.symmetric_orth.html b/dev/generated/mne_connectivity.symmetric_orth.html
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diff --git a/dev/generated/mne_connectivity.vector_auto_regression.html b/dev/generated/mne_connectivity.vector_auto_regression.html
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@@ -979,7 +979,7 @@ <h2 id="X">X</h2>
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"high": [1, 15, 39], "tempor": [1, 2, 8, 26, 28, 29, 39], "resolut": [1, 39], "often": [1, 4], "desir": [1, 8, 11, 13, 14, 15, 16, 17, 18], "where": [1, 3, 4, 8, 9, 11, 17, 29, 35, 36, 38, 39, 41, 48], "you": [1, 2, 8, 11, 12, 32, 39, 41, 45], "an": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 36, 38, 39, 41, 44], "effect": [1, 4, 21, 33, 39, 41], "occur": [1, 11], "approach": [1, 4, 8, 11, 41], "feasibl": 1, "singl": [1, 8, 9, 11, 13, 14, 17, 18, 38, 39, 41], "result": [1, 4, 8, 9, 11, 18, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 41], "error": [1, 8, 15, 16, 18, 37, 38, 39, 45], "On": [1, 8, 21], "other": [1, 2, 3, 4, 8, 11, 38, 39], "hand": [1, 2, 8], "determin": [1, 8, 11, 22, 23, 24, 25, 26, 27, 28, 29, 42], "experi": [1, 2, 4, 21, 41], "do": [1, 4, 6, 8, 12, 36, 48], "involv": [1, 9, 11], "exactli": [1, 48], "should": [1, 2, 4, 6, 8, 11, 12, 15, 16, 19, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 38, 39, 40, 41, 45], "emploi": [1, 12, 15, 16], "take": [1, 12, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 32, 42], "form": [1, 6, 8, 9, 11, 22, 23, 24, 25, 26, 27, 28, 29], "mai": [1, 4, 8, 11, 22, 23, 24, 25, 26, 27, 28, 29, 39, 42, 45], "consist": [1, 8, 11, 21, 38, 39], "separ": [1, 6, 8, 11, 29, 39, 41], "averag": [1, 2, 3, 4, 11, 12, 13, 14, 15, 16, 17, 18, 19, 38, 39, 41, 48], "To": [1, 4, 6, 8, 9, 11, 13, 22, 23, 24, 25, 26, 27, 28, 29, 39, 45], "illustr": [1, 4], "usag": [1, 18, 39, 41, 48], "them": [1, 6, 9, 15, 16], "case": [1, 4, 8, 11, 38, 39], "analyz": [1, 6], "visual": [1, 2, 3, 4, 6, 10, 13, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 33, 35, 38, 42, 43, 44, 46], "dataset": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41], "author": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "qianliang": [1, 47], "glia": 1, "dtu": 1, "dk": 1, "licens": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "bsd": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "3": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 35, 36, 38, 39, 41, 42, 45], "claus": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "import": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 45], "np": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 15, 17, 18, 22, 23, 24, 25, 26, 27, 28, 29, 33, 35, 36, 37, 38, 39, 41], "matplotlib": [1, 4, 6, 8, 11, 12, 14, 15, 17, 22, 23, 24, 25, 26, 27, 28, 29, 42, 43, 45], "pyplot": [1, 4, 6, 8, 11, 12, 14, 15, 17, 22, 23, 24, 25, 26, 27, 28, 29, 42], "plt": [1, 4, 6, 8, 11, 12, 14, 15, 17], "viz": [1, 12, 15, 17, 19, 22, 23, 24, 25, 26, 27, 28, 29, 47, 48], "plot_sensors_connect": [1, 19, 47], "sampl": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41], "rng": 1, "random": [1, 4, 9], "default_rng": 1, "1234": 1, "set": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 36, 39, 41, 42, 47], "seed": [1, 8, 9, 10, 11, 13, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 36, 38, 39, 46], "reproduc": 1, "print": [1, 2, 3, 6, 8, 9, 11, 13, 14, 17, 18, 19], "__doc__": [1, 3, 13, 14, 17, 18, 19], "repetit": 1, "let": 1, "gener": [1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 35, 36, 38, 40, 41, 42, 45], "some": [1, 2, 4, 6, 8, 9, 11, 14, 15, 16, 32, 38, 39, 48], "format": [1, 6, 22, 23, 24, 25, 26, 27, 28, 29], "epochsarrai": 1, "5": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 36, 38, 39, 42, 45], "just": [1, 2, 4, 9, 12, 19], "exact": [1, 4], "replic": 1, "first": [1, 4, 6, 9, 11, 13, 17, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 41], "collect": 1, "n_epoch": [1, 6, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 39, 40, 41], "number": [1, 2, 3, 4, 9, 11, 13, 15, 16, 17, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 36, 37, 38, 39, 40, 41, 43, 47], "n_channel": [1, 2, 4, 11, 12, 13, 19, 22, 23, 24, 25, 26, 27, 28, 29, 37, 43], "n_time": [1, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 37, 38, 39, 40, 41], "2000": [1, 6], "point": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41], "sfreq": [1, 2, 3, 4, 6, 9, 12, 13, 14, 15, 17, 18, 19, 33, 38, 39, 48], "250": [1, 4, 6], "freq": [1, 2, 3, 8, 9, 11, 13, 14, 17, 18, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39], "overwrit": 1, "rang": [1, 2, 3, 4, 11, 12, 13, 14, 17, 18, 19, 39], "0": [1, 2, 3, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 33, 35, 36, 38, 39, 41, 42, 45, 46], "ch_name": [1, 3, 6, 8, 11, 15, 16], "c3": 1, "cz": 1, "c4": 1, "three": [1, 4, 32], "info": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 38, 39, 41, 43], "create_info": 1, "ch_type": 1, "object": [1, 6, 9, 13, 14, 15, 17, 19, 32, 36, 38, 48], "data_epoch": 1, "plot": [1, 3, 4, 6, 8, 11, 12, 14, 15, 18, 22, 23, 24, 25, 26, 27, 28, 29, 42, 47], "scale": [1, 4, 12, 13, 14, 15, 16, 17, 18, 21, 32, 38], "75": [1, 2, 4, 6, 8, 11, 12, 15, 16], "Not": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "metadata": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 48], "match": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "found": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 36, 38, 39], "No": [1, 3, 6, 8, 11, 15, 16], "baselin": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "correct": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 38, 39, 40, 41], "appli": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 32, 39], "project": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 42], "item": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "activ": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 32, 39, 45], "qt": 1, "2d": [1, 22, 23, 24, 25, 26, 27, 28, 29, 40], "backend": [1, 19], "mne_qt_brows": 1, "_pg_figur": 1, "mneqtbrows": 1, "0x7fb07eb2d900": 1, "band": [1, 2, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 19, 21, 24, 25, 27, 28, 32, 33, 38, 39], "freq_band": 1, "theta": [1, 21], "4": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 35, 36, 37, 38, 39, 45], "8": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39, 42, 45], "alpha": [1, 2, 11, 12, 13, 17, 18, 21, 38, 39], "13": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39], "beta": [1, 11, 13, 15, 38, 39], "30": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 38, 39], "n_freq_band": 1, "len": [1, 3, 9, 11, 12, 17, 18, 33, 38, 39], "min_freq": 1, "min": [1, 15, 16], "max_freq": 1, "max": [1, 9, 11, 12, 15, 16, 18], "linspac": [1, 2, 4], "int": [1, 4, 22, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 43], "dictionari": [1, 2], "convert": [1, 13, 15], "tupl": [1, 9, 22, 23, 24, 25, 26, 27, 28, 29, 30, 33, 35, 36, 38, 39, 42], "fmin": [1, 2, 4, 8, 9, 11, 12, 13, 14, 17, 18, 19, 33, 38, 39], "f": [1, 4, 6, 8, 11, 13, 14, 15, 16, 21, 32], "fmax": [1, 2, 4, 8, 9, 11, 12, 13, 14, 17, 18, 19, 33, 38, 39], "try": [1, 8, 12], "connectivity_method": 1, "coh": [1, 13, 38, 39], "plv": [1, 38, 39], "n_con_method": 1, "pre": [1, 4], "allocat": 1, "memori": [1, 13, 17, 21, 33, 38, 39, 48], "matric": [1, 32, 41], "con_epochs_arrai": 1, "zero": [1, 4, 6, 8, 11, 12, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 39], "nan": [1, 9], "matrix": [1, 2, 4, 8, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 38, 39, 41, 42], "con_epoch": 1, "mode": [1, 2, 3, 4, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39, 41, 48], "cwt_morlet": [1, 2, 3, 33, 38, 39], "cwt_freq": [1, 2, 3, 33, 38, 39], "faverag": [1, 2, 4, 12, 13, 17, 19, 38, 39, 48], "true": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 39, 42, 48], "get": [1, 2, 4, 6, 8, 11, 12, 13, 17, 22, 23, 24, 25, 26, 27, 28, 29, 48], "c": [1, 4, 11, 17, 21, 38, 39, 45], "get_data": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 48], "output": [1, 2, 8, 12, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 32, 38, 39, 40, 41, 42, 44, 48], "dens": [1, 2, 4, 12, 14, 15, 17, 19, 22, 23, 24, 25, 26, 27, 28, 29], "home": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "circleci": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "py": [1, 2, 3, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 46], "842": 1, "runtimewarn": [1, 6], "were": [1, 8, 11, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 38], "annot": [1, 6, 12, 15, 17], "store": [1, 2, 9, 11, 22, 23, 24, 25, 26, 27, 28, 29, 36, 37, 39, 48], "good": [1, 6, 39, 41, 43], "7": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39, 41, 45], "996": [1, 4], "off": [1, 6, 12, 17, 22, 23, 24, 25, 26, 27, 28, 29, 42], "243": [1, 4, 6], "kb": [1, 6], "load": [1, 2, 3, 4, 8, 11, 12, 13, 14, 15, 16, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 48], "so": [1, 2, 3, 6, 8, 9, 11, 13, 15], "wa": [1, 4, 6, 8, 11, 12, 13, 17, 22, 23, 24, 25, 26, 27, 28, 29, 47], "modifi": 1, "add_annotations_to_metadata": 1, "onli": [1, 2, 4, 6, 8, 9, 11, 12, 13, 14, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 39, 40, 41, 42], "indic": [1, 2, 3, 4, 8, 10, 11, 12, 13, 14, 17, 18, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 35, 36, 38, 39, 42, 43, 46, 48], "lower": [1, 2, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 38, 39], "triangular": [1, 2, 4, 12, 14, 17, 19, 38, 39], "t": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 41, 48], "000": [1, 2, 4, 6, 8, 11, 12, 14, 15, 16, 17, 18, 19], "0hz": [1, 2, 3, 4, 8, 11], "17": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "2": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 38, 39, 41, 42, 45], "21": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 17, 18, 19], "69": [1, 4, 6, 8, 11, 15, 16, 48], "score": [1, 4, 8, 11, 12, 13, 17, 18, 19, 38, 39, 42], "cwt": [1, 2, 3], "spectra": [1, 2, 3, 8, 13, 33, 38], "metric": [1, 2, 3, 4, 8, 11, 12, 13, 14, 17, 18, 19], "cross": [1, 2, 3, 4, 8, 11, 12, 13, 14, 17, 18, 19, 21, 38, 39], "densiti": [1, 2, 3, 4, 8, 11, 12, 13, 14, 17, 18, 19, 21, 38, 39], "assembl": [1, 2, 4, 12, 14, 17, 19], "done": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 41], "As": [1, 4, 8, 9, 11], "previous": [1, 11], "mention": [1, 4], "can": [1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 17, 18, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 36, 38, 39, 41, 42, 43, 48], "here": [1, 2, 4, 6, 9, 11, 14, 15, 16, 17, 29, 47], "spectrotemporalconnect": [1, 33, 38, 48], "notic": [1, 8, 17], "instanc": [1, 4, 8, 11, 12, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 34, 38, 39, 42, 43], "spectralconnect": [1, 18, 33, 38, 39, 48], "doe": [1, 8, 9, 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our data": [[17, "load-our-data"]], "Compute inverse solutions and their connectivity": [[17, "compute-inverse-solutions-and-their-connectivity"]], "Make a connectivity plot": [[17, "make-a-connectivity-plot"]], "Make multiple connectivity plots in the same figure": [[17, "make-multiple-connectivity-plots-in-the-same-figure"]], "Compute Phase Slope Index (PSI) in source space for a visual stimulus": [[18, "compute-phase-slope-index-psi-in-source-space-for-a-visual-stimulus"]], "Compute all-to-all connectivity in sensor space": [[19, "compute-all-to-all-connectivity-in-sensor-space"]], "General bibliography": [[21, "general-bibliography"]], "mne_connectivity.Connectivity": [[22, "mne-connectivity-connectivity"]], "Examples using mne_connectivity.Connectivity": [[22, "examples-using-mne-connectivity-connectivity"]], "mne_connectivity.EpochConnectivity": [[23, "mne-connectivity-epochconnectivity"]], "mne_connectivity.EpochSpectralConnectivity": [[24, 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"mne_connectivity.seed_target_multivariate_indices": [[36, "mne-connectivity-seed-target-multivariate-indices"]], "mne_connectivity.select_order": [[37, "mne-connectivity-select-order"]], "mne_connectivity.spectral_connectivity_epochs": [[38, "mne-connectivity-spectral-connectivity-epochs"]], "Examples using mne_connectivity.spectral_connectivity_epochs": [[38, "examples-using-mne-connectivity-spectral-connectivity-epochs"]], "mne_connectivity.spectral_connectivity_time": [[39, "mne-connectivity-spectral-connectivity-time"]], "Examples using mne_connectivity.spectral_connectivity_time": [[39, "examples-using-mne-connectivity-spectral-connectivity-time"]], "mne_connectivity.symmetric_orth": [[40, "mne-connectivity-symmetric-orth"]], "Examples using mne_connectivity.symmetric_orth": [[40, "examples-using-mne-connectivity-symmetric-orth"]], "mne_connectivity.vector_auto_regression": [[41, "mne-connectivity-vector-auto-regression"]], "Examples using 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"enhancements"], [48, "enhancements"], [48, "id1"], [48, "id4"]], "Bug": [[47, "bug"], [48, "bug"], [48, "id2"], [48, "id5"]], "Authors": [[47, "authors"], [48, "authors"], [48, "id3"], [48, "id7"], [48, "id9"], [48, "id10"]], "What was new in previous releases?": [[48, "what-was-new-in-previous-releases"]], "Version 0.5 (2023-01-13)": [[48, "version-0-5-2023-01-13"]], "Version 0.4 (2022-10-05)": [[48, "version-0-4-2022-10-05"]], "Version 0.3 (2022-03-01)": [[48, "version-0-3-2022-03-01"]], "Version 0.2 (2021-09-07)": [[48, "version-0-2-2021-09-07"]], "Changelog": [[48, "changelog"]], "Version 0.1 (2021-06-25)": [[48, "version-0-1-2021-06-25"]], "Changes when mne-connectivity was part of MNE-Python": [[48, "changes-when-mne-connectivity-was-part-of-mne-python"]]}, "indexentries": {"mne_connectivity": [[0, "module-mne_connectivity"]], "module": [[0, "module-mne_connectivity"]], "connectivity (class in mne_connectivity)": [[22, "mne_connectivity.Connectivity"]], "append() 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\ No newline at end of file
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22, 23, 24, 25, 26, 27, 28, 29, 39, 41, 45, 47, 48], "choos": [1, 11, 39, 45], "crucial": [1, 8], "when": [1, 2, 4, 6, 8, 9, 11, 12, 17, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 39, 41, 42], "us": [1, 3, 4, 8, 9, 10, 11, 14, 15, 16, 18, 19, 20, 21, 23, 24, 25, 45, 46, 48], "li": [1, 2, 6, 21, 41, 47, 48], "experiment": [1, 2, 6], "setup": [1, 2, 3, 12, 19], "task": [1, 6, 8, 11, 15, 16], "If": [1, 12, 17, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 37, 38, 39, 40, 41, 42, 43, 45], "obtain": [1, 8, 17, 22, 23, 24, 25, 26, 27, 28, 29], "repeat": [1, 22, 23, 24, 25, 26, 27, 28, 29, 42], "event": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 45, 48], "erp": 1, "most": [1, 4, 12, 13, 14, 15, 17, 18], "like": [1, 6, 9, 11, 12, 30, 32, 35, 36, 38, 39], "correspond": [1, 2, 11, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39, 42, 48], "util": [1, 2, 39], "rest": [1, 4, 13, 15, 16, 21, 32], "state": [1, 8, 15, 16, 21, 32, 38, 39], "free": [1, 11, 12, 15, 16, 21, 38], "move": [1, 17, 48], "mirror": [1, 21], "game": [1, 21], "paradigm": [1, 21], "1": [1, 2, 3, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 45], "might": [1, 2, 6, 29], "better": 1, "suit": 1, "assumpt": [1, 6, 38, 39], "interpret": [1, 8, 11, 38, 39, 41, 43], "wai": [1, 2, 4, 8, 41], "slightli": 1, "thu": [1, 4, 6, 11, 32, 38, 39], "hypothes": 1, "being": [1, 8, 9, 11], "test": [1, 8, 21, 38, 39], "assum": [1, 11, 32, 38, 41], "have": [1, 2, 4, 6, 8, 9, 11, 13, 18, 29, 32, 35, 41, 48], "been": [1, 32, 35], "creat": [1, 2, 3, 4, 9, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 42, 45], "around": [1, 8, 11, 15, 22, 23, 24, 25, 26, 27, 28, 29, 42], "each": [1, 2, 4, 6, 9, 11, 12, 13, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 35, 36, 37, 38, 39, 41, 42, 48], "timepoint": [1, 8], "same": [1, 4, 6, 8, 11, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41, 48], "give": [1, 8, 11, 33, 45], "high": [1, 15, 39], "tempor": [1, 2, 8, 26, 28, 29, 39], "resolut": [1, 39], "often": [1, 4], "desir": [1, 8, 11, 13, 14, 15, 16, 17, 18], "where": [1, 3, 4, 8, 9, 11, 17, 29, 35, 36, 38, 39, 41, 48], "you": [1, 2, 8, 11, 12, 32, 39, 41, 45], "an": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 36, 38, 39, 41, 44], "effect": [1, 4, 21, 33, 39, 41], "occur": [1, 11], "approach": [1, 4, 8, 11, 41], "feasibl": 1, "singl": [1, 8, 9, 11, 13, 14, 17, 18, 38, 39, 41], "result": [1, 4, 8, 9, 11, 18, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 41], "error": [1, 8, 15, 16, 18, 37, 38, 39, 45], "On": [1, 8, 21], "other": [1, 2, 3, 4, 8, 11, 38, 39], "hand": [1, 2, 8], "determin": [1, 8, 11, 22, 23, 24, 25, 26, 27, 28, 29, 42], "experi": [1, 2, 4, 21, 41], "do": [1, 4, 6, 8, 12, 36, 48], "involv": [1, 9, 11], "exactli": [1, 48], "should": [1, 2, 4, 6, 8, 11, 12, 15, 16, 19, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 38, 39, 40, 41, 45], "emploi": [1, 12, 15, 16], "take": [1, 12, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 32, 42], "form": [1, 6, 8, 9, 11, 22, 23, 24, 25, 26, 27, 28, 29], "mai": [1, 4, 8, 11, 22, 23, 24, 25, 26, 27, 28, 29, 39, 42, 45], "consist": [1, 8, 11, 21, 38, 39], "separ": [1, 6, 8, 11, 29, 39, 41], "averag": [1, 2, 3, 4, 11, 12, 13, 14, 15, 16, 17, 18, 19, 38, 39, 41, 48], "To": [1, 4, 6, 8, 9, 11, 13, 22, 23, 24, 25, 26, 27, 28, 29, 39, 45], "illustr": [1, 4], "usag": [1, 18, 39, 41, 48], "them": [1, 6, 9, 15, 16], "case": [1, 4, 8, 11, 38, 39], "analyz": [1, 6], "visual": [1, 2, 3, 4, 6, 10, 13, 19, 20, 22, 23, 24, 25, 26, 27, 28, 29, 33, 35, 38, 42, 43, 44, 46], "dataset": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41], "author": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21], "qianliang": [1, 47], "glia": 1, "dtu": 1, "dk": 1, "licens": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "bsd": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "3": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 35, 36, 38, 39, 41, 42, 45], "claus": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "import": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 45], "np": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 15, 17, 18, 22, 23, 24, 25, 26, 27, 28, 29, 33, 35, 36, 37, 38, 39, 41], "matplotlib": [1, 4, 6, 8, 11, 12, 14, 15, 17, 22, 23, 24, 25, 26, 27, 28, 29, 42, 43, 45], "pyplot": [1, 4, 6, 8, 11, 12, 14, 15, 17, 22, 23, 24, 25, 26, 27, 28, 29, 42], "plt": [1, 4, 6, 8, 11, 12, 14, 15, 17], "viz": [1, 12, 15, 17, 19, 22, 23, 24, 25, 26, 27, 28, 29, 47, 48], "plot_sensors_connect": [1, 19, 47], "sampl": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41], "rng": 1, "random": [1, 4, 9], "default_rng": 1, "1234": 1, "set": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 36, 39, 41, 42, 47], "seed": [1, 8, 9, 10, 11, 13, 18, 20, 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 36, 38, 39, 46], "reproduc": 1, "print": [1, 2, 3, 6, 8, 9, 11, 13, 14, 17, 18, 19], "__doc__": [1, 3, 13, 14, 17, 18, 19], "repetit": 1, "let": 1, "gener": [1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 12, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 35, 36, 38, 40, 41, 42, 45], "some": [1, 2, 4, 6, 8, 9, 11, 14, 15, 16, 32, 38, 39, 48], "format": [1, 6, 22, 23, 24, 25, 26, 27, 28, 29], "epochsarrai": 1, "5": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 33, 36, 38, 39, 42, 45], "just": [1, 2, 4, 9, 12, 19], "exact": [1, 4], "replic": 1, "first": [1, 4, 6, 9, 11, 13, 17, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 41], "collect": 1, "n_epoch": [1, 6, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 39, 40, 41], "number": [1, 2, 3, 4, 9, 11, 13, 15, 16, 17, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 36, 37, 38, 39, 40, 41, 43, 47], "n_channel": [1, 2, 4, 11, 12, 13, 19, 22, 23, 24, 25, 26, 27, 28, 29, 37, 43], "n_time": [1, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 37, 38, 39, 40, 41], "2000": [1, 6], "point": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 24, 25, 26, 27, 28, 29, 33, 38, 39, 41], "sfreq": [1, 2, 3, 4, 6, 9, 12, 13, 14, 15, 17, 18, 19, 33, 38, 39, 48], "250": [1, 4, 6], "freq": [1, 2, 3, 8, 9, 11, 13, 14, 17, 18, 22, 23, 24, 25, 26, 27, 28, 29, 33, 38, 39], "overwrit": 1, "rang": [1, 2, 3, 4, 11, 12, 13, 14, 17, 18, 19, 39], "0": [1, 2, 3, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 33, 35, 36, 38, 39, 41, 42, 45, 46], "ch_name": [1, 3, 6, 8, 11, 15, 16], "c3": 1, "cz": 1, "c4": 1, "three": [1, 4, 32], "info": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 38, 39, 41, 43], "create_info": 1, "ch_type": 1, "object": [1, 6, 9, 13, 14, 15, 17, 19, 32, 36, 38, 48], "data_epoch": 1, "plot": [1, 3, 4, 6, 8, 11, 12, 14, 15, 18, 22, 23, 24, 25, 26, 27, 28, 29, 42, 47], "scale": [1, 4, 12, 13, 14, 15, 16, 17, 18, 21, 32, 38], "75": [1, 2, 4, 6, 8, 11, 12, 15, 16], "Not": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19], "metadata": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 48], "match": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "found": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 36, 38, 39], "No": [1, 3, 6, 8, 11, 15, 16], "baselin": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "correct": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 38, 39, 40, 41], "appli": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 32, 39], "project": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 42], "item": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "activ": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 32, 39, 45], "qt": 1, "2d": [1, 22, 23, 24, 25, 26, 27, 28, 29, 40], "backend": [1, 19], "mne_qt_brows": 1, "_pg_figur": 1, "mneqtbrows": 1, "0x7fe338a6d900": 1, "band": [1, 2, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 19, 21, 24, 25, 27, 28, 32, 33, 38, 39], "freq_band": 1, "theta": [1, 21], "4": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 35, 36, 37, 38, 39, 45], "8": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39, 42, 45], "alpha": [1, 2, 11, 12, 13, 17, 18, 21, 38, 39], "13": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39], "beta": [1, 11, 13, 15, 38, 39], "30": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 33, 38, 39], "n_freq_band": 1, "len": [1, 3, 9, 11, 12, 17, 18, 33, 38, 39], "min_freq": 1, "min": [1, 15, 16], "max_freq": 1, "max": [1, 9, 11, 12, 15, 16, 18], "linspac": [1, 2, 4], "int": [1, 4, 22, 23, 24, 25, 26, 27, 28, 29, 30, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 43], "dictionari": [1, 2], "convert": [1, 13, 15], "tupl": [1, 9, 22, 23, 24, 25, 26, 27, 28, 29, 30, 33, 35, 36, 38, 39, 42], "fmin": [1, 2, 4, 8, 9, 11, 12, 13, 14, 17, 18, 19, 33, 38, 39], "f": [1, 4, 6, 8, 11, 13, 14, 15, 16, 21, 32], "fmax": [1, 2, 4, 8, 9, 11, 12, 13, 14, 17, 18, 19, 33, 38, 39], "try": [1, 8, 12], "connectivity_method": 1, "coh": [1, 13, 38, 39], "plv": [1, 38, 39], "n_con_method": 1, "pre": [1, 4], "allocat": 1, "memori": [1, 13, 17, 21, 33, 38, 39, 48], "matric": [1, 32, 41], "con_epochs_arrai": 1, "zero": [1, 4, 6, 8, 11, 12, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 39], "nan": [1, 9], "matrix": [1, 2, 4, 8, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 31, 32, 38, 39, 41, 42], "con_epoch": 1, "mode": [1, 2, 3, 4, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39, 41, 48], "cwt_morlet": [1, 2, 3, 33, 38, 39], "cwt_freq": [1, 2, 3, 33, 38, 39], "faverag": [1, 2, 4, 12, 13, 17, 19, 38, 39, 48], "true": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 38, 39, 42, 48], "get": [1, 2, 4, 6, 8, 11, 12, 13, 17, 22, 23, 24, 25, 26, 27, 28, 29, 48], "c": [1, 4, 11, 17, 21, 38, 39, 45], "get_data": [1, 2, 3, 4, 6, 8, 9, 11, 12, 13, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 38, 39, 48], "output": [1, 2, 8, 12, 14, 15, 17, 18, 19, 22, 23, 24, 25, 26, 27, 28, 29, 32, 38, 39, 40, 41, 42, 44, 48], "dens": [1, 2, 4, 12, 14, 15, 17, 19, 22, 23, 24, 25, 26, 27, 28, 29], "home": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "circleci": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19], "py": [1, 2, 3, 4, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 46], "842": 1, "runtimewarn": [1, 6], "were": [1, 8, 11, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 38], "annot": [1, 6, 12, 15, 17], "store": [1, 2, 9, 11, 22, 23, 24, 25, 26, 27, 28, 29, 36, 37, 39, 48], "good": [1, 6, 39, 41, 43], "7": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21, 33, 38, 39, 41, 45], "996": [1, 4], "off": [1, 6, 12, 17, 22, 23, 24, 25, 26, 27, 28, 29, 42], "243": [1, 4, 6], "kb": 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29, 30, 31, 32, 33, 35, 36, 38, 39, 41, 42, 45], "21": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 17, 18, 19], "69": [1, 4, 6, 8, 11, 15, 16, 48], "score": [1, 4, 8, 11, 12, 13, 17, 18, 19, 38, 39, 42], "cwt": [1, 2, 3], "spectra": [1, 2, 3, 8, 13, 33, 38], "metric": [1, 2, 3, 4, 8, 11, 12, 13, 14, 17, 18, 19], "cross": [1, 2, 3, 4, 8, 11, 12, 13, 14, 17, 18, 19, 21, 38, 39], "densiti": [1, 2, 3, 4, 8, 11, 12, 13, 14, 17, 18, 19, 21, 38, 39], "assembl": [1, 2, 4, 12, 14, 17, 19], "done": [1, 2, 3, 4, 6, 8, 11, 12, 13, 14, 15, 16, 17, 18, 19, 41], "As": [1, 4, 8, 9, 11], "previous": [1, 11], "mention": [1, 4], "can": [1, 2, 3, 4, 5, 6, 8, 9, 10, 11, 13, 17, 18, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 36, 38, 39, 41, 42, 43, 48], "here": [1, 2, 4, 6, 9, 11, 14, 15, 16, 17, 29, 47], "spectrotemporalconnect": [1, 33, 38, 48], "notic": [1, 8, 17], "instanc": [1, 4, 8, 11, 12, 15, 16, 22, 23, 24, 25, 26, 27, 28, 29, 32, 33, 34, 38, 39, 42, 43], "spectralconnect": [1, 18, 33, 38, 39, 48], "doe": [1, 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[[15, "compute-envelope-correlations-in-source-space"]], "Compute the forward and inverse": [[15, "compute-the-forward-and-inverse"], [16, "compute-the-forward-and-inverse"]], "Do pairwise-orthogonalized envelope correlation": [[15, "do-pairwise-orthogonalized-envelope-correlation"]], "Do symmetric-orthogonalized envelope correlation": [[15, "do-symmetric-orthogonalized-envelope-correlation"]], "Compute envelope correlations in volume source space": [[16, "compute-envelope-correlations-in-volume-source-space"]], "Compute label time series and do envelope correlation": [[16, "compute-label-time-series-and-do-envelope-correlation"]], "Compute the degree and plot it": [[16, "compute-the-degree-and-plot-it"]], "Compute source space connectivity and visualize it using a circular graph": [[17, "compute-source-space-connectivity-and-visualize-it-using-a-circular-graph"]], "Load our data": [[17, "load-our-data"]], "Compute inverse solutions and their connectivity": [[17, "compute-inverse-solutions-and-their-connectivity"]], "Make a connectivity plot": [[17, "make-a-connectivity-plot"]], "Make multiple connectivity plots in the same figure": [[17, "make-multiple-connectivity-plots-in-the-same-figure"]], "Compute Phase Slope Index (PSI) in source space for a visual stimulus": [[18, "compute-phase-slope-index-psi-in-source-space-for-a-visual-stimulus"]], "Compute all-to-all connectivity in sensor space": [[19, "compute-all-to-all-connectivity-in-sensor-space"]], "General bibliography": [[21, "general-bibliography"]], "mne_connectivity.Connectivity": [[22, "mne-connectivity-connectivity"]], "Examples using mne_connectivity.Connectivity": [[22, "examples-using-mne-connectivity-connectivity"]], "mne_connectivity.EpochConnectivity": [[23, "mne-connectivity-epochconnectivity"]], "mne_connectivity.EpochSpectralConnectivity": [[24, "mne-connectivity-epochspectralconnectivity"]], "mne_connectivity.EpochSpectroTemporalConnectivity": [[25, "mne-connectivity-epochspectrotemporalconnectivity"]], "mne_connectivity.EpochTemporalConnectivity": [[26, "mne-connectivity-epochtemporalconnectivity"]], "Examples using mne_connectivity.EpochTemporalConnectivity": [[26, "examples-using-mne-connectivity-epochtemporalconnectivity"]], "mne_connectivity.SpectralConnectivity": [[27, "mne-connectivity-spectralconnectivity"]], "Examples using mne_connectivity.SpectralConnectivity": [[27, "examples-using-mne-connectivity-spectralconnectivity"]], "mne_connectivity.SpectroTemporalConnectivity": [[28, "mne-connectivity-spectrotemporalconnectivity"]], "Examples using mne_connectivity.SpectroTemporalConnectivity": [[28, "examples-using-mne-connectivity-spectrotemporalconnectivity"]], "mne_connectivity.TemporalConnectivity": [[29, "mne-connectivity-temporalconnectivity"]], "Examples using mne_connectivity.TemporalConnectivity": [[29, "examples-using-mne-connectivity-temporalconnectivity"]], "mne_connectivity.check_indices": [[30, "mne-connectivity-check-indices"]], "mne_connectivity.degree": [[31, "mne-connectivity-degree"]], "Examples using mne_connectivity.degree": [[31, "examples-using-mne-connectivity-degree"]], "mne_connectivity.envelope_correlation": [[32, "mne-connectivity-envelope-correlation"]], "Examples using mne_connectivity.envelope_correlation": [[32, "examples-using-mne-connectivity-envelope-correlation"]], "mne_connectivity.phase_slope_index": [[33, "mne-connectivity-phase-slope-index"]], "Examples using mne_connectivity.phase_slope_index": [[33, "examples-using-mne-connectivity-phase-slope-index"]], "mne_connectivity.read_connectivity": [[34, "mne-connectivity-read-connectivity"]], "mne_connectivity.seed_target_indices": [[35, "mne-connectivity-seed-target-indices"]], "Examples using mne_connectivity.seed_target_indices": [[35, "examples-using-mne-connectivity-seed-target-indices"]], "mne_connectivity.seed_target_multivariate_indices": [[36, "mne-connectivity-seed-target-multivariate-indices"]], "mne_connectivity.select_order": [[37, "mne-connectivity-select-order"]], "mne_connectivity.spectral_connectivity_epochs": [[38, "mne-connectivity-spectral-connectivity-epochs"]], "Examples using mne_connectivity.spectral_connectivity_epochs": [[38, "examples-using-mne-connectivity-spectral-connectivity-epochs"]], "mne_connectivity.spectral_connectivity_time": [[39, "mne-connectivity-spectral-connectivity-time"]], "Examples using mne_connectivity.spectral_connectivity_time": [[39, "examples-using-mne-connectivity-spectral-connectivity-time"]], "mne_connectivity.symmetric_orth": [[40, "mne-connectivity-symmetric-orth"]], "Examples using mne_connectivity.symmetric_orth": [[40, "examples-using-mne-connectivity-symmetric-orth"]], "mne_connectivity.vector_auto_regression": [[41, "mne-connectivity-vector-auto-regression"]], "Examples using mne_connectivity.vector_auto_regression": [[41, "examples-using-mne-connectivity-vector-auto-regression"]], "mne_connectivity.viz.plot_connectivity_circle": [[42, "mne-connectivity-viz-plot-connectivity-circle"]], "Examples using mne_connectivity.viz.plot_connectivity_circle": [[42, "examples-using-mne-connectivity-viz-plot-connectivity-circle"]], "mne_connectivity.viz.plot_sensors_connectivity": [[43, "mne-connectivity-viz-plot-sensors-connectivity"]], "Examples using mne_connectivity.viz.plot_sensors_connectivity": [[43, "examples-using-mne-connectivity-viz-plot-sensors-connectivity"]], "MNE-Connectivity": [[44, "id1"]], "Installation": [[45, "installation"]], "Dependencies": [[45, "dependencies"]], "Installation via Conda": [[45, "installation-via-conda"]], "Installation via Pip": [[45, "installation-via-pip"]], "What\u2019s new?": [[47, "what-s-new"]], "Contents": [[47, "contents"]], "Version 0.6 (unreleased)": [[47, "version-0-6-unreleased"]], "Enhancements": [[47, "enhancements"], [48, "enhancements"], [48, "id1"], [48, "id4"]], "Bug": [[47, "bug"], [48, "bug"], [48, "id2"], [48, "id5"]], "Authors": [[47, "authors"], [48, "authors"], [48, "id3"], [48, "id7"], [48, "id9"], [48, "id10"]], "What was new in previous releases?": [[48, "what-was-new-in-previous-releases"]], "Version 0.5 (2023-01-13)": [[48, "version-0-5-2023-01-13"]], "Version 0.4 (2022-10-05)": [[48, "version-0-4-2022-10-05"]], "Version 0.3 (2022-03-01)": [[48, "version-0-3-2022-03-01"]], "Version 0.2 (2021-09-07)": [[48, "version-0-2-2021-09-07"]], "Changelog": [[48, "changelog"]], "Version 0.1 (2021-06-25)": [[48, "version-0-1-2021-06-25"]], "Changes when mne-connectivity was part of MNE-Python": [[48, "changes-when-mne-connectivity-was-part-of-mne-python"]]}, "indexentries": {"mne_connectivity": [[0, "module-mne_connectivity"]], "module": [[0, "module-mne_connectivity"]], "connectivity (class in mne_connectivity)": [[22, "mne_connectivity.Connectivity"]], "append() (mne_connectivity.connectivity method)": [[22, 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(mne_connectivity.spectrotemporalconnectivity method)": [[28, "mne_connectivity.SpectroTemporalConnectivity.get_data"]], "indices (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.indices"]], "method (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.method"]], "n_epochs (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.n_epochs"]], "n_epochs_used (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.n_epochs_used"]], "n_nodes (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.n_nodes"]], "names (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.names"]], "plot_circle() (mne_connectivity.spectrotemporalconnectivity method)": [[28, "mne_connectivity.SpectroTemporalConnectivity.plot_circle"]], "predict() (mne_connectivity.spectrotemporalconnectivity method)": [[28, "mne_connectivity.SpectroTemporalConnectivity.predict"]], "rename_nodes() (mne_connectivity.spectrotemporalconnectivity method)": [[28, "mne_connectivity.SpectroTemporalConnectivity.rename_nodes"]], "save() (mne_connectivity.spectrotemporalconnectivity method)": [[28, "mne_connectivity.SpectroTemporalConnectivity.save"]], "shape (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.shape"]], "simulate() (mne_connectivity.spectrotemporalconnectivity method)": [[28, "mne_connectivity.SpectroTemporalConnectivity.simulate"]], "times (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.times"]], "xarray (mne_connectivity.spectrotemporalconnectivity property)": [[28, "mne_connectivity.SpectroTemporalConnectivity.xarray"]], "temporalconnectivity (class in mne_connectivity)": [[29, "mne_connectivity.TemporalConnectivity"]], "append() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.append"]], "attrs (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.attrs"]], "combine() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.combine"]], "companion (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.companion"]], "coords (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.coords"]], "dims (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.dims"]], "get_data() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.get_data"]], "indices (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.indices"]], "method (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.method"]], "n_epochs (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.n_epochs"]], "n_epochs_used (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.n_epochs_used"]], "n_nodes (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.n_nodes"]], "names (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.names"]], "plot_circle() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.plot_circle"]], "predict() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.predict"]], "rename_nodes() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.rename_nodes"]], "save() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.save"]], "shape (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.shape"]], "simulate() (mne_connectivity.temporalconnectivity method)": [[29, "mne_connectivity.TemporalConnectivity.simulate"]], "times (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.times"]], "xarray (mne_connectivity.temporalconnectivity property)": [[29, "mne_connectivity.TemporalConnectivity.xarray"]], "check_indices() (in module mne_connectivity)": [[30, "mne_connectivity.check_indices"]], "degree() (in module mne_connectivity)": [[31, "mne_connectivity.degree"]], "envelope_correlation() (in module mne_connectivity)": [[32, "mne_connectivity.envelope_correlation"]], "phase_slope_index() (in module mne_connectivity)": [[33, "mne_connectivity.phase_slope_index"]], "read_connectivity() (in module mne_connectivity)": [[34, "mne_connectivity.read_connectivity"]], "seed_target_indices() (in module mne_connectivity)": [[35, "mne_connectivity.seed_target_indices"]], "seed_target_multivariate_indices() (in module mne_connectivity)": [[36, "mne_connectivity.seed_target_multivariate_indices"]], "select_order() (in module mne_connectivity)": [[37, "mne_connectivity.select_order"]], "spectral_connectivity_epochs() (in module mne_connectivity)": [[38, "mne_connectivity.spectral_connectivity_epochs"]], "spectral_connectivity_time() (in module mne_connectivity)": [[39, "mne_connectivity.spectral_connectivity_time"]], "symmetric_orth() (in module mne_connectivity)": [[40, "mne_connectivity.symmetric_orth"]], "vector_auto_regression() (in module mne_connectivity)": [[41, "mne_connectivity.vector_auto_regression"]], "plot_connectivity_circle() (in module mne_connectivity.viz)": [[42, "mne_connectivity.viz.plot_connectivity_circle"]], "plot_sensors_connectivity() (in module mne_connectivity.viz)": [[43, "mne_connectivity.viz.plot_sensors_connectivity"]]}})
\ No newline at end of file
diff --git a/dev/sg_execution_times.html b/dev/sg_execution_times.html
index 9b651508..de031d6d 100644
--- a/dev/sg_execution_times.html
+++ b/dev/sg_execution_times.html
@@ -401,7 +401,7 @@
                   
   <section id="computation-times">
 <span id="sphx-glr-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Permalink to this heading">#</a></h1>
-<p><strong>05:01.347</strong> total execution time for 16 files <strong>from all galleries</strong>:</p>
+<p><strong>05:08.749</strong> total execution time for 16 files <strong>from all galleries</strong>:</p>
 <div class="docutils container">
 <style scoped>
 <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -427,68 +427,68 @@
 </tr>
 </thead>
 <tbody>
-<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/dynamic/mne_var_connectivity.html#sphx-glr-auto-examples-dynamic-mne-var-connectivity-py"><span class="std std-ref">Compute vector autoregressive model (linear system)</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamic/mne_var_connectivity.py</span></code>)</p></td>
-<td><p>00:59.424</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/mne_inverse_envelope_correlation.html#sphx-glr-auto-examples-mne-inverse-envelope-correlation-py"><span class="std std-ref">Compute envelope correlations in source space</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_envelope_correlation.py</span></code>)</p></td>
+<td><p>00:54.104</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/mne_inverse_envelope_correlation.html#sphx-glr-auto-examples-mne-inverse-envelope-correlation-py"><span class="std std-ref">Compute envelope correlations in source space</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_envelope_correlation.py</span></code>)</p></td>
-<td><p>00:47.029</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/dynamic/mne_var_connectivity.html#sphx-glr-auto-examples-dynamic-mne-var-connectivity-py"><span class="std std-ref">Compute vector autoregressive model (linear system)</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dynamic/mne_var_connectivity.py</span></code>)</p></td>
+<td><p>00:50.157</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/mic_mim.html#sphx-glr-auto-examples-mic-mim-py"><span class="std std-ref">Compute multivariate measures of the imaginary part of coherency</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mic_mim.py</span></code>)</p></td>
-<td><p>00:35.493</p></td>
+<td><p>00:37.640</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/mne_inverse_envelope_correlation_volume.html#sphx-glr-auto-examples-mne-inverse-envelope-correlation-volume-py"><span class="std std-ref">Compute envelope correlations in volume source space</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_envelope_correlation_volume.py</span></code>)</p></td>
-<td><p>00:25.201</p></td>
+<td><p>00:32.233</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/connectivity_classes.html#sphx-glr-auto-examples-connectivity-classes-py"><span class="std std-ref">Using the connectivity classes</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/connectivity_classes.py</span></code>)</p></td>
-<td><p>00:20.813</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/compare_connectivity_over_time_over_trial.html#sphx-glr-auto-examples-compare-connectivity-over-time-over-trial-py"><span class="std std-ref">Comparing spectral connectivity computed over time or over trials</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/compare_connectivity_over_time_over_trial.py</span></code>)</p></td>
+<td><p>00:20.825</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/granger_causality.html#sphx-glr-auto-examples-granger-causality-py"><span class="std std-ref">Compute directionality of connectivity with multivariate Granger causality</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/granger_causality.py</span></code>)</p></td>
-<td><p>00:20.736</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/connectivity_classes.html#sphx-glr-auto-examples-connectivity-classes-py"><span class="std std-ref">Using the connectivity classes</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/connectivity_classes.py</span></code>)</p></td>
+<td><p>00:19.945</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/compare_connectivity_over_time_over_trial.html#sphx-glr-auto-examples-compare-connectivity-over-time-over-trial-py"><span class="std std-ref">Comparing spectral connectivity computed over time or over trials</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/compare_connectivity_over_time_over_trial.py</span></code>)</p></td>
-<td><p>00:19.062</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/granger_causality.html#sphx-glr-auto-examples-granger-causality-py"><span class="std std-ref">Compute directionality of connectivity with multivariate Granger causality</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/granger_causality.py</span></code>)</p></td>
+<td><p>00:19.132</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/mixed_source_space_connectivity.html#sphx-glr-auto-examples-mixed-source-space-connectivity-py"><span class="std std-ref">Compute mixed source space connectivity and visualize it using a circular graph</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mixed_source_space_connectivity.py</span></code>)</p></td>
-<td><p>00:18.905</p></td>
+<td><p>00:17.1000</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/dpli_wpli_pli.html#sphx-glr-auto-examples-dpli-wpli-pli-py"><span class="std std-ref">Comparing PLI, wPLI, and dPLI</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dpli_wpli_pli.py</span></code>)</p></td>
-<td><p>00:14.631</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/mne_inverse_psi_visual.html#sphx-glr-auto-examples-mne-inverse-psi-visual-py"><span class="std std-ref">Compute Phase Slope Index (PSI) in source space for a visual stimulus</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_psi_visual.py</span></code>)</p></td>
+<td><p>00:14.531</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/mne_inverse_psi_visual.html#sphx-glr-auto-examples-mne-inverse-psi-visual-py"><span class="std std-ref">Compute Phase Slope Index (PSI) in source space for a visual stimulus</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_psi_visual.py</span></code>)</p></td>
-<td><p>00:12.927</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/dpli_wpli_pli.html#sphx-glr-auto-examples-dpli-wpli-pli-py"><span class="std std-ref">Comparing PLI, wPLI, and dPLI</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/dpli_wpli_pli.py</span></code>)</p></td>
+<td><p>00:14.372</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/mne_inverse_coherence_epochs.html#sphx-glr-auto-examples-mne-inverse-coherence-epochs-py"><span class="std std-ref">Compute coherence in source space using a MNE inverse solution</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_coherence_epochs.py</span></code>)</p></td>
-<td><p>00:11.015</p></td>
+<td><p>00:12.429</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/mne_inverse_label_connectivity.html#sphx-glr-auto-examples-mne-inverse-label-connectivity-py"><span class="std std-ref">Compute source space connectivity and visualize it using a circular graph</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_label_connectivity.py</span></code>)</p></td>
-<td><p>00:06.678</p></td>
+<td><p>00:05.722</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/cwt_sensor_connectivity.html#sphx-glr-auto-examples-cwt-sensor-connectivity-py"><span class="std std-ref">Compute seed-based time-frequency connectivity in sensor space</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/cwt_sensor_connectivity.py</span></code>)</p></td>
-<td><p>00:04.236</p></td>
+<td><p>00:04.358</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/sensor_connectivity.html#sphx-glr-auto-examples-sensor-connectivity-py"><span class="std std-ref">Compute all-to-all connectivity in sensor space</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/sensor_connectivity.py</span></code>)</p></td>
-<td><p>00:02.372</p></td>
+<td><p>00:02.531</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/mne_inverse_connectivity_spectrum.html#sphx-glr-auto-examples-mne-inverse-connectivity-spectrum-py"><span class="std std-ref">Compute full spectrum source space connectivity between labels</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/mne_inverse_connectivity_spectrum.py</span></code>)</p></td>
-<td><p>00:02.350</p></td>
+<td><p>00:02.398</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/handling_ragged_arrays.html#sphx-glr-auto-examples-handling-ragged-arrays-py"><span class="std std-ref">Working with ragged indices for multivariate connectivity</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/handling_ragged_arrays.py</span></code>)</p></td>
-<td><p>00:00.473</p></td>
+<td><p>00:00.373</p></td>
 <td><p>0.0</p></td>
 </tr>
 </tbody>
@@ -539,7 +539,7 @@
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/whats_new.html b/dev/whats_new.html
index 8296ce67..25cbb8c7 100644
--- a/dev/whats_new.html
+++ b/dev/whats_new.html
@@ -531,7 +531,7 @@ <h3><a class="toc-backref" href="#id5">Authors</a><a class="headerlink" href="#a
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>
diff --git a/dev/whats_new_previous_releases.html b/dev/whats_new_previous_releases.html
index 9b3f2a1d..bc749c2c 100644
--- a/dev/whats_new_previous_releases.html
+++ b/dev/whats_new_previous_releases.html
@@ -666,7 +666,7 @@ <h3>Authors<a class="headerlink" href="#id10" title="Permalink to this heading">
         <div class="footer-item">
   <p class="copyright">
     
-      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-27.
+      © Copyright 2021-2023, MNE Developers. Last updated on 2023-11-28.
       <br/>
     
   </p>