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Advances in functional and structural MR image analysis and implementation as FSL
The techniques available for the interrogation and analysis of neuroimaging data have a large influence in determining the flexibility, sensitivity, and scope of neuroimaging experiments. TheExpand
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Characterization and propagation of uncertainty in diffusion‐weighted MR imaging
A fully probabilistic framework is presented for estimating local probability density functions on parameters of interest in a model of diffusion. This technique is applied to the estimation ofExpand
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FSL (the FMRIB Software Library) is a comprehensive library of analysis tools for functional, structural and diffusion MRI brain imaging data, written mainly by members of the Analysis Group, FMRIB,Expand
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Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?
We present a direct extension of probabilistic diffusion tractography to the case of multiple fibre orientations. Using automatic relevance determination, we are able to perform online selection ofExpand
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Bayesian analysis of neuroimaging data in FSL
Typically in neuroimaging we are looking to extract some pertinent information from imperfect, noisy images of the brain. This might be the inference of percent changes in blood flow in perfusionExpand
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Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging
Evidence concerning anatomical connectivities in the human brain is sparse and based largely on limited post-mortem observations. Diffusion tensor imaging has previously been used to define largeExpand
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Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data
In functional magnetic resonance imaging statistical analysis there are problems with accounting for temporal autocorrelations when assessing change within voxels. Techniques to date have utilizedExpand
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Network modelling methods for FMRI
There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting aExpand
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Learning the value of information in an uncertain world
Our decisions are guided by outcomes that are associated with decisions made in the past. However, the amount of influence each past outcome has on our next decision remains unclear. To ensureExpand
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Investigating the electrophysiological basis of resting state networks using magnetoencephalography
In recent years the study of resting state brain networks (RSNs) has become an important area of neuroimaging. The majority of studies have used functional magnetic resonance imaging (fMRI) toExpand
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