fMRI is a powerful tool used in the study of brain function. It can noninvasively detect signal changes in areas of the brain where neuronal activity is varying. This chapter is a comprehensive description of the various steps in the statistical analysis of fMRI data. This will cover topics such as the general linear model (including orthogonality, hemodynamic variability, noise modeling, and the use of contrasts), multi-subject statistics, and statistical thresholding (including random field theory and permutation methods, as well as a discussion of some recent controversies about correction for multiple comparisons of statistical models).

Statistical Analysis of fMRI Data / Woolrich, M. W.; Beckmann, C. F.; Nichols, T. E.; Smith, S. M.; Valsasina, P.; Rocca, M. A.; Filippi, M.. - 220:(2025), pp. 193-252. [10.1007/978-1-0716-4438-6_7]

Statistical Analysis of fMRI Data

Rocca M. A.
Penultimo
;
Filippi M.
Ultimo
2025-01-01

Abstract

fMRI is a powerful tool used in the study of brain function. It can noninvasively detect signal changes in areas of the brain where neuronal activity is varying. This chapter is a comprehensive description of the various steps in the statistical analysis of fMRI data. This will cover topics such as the general linear model (including orthogonality, hemodynamic variability, noise modeling, and the use of contrasts), multi-subject statistics, and statistical thresholding (including random field theory and permutation methods, as well as a discussion of some recent controversies about correction for multiple comparisons of statistical models).
2025
978-1-0716-4437-9
fMRI analysis
Statistics
Multi-subject statistics
Statistical thresholding
General linear model (GLM)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/186116
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