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Titolo:
PROBABILISTIC ANALYSIS OF FUNCTIONAL MAGNETIC-RESONANCE-IMAGING DATA
Autore:
FRANK LR; BUXTON RB; WONG EC;
Indirizzi:
VET ADM MED CTR,9114-MRI,3350 LA JOLLA VILLAGE DR SAN DIEGO CA 92161 UNIV CALIF SAN DIEGO,DEPT RADIOL SAN DIEGO CA 92103
Titolo Testata:
Magnetic resonance in medicine
fascicolo: 1, volume: 39, anno: 1998,
pagine: 132 - 148
SICI:
0740-3194(1998)39:1<132:PAOFMD>2.0.ZU;2-I
Fonte:
ISI
Lingua:
ENG
Soggetto:
HUMAN BRAIN; BAYESIAN-ANALYSIS; PARAMETER-ESTIMATION; SENSORY STIMULATION; SIGNAL-DETECTION; MODEL SELECTION; FMRI; MRI; ACTIVATION; ARTIFACTS;
Keywords:
FMRI DATA ANALYSIS; PROBABILITY THEORY; TIME SERIES ANALYSIS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Science Citation Index Expanded
Citazioni:
35
Recensione:
Indirizzi per estratti:
Citazione:
L.R. Frank et al., "PROBABILISTIC ANALYSIS OF FUNCTIONAL MAGNETIC-RESONANCE-IMAGING DATA", Magnetic resonance in medicine, 39(1), 1998, pp. 132-148

Abstract

Probability theory is applied to the analysis of fMRI data. The posterior distribution of the parameters is shown to incorporate all the information available from the data, the hypotheses, and the prior information. Under appropriate simplifying conditions, the theory reduces to the standard statistical test, including the general linear model. The theory is particularly suited to handle the spatial variations in the noise present in fMRI, allowing the comparison of activated voxels that have different, and unknown, noise. The theory also explicitly includes prior information, which is shown to be critical in the attainment of reliable activation maps.

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Documento generato il 31/03/20 alle ore 22:32:13