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The General Linear Model for fMRI analysis

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The General Linear Model for fMRI analysis

Global effects, correlation/orthogonalisation, time-series convolution models, high-pass filtering, temporal auto-correlation, maximum likelihood (ML) estimation, non-sphericity, Statistical Parametric Maps (SPMs) and Random Field Theory Correction, Group-level inference; Parametric Empirical Bayesian Inference

This talk is part of the Statistical Parametric Mapping (SPM) series.

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