Metadata-Version: 1.1
Name: fmristats
Version: 0.0.2
Summary: Rigorous statistical estimation of FMRI models
Home-page: https://fmristats.github.io/
Author: Thomas W. D. Möbius
Author-email: moebius@medinfo.uni-kiel.de
License: GPLv3+
Description: Rigorous statistical modelling of functional MRI data of the brain
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        The current state-of-the-art approach to the statistical analysis of
        functional MR-images involves a variety of pre-processing steps, which
        alter the signal to noise ratio of the original data.
        
        This is a new and original approach for the statistical analysis of
        functional MR-imaging data of brain scans. The method essentially fits a
        weighted least squares model to arbitrary points of a 3D-random field.
        Without prior spacial smoothing, i.e., without altering the original
        4D-image, the method nevertheless results in a smooth fit of the
        underlying activation pattern. More importantly, though, the method
        yields a trustworthy estimate of the uncertainty of the estimated
        activation field for each subject in a study. The availability of this
        uncertainty field allows for the first time to model group studies and
        group-wise comparisons using random effects meta regression models,
        acknowledging the fact that (i) individual subjects are random entities
        in group studies, and that (ii) the variability in the estimated
        individual activation patterns varies across the brain and between
        subjects.
        
Keywords: fmri mri statistics meta-analysis meta-regression imaging neuroimaging
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3.5
