Metadata-Version: 1.1
Name: fmristats
Version: 0.0.6
Summary: Modelling the data and not the images in FMRI
Home-page: https://fmristats.github.io/
Author: Thomas W. D. Möbius
Author-email: moebius@medinfo.uni-kiel.de
License: GPLv3+
Description: Modelling the data and not the images in FMRI
        =============================================
        
        Current approaches to the analysis of functional magnetic resonance
        imaging (FMRI) data apply various preprocessing steps to the original
        FMRI. These preprocessings lead to a general underestimation of residual
        variance in the downstream analysis. This negatively impacts the type I
        error of statistical tests and increases the risk for reporting false
        positive results.
        
        This is the first statistical software tool which implements the *model
        based* (MB) estimator for FMRI data models. It is a new and original
        method for the statistical analysis of FMRI of brain scans. MB
        estimation combines all preprocessing steps of the standard approaches
        into one single modelling step. Without altering the original 4D-image,
        the method results in smooth fits of the underlying parameter fields.
        More importantly, the method yields a trustworthy estimate of the
        uncertainty in BOLD effect estimation.
        
        The availability of these uncertainty fields allows to model FMRI
        studies by random effects meta regression models, acknowledging that
        individual subjects are random entities, and that the certainty at which
        the actual BOLD effect in an individual can be estimated from an FMRI
        varies across the brain and between the subjects.
        
        MB estimation allows to process and report BOLD effects in ati units. In
        particular multicentre studies gain power by its use: if an effect is
        present in your data, you will be more likely to find it.
        
        Citing the MB estimator and this software:
        
            Thomas W. D. Möbius (2018) Modelling the data and not the images in
            FMRI, ArXiv e-prints, arXiv:1809.07232
        
            Thomas W. D. Möbius (2018) fmristats: Modelling the data and not the
            images in FMRI (Version 0.0.6) [Computer program]. Available at
            http://fmristats.github.io/
        
        Thank you for citing this project.
        
        .. changelog:: 0.0.6
        
            * Added .ravel to Image: image.ravel() will return a copy of the 1-D
              flattend data that do not contain zeros or nan.
            * Added .components to Image: image.components() will label the
              non-zero, path-connected components in the image.
            * Added .detect_peaks() to Image: Detect the peaks in an image and
              return a list of their indicies.
            * Beautified the output of picture(). (A legend and a colourbar are
              now added by default.)
            * MetaResult has been renamed to PopulationResult. It is still
              possible to load a MetaResult from disk. However, this is now
              depreciated.
            * A PopulationMap can now store an ATI-reference.
            * Result has now the option to norm the BOLD-effect field to ATI
              with result.norm_to_ati().
            * The function image2nii has now the option to zero any nan in the
              image. Needed for data export to Nistats.
            * fmriprune and fsl4prune now give a name to mask they produce.
            * Added nipype to install_requires.
            * Added a warning to --inverse in fmrimap that the function
              currently only works for Warp and Displacement.
        
        
        .. changelog:: 0.0.5
        
            * Thus far creating the data matrix dropped between block
              observations and demeaned the time vector for numerical stability
              and convenience. This is still the default behaviour but there is
              now the option to not follow the default.
        
            * CLI-argument to --fit was ignored in fmriprune, fsl4prune and
              thus always reverted to the default template. Fixed.
        
        .. changelog:: 0.0.4
        
            This is the first official version.
        
Keywords: fmri neuroimaging neuroscience statistics
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
