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 Control verbosity of the logging output. If
None, use the default verbosity level. See the logging documentation andmne.verbose()for details. Should only be passed as a keyword argument.
- rawinstance of
- Returns
- rawinstance of
Raw Data with TDDR applied.
- rawinstance of
Notes
There is a shorter alias
mne.preprocessing.nirs.tddrthat 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.
