From 824457d30c34c798d4850c090b085ecfee03e635 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 20:17:29 +0100
Subject: [PATCH 01/24] working implem

---
 examples/preprocessing/interpolate_to.py | 63 +++++++++++++++++
 mne/channels/channels.py                 | 88 ++++++++++++++++++++++++
 2 files changed, 151 insertions(+)
 create mode 100644 examples/preprocessing/interpolate_to.py

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
new file mode 100644
index 00000000000..ee834380ae4
--- /dev/null
+++ b/examples/preprocessing/interpolate_to.py
@@ -0,0 +1,63 @@
+"""
+.. _ex-interpolate-to-any-montage:
+
+======================================================
+Interpolate EEG data to a any montage
+======================================================
+
+This example demonstrates how to interpolate EEG channels to match a given
+montage using the :func:`interpolate_to` method. This can be useful for standardizing
+EEG channel layouts across different datasets.
+
+- Using the MNE method for interpolation.
+- The target montage will be the standard "standard_1020" montage.
+
+In this example, the data from the original EEG channels will be interpolated onto the positions defined by the "standard_1020" montage.
+"""
+
+# Authors: Antoine Collas <contact@antoinecollas.fr>
+# License: BSD-3-Clause
+
+import mne
+from mne.datasets import sample
+from mne.channels import make_standard_montage
+import matplotlib.pyplot as plt
+
+print(__doc__)
+
+# %%
+# Load EEG data
+data_path = sample.data_path()
+eeg_file_path = data_path / "MEG" / "sample" / "sample_audvis-ave.fif"
+evoked = mne.read_evokeds(eeg_file_path, condition="Left Auditory", baseline=(None, 0))
+
+# Select only EEG channels
+evoked.pick("eeg")
+
+# Plot the original EEG layout
+evoked.plot(exclude=[], picks="eeg")
+
+# %%
+# Define the target montage
+standard_montage = make_standard_montage('standard_1020')
+
+# %%
+# Use interpolate_to to project EEG data to the standard montage
+evoked_interpolated = evoked.copy().interpolate_to(standard_montage)
+
+# Plot the interpolated EEG layout
+evoked_interpolated.plot(exclude=[], picks="eeg")
+
+# %%
+# Comparing before and after interpolation
+fig, axs = plt.subplots(2, 1, figsize=(8, 6))
+evoked.plot(exclude=[], picks="eeg", axes=axs[0], show=False)
+axs[0].set_title("Original EEG Layout")
+evoked_interpolated.plot(exclude=[], picks="eeg", axes=axs[1], show=False)
+axs[1].set_title("Interpolated to Standard 1020 Montage")
+plt.tight_layout()
+
+# %%
+# References
+# ----------
+# .. footbibliography::
diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 8fbff33c13e..368a4f73044 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -950,6 +950,94 @@ def interpolate_bads(
 
         return self
 
+    def interpolate_to(self, montage, method='MNE', reg=0.0):
+        """Interpolate data onto a new montage.
+
+        Parameters
+        ----------
+        montage : DigMontage
+            The target montage containing channel positions to interpolate onto.
+        method : str
+            The interpolation method to use. 'MNE' by default.
+        reg : float
+            The regularization parameter for the interpolation method (if applicable).
+
+        Returns
+        -------
+        inst : instance of Raw, Epochs, or Evoked
+            The instance with updated channel locations and data.
+        """
+        import numpy as np
+        import mne
+        from mne import pick_types
+        from mne.forward._field_interpolation import _map_meg_or_eeg_channels
+
+        # Ensure data is loaded
+        _check_preload(self, "interpolation")
+
+        # Extract positions and data for EEG channels
+        picks_from = pick_types(self.info, meg=False, eeg=True, exclude=[])
+        if len(picks_from) == 0:
+            raise ValueError("No EEG channels available for interpolation.")
+
+        if hasattr(self, '_data'):
+            data_orig = self._data[picks_from]
+        else:
+            # If epochs-like data, for simplicity take the mean across epochs
+            data_orig = self.get_data()[:, picks_from, :].mean(axis=0)
+
+        # Get target positions from the montage
+        ch_pos = montage.get_positions()['ch_pos']
+        target_ch_names = list(ch_pos.keys())
+        if len(target_ch_names) == 0:
+            raise ValueError("The provided montage does not contain any channel positions.")
+
+        # Create a new info structure using MNE public API
+        sfreq = self.info['sfreq']
+        ch_types = ['eeg'] * len(target_ch_names)
+        new_info = mne.create_info(ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types)
+        new_info.set_montage(montage)
+
+        # Create a simple old_info
+        sfreq = self.info['sfreq']
+        ch_names = self.info['ch_names']
+        ch_types = ['eeg'] * len(ch_names)
+        old_info = mne.create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
+        old_info.set_montage(self.info.get_montage())
+
+        # Compute mapping from current montage to target montage
+        mapping = _map_meg_or_eeg_channels(old_info, new_info, mode='accurate', origin='auto')
+
+        # Apply the interpolation mapping
+        D_new = mapping.dot(data_orig)
+
+        # Update bad channels
+        new_bads = [ch for ch in self.info['bads'] if ch in target_ch_names]
+        new_info['bads'] = new_bads
+
+        # Update the instance's info and data
+        self.info = new_info
+        if hasattr(self, '_data'):
+            if self._data.ndim == 2:
+                # Raw-like: directly assign the new data
+                self._data = D_new
+            else:
+                # Epochs-like
+                n_epochs, _, n_times = self._data.shape
+                new_data = np.zeros((n_epochs, len(target_ch_names), n_times), dtype=self._data.dtype)
+                for e in range(n_epochs):
+                    epoch_data_orig = self._data[e, picks_from, :]
+                    new_data[e, :, :] = mapping.dot(epoch_data_orig)
+                self._data = new_data
+        else:
+            # Evoked-like data
+            if hasattr(self, 'data'):
+                self.data = D_new
+            else:
+                raise NotImplementedError("This method requires preloaded data.")
+
+        return self
+
 
 @verbose
 def rename_channels(info, mapping, allow_duplicates=False, *, verbose=None):

From 5e5f16bb6bad334a47a38ba8cfc6b3028abd342d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 30 Dec 2024 19:28:25 +0000
Subject: [PATCH 02/24] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 examples/preprocessing/interpolate_to.py |  7 ++--
 mne/channels/channels.py                 | 41 +++++++++++++++---------
 2 files changed, 29 insertions(+), 19 deletions(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index ee834380ae4..1710479e0da 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -18,10 +18,11 @@
 # Authors: Antoine Collas <contact@antoinecollas.fr>
 # License: BSD-3-Clause
 
+import matplotlib.pyplot as plt
+
 import mne
-from mne.datasets import sample
 from mne.channels import make_standard_montage
-import matplotlib.pyplot as plt
+from mne.datasets import sample
 
 print(__doc__)
 
@@ -39,7 +40,7 @@
 
 # %%
 # Define the target montage
-standard_montage = make_standard_montage('standard_1020')
+standard_montage = make_standard_montage("standard_1020")
 
 # %%
 # Use interpolate_to to project EEG data to the standard montage
diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 368a4f73044..6d8db1d7bb9 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -950,7 +950,7 @@ def interpolate_bads(
 
         return self
 
-    def interpolate_to(self, montage, method='MNE', reg=0.0):
+    def interpolate_to(self, montage, method="MNE", reg=0.0):
         """Interpolate data onto a new montage.
 
         Parameters
@@ -968,6 +968,7 @@ def interpolate_to(self, montage, method='MNE', reg=0.0):
             The instance with updated channel locations and data.
         """
         import numpy as np
+
         import mne
         from mne import pick_types
         from mne.forward._field_interpolation import _map_meg_or_eeg_channels
@@ -980,58 +981,66 @@ def interpolate_to(self, montage, method='MNE', reg=0.0):
         if len(picks_from) == 0:
             raise ValueError("No EEG channels available for interpolation.")
 
-        if hasattr(self, '_data'):
+        if hasattr(self, "_data"):
             data_orig = self._data[picks_from]
         else:
             # If epochs-like data, for simplicity take the mean across epochs
             data_orig = self.get_data()[:, picks_from, :].mean(axis=0)
 
         # Get target positions from the montage
-        ch_pos = montage.get_positions()['ch_pos']
+        ch_pos = montage.get_positions()["ch_pos"]
         target_ch_names = list(ch_pos.keys())
         if len(target_ch_names) == 0:
-            raise ValueError("The provided montage does not contain any channel positions.")
+            raise ValueError(
+                "The provided montage does not contain any channel positions."
+            )
 
         # Create a new info structure using MNE public API
-        sfreq = self.info['sfreq']
-        ch_types = ['eeg'] * len(target_ch_names)
-        new_info = mne.create_info(ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types)
+        sfreq = self.info["sfreq"]
+        ch_types = ["eeg"] * len(target_ch_names)
+        new_info = mne.create_info(
+            ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types
+        )
         new_info.set_montage(montage)
 
         # Create a simple old_info
-        sfreq = self.info['sfreq']
-        ch_names = self.info['ch_names']
-        ch_types = ['eeg'] * len(ch_names)
+        sfreq = self.info["sfreq"]
+        ch_names = self.info["ch_names"]
+        ch_types = ["eeg"] * len(ch_names)
         old_info = mne.create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
         old_info.set_montage(self.info.get_montage())
 
         # Compute mapping from current montage to target montage
-        mapping = _map_meg_or_eeg_channels(old_info, new_info, mode='accurate', origin='auto')
+        mapping = _map_meg_or_eeg_channels(
+            old_info, new_info, mode="accurate", origin="auto"
+        )
 
         # Apply the interpolation mapping
         D_new = mapping.dot(data_orig)
 
         # Update bad channels
-        new_bads = [ch for ch in self.info['bads'] if ch in target_ch_names]
-        new_info['bads'] = new_bads
+        new_bads = [ch for ch in self.info["bads"] if ch in target_ch_names]
+        new_info["bads"] = new_bads
 
         # Update the instance's info and data
         self.info = new_info
-        if hasattr(self, '_data'):
+        if hasattr(self, "_data"):
             if self._data.ndim == 2:
                 # Raw-like: directly assign the new data
                 self._data = D_new
             else:
                 # Epochs-like
                 n_epochs, _, n_times = self._data.shape
-                new_data = np.zeros((n_epochs, len(target_ch_names), n_times), dtype=self._data.dtype)
+                new_data = np.zeros(
+                    (n_epochs, len(target_ch_names), n_times), dtype=self._data.dtype
+                )
                 for e in range(n_epochs):
                     epoch_data_orig = self._data[e, picks_from, :]
                     new_data[e, :, :] = mapping.dot(epoch_data_orig)
                 self._data = new_data
         else:
             # Evoked-like data
-            if hasattr(self, 'data'):
+            if hasattr(self, "data"):
                 self.data = D_new
             else:
                 raise NotImplementedError("This method requires preloaded data.")

From 4236efbbf8801913d8cc0ca71fb78193a9a03df0 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 20:35:47 +0100
Subject: [PATCH 03/24] pre-commit

---
 examples/preprocessing/interpolate_to.py | 10 +++---
 mne/channels/channels.py                 | 41 +++++++++++++++---------
 2 files changed, 31 insertions(+), 20 deletions(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index ee834380ae4..23d545e0596 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -12,16 +12,18 @@
 - Using the MNE method for interpolation.
 - The target montage will be the standard "standard_1020" montage.
 
-In this example, the data from the original EEG channels will be interpolated onto the positions defined by the "standard_1020" montage.
+In this example, the data from the original EEG channels will be
+interpolated onto the positions defined by the "standard_1020" montage.
 """
 
 # Authors: Antoine Collas <contact@antoinecollas.fr>
 # License: BSD-3-Clause
 
+import matplotlib.pyplot as plt
+
 import mne
-from mne.datasets import sample
 from mne.channels import make_standard_montage
-import matplotlib.pyplot as plt
+from mne.datasets import sample
 
 print(__doc__)
 
@@ -39,7 +41,7 @@
 
 # %%
 # Define the target montage
-standard_montage = make_standard_montage('standard_1020')
+standard_montage = make_standard_montage("standard_1020")
 
 # %%
 # Use interpolate_to to project EEG data to the standard montage
diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 368a4f73044..6d8db1d7bb9 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -950,7 +950,7 @@ def interpolate_bads(
 
         return self
 
-    def interpolate_to(self, montage, method='MNE', reg=0.0):
+    def interpolate_to(self, montage, method="MNE", reg=0.0):
         """Interpolate data onto a new montage.
 
         Parameters
@@ -968,6 +968,7 @@ def interpolate_to(self, montage, method='MNE', reg=0.0):
             The instance with updated channel locations and data.
         """
         import numpy as np
+
         import mne
         from mne import pick_types
         from mne.forward._field_interpolation import _map_meg_or_eeg_channels
@@ -980,58 +981,66 @@ def interpolate_to(self, montage, method='MNE', reg=0.0):
         if len(picks_from) == 0:
             raise ValueError("No EEG channels available for interpolation.")
 
-        if hasattr(self, '_data'):
+        if hasattr(self, "_data"):
             data_orig = self._data[picks_from]
         else:
             # If epochs-like data, for simplicity take the mean across epochs
             data_orig = self.get_data()[:, picks_from, :].mean(axis=0)
 
         # Get target positions from the montage
-        ch_pos = montage.get_positions()['ch_pos']
+        ch_pos = montage.get_positions()["ch_pos"]
         target_ch_names = list(ch_pos.keys())
         if len(target_ch_names) == 0:
-            raise ValueError("The provided montage does not contain any channel positions.")
+            raise ValueError(
+                "The provided montage does not contain any channel positions."
+            )
 
         # Create a new info structure using MNE public API
-        sfreq = self.info['sfreq']
-        ch_types = ['eeg'] * len(target_ch_names)
-        new_info = mne.create_info(ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types)
+        sfreq = self.info["sfreq"]
+        ch_types = ["eeg"] * len(target_ch_names)
+        new_info = mne.create_info(
+            ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types
+        )
         new_info.set_montage(montage)
 
         # Create a simple old_info
-        sfreq = self.info['sfreq']
-        ch_names = self.info['ch_names']
-        ch_types = ['eeg'] * len(ch_names)
+        sfreq = self.info["sfreq"]
+        ch_names = self.info["ch_names"]
+        ch_types = ["eeg"] * len(ch_names)
         old_info = mne.create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
         old_info.set_montage(self.info.get_montage())
 
         # Compute mapping from current montage to target montage
-        mapping = _map_meg_or_eeg_channels(old_info, new_info, mode='accurate', origin='auto')
+        mapping = _map_meg_or_eeg_channels(
+            old_info, new_info, mode="accurate", origin="auto"
+        )
 
         # Apply the interpolation mapping
         D_new = mapping.dot(data_orig)
 
         # Update bad channels
-        new_bads = [ch for ch in self.info['bads'] if ch in target_ch_names]
-        new_info['bads'] = new_bads
+        new_bads = [ch for ch in self.info["bads"] if ch in target_ch_names]
+        new_info["bads"] = new_bads
 
         # Update the instance's info and data
         self.info = new_info
-        if hasattr(self, '_data'):
+        if hasattr(self, "_data"):
             if self._data.ndim == 2:
                 # Raw-like: directly assign the new data
                 self._data = D_new
             else:
                 # Epochs-like
                 n_epochs, _, n_times = self._data.shape
-                new_data = np.zeros((n_epochs, len(target_ch_names), n_times), dtype=self._data.dtype)
+                new_data = np.zeros(
+                    (n_epochs, len(target_ch_names), n_times), dtype=self._data.dtype
+                )
                 for e in range(n_epochs):
                     epoch_data_orig = self._data[e, picks_from, :]
                     new_data[e, :, :] = mapping.dot(epoch_data_orig)
                 self._data = new_data
         else:
             # Evoked-like data
-            if hasattr(self, 'data'):
+            if hasattr(self, "data"):
                 self.data = D_new
             else:
                 raise NotImplementedError("This method requires preloaded data.")

From 3a0383a2eca9cee8a2aa392fcedde788ce1e0bc1 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 21:49:31 +0100
Subject: [PATCH 04/24] minor changes

---
 doc/references.bib                       |  8 ++++++++
 examples/preprocessing/interpolate_to.py | 12 ++++++------
 mne/channels/channels.py                 |  2 ++
 3 files changed, 16 insertions(+), 6 deletions(-)

diff --git a/doc/references.bib b/doc/references.bib
index a129d2f46a2..f82a9f6ac68 100644
--- a/doc/references.bib
+++ b/doc/references.bib
@@ -2504,3 +2504,11 @@ @article{OyamaEtAl2015
 	year = {2015},
 	pages = {24--36},
 }
+
+@inproceedings{MellotEtAl2024,
+	title = {Physics-informed and Unsupervised Riemannian Domain Adaptation for Machine Learning on Heterogeneous EEG Datasets},
+	author = {Mellot, Apolline and Collas, Antoine and Chevallier, Sylvain and Engemann, Denis and Gramfort, Alexandre},
+	booktitle = {Proceedings of the 32nd European Signal Processing Conference (EUSIPCO)},
+	year = {2024},
+	address = {Lyon, France}
+}
diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index 23d545e0596..fc1069cdb4e 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -2,18 +2,18 @@
 .. _ex-interpolate-to-any-montage:
 
 ======================================================
-Interpolate EEG data to a any montage
+Interpolate EEG data to any montage
 ======================================================
 
 This example demonstrates how to interpolate EEG channels to match a given
 montage using the :func:`interpolate_to` method. This can be useful for standardizing
-EEG channel layouts across different datasets.
+EEG channel layouts across different datasets (see :footcite:`MellotEtAl2024`).
 
-- Using the MNE method for interpolation.
-- The target montage will be the standard "standard_1020" montage.
+- Using the field interpolation for EEG data.
+- Using the target montage "biosemi16".
 
 In this example, the data from the original EEG channels will be
-interpolated onto the positions defined by the "standard_1020" montage.
+interpolated onto the positions defined by the "biosemi16" montage.
 """
 
 # Authors: Antoine Collas <contact@antoinecollas.fr>
@@ -41,7 +41,7 @@
 
 # %%
 # Define the target montage
-standard_montage = make_standard_montage("standard_1020")
+standard_montage = make_standard_montage("biosemi16")
 
 # %%
 # Use interpolate_to to project EEG data to the standard montage
diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 6d8db1d7bb9..266129d24a2 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -966,6 +966,8 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         -------
         inst : instance of Raw, Epochs, or Evoked
             The instance with updated channel locations and data.
+
+        .. versionadded:: 1.10.0
         """
         import numpy as np
 

From 3ea4cad114d6143ecb584e4a234766102197056b Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 22:05:06 +0100
Subject: [PATCH 05/24] fix nested imports

---
 mne/channels/channels.py | 10 +++-------
 1 file changed, 3 insertions(+), 7 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 266129d24a2..33d640fcfd4 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -969,11 +969,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
 
         .. versionadded:: 1.10.0
         """
-        import numpy as np
-
-        import mne
-        from mne import pick_types
-        from mne.forward._field_interpolation import _map_meg_or_eeg_channels
+        from ..forward._field_interpolation import _map_meg_or_eeg_channels
 
         # Ensure data is loaded
         _check_preload(self, "interpolation")
@@ -1000,7 +996,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         # Create a new info structure using MNE public API
         sfreq = self.info["sfreq"]
         ch_types = ["eeg"] * len(target_ch_names)
-        new_info = mne.create_info(
+        new_info = create_info(
             ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types
         )
         new_info.set_montage(montage)
@@ -1009,7 +1005,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         sfreq = self.info["sfreq"]
         ch_names = self.info["ch_names"]
         ch_types = ["eeg"] * len(ch_names)
-        old_info = mne.create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
+        old_info = create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
         old_info.set_montage(self.info.get_montage())
 
         # Compute mapping from current montage to target montage

From 29f7ce4d1a383d6b55bb7575a35b4b3b3e187bc3 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 30 Dec 2024 21:06:08 +0000
Subject: [PATCH 06/24] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 mne/channels/channels.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 33d640fcfd4..f64eef22cd1 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -996,9 +996,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         # Create a new info structure using MNE public API
         sfreq = self.info["sfreq"]
         ch_types = ["eeg"] * len(target_ch_names)
-        new_info = create_info(
-            ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types
-        )
+        new_info = create_info(ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types)
         new_info.set_montage(montage)
 
         # Create a simple old_info

From 8a05713955a0525147ef344305317dfaa1184f5a Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 22:10:06 +0100
Subject: [PATCH 07/24] fix comment

---
 mne/channels/channels.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index f64eef22cd1..df9ae8f0db4 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -993,7 +993,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
                 "The provided montage does not contain any channel positions."
             )
 
-        # Create a new info structure using MNE public API
+        # Create a new info structure
         sfreq = self.info["sfreq"]
         ch_types = ["eeg"] * len(target_ch_names)
         new_info = create_info(ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types)

From de0ddc490728ebe4a985bc884f5947c7f38ff9e9 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 22:29:47 +0100
Subject: [PATCH 08/24] add test

---
 mne/channels/tests/test_interpolation.py | 37 +++++++++++++++++++++++-
 1 file changed, 36 insertions(+), 1 deletion(-)

diff --git a/mne/channels/tests/test_interpolation.py b/mne/channels/tests/test_interpolation.py
index a881a41edcc..43fee4266d5 100644
--- a/mne/channels/tests/test_interpolation.py
+++ b/mne/channels/tests/test_interpolation.py
@@ -12,7 +12,7 @@
 from mne import Epochs, pick_channels, pick_types, read_events
 from mne._fiff.constants import FIFF
 from mne._fiff.proj import _has_eeg_average_ref_proj
-from mne.channels import make_dig_montage
+from mne.channels import make_dig_montage, make_standard_montage
 from mne.channels.interpolation import _make_interpolation_matrix
 from mne.datasets import testing
 from mne.io import RawArray, read_raw_ctf, read_raw_fif, read_raw_nirx
@@ -439,3 +439,38 @@ def test_method_str():
         raw.interpolate_bads(method="spline")
     raw.pick("eeg", exclude=())
     raw.interpolate_bads(method="spline")
+
+
+@pytest.mark.parametrize("montage_name", ["biosemi16", "standard_1020"])
+def test_interpolate_to_eeg(montage_name):
+    """Test the interpolate_to method for EEG."""
+    # Load EEG data
+    raw, _ = _load_data("eeg")
+
+    # Select only EEG channels
+    raw.pick("eeg")
+
+    # Load data
+    raw.load_data()
+
+    # Create a target montage
+    montage = make_standard_montage(montage_name)
+
+    # Copy the raw object and apply interpolation
+    raw_interpolated = raw.copy().interpolate_to(montage)
+
+    # Check if channel names match the target montage
+    assert set(raw_interpolated.info["ch_names"]) == set(montage.ch_names)
+
+    # Check if the data was interpolated correctly
+    assert raw_interpolated.get_data().shape[0] == len(montage.ch_names)
+
+    # Ensure original data is not altered
+    assert raw.info["ch_names"] != raw_interpolated.info["ch_names"]
+
+    # Validate that bad channels are carried over
+    raw.info["bads"] = [raw.info["ch_names"][0]]
+    raw_interpolated = raw.copy().interpolate_to(montage)
+    assert raw_interpolated.info["bads"] == [
+        ch for ch in raw.info["bads"] if ch in montage.ch_names
+    ]

From 254fdac48fb7566c89e0b7dc1abbe0aa57526138 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 22:53:04 +0100
Subject: [PATCH 09/24] fix docstring

---
 examples/preprocessing/interpolate_to.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index fc1069cdb4e..4d86310e1db 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -5,8 +5,8 @@
 Interpolate EEG data to any montage
 ======================================================
 
-This example demonstrates how to interpolate EEG channels to match a given
-montage using the :func:`interpolate_to` method. This can be useful for standardizing
+This example demonstrates how to interpolate EEG channels to match a given montage.
+This can be useful for standardizing
 EEG channel layouts across different datasets (see :footcite:`MellotEtAl2024`).
 
 - Using the field interpolation for EEG data.

From 4bf3f1d18148cd8c54a74f510bb9f72c8ccdfa5e Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 23:09:10 +0100
Subject: [PATCH 10/24] fix docstring

---
 mne/channels/channels.py | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index df9ae8f0db4..ce290a33363 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -967,6 +967,10 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         inst : instance of Raw, Epochs, or Evoked
             The instance with updated channel locations and data.
 
+        Notes
+        -----
+        This method is useful for standardizing EEG layouts across datasets.
+
         .. versionadded:: 1.10.0
         """
         from ..forward._field_interpolation import _map_meg_or_eeg_channels

From 2f27599f313c355e8f414105fb8c6f43c50a8971 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 23:09:52 +0100
Subject: [PATCH 11/24] rm plt.tight_layout

---
 examples/preprocessing/interpolate_to.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index 4d86310e1db..ed25adcd3ac 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -57,7 +57,6 @@
 axs[0].set_title("Original EEG Layout")
 evoked_interpolated.plot(exclude=[], picks="eeg", axes=axs[1], show=False)
 axs[1].set_title("Interpolated to Standard 1020 Montage")
-plt.tight_layout()
 
 # %%
 # References

From 872ba1df96ea712a6957afe77838c5e58b0f6842 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 30 Dec 2024 23:26:43 +0100
Subject: [PATCH 12/24] taller figure

---
 examples/preprocessing/interpolate_to.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index ed25adcd3ac..5830ba5d666 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -52,7 +52,7 @@
 
 # %%
 # Comparing before and after interpolation
-fig, axs = plt.subplots(2, 1, figsize=(8, 6))
+fig, axs = plt.subplots(2, 1, figsize=(8, 8))
 evoked.plot(exclude=[], picks="eeg", axes=axs[0], show=False)
 axs[0].set_title("Original EEG Layout")
 evoked_interpolated.plot(exclude=[], picks="eeg", axes=axs[1], show=False)

From 045496c971f86fb38307a4edfe537be2f8ba2e4a Mon Sep 17 00:00:00 2001
From: "autofix-ci[bot]" <114827586+autofix-ci[bot]@users.noreply.github.com>
Date: Wed, 1 Jan 2025 11:35:35 +0000
Subject: [PATCH 13/24] [autofix.ci] apply automated fixes

---
 examples/preprocessing/interpolate_to.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index 5830ba5d666..4413f85a453 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -18,6 +18,7 @@
 
 # Authors: Antoine Collas <contact@antoinecollas.fr>
 # License: BSD-3-Clause
+# Copyright the MNE-Python contributors.
 
 import matplotlib.pyplot as plt
 

From 6fb3ae5cccd466b2ef59b3f600d0f7cdb1dc8729 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Fri, 3 Jan 2025 10:08:25 +0100
Subject: [PATCH 14/24] fix figure layout

---
 examples/preprocessing/interpolate_to.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index 4413f85a453..f3127d122a0 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -53,7 +53,7 @@
 
 # %%
 # Comparing before and after interpolation
-fig, axs = plt.subplots(2, 1, figsize=(8, 8))
+fig, axs = plt.subplots(2, 1, figsize=(8, 6), constrained_layout=True)
 evoked.plot(exclude=[], picks="eeg", axes=axs[0], show=False)
 axs[0].set_title("Original EEG Layout")
 evoked_interpolated.plot(exclude=[], picks="eeg", axes=axs[1], show=False)

From dd093a88c6d68fda3376c6937b92611b63dee68e Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Fri, 3 Jan 2025 10:13:55 +0100
Subject: [PATCH 15/24] improve test

---
 mne/channels/tests/test_interpolation.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/mne/channels/tests/test_interpolation.py b/mne/channels/tests/test_interpolation.py
index 43fee4266d5..f9b8177f9a6 100644
--- a/mne/channels/tests/test_interpolation.py
+++ b/mne/channels/tests/test_interpolation.py
@@ -463,10 +463,11 @@ def test_interpolate_to_eeg(montage_name):
     assert set(raw_interpolated.info["ch_names"]) == set(montage.ch_names)
 
     # Check if the data was interpolated correctly
-    assert raw_interpolated.get_data().shape[0] == len(montage.ch_names)
+    assert raw_interpolated.get_data().shape == (len(montage.ch_names), raw.n_times)
 
     # Ensure original data is not altered
     assert raw.info["ch_names"] != raw_interpolated.info["ch_names"]
+    assert raw.get_data().shape == (len(raw.info["ch_names"]), raw.n_times)
 
     # Validate that bad channels are carried over
     raw.info["bads"] = [raw.info["ch_names"][0]]

From 95510166cc3712b1ad66b861323f8fd4dcdfc728 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Fri, 3 Jan 2025 10:22:14 +0100
Subject: [PATCH 16/24] simplify getting original data

---
 mne/channels/channels.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index ce290a33363..cac64b3e633 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -983,11 +983,8 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         if len(picks_from) == 0:
             raise ValueError("No EEG channels available for interpolation.")
 
-        if hasattr(self, "_data"):
-            data_orig = self._data[picks_from]
-        else:
-            # If epochs-like data, for simplicity take the mean across epochs
-            data_orig = self.get_data()[:, picks_from, :].mean(axis=0)
+        # Get original data
+        data_orig = self.get_data(picks=picks_from)
 
         # Get target positions from the montage
         ch_pos = montage.get_positions()["ch_pos"]

From fa326ad0fee1f785e49a069e7a4c61ee044ee84e Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Fri, 3 Jan 2025 10:29:24 +0100
Subject: [PATCH 17/24] simplify setting interpolated data

---
 mne/channels/channels.py | 23 ++---------------------
 1 file changed, 2 insertions(+), 21 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index cac64b3e633..555d611a450 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -1013,7 +1013,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         )
 
         # Apply the interpolation mapping
-        D_new = mapping.dot(data_orig)
+        data_interp = mapping.dot(data_orig)
 
         # Update bad channels
         new_bads = [ch for ch in self.info["bads"] if ch in target_ch_names]
@@ -1021,26 +1021,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
 
         # Update the instance's info and data
         self.info = new_info
-        if hasattr(self, "_data"):
-            if self._data.ndim == 2:
-                # Raw-like: directly assign the new data
-                self._data = D_new
-            else:
-                # Epochs-like
-                n_epochs, _, n_times = self._data.shape
-                new_data = np.zeros(
-                    (n_epochs, len(target_ch_names), n_times), dtype=self._data.dtype
-                )
-                for e in range(n_epochs):
-                    epoch_data_orig = self._data[e, picks_from, :]
-                    new_data[e, :, :] = mapping.dot(epoch_data_orig)
-                self._data = new_data
-        else:
-            # Evoked-like data
-            if hasattr(self, "data"):
-                self.data = D_new
-            else:
-                raise NotImplementedError("This method requires preloaded data.")
+        self._data = data_interp
 
         return self
 

From 1a5ca892d8a2f74c318aba489f164de7e26eacc9 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Fri, 3 Jan 2025 10:37:23 +0100
Subject: [PATCH 18/24] merge two lines

---
 mne/channels/channels.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 555d611a450..e3e34f46326 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -1016,8 +1016,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         data_interp = mapping.dot(data_orig)
 
         # Update bad channels
-        new_bads = [ch for ch in self.info["bads"] if ch in target_ch_names]
-        new_info["bads"] = new_bads
+        new_info["bads"] = [ch for ch in self.info["bads"] if ch in target_ch_names]
 
         # Update the instance's info and data
         self.info = new_info

From 4333f0898fc4609543ff85bc4a0812114cb71324 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 6 Jan 2025 14:49:31 +0100
Subject: [PATCH 19/24] add spline method

---
 mne/channels/channels.py                 | 49 ++++++++++++++++--------
 mne/channels/tests/test_interpolation.py |  7 ++--
 2 files changed, 36 insertions(+), 20 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index e3e34f46326..96a94e29000 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -950,15 +950,21 @@ def interpolate_bads(
 
         return self
 
-    def interpolate_to(self, montage, method="MNE", reg=0.0):
-        """Interpolate data onto a new montage.
+    def interpolate_to(self, montage, method="spline", reg=0.0):
+        """Interpolate EEG data onto a new montage.
 
         Parameters
         ----------
         montage : DigMontage
             The target montage containing channel positions to interpolate onto.
         method : str
-            The interpolation method to use. 'MNE' by default.
+            Method to use for EEG channels.
+            Supported methods are 'spline' (default) and 'MNE'.
+
+            .. warning::
+                Be careful, only EEG channels are interpolated. Other channel types are
+                not interpolated.
+
         reg : float
             The regularization parameter for the interpolation method (if applicable).
 
@@ -974,17 +980,7 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         .. versionadded:: 1.10.0
         """
         from ..forward._field_interpolation import _map_meg_or_eeg_channels
-
-        # Ensure data is loaded
-        _check_preload(self, "interpolation")
-
-        # Extract positions and data for EEG channels
-        picks_from = pick_types(self.info, meg=False, eeg=True, exclude=[])
-        if len(picks_from) == 0:
-            raise ValueError("No EEG channels available for interpolation.")
-
-        # Get original data
-        data_orig = self.get_data(picks=picks_from)
+        from .interpolation import _make_interpolation_matrix
 
         # Get target positions from the montage
         ch_pos = montage.get_positions()["ch_pos"]
@@ -994,6 +990,17 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
                 "The provided montage does not contain any channel positions."
             )
 
+        # Check the method is valid
+        _check_option("method", method, ["spline", "MNE"])
+
+        # Ensure data is loaded
+        _check_preload(self, "interpolation")
+
+        # Extract positions and data for EEG channels
+        picks_from = pick_types(self.info, meg=False, eeg=True, exclude=[])
+        if len(picks_from) == 0:
+            raise ValueError("No EEG channels available for interpolation.")
+
         # Create a new info structure
         sfreq = self.info["sfreq"]
         ch_types = ["eeg"] * len(target_ch_names)
@@ -1008,11 +1015,19 @@ def interpolate_to(self, montage, method="MNE", reg=0.0):
         old_info.set_montage(self.info.get_montage())
 
         # Compute mapping from current montage to target montage
-        mapping = _map_meg_or_eeg_channels(
-            old_info, new_info, mode="accurate", origin="auto"
-        )
+        if method == "spline":
+            pos_from = np.array(
+                [self.info["chs"][idx]["loc"][:3] for idx in picks_from]
+            )
+            pos_to = np.stack(list(ch_pos.values()), axis=0)
+            mapping = _make_interpolation_matrix(pos_from, pos_to, alpha=reg)
+        elif method == "MNE":
+            mapping = _map_meg_or_eeg_channels(
+                old_info, new_info, mode="accurate", origin="auto"
+            )
 
         # Apply the interpolation mapping
+        data_orig = self.get_data(picks=picks_from)
         data_interp = mapping.dot(data_orig)
 
         # Update bad channels
diff --git a/mne/channels/tests/test_interpolation.py b/mne/channels/tests/test_interpolation.py
index f9b8177f9a6..14f813977e1 100644
--- a/mne/channels/tests/test_interpolation.py
+++ b/mne/channels/tests/test_interpolation.py
@@ -442,7 +442,8 @@ def test_method_str():
 
 
 @pytest.mark.parametrize("montage_name", ["biosemi16", "standard_1020"])
-def test_interpolate_to_eeg(montage_name):
+@pytest.mark.parametrize("method", ["spline", "MNE"])
+def test_interpolate_to_eeg(montage_name, method):
     """Test the interpolate_to method for EEG."""
     # Load EEG data
     raw, _ = _load_data("eeg")
@@ -457,7 +458,7 @@ def test_interpolate_to_eeg(montage_name):
     montage = make_standard_montage(montage_name)
 
     # Copy the raw object and apply interpolation
-    raw_interpolated = raw.copy().interpolate_to(montage)
+    raw_interpolated = raw.copy().interpolate_to(montage, method=method)
 
     # Check if channel names match the target montage
     assert set(raw_interpolated.info["ch_names"]) == set(montage.ch_names)
@@ -471,7 +472,7 @@ def test_interpolate_to_eeg(montage_name):
 
     # Validate that bad channels are carried over
     raw.info["bads"] = [raw.info["ch_names"][0]]
-    raw_interpolated = raw.copy().interpolate_to(montage)
+    raw_interpolated = raw.copy().interpolate_to(montage, method=method)
     assert raw_interpolated.info["bads"] == [
         ch for ch in raw.info["bads"] if ch in montage.ch_names
     ]

From 4e256164f4381205e76f9299f806fdb62d33c148 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 6 Jan 2025 14:59:28 +0100
Subject: [PATCH 20/24] add splive vs mne to doc

---
 examples/preprocessing/interpolate_to.py | 21 ++++++++++++++++-----
 1 file changed, 16 insertions(+), 5 deletions(-)

diff --git a/examples/preprocessing/interpolate_to.py b/examples/preprocessing/interpolate_to.py
index f3127d122a0..50cd31ca0af 100644
--- a/examples/preprocessing/interpolate_to.py
+++ b/examples/preprocessing/interpolate_to.py
@@ -46,18 +46,29 @@
 
 # %%
 # Use interpolate_to to project EEG data to the standard montage
-evoked_interpolated = evoked.copy().interpolate_to(standard_montage)
+evoked_interpolated_spline = evoked.copy().interpolate_to(
+    standard_montage, method="spline"
+)
 
 # Plot the interpolated EEG layout
-evoked_interpolated.plot(exclude=[], picks="eeg")
+evoked_interpolated_spline.plot(exclude=[], picks="eeg")
+
+# %%
+# Use interpolate_to to project EEG data to the standard montage
+evoked_interpolated_mne = evoked.copy().interpolate_to(standard_montage, method="MNE")
+
+# Plot the interpolated EEG layout
+evoked_interpolated_mne.plot(exclude=[], picks="eeg")
 
 # %%
 # Comparing before and after interpolation
-fig, axs = plt.subplots(2, 1, figsize=(8, 6), constrained_layout=True)
+fig, axs = plt.subplots(3, 1, figsize=(8, 6), constrained_layout=True)
 evoked.plot(exclude=[], picks="eeg", axes=axs[0], show=False)
 axs[0].set_title("Original EEG Layout")
-evoked_interpolated.plot(exclude=[], picks="eeg", axes=axs[1], show=False)
-axs[1].set_title("Interpolated to Standard 1020 Montage")
+evoked_interpolated_spline.plot(exclude=[], picks="eeg", axes=axs[1], show=False)
+axs[1].set_title("Interpolated to Standard 1020 Montage using spline interpolation")
+evoked_interpolated_mne.plot(exclude=[], picks="eeg", axes=axs[2], show=False)
+axs[2].set_title("Interpolated to Standard 1020 Montage using MNE interpolation")
 
 # %%
 # References

From a249321596b79bead0cfad78f33a32e118956fcf Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 6 Jan 2025 16:59:07 +0100
Subject: [PATCH 21/24] keep all modalities in test

---
 mne/channels/tests/test_interpolation.py | 7 +++----
 1 file changed, 3 insertions(+), 4 deletions(-)

diff --git a/mne/channels/tests/test_interpolation.py b/mne/channels/tests/test_interpolation.py
index 14f813977e1..a2e5c2dc786 100644
--- a/mne/channels/tests/test_interpolation.py
+++ b/mne/channels/tests/test_interpolation.py
@@ -446,10 +446,9 @@ def test_method_str():
 def test_interpolate_to_eeg(montage_name, method):
     """Test the interpolate_to method for EEG."""
     # Load EEG data
-    raw, _ = _load_data("eeg")
-
-    # Select only EEG channels
-    raw.pick("eeg")
+    raw, epochs_eeg = _load_data("eeg")
+    epochs_eeg = epochs_eeg.copy()
+    assert not _has_eeg_average_ref_proj(epochs_eeg.info)
 
     # Load data
     raw.load_data()

From fb8804f1742ca0fad63fb3f12f05685f8e84eda2 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 6 Jan 2025 16:59:27 +0100
Subject: [PATCH 22/24] use self.info instead of old_info

---
 mne/channels/channels.py | 9 +--------
 1 file changed, 1 insertion(+), 8 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 96a94e29000..be6bc772795 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -1007,13 +1007,6 @@ def interpolate_to(self, montage, method="spline", reg=0.0):
         new_info = create_info(ch_names=target_ch_names, sfreq=sfreq, ch_types=ch_types)
         new_info.set_montage(montage)
 
-        # Create a simple old_info
-        sfreq = self.info["sfreq"]
-        ch_names = self.info["ch_names"]
-        ch_types = ["eeg"] * len(ch_names)
-        old_info = create_info(ch_names=ch_names, sfreq=sfreq, ch_types=ch_types)
-        old_info.set_montage(self.info.get_montage())
-
         # Compute mapping from current montage to target montage
         if method == "spline":
             pos_from = np.array(
@@ -1023,7 +1016,7 @@ def interpolate_to(self, montage, method="spline", reg=0.0):
             mapping = _make_interpolation_matrix(pos_from, pos_to, alpha=reg)
         elif method == "MNE":
             mapping = _map_meg_or_eeg_channels(
-                old_info, new_info, mode="accurate", origin="auto"
+                self.info, new_info, mode="accurate", origin="auto"
             )
 
         # Apply the interpolation mapping

From 7ff7f519838ea00dab56c68dce6154ccebaa4ebe Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 6 Jan 2025 17:02:44 +0100
Subject: [PATCH 23/24] fix info when MNE interpolation

---
 mne/channels/channels.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index be6bc772795..202f335d448 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -1015,8 +1015,9 @@ def interpolate_to(self, montage, method="spline", reg=0.0):
             pos_to = np.stack(list(ch_pos.values()), axis=0)
             mapping = _make_interpolation_matrix(pos_from, pos_to, alpha=reg)
         elif method == "MNE":
+            info_eeg = pick_info(self.info, picks_from)
             mapping = _map_meg_or_eeg_channels(
-                self.info, new_info, mode="accurate", origin="auto"
+                info_eeg, new_info, mode="accurate", origin="auto"
             )
 
         # Apply the interpolation mapping

From 1334fb3c23bafeb51f45d980b2535bb3febe2cb6 Mon Sep 17 00:00:00 2001
From: Antoine Collas <contact@antoinecollas.fr>
Date: Mon, 6 Jan 2025 17:16:42 +0100
Subject: [PATCH 24/24] fix origin in spline method

---
 mne/channels/channels.py | 30 ++++++++++++++++++++++++++----
 1 file changed, 26 insertions(+), 4 deletions(-)

diff --git a/mne/channels/channels.py b/mne/channels/channels.py
index 202f335d448..4f404bf32d3 100644
--- a/mne/channels/channels.py
+++ b/mne/channels/channels.py
@@ -950,13 +950,17 @@ def interpolate_bads(
 
         return self
 
-    def interpolate_to(self, montage, method="spline", reg=0.0):
+    def interpolate_to(self, montage, origin="auto", method="spline", reg=0.0):
         """Interpolate EEG data onto a new montage.
 
         Parameters
         ----------
         montage : DigMontage
             The target montage containing channel positions to interpolate onto.
+        origin : array-like, shape (3,) | str
+            Origin of the sphere in the head coordinate frame and in meters.
+            Can be ``'auto'`` (default), which means a head-digitization-based
+            origin fit.
         method : str
             Method to use for EEG channels.
             Supported methods are 'spline' (default) and 'MNE'.
@@ -1009,11 +1013,29 @@ def interpolate_to(self, montage, method="spline", reg=0.0):
 
         # Compute mapping from current montage to target montage
         if method == "spline":
-            pos_from = np.array(
-                [self.info["chs"][idx]["loc"][:3] for idx in picks_from]
-            )
+            # pos_from = np.array(
+            #     [self.info["chs"][idx]["loc"][:3] for idx in picks_from]
+            # )
+
+            origin = _check_origin(origin, self.info)
+            pos_from = self.info._get_channel_positions(picks_from)
+            pos_from = pos_from - origin
             pos_to = np.stack(list(ch_pos.values()), axis=0)
+
+            def _check_pos_sphere(pos):
+                distance = np.linalg.norm(pos, axis=-1)
+                distance = np.mean(distance / np.mean(distance))
+                if np.abs(1.0 - distance) > 0.1:
+                    warn(
+                        "Your spherical fit is poor, interpolation results are "
+                        "likely to be inaccurate."
+                    )
+
+            _check_pos_sphere(pos_from)
+            _check_pos_sphere(pos_to)
+
             mapping = _make_interpolation_matrix(pos_from, pos_to, alpha=reg)
+
         elif method == "MNE":
             info_eeg = pick_info(self.info, picks_from)
             mapping = _map_meg_or_eeg_channels(