Fix read_raw_nirx for newer Aurora software

doc/changes/dev/14055.newfeature.rst

@@ -0,0 +1 @@
+Added support for newer recording software in :func:`mne.io.read_raw_nirx`, by `Emma Bailey`_.

doc/changes/names.inc

@@ -90,7 +90,7 @@
 .. _Eberhard Eich: https://github.com/ebeich
 .. _Eduard Ort: https://github.com/eort
 .. _Emily Stephen: https://github.com/emilyps14
-.. _Emma Bailey: https://www.cbs.mpg.de/employees/bailey
+.. _Emma Bailey: https://github.com/emma-bailey
 .. _Emma Zhang: https://portfolio-production-ed03.up.railway.app/
 .. _Emmanuel Ferdman: https://github.com/emmanuel-ferdman
 .. _Emrecan Çelik: https://github.com/emrecncelik

mne/io/nirx/nirx.py

@@ -119,8 +119,6 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
                 "description.json",
                 "wl1",
                 "wl2",
-                "probeInfo.mat",
-                "tri",
             )
         else:
             # NIRScout devices and NIRSport1 devices
@@ -132,7 +130,6 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
                 "wl1",
                 "wl2",
                 "config.txt",
-                "probeInfo.mat",
             )
             n_dat = len(glob.glob(f"{fname}/*{'dat'}"))
             if n_dat != 1:
@@ -175,6 +172,21 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
                     nan_mask[key] = files[key][0 if noidx == 1 else 1]
             files[key] = files[key][fidx]
 
+        # Locate probeInfo file — either .mat (legacy) or .json (newer Aurora)
+        probe_mat = glob.glob(f"{fname}/*probeInfo.mat")
+        probe_json = glob.glob(f"{fname}/*probeInfo.json")
+        if len(probe_json) == 1:
+            files["probeInfo"] = probe_json[0]
+            probe_format = "json"
+        elif len(probe_mat) == 1:
+            files["probeInfo"] = probe_mat[0]
+            probe_format = "mat"
+        else:
+            raise RuntimeError(
+                f"Need one probeInfo.mat or probeInfo.json file, "
+                f"got {len(probe_mat)} .mat and {len(probe_json)} .json"
+            )
+
         # Read number of rows/samples of wavelength data
         with _open(files["wl1"]) as fid:
             last_sample = fid.read().count("\n") - 1
@@ -197,6 +209,7 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
                 "2021.4.0-34-ge9fdbbc8",
                 "2021.9.0-5-g3eb32851",
                 "2021.9.0-6-g14ef4a71",
+                "2025.2.0-17-geea6971f",
             ]:
                 warn(
                     "MNE has not been tested with Aurora version "
@@ -361,12 +374,28 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
         #   Sources and detectors are both called optodes
         #   Each source - detector pair produces a channel
         #   Channels are defined as the midpoint between source and detector
-        mat_data = loadmat(files["probeInfo.mat"])
-        probes = mat_data["probeInfo"]["probes"][0, 0]
-        requested_channels = probes["index_c"][0, 0]
-        src_locs = probes["coords_s3"][0, 0] / 100.0
-        det_locs = probes["coords_d3"][0, 0] / 100.0
-        ch_locs = probes["coords_c3"][0, 0] / 100.0
+        if probe_format == "json":
+            with open(files["probeInfo"], encoding="utf-8") as _f:
+                _probe_json = json.load(_f)
+            probes = _probe_json["probeInfo"]["probes"]
+            requested_channels = np.array(probes["index_c"])
+            src_locs = np.array(probes["coords_s3"]) / 1000.0
+            det_locs = np.array(probes["coords_d3"]) / 1000.0
+            ch_locs = np.array(probes["coords_c3"]) / 1000.0
+            if _probe_json["probeInfo"]["head_circumference"] != 610.0:
+                warn(
+                    "The head circumference in the probeInfo.json file is "
+                    f"{_probe_json['probeInfo']['head_circumference']} mm, "
+                    "as opposed to standard 610.0 mm. This may cause misalignment of "
+                    "the optode locations with the subject's head in later steps."
+                )
+        else:
+            mat_data = loadmat(files["probeInfo"])
+            probes = mat_data["probeInfo"]["probes"][0, 0]
+            requested_channels = probes["index_c"][0, 0]
+            src_locs = probes["coords_s3"][0, 0] / 100.0
+            det_locs = probes["coords_d3"][0, 0] / 100.0
+            ch_locs = probes["coords_c3"][0, 0] / 100.0
 
         # These are all in MNI coordinates, so let's transform them to
         # the Neuromag head coordinate frame
@@ -425,11 +454,11 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
         # The detector location is stored in the third 3 entries of loc.
         # NIRx NIRSite uses MNI coordinates.
         # Also encode the light frequency in the structure.
-        for ch_idx2 in range(requested_channels.shape[0]):
+        for ch_idx2, wl_idx in enumerate(req_ind):
             # Find source and store location
-            src = int(requested_channels[ch_idx2, 0]) - 1
+            src = int(sources[wl_idx]) - 1
             # Find detector and store location
-            det = int(requested_channels[ch_idx2, 1]) - 1
+            det = int(detectors[wl_idx]) - 1
             # Store channel location as midpoint between source and detector.
             midpoint = (src_locs[src, :] + det_locs[det, :]) / 2
             for ii in range(2):
@@ -508,6 +537,9 @@ def __init__(self, fname, saturated, *, preload=False, encoding=None, verbose=No
         # Read triggers from event file
         if not is_aurora:
             files["tri"] = files["hdr"][:-3] + "evt"
+        else:
+            tri_files = glob.glob(f"{fname}/*.tri")
+            files["tri"] = tri_files[0] if len(tri_files) == 1 else ""
         if op.isfile(files["tri"]):
             with _open(files["tri"]) as fid:
                 t = [re.findall(r"(\d+)", line) for line in fid]

mne/io/nirx/tests/test_nirx.py

@@ -55,6 +55,7 @@
 nirsport2 = testing_path / "NIRx" / "nirsport_v2" / "aurora_recording _w_short_and_acc"
 nirsport2_2021_9 = testing_path / "NIRx" / "nirsport_v2" / "aurora_2021_9"
 nirsport2_2021_9_6 = testing_path / "NIRx" / "nirsport_v2" / "aurora_2021_9_6"
+nirsport2_2025_2 = testing_path / "NIRx" / "nirsport_v2" / "aurora_2025_2"
 
 
 def test_nirsport_v2_matches_snirf(nirx_snirf):
@@ -551,6 +552,41 @@ def test_nirx_aurora_2021_9_6():
     assert raw.annotations.description[2] == "3.0"
 
 
+@requires_testing_data
+@pytest.mark.filterwarnings("ignore:.*Extraction of measurement.*:")
+def test_nirx_aurora_2025_2():
+    """Test reading Aurora dataset with probeInfo.json."""
+    raw = read_raw_nirx(nirsport2_2025_2, preload=True)
+
+    # 50 channels × 2 wavelengths
+    assert raw._data.shape[0] == 100
+
+    # Test triggers
+    assert len(raw.annotations) == 10
+    assert (raw.annotations.description == "1.0").sum() == 5
+    assert (raw.annotations.description == "2.0").sum() == 5
+
+    # Test detector locations derived from probeInfo.json (MNI coords in mm)
+    allowed_dist_error = 0.0002
+    locs = [ch["loc"][6:9] for ch in raw.info["chs"]]
+    head_mri_t, _ = _get_trans("fsaverage", "head", "mri")
+    mni_locs = apply_trans(head_mri_t, locs)
+
+    assert raw.info["ch_names"][0][3:5] == "D1"
+    assert_allclose(
+        mni_locs[0], [-0.035971, 0.027644, 0.077821], atol=allowed_dist_error
+    )
+
+    # Test source locations
+    locs = [ch["loc"][3:6] for ch in raw.info["chs"]]
+    mni_locs = apply_trans(head_mri_t, locs)
+
+    assert raw.info["ch_names"][0][:2] == "S1"
+    assert_allclose(
+        mni_locs[0], [-0.02948, 0.060438, 0.057351], atol=allowed_dist_error
+    )
+
+
 @requires_testing_data
 def test_nirx_15_0():
     """Test reading NIRX files."""