mne.preprocessing.nirs.temporal_derivative_distribution_repair(raw, *, verbose=None)[source]

Apply temporal derivative distribution repair to data.

Applies temporal derivative distribution repair (TDDR) to data 1. This approach removes baseline shift and spike artifacts without the need for any user-supplied parameters.

rawinstance of Raw

The raw data.

verbosebool, str, int, or None

If not None, override default verbose level (see mne.verbose() and Logging documentation for more). If used, it should be passed as a keyword-argument only.

rawinstance of Raw

Data with TDDR applied.


There is a shorter alias mne.preprocessing.nirs.tddr that can be used instead of this function (e.g. if line length is an issue).



Frank A Fishburn, Ruth S Ludlum, Chandan J Vaidya, and Andrei V Medvedev. Temporal derivative distribution repair (tddr): a motion correction method for fnirs. NeuroImage, 184:171–179, 2019. doi:10.1016/j.neuroimage.2018.09.025.

Examples using mne.preprocessing.nirs.temporal_derivative_distribution_repair