Imaging software

Version: 2.0
Current developers: David Abbott, PhD; Amir Omidvarnia, PhD; Chris Tailby, PhD
Past developers: Richard Masterton, PhD

A software toolbox to perform Event-related Independent Component Analysis (eICA).

• Particularly useful for event-related fMRI when the neuronal and/or haemodynamic response to events (the “fMRI response”) is not known a-priori
• Assumes only that the peri-event fMRI time-course is similar for each event
• Requires fMRI time-series input data along with event timing
• Otherwise makes no assumptions about neuronal or haemodynamic response

Step 1: At each voxel, the toolbox estimates the fMRI response associated with the events of interest
Step 2: The toolbox performs a spatial ICA on the resultant 4D spatio-temporal response map

• Result is a series of spatial maps and associated peri-event time-series
• Can detect neuronal responses even if they precede the events (e.g. anticipatory effects, EEG-fMRI)
• Can be helpful when the fMRI response is spatially heterogeneous (i.e. can detect sub-networks with different peri-event time-courses)

The method is described in Mapping brain activity using event-related independent components analysis (eICA): Specific advantages for EEG-fMRI. Richard A.J.Masterton, Graeme D.Jackson, David F.Abbott, 2013. Neuroimage. DOI:10.1016/j.neuroimage.2012.12.025

The ERICA Toolbox is released under the GNU General Public License and is available for download.

Dual-tree complex wavelet combined with non-local means for ASL fMRI denoising

Version: 1.0
Developer: Xiaoyun Liang, PhD

Dual-tree complex wavelet combined with non-local means (DT-CWT-NLM) for Arterial-Spin-Labelling (ASL) fMRI denoising is a software toolbox that can denoise MR images, especially ASL fMRI. The software is typically used as a pre-processing step, reading, denoising and writing NIfTI format images. Variable denoising outcomes are possible by changing certain parameters. The software can also be employed for denoising other MR image types, such as diffusion MRI.

The method is described in Voxel-wise functional connectomics using arterial spin labeling fMRI: the role of denoising. Xiaoyun Liang, Alan Connelly, Fernando Calamante, 2015. Brain connectivity. DOI: 10.1089/brain.2014.0290.c

DT-CWT-NLM is released under the GNU General Public License and is available for download.

The Integrated Brain Analysis Toolbox for SPM (iBT) (also known as the iBrain Analysis Toolbox for SPM), and the iBrain Laterality Toolbox

Principal developer: David Abbott, PhD

iBT and iBrain software comprise several easy-to-use neuroimage processing and visualisation packages developed by David Abbott and his team.

Joint graphical models combined with stability selection

Version: 1.0
Developer: Xiaoyun Liang, PhD

Joint graphical models combined with stability selection (JGMSS) is a software toolbox that can be employed to robustly estimate both individual- and group-level sparse networks. The software:

• Reads time series from a group of subjects;
• Subsamples data 100 times to estimate stability (i.e. stability selection);
• Group graphical-lasso constraints are applied, including two regularization parameters;
• Ranges of regularization parameters are chosen to implement stability selection; and
• The alternating direction method of multipliers (ADMM) approach is employed to solve the problem.

The method is described in A novel joint sparse partial correlation method for estimating group functional networks. Xiaoyun Liang, Alan Connelly, Fernando Calamante. Human Brain Mapping 12/2015. DOI: 10.1002/hbm.23092.

JGMSS is released under the GNU General Public License and is available for download.

MR tractography including crossing fibres

Principal developer: Donald Tournier, PhD
Co-developers: David Raffelt, PhD; Robert Smith, PhD; Ben Jeurissen, PhD; Fernando Calamante, PhD

MRtrix provides a set of tools to perform diffusion-weighted MR white-matter tractography in a manner robust to crossing fibres, using constrained spherical deconvolution (CSD) and probabilistic streamlines.

MRtrix is released under the GNU General Public License. The stable 0.2 version is available for download at NITRC and documentation for this version is available on Github. Note that this version is no longer under active development and now only receives bug fix updates.

The new MRtrix3 release, which includes the latest developments, is available on the MRtrix3 Website, along with its documentation. While this version isn’t yet an official release, it is already very stable. However, note that it is under active development, and as such subject to frequent changes.

The Numerical Fibre Generator

Version: 1.1.1
Developer: Tom Close

NFG is a collection of command-line tools that enable the generation of numerical fibre structures with a range of complexities spanning the levels expected of human white matter. Also included is a tool to simulate the diffusion-weighted MR (DW-MR) images that would arise from these structures under various imaging conditions. The primary use of the ‘Numerical Fibre Generator’ is to enable the testing of white-matter fibre tracking techniques based on DW-MRI.

All included tools are distributed under the GNU public licence (GPL) and are available for download.

Version: 1.4
Principal developer: Kaushik Bhaganagarapu
Co-developer: David Abbott, PhD.

SOCK (Spatially Organized Component Klassifikator) can be used to automatically identify a high proportion of the artifactual components arising in Independent Componenets Analysis (ICA) of fMRI. It is described in detail in An automated method for identifying artifact in Independent Component Analysis of resting-state fMRI. Bhaganagarapu K, Jackson GD, Abbott DF. Frontiers in Human Neuroscience 7(343):1-16 (2013). (doi: 10.3389/fnhum.2013.00343).

SOCK can also be used as an automated pre-processing noise filter in fMRI analysis pilpelines, via the included batch_SOCK routine. Use of SOCK as a noise filter is described in De-noising with a SOCK can improve the performance of event-related ICA. Bhaganagarapu K, Jackson GD, Abbott DF. Frontiers in Neuroscience 8(285):1-9 (2014). (doi: 10.3389/fnins.2014.00285).

The SOCK software is written in Matlab and presently works well with MELODIC ICA software (part of FSL from FMRIB).

SOCK software is released under the GNU General Public License, and is now available for download.

Group-fused multiple-graphical lasso combined with stability selection

A novel group-fused sparse partial correlation method for simultaneous estimation of functional networks in group comparisons. Group-fused multiple-graphical lasso combined with stability selection (GMGLASS) is a software toolbox that can be employed to simultaneously estimate both individual- and group-level functional networks from 2 groups.

The software:

• Reads time series from 2 groups of subjects;
• Randomly subsamples data 100 times to estimate stability with stability selection;
• Group-fused multiple-graphical lasso is applied with two hyper-parameters: alpha and beta;
• Appropriate ranges of hyper-parameters are chosen for achieving stability selection;
• Both individual- and group-level functional networks can be estimated.

The method is described in A novel group-fused sparse partial correlation method for simultaneous estimation of functional networks.in group comparison studies. Xiaoyun Liang, David N. Vaughan, Alan Connelly, Fernando Calamante. Brain Topography, 12/2017; DOI:10.1007/s10548-017-0615-6.

GMGLASS is released under the GNU General Public License and is available for download.

Group-level Network Hierarchical Clustering

Developer: Xiaoyun Liang, PhD

Group-level Network Hierarchical Clustering (GNetHiClus) is a software toolbox that can be used to extract hierarchical brain network modules at group level.

The software: (1) reads connectivity matrices from a group of subjects; (2) subsamples data to obtain subgroups; (3) extracts hierarchical brain subnetworks; (4) uses bootstrap method to estimate the most reliable subnetworks.

The method is described in A novel method for extracting hierarchical functional subnetworks based on a multi-subject spectral clustering approach. Xiaoyun Liang, Chun-Hung Yeh, Alan Connelly, Fernando Calamante. Brain Connectivity, 03/2019; DOI: 10.1089/brain.2019.0668.

GNetHiClus is released under the GNU General Public License and is available for download.