Advances in functional and structural MR image analysis and implementation as FSL
Introduction
In recent years, magnetic resonance imaging and functional MRI have played an increasingly important role in the investigation of brain structure, function, development, and pathologies. The increasing flexibility and power of MRI and FMRI to answer scientifically interesting and clinically relevant questions have led to a demand for analysis techniques that allow investigators to interrogate their data in as flexible, scientifically informative, and convenient a manner as is possible. This paper presents an overview of research carried out with this aim in the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB).
The broadest distinction that can be drawn between MRI experiments in the brain is between structural experiments, which are sensitive to biophysical properties of local brain tissue, and functional experiments, which are sensitive to temporally changing neural activity. The two types of MRI data require very different analysis techniques and are grouped into separate sections in this paper, but the relationship between structure and function is fundamental to brain organization. The data analysis techniques and tools described in Functional MRI analysis research and Structural MRI analysis research allow investigators not only to learn from each source of information, but also to combine data from functional and structural experiments to better inform neuropsychological inference. FDT—diffusion and white matter connectivity analysis is an example of this interdependence between structure and function, investigating the influence of structural connectivity on brain function. Fundamental to the ability to draw inference from data is a thorough understanding of the processes involved in the data's creation. The research outlined in MR physics-related research gives examples of how to improve this understanding via direct modeling of the MR image acquisition process. Crucially, this allows investigators to increase the sensitivity of their MRI experiments through both improved experimental design and the reduction of acquisition-related image artefacts. Finally, FSL—FMRIB's software library describes briefly the freely available FSL software package, within which most of the research covered in this paper has been implemented.
Section snippets
Functional MRI analysis research
The fundamental challenge in the analysis of functional MRI experiments is to identify voxels that show signal changes varying with changing brain states. This is a difficult problem: firstly because the signal to noise ratio is generally poor, with the activation signal being often no larger than the noise level; secondly, the neurophysiology that couples the underlying brain activity to the measured response in FMRI is complex and generally poorly understood; and thirdly, the noise consists
Structural MRI analysis research
This section presents an overview of our research into the analysis of structural MRI data. The tools resulting from this research provide the means for making quantitative measurements of physiologically or clinically relevant parameters. For example, the combination in SIENA of brain extraction, tissue-type segmentation, and robust affine registration allows for the accurate measurement of temporal brain-volume change. However, these tools are also of crucial importance in the processing
FDT—diffusion and white matter connectivity analysis
The self-diffusion of water molecules in the brain is a sensitive probe of biological tissue microstructure and micro-biophysics. Among the tissue properties that contribute to the local diffusion characteristics is the local orientational structure of the tissue; most interestingly, diffusion is anisotropic in white matter, being greater in the direction of white matter tracts. By sensitizing the magnitude of the NMR spin-echo to local diffusion and by making assumptions about the structure of
PRELUDE and FUGUE—EPI distortion correction
Distortion of EPI-based functional images is a particular problem for high-field (3T and higher) MR scanners. The inhomogeneities in the magnetic field caused by susceptibility differences at air–tissue interfaces (predominantly near air-filled sinuses) result in both signal loss and geometric distortion of images. Such artefacts are particularly noticeable in the inferior temporal and frontal lobes, and restrict the use of standard FMRI or diffusion imaging techniques in these areas. In
FSL—FMRIB's software library
Most of the research carried out by the FMRIB Analysis Group has been made available to the wider community as a single integrated software package, FMRIB's Software Library (FSL). FSL is available as both source code and as self-contained binary distributions for Linux, MacOS X (Apple), Windows XP (under Cygwin), Solaris (Sun), and IRIX (Silicon Graphics). It is freely available for academic (noncommercial) use. Almost all tools can be run both from the command line and via GUIs. The FSL
Acknowledgments
We are grateful for financial support from the UK Medical Research Council, the UK Engineering and Physical Sciences Research Council, The Wellcome Trust, GlaxoSmithKline, and the Medical Images and Signals Inter-disciplinary Research Consortium (MIAS IRC). We also acknowledge vital collaborations with the many individuals listed at www.fmrib.ox.ac.uk/fsl/contributors.html.
References (45)
- et al.
Modelling geometric distortions in EPI time series
NeuroImage
(2001) - et al.
Estimation of the effective self-diffusion tensor from the NMR spin echo
J. Magn. Reson., B
(1994) - et al.
General multi-level linear modelling for group analysis in FMRI
NeuroImage
(2003) - et al.
To smooth or not to smooth?
NeuroImage
(2000) - et al.
Classical and Bayesian inference in neuroimaging: theory
NeuroImage
(2002) - et al.
Generalisability, random effects and population inference
- et al.
A global optimisation method for robust affine registration of brain images
Med. Image Anal.
(2001) - et al.
Improved optimisation for the robust and accurate linear registration and motion correction of brain images
NeuroImage
(2002) - et al.
Variability in fMRI: an examination of intersession differences
NeuroImage
(2000) - et al.
Accurate, robust and automated longitudinal and cross-sectional brain change analysis
NeuroImage
(2002)
Temporal autocorrelation in univariate linear modelling of FMRI data
NeuroImage
Multi-level linear modelling for FMRI group analysis using Bayesian inference
NeuroImage
Constrained linear basis sets for HRF modelling using Variational Bayes
NeuroImage
Spatio-temporal realignment of FMRI data
Probabilistic independent component analysis for functional magnetic resonance imaging
IEEE Trans. Med. Imag.
Tensorial extensions to independent component analysis for multi-subject/session FMRI data
Gaussian/Gamma mixture modelling of ICA/GLM spatial maps
Characterization and propagation of uncertainty in diffusion-weighted MR imaging
Magn. Reson. Med.
Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging
Nat. Neurosci.
How experimental design and first-level filtering influence efficiency in second-level analysis of event-related fMRI data
Functional connectivity in the motor cortex of resting human brain using echo-planar MRI
Magn. Reson. Med.
Dynamics of blood flow and oxygenation changes during brain activation: the balloon model
Magn. Reson. Med.
Cited by (10581)
CycleFormer: Brain tissue segmentation in the presence of Multiple Sclerosis lesions and Intensity Non-Uniformity artifact
2024, Biomedical Signal Processing and ControlVolumetric brain MRI signatures of heart failure with preserved ejection fraction in the setting of dementia
2024, Magnetic Resonance ImagingNeural correlates of inhibitory control in the context of infant cry and paternal postpartum mental health
2024, Behavioural Brain Research