mne.preprocessing.nirs.temporal_derivative_distribution_repair

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.

Parameters
rawinstance of Raw

The raw data.

verbosebool | str | int | 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.

Returns
rawinstance of Raw

Data with TDDR applied.

Notes

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).

References

1

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