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Open AccessJournal ArticleDOI

Statistical analysis of longitudinal neuroimage data with Linear Mixed Effects models.

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TLDR
The theory behind LME models is presented, it is contrasted with other popular approaches in the context of LNI, and the results suggest that the LME approach offers superior statistical power in detecting longitudinal group differences.
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This article is published in NeuroImage.The article was published on 2013-02-01 and is currently open access. It has received 317 citations till now.

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Journal ArticleDOI

Early role of vascular dysregulation on late-onset Alzheimer’s disease based on multifactorial data-driven analysis

Yasser Iturria-Medina, +314 more
TL;DR: Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development, suggesting early memory deficit associated with the primary disease factors.
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Head Motion during MRI Acquisition Reduces Gray Matter Volume and Thickness Estimates

TL;DR: It is shown that volume and thickness estimates of the cortical gray matter are biased by head motion with an average apparent volume loss of roughly 0.7%/mm/min of subject motion, suggesting that reported morphometric effects of movement disorders or other conditions with increased motion tendency may need to be revisited.
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Spatial patterns of neuroimaging biomarker change in individuals from families with autosomal dominant Alzheimer's disease: a longitudinal study

TL;DR: Mutation carriers had elevations in Aβ deposition, reduced glucose metabolism, and cortical thinning which preceded the expected onset of dementia, suggesting differential regional and temporal vulnerabilities to Aβ, metabolic decline, and structural atrophy, which should be taken into account when using biomarkers in a clinical setting.
Journal ArticleDOI

Linear mixed-effects modeling approach to FMRI group analysis

TL;DR: The simulations of one prototypical scenario indicate that the LME modeling keeps a balance between the control for false positives and the sensitivity for activation detection, and the importance of hypothesis formulation is also illustrated in the simulations.
References
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Journal ArticleDOI

Advances in functional and structural MR image analysis and implementation as FSL.

TL;DR: A review of the research carried out by the Analysis Group at the Oxford Centre for Functional MRI of the Brain (FMRIB) on the development of new methodologies for the analysis of both structural and functional magnetic resonance imaging data.
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Robust Locally Weighted Regression and Smoothing Scatterplots

TL;DR: Robust locally weighted regression as discussed by the authors is a method for smoothing a scatterplot, in which the fitted value at z k is the value of a polynomial fit to the data using weighted least squares, where the weight for (x i, y i ) is large if x i is close to x k and small if it is not.
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Cortical surface-based analysis. I. Segmentation and surface reconstruction

TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.
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Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain.

TL;DR: In this paper, a technique for automatically assigning a neuroanatomical label to each voxel in an MRI volume based on probabilistic information automatically estimated from a manually labeled training set is presented.
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Cortical Surface-Based Analysis II: Inflation, Flattening, and a Surface-Based Coordinate System

TL;DR: A set of procedures for modifying the representation of the cortical surface to inflate it so that activity buried inside sulci may be visualized, cut and flatten an entire hemisphere, and transform a hemisphere into a simple parameterizable surface such as a sphere for the purpose of establishing a surface-based coordinate system are designed.
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