SNIRF Support in MNE

.nirs files

MNE does not support reading .nirs files. If you have .nirs files that you would like to process in MNE, you should first convert them to SNIRF. To convert .nirs files to SNIRF you can use the Homer3 Nirs2Snirf function. See fNIRS/snirf_homer3

SNIRF is a file format for storing functional near-infrared spectroscopy (fNIRS) data. The specification is maintained by the society for functional near infrared spectroscopy.

MNE Python and MNE-NIRS can be used to read and write SNIRF files respectively. In this tutorial we demonstrate how to convert your MNE data to SNIRF and write it to disk and also how to read SNIRF files. We also demonstrate how to validate that a SNIRF file conforms to the SNIRF specification.

You can read the SNIRF protocol at the official site fNIRS/snirf.

# Authors: Robert Luke <mail@robertluke.net>
#
# License: BSD (3-clause)

import os

import mne
import snirf
from mne.io import read_raw_nirx, read_raw_snirf
from mne.preprocessing.nirs import beer_lambert_law, optical_density
from numpy.testing import assert_allclose

from mne_nirs.io import write_raw_snirf

Import raw NIRS data from vendor

First we import some example data recorded with a NIRX device.

fnirs_data_folder = mne.datasets.fnirs_motor.data_path()
fnirs_raw_dir = os.path.join(fnirs_data_folder, "Participant-1")
raw_intensity = read_raw_nirx(fnirs_raw_dir).load_data()

Write data as SNIRF

Now we can write this data back to disk in the SNIRF format.

write_raw_snirf(raw_intensity, "test_raw.snirf")

Read back SNIRF file

Next we can read back the snirf file.

snirf_intensity = read_raw_snirf("test_raw.snirf")

Compare files

Finally we can compare the data of the original to the SNIRF format and ensure that the values are the same.

assert_allclose(raw_intensity.get_data(), snirf_intensity.get_data())

snirf_intensity.plot(n_channels=30, duration=300, show_scrollbars=False)

<mne_qt_browser._pg_figure.MNEQtBrowser object at 0x7fefe8967520>

Validate SNIRF File

To validate that a file complies with the SNIRF standard you should use the official SNIRF validator from the Boston University Neurophotonics Center called snirf. Detailed instructions for this program can be found at BUNPC/pysnirf2. Below we demonstrate that the files created by MNE-NIRS are compliant with the specification.

result = snirf.validateSnirf("test_raw.snirf")
assert result.is_valid()
result.display()

<snirf.pysnirf2.ValidationResult object at 0x7fefe85c9690>

Found 304 OK      (hidden)
Found 522 INFO    (hidden)
Found 0 WARNING
Found 0 FATAL

File is VALID

Optical Density

MNE-NIRS cal also be used to write optical density data to SNIRF files.

raw_od = optical_density(raw_intensity)
write_raw_snirf(raw_od, "test_raw_od.snirf")

result = snirf.validateSnirf("test_raw_od.snirf")
assert result.is_valid()
result.display()

<snirf.pysnirf2.ValidationResult object at 0x7fefe85cb8b0>

Found 360 OK      (hidden)
Found 466 INFO    (hidden)
Found 0 WARNING
Found 0 FATAL

File is VALID

Haemoglobin

And it can write valid haemoglobin data to SNIRF files.

raw_hb = beer_lambert_law(raw_od)
write_raw_snirf(raw_hb, "test_raw_hb.snirf")

result = snirf.validateSnirf("test_raw_hb.snirf")
assert result.is_valid()
result.display()

<snirf.pysnirf2.ValidationResult object at 0x7fefe92b8040>

Found 360 OK      (hidden)
Found 466 INFO    (hidden)
Found 0 WARNING
Found 0 FATAL

File is VALID

Estimated memory usage: 463 MB