This is a library to assist with processing near-infrared spectroscopy data with MNE.
MNE-NIRS and MNE-Python provide a wide variety of tools to use when processing fNIRS data including:
Apply 3D sensor locations from common digitisation systems such as Polhemus.
Standard preprocessing including optical density calculation and Beer-Lambert Law conversion, filtering, etc.
GLM analysis with a wide variety of customisation including including FIR or canonical HRF analysis, higher order autoregressive noise models, short channel regression, region of interest analysis, etc.
Visualisation tools for all stages of processing from raw data to processed waveforms, GLM result visualisation, including both sensor and cortical surface projections.
Data cleaning functions including popular short channel techniques and negative correlation enhancement.
Before installing MNE-NIRS you must install Python and MNE-Python. To install Python and MNE-Python follow these instructions. We recommend using the standalone installer option unless you are a python expert.
Upgrading your software version#
See the MNE-Python instructions for how to update the MNE-Python version. Similarly, you can update MNE-NIRS to the latest development version by running
$ pip install -U --no-deps git+https://github.com/mne-tools/mne-nirs.git@main
This library is built on top of other great packages. If you use MNE-NIRS you should also acknowledge these packages:
Until there is a journal article specifically on MNE-NIRS, please cite this article.