DNM: Add support for fNIRS data

config.py

@@ -158,7 +158,7 @@
 automatically.
 """
 
-ch_types: Iterable[Literal['meg', 'mag', 'grad', 'eeg']] = []
+ch_types: Iterable[Literal['meg', 'mag', 'grad', 'eeg', 'nirs']] = []
 """
 The channel types to consider.
 
@@ -178,7 +178,7 @@
     ```
 """
 
-data_type: Optional[Literal['meg', 'eeg']] = None
+data_type: Optional[Literal['meg', 'eeg', 'nirs']] = None
 """
 The BIDS data type.
 
@@ -362,6 +362,32 @@
     ```
 """
 
+###############################################################################
+# NIRS PROCESSING
+# ---------------
+
+nirs_only_long_channels: Optional[bool] = True
+"""
+Specifies if only long NIRS channels should be retained for processing.
+
+???+ example "Example"
+    ```python
+    nirs_only_long_channels = True  # processes only long channels
+    nirs_only_long_channels = False  # process both long and short channels
+    ```
+"""
+
+nirs_short_channel_correction: Optional[bool] = True
+"""
+Specifies if short channel correction should be applied to fNIRS data.
+
+???+ example "Example"
+    ```python
+    nirs_short_channel_correction = True  # use short correction
+    nirs_short_channel_correction = False  # do not use short correction
+    ```
+"""
+
 ###############################################################################
 # MAXWELL FILTER PARAMETERS
 # -------------------------
@@ -1341,7 +1367,7 @@ def get_t1_from_meeg(bids_path):
     msg = ('EEG data can only be analyzed separately from other channel '
            'types. Please adjust `ch_types` in your configuration.')
     raise ValueError(msg)
-elif any([ch_type not in ('meg', 'mag', 'grad') for ch_type in ch_types]):
+elif any([ch_type not in ('meg', 'mag', 'grad', 'nirs') for ch_type in ch_types]):
     msg = ('Invalid channel type passed. Please adjust `ch_types` in your '
            'configuration.')
     raise ValueError(msg)
@@ -1649,13 +1675,15 @@ def get_task() -> Optional[str]:
         return task
 
 
-def get_datatype() -> Literal['meg', 'eeg']:
+def get_datatype() -> Literal['meg', 'eeg', 'nirs']:
     # Content of ch_types should be sanitized already, so we don't need any
     # extra sanity checks here.
     if data_type is not None:
         return data_type
     elif data_type is None and ch_types == ['eeg']:
         return 'eeg'
+    elif data_type is None and ch_types == ['nirs']:
+        return 'nirs'
     elif data_type is None and any([t in ['meg', 'mag', 'grad']
                                     for t in ch_types]):
         return 'meg'
@@ -1824,6 +1852,9 @@ def get_channels_to_analyze(info) -> List[str]:
     elif ch_types == ['eeg']:
         pick_idx = mne.pick_types(info, meg=False, eeg=True, eog=True,
                                   ecg=True, exclude=[])
+    elif ch_types == ['nirs']:
+        pick_idx = mne.pick_types(info, meg=False, eeg=False, eog=False,
+                                  ecg=False, fnirs=True, exclude=[])
     else:
         raise RuntimeError('Something unexpected happened. Please contact '
                            'the mne-bids-pipeline developers. Thank you.')

scripts/preprocessing/01-import_and_maxfilter.py

@@ -39,9 +39,13 @@
 
 import mne
 from mne.preprocessing import find_bad_channels_maxwell
+from mne.preprocessing.nirs import optical_density, beer_lambert_law
 from mne.parallel import parallel_func
 from mne_bids import BIDSPath, read_raw_bids
 
+from mne_nirs.signal_enhancement import short_channel_regression
+from mne_nirs.channels import get_long_channels
+
 import config
 from config import gen_log_message, on_error, failsafe_run
 
@@ -238,6 +242,16 @@ def load_data(bids_path):
     if hasattr(raw, 'fix_mag_coil_types'):
         raw.fix_mag_coil_types()
 
+    if config.get_datatype() == 'nirs':
+        if 'fnirs_cw_amplitude' in raw:
+            raw = optical_density(raw)
+        if 'fnirs_od' in raw:
+            if config.nirs_short_channel_correction:
+                raw = short_channel_regression(raw)
+            raw = beer_lambert_law(raw)
+        if config.nirs_only_long_channels:
+            raw = get_long_channels(raw, min_dist=0.01)
+
     montage_name = config.eeg_template_montage
     if config.get_datatype() == 'eeg' and montage_name:
         msg = (f'Setting EEG channel locations to template montage: '

tests/requirements.txt

@@ -24,3 +24,5 @@ coloredlogs
 openneuro-py
 https://api.github.com/repos/mne-tools/mne-python/zipball/main
 https://api.github.com/repos/mne-tools/mne-bids/zipball/main
+mne-nirs
+nilearn