Classical and Bayesian inference in neuroimaging: theory
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Classical and Bayesian inference in neuroimaging: theory | |
Authors: | Karl J. Friston, Will Penny, Christophe Phillips, Stefan Kiebel, Geoffrey E. Hinton, John Ashburner |
Citation: | NeuroImage 16 : 465-483. 2002 |
Database(s): | Google Scholar cites PubMed (PMID/12030832) |
DOI: | 10.1006/nimg.2002.1090. |
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Restricted: | DTU Digital Library |
Other: | NIF |
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Format: | BibTeX Template from PMID |
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Classical and Bayesian inference in neuroimaging: theory describes methods for neuroimaging analysis of functional magnetic resonance imaging (fMRI). Specifically, Bayesian estimation of applied for the following topic:
- estimation of the serial correlation of fMRI scans
- spatiotemporal modeling, i.e., correlation among voxels and time.
- estimation of non-linear hemodynamic response models
- EEG source localization