#### Filter Results:

- Full text PDF available (3)

#### Publication Year

2006

2015

- This year (0)
- Last 5 years (1)
- Last 10 years (6)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

#### Method

Learn More

- Alicia Quirós Carretero, Raquel Montes Diez, Dani Gamerman
- NeuroImage
- 2010

This research describes a new Bayesian spatiotemporal model to analyse block-design BOLD fMRI studies. In the temporal dimension, we parameterise the hemodynamic response function's (HRF) shape with a potential increase of signal and a subsequent exponential decay. In the spatial dimension, we use Gaussian Markov random fields (GMRF) priors on activation… (More)

- Alicia Quirós Carretero, Raquel Montes Diez, Simon P. Wilson
- NeuroImage
- 2010

This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. The spatial continuity and local homogeneity of the evoked responses are modelled by a Gaussian Markov random field prior on the parameter… (More)

- Alicia Quirós Carretero, Simon P. Wilson, Raquel Montes Diez, Ana Beatriz Solana, Juan Antonio Hernández Tamames
- Digital Signal Processing
- 2015

a r t i c l e i n f o a b s t r a c t Article history: Available online xxxx Keywords: Bayesian analysis Dynamic linear models fMRI Resting-state This work shows an example of the application of Bayesian dynamic linear models in fMRI analysis. Estimating the error variances of such a model, we are able to obtain samples from the posterior distribution of… (More)

- Alicia Quirós Carretero, Simon P. Wilson
- 2011 19th European Signal Processing Conference
- 2011

Source separation is a common task in signal processing and is often analogous to factor analysis. In this work we look at a factor analysis model for source separation of multi-spectral image data where prior information about the sources and their dependencies is quantified as a multivariate Gaussian mixture model with an unknown number of factors.… (More)

- Simon P. Wilson, Ercan E. Kuruoglu, Alicia Quirós Carretero
- 2010 2nd International Workshop on Cognitive…
- 2010

In this paper a fully Bayesian factor analysis model is developed that assumes a very general model for each factor, namely the Gaussian mixture. We discuss the cases where factors are both independent and dependent. In the statistical literature, factor analysis has been used principally as a dimension reduction technique, with little interest in a priori… (More)

- Alicia Quirós Carretero, Raquel Montes Diez
- BIOSIGNALS
- 2009

- ‹
- 1
- ›