Resource:A general statistical analysis for fMRI data
|Name:||Resource:A general statistical analysis for fMRI data|
The fMRI data was first converted to percentage of whole volume. The statistical analysis of the percentages was based on a linear model with correlated errors. The design matrix of the linear model was first convolved with a hemodynamic response function modelled as a difference of two gamma functions timed to coincide with the acquisition of each slice. Temporal drift was removed by adding a cubic spline in the frame times to the design matrix (one covariate per 2 minutes of scan time), and spatial drift was removed by adding a covariate in the whole volume average. The correlation structure was modelled as an autoregressive process of degree 1. At each voxel, the autocorrelation parameter was estimated from the least squares residuals using the Yule-Walker equations, after a bias correction for correlations induced by the linear model. The autocorrelation parameter was first regularized by spatial smoothing, then used to `whiten' the data and the design matrix. The linear model was then re-estimated using least squares on the whitened data to produce estimates of effects and their standard errors.
|Is part of:||McGill University; Montreal; Canada|
|Has role:||web accessible database (nlx_res_090910)|
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Curation status: Curated
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The fMRI data was first converted …
f effects and their standard errors.
|Has role||Web accessible database (nlx res 090910) +|
|Is part of||McGill University; Montreal; Canada +|
|Label||Resource:A general statistical analysis for fMRI data +|
|ModifiedDate||18 May 2011 +|
|Page has default formThis property is a special property in this wiki.||Resource +|