{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "\n\n# Importing Data From fNIRS Devices\n\n
This tutorial is a mirror of the\n ([MNE tutorial](https://mne.tools/dev/auto_tutorials/io/30_reading_fnirs_data.html)_),\n and is reproduced in MNE-NIRS for convenience and so that all\n relevant material is easily accessible to users.
MNE-Python stores metadata internally with a specific structure,\n and internal functions expect specific naming conventions.\n Manual modification of channel names and metadata\n is not recommended.
The SNIRF format has provisions for many different types of fNIRS\n recordings. MNE-Python currently only supports reading continuous\n wave or haemoglobin data stored in the .snirf format.
This method is not supported and users are discouraged to use it.\n You should convert your data to the\n [SNIRF](https://github.com/fNIRS/snirf) format using the tools\n provided by the Society for functional Near-Infrared Spectroscopy,\n and then load it using :func:`mne:mne.io.read_raw_snirf`.
In MNE-Python the naming of channels MUST follow the structure\n ``S#_D# type`` where # is replaced by the appropriate source and\n detector numbers and type is either ``hbo``, ``hbr`` or the\n wavelength.
It is also possible to create a custom montage from a file for\n fNIRS with :func:`mne.channels.read_custom_montage` by setting\n ``coord_frame`` to ``'mri'``.