DESCRIPTION

Package: pTFCE
Title: Probabilitic Threshold-free Cluster Enhancement of Neuroimages
Version: 0.2.2.1
Authors@R: person("Tamas", "Spisak", email = "tamas.spisak@uk-essen.de", role = c("aut", "cre"))
Description: The threshold-free cluster enhancement (TFCE) approach integrates cluster information into voxel-wise statistical inference to enhance detectability of neuroimaging signal. Despite the significantly increased sensitivity, the application of TFCE is limited by several factors: (i) generalization to data structures, like brain network connectivity data is not trivial, (ii) TFCE values are in an arbitrary unit, therefore, P-values can only be obtained by a computationally demanding permutation-test.
    Here, we introduce a probabilistic approach for TFCE (pTFCE), that gives a simple general framework for topology-based belief boosting.
    The core of pTFCE is a conditional probability, calculated based on Bayes' rule, from the probability of voxel intensity and the threshold-wise likelihood function of the measured cluster size. We provide an estimation of these distributions based on Gaussian Random Field (GRF) theory. The conditional probabilities are then aggregated across cluster-forming thresholds by a novel incremental aggregation method. Our approach is validated on simulated and real fMRI data.
    pTFCE is shown to be more robust to various ground truth shapes and provides a stricter control over cluster "leaking" than TFCE and, in the most realistic cases, further improves its sensitivity. Correction for multiple comparison can be trivially performed on the enhanced P-values, without the need for permutation testing, thus pTFCE is well-suitable for the improvement of statistical inference in any neuroimaging workflow.
URL: http://github.com/spisakt/pTFCE
BugReports: http://github.com/spisakt/pTFCE/issues
Depends: R (>= 3.2.2)
License: GPL (>= 3) + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
Imports: 
    oro.nifti,
    mmand,
    methods
Suggests: testthat