Release Name: niak "ammo" version 0.7.1 -- stable

This release corresponds to NIAK version 1887 and PSOM version 760 (release 1.0.2), as numbered by the subversion repository. Main features:

* A new pipeline for region growing. This can be used to generate a functional brain parcellation, controlling for the regions' size and/or homogeneity, at the level of an individual or a group. Methods as described in Bellec et al., Neuroimage 2006.
A new pipeline to generate connectomes, functional connectivity maps as well as graph properties. This pipeline depends on the brain connectivity toolbox.
* A revamp of the fMRI preprocessing pipeline. Now includes regression of average signals in the ventricles and the white matter, scrubbing, regression of the global signal "a la Carbonell", regression of the motion parameters after PCA reduction, COMPCOR, symmetric or asymmetric MNI brain template, and other goodies.
* The default of FLAG_NU_CORRECT in the slice timing brick was also set to off, because for a reason that is unknown at this time this operation behaves differently on different computational platforms. With default parameters, the three pipelines released as part of NIAK 0.7.1 have been successfully tested for reproducibility on two different computational platforms (Ubuntu 12.04 vs CentOS 5.5, both with Octave 3.6.2 and minc-toolkit 0.3.18). The tests were performed both within and between platforms.
* Lots of other minor features and bug fixes.

* New pipeline to generate graph properties on connectomes and functional connectivity maps (niak_pipeline_connectome). The graph measures are based on the brain connectivity toolbox
* New pipeline for region growing
* a command for region growing in 3D (niak_region_growing)
* a new brick for region growing on a single subject's fMRI (niak_brick_region_growing)
* a new pipeline for region growing with multiple fMRI datasets (niak_pipeline_region_growing)
* New tools for linear model analysis:
* read a model in CSV format (niak_read_model)
* least-square estimation (niak_lse)
* general linear model analysis (niak_glm)
* "normalization" of a model, i.e. orthogonalize, correct for mean/variance, create interaction terms, select subsects of the data, etc. (niak_normalize_model).
* White's test for heteroskedasticity (niak_white_test_hetero)
* New statistical tools
* bootstrap of time series (niak_bootstrap_tseries)
* false-discovery rate in a family of p values (niak_fdr)
* New tools for clustering:
* hierarchical clustering (niak_hierarchical_clustering)
* threshold a hierarchy (niak_threshold_hierarchy)
* re-order points based on a hierarchy (niak_hier2order)
* re-order points based on a similarity matrix and a partition (niak_part2order)
* visualize a hierarchy (niak_dendrogram)
* visualize a partition (niak_visu_part).
* An improved version of k-means clustering (with bisecting approach, k-means++ initialization, optimized code, and others)
* Surface analysis:
* A new reader for surface data (niak_read_surf)
* A new tool to visualize surface data (niak_visu_surf)
* New surface template
* A new brick to interpolate volumetric data on the surface (niak_brick_vol2surf)
* fMRI preprocessing:
* Added the scrubbing method of Power 2012
* Preprocessed file now have a xxxx_extra.mat companion, including all confounds that have been regressed out as well as a list of scrubbed volumes.
* Added some regression of confounds in the pipeline (niak_brick_regress_confounds)
* Added a correction of the global average "à la Carbonell" in niak_brick_regress_confounds
* Added the COMPCOR method to correct structured noise in fMRI
* the CORSICA method is now off by default
* The default resolution for the normalized fMRI datasets resampled in stereotaxic space is now 3 mm isotropic.
* It is now possible to choose between the symmetric (default) and asymmetric MNI brain templates for coregistration of T1 scans in stereotaxic space.
* lots of new measures for quality control
* A new tool to estimate partial volume effects on a T1 volume (thanks to Jussi Tohka, niak_brick_pve)
* A new version of the AAL parcellation, tweaked to fit the non-linear symmetric MNI template (40 iterations).
* A new "grabber", i.e. a function to parse the outputs of the fMRI preprocessing pipeline, select a subset of QCed subjects, and generate a structure that can be fed in other pipelines such as the region growing pipeline (niak_grab_fmri_preprocess).
* Many bug fixes and minor improvements.