Bayesian modelling of fMRI time series

Advances in Neural Information Processing Systems

Volumn , Issue , 2000, Pages 754-760

  Højen Sørensen, Pedro A D F R ^a   Hansen, Lars K ^a   Rasmussen, Carl Edward ^a  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

HIDDEN MARKOV MODELS; NEURONS;

BAYESIAN METHODOLOGY; BAYESIAN MODELLING; LEARNING EFFECTS; MARKOV CHAIN MONTE CARLO; NEURAL ACTIVITY; PSYCHOLOGICAL STATE; SAMPLING TECHNIQUE; SINGLE TRIAL;

EXPERIMENTS;

EID: 17644380855     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

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2. Dale, A. M. and R. L. Buckner (1997). Selective Averaging of Individual Trials Using fMRI. Neurolmage 5, Abstract S47.
3. Green, P. J. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82,711-732.
4. Gilks, W. R. and P. Wild (1992). Adaptive rejection sampling for Gibbs sampling. Applied Statistics 41, 337-348.
5. Hansen, L. K. et al. (1999). Generalizable Patterns in Neuroimaging: How Many Principal Components? Neurolmage, to appear.
6. Lange, N. and S. L. Zeger (1997). Non-linear Fourier time series analysis for human brain mapping by functional magnetic resonance imaging. Journal of the Royal Statistical Society-Series C Applied Statistics 46, 1-30.
7. McKeown, M. J. et al. (1998). Spatially independent activity patterns in functional magnetic resonance imaging data during the stroop color-naming task. Proc. Natl. Acad. Sci. USA. 95, 803-810.
8. Worsley, K. J. et al. (1997). Characterizing the Response of PET and fMRI Data Using Multivariate Linear Models (MLM). Neurolmage 6, 305-319.