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Dec 11, 2018 – MOTU PATLUKINGFKINGS Bollywood Dubbed Movie King. between the two brains, which can be quantitatively measured as regional mean thickness for a set of ROI. Differences in thickness across the two brains can be compared in conjunction with other structural parameters, such as volume, surface area, and spatial extent. While there are numerous potential measures for this calculation, this example uses an ‘average over all the ROIs’ approach. The underlying assumption is that, on average, this measure is a good proxy of any regionally specific change. To assess the adequacy of this assumption, the difference in grey matter thickness between the two brains should be correlated with other measures of structural change in either brain, such as differences in volume and surface area in the left hemisphere, or differences in spatial extent in the right hemisphere.
Spatial normalisation
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The second major component of using the VBM toolbox is registration. The shape of the brain varies widely in the population, both within and between individuals. For example, children differ in their brain size from adults, and frequently have higher overall surface area, which corresponds with higher white matter volumes \[[@B22]\]. Using a single template for the entire population can mask significant differences between individuals, which are ultimately of interest, and produce a baseline that is not representative of a single individual. Therefore, it is generally more informative to compare brains between individuals with a normalisation step. There are two major approaches to this normalisation: coarse or fine (manual or automated). For many analyses, which require a set of common images, coarse normalisation, typically by aligning the images to the MNI space with affine transformations, can be performed adequately. For some analyses, finer normalisation (to the study-specific template), which uses the information to estimate rigid transformations, should be performed to align the images with better accuracy \[[@B23]\]. The criteria for choosing which type of normalisation method to use are numerous, including the brain size of the sample, the spatially localised changes of interest, the type and distribution of structural abnormalities in the population, the amount of localised change desired, and the degree of accuracy required for the analysis. In this study, rigid registration was used for all the comparisons.
Post-processing and statistical analysis
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The third component is post-processing. The segmentation and normalisation steps cannot alter the input data, but may significantly affect
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