Martedì 20 luglio, dalle 18 alle 19
Aula B del Dipartimento di Matematica

Palazzo delle Scienze - Via Ospedale

  

Seminario di statistica “ Spatiotemporal modelling of fMRI data” a cura di:

 

Departmento de Estadística e Investigación Operativa

Universidad Rey Juan Carlos (Madrid)

 

  

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SCHEDA

We analyse functional Magnetic Resonance Imaging (fMRI) data to find areas of brain activity. fMRI is a non-invasive technique for obtaining a series of images over time under a certain stimulation paradigm and regions of brain activity are detected by observing diferences in blood magnetism due to hemodynamic response to this stimulus.

In this work we propose a Bayesian spatiotemporal model to analyse fMRI studies. In the temporal dimension, we parameterise the hemodynamic response function's shape with a transfer function model. In the spatial dimension, we use Gaussian Markov random fields priors that embody our prior knowledge that evoked responses are spatially contiguous and locally homogeneous. These powerful tools provide a framework for detecting active regions much as a neurologist might as they allow us to consider the level of the voxel magnitudes along with the size of the activated area.

Due to the model complexity, we use MCMC methods to make inference over the unknown parameters. Simulations from the model are performed in order to ascertain the performance of the sampling scheme and the ability of the posterior to estimate model parameters. Results are shown on synthetic data and on real data from a block-design fMRI experiment. 

 

  

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INFO

 

Stefano Cabras

Dipartimento di Matematica e Informatica

Via Ospedale, 72 (+39 070/6758516)

s.cabras@unica.it