Modelling the neurovascular habituation effect on fMRI time series

In this paper, a novel non-stationary model of functional Magnetic Resonance Imaging (fMRI) time series is proposed. It allows us to account for some putative habituation effect arising in event-related fMRI paradigms that involves the so-called repetitionsuppression phenomenon [1] and induces decreasing magnitude responses over successive trials. Akin to [2], this model is defined over functionnally homogeneous regions-of-interest (ROIs) and embedded in a joint detection-estimation approach of brain activity. Importantly, its non-stationarity character is embodied in the trial-varying nature of the BOLD response magnitude. Habituation and activation maps are then estimated within the Bayesian framework in a fully unsupervised MCMC procedure. On artificial fMRI datasets, we show that habituation effects can be accurately recovered in activating voxels.

• Type: Journal
• Year: 2009
• Where: ICASSP
• Authors: Philippe Ciuciu, Stéphane Sockeel, Thomas Vincent, Jérôme Idier
• Keywords: FMRI, Functional Magnetic Resonance Imaging, Habituation Effects, ICASSP 2009, Signal Processing