This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.
Improve SNR on masked fMRI signals.
This function can do several things on the input signals, in the following order:
Low-pass filtering improves specificity.
High-pass filtering should be kept small, to keep some sensitivity.
Filtering is only meaningful on evenly-sampled signals.
New in version 0.2.5.
imgs: Niimg-like object
sessions : numpy array, optional
confounds: numpy.ndarray, str or list of
low_pass, high_pass: float
t_r: float, optional
cleaned_img: Niimg-like object
Confounds removal is based on a projection on the orthogonal of the signal space. See Friston, K. J., A. P. Holmes, K. J. Worsley, J.-P. Poline, C. D. Frith, et R. S. J. Frackowiak. “Statistical Parametric Maps in Functional Imaging: A General Linear Approach”. Human Brain Mapping 2, no 4 (1994): 189-210.