کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6023742 | 1580876 | 2016 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب شناختی
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![عکس صفحه اول مقاله: Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data](/preview/png/6023742.png)
چکیده انگلیسی
Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: NeuroImage - Volume 132, 15 May 2016, Pages 373-389
Journal: NeuroImage - Volume 132, 15 May 2016, Pages 373-389
نویسندگان
Martyn McFarquhar, Shane McKie, Richard Emsley, John Suckling, Rebecca Elliott, Stephen Williams,