title: EEG-fMRI Bayesian framework for neural activity estimation: a simulation study.
abstract: Due to the complementary nature of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), and given the possibility of simultaneous acquisition, the joint data analysis can afford a better understanding of the underlying neural activity estimation. In this simulation study we want to show the benefit of the joint EEG-fMRI neural activity estimation in a Bayesian framework.
  
  
  
  We built a dynamic Bayesian framework in order to perform joint EEG-fMRI neural activity time course estimation. The neural activity is originated by a given brain area and detected by means of both measurement techniques. We have chosen a resting state neural activity situation to address the worst case in terms of the signal-to-noise ratio. To infer information by EEG and fMRI concurrently we used a tool belonging to the sequential Monte Carlo (SMC) methods: the particle filter (PF).
  
  
  
  First, despite a high computational cost, we showed the feasibility of such an approach. Second, we obtained an improvement in neural activity reconstruction when using both EEG and fMRI measurements.
  
  
  
  The proposed simulation shows the improvements in neural activity reconstruction with EEG-fMRI simultaneous data. The application of such an approach to real data allows a better comprehension of the neural dynamics.
authors: Department of Neuroscience, Imaging and Clinical Sciences, "G.d'Annunzio" University, Chieti, Italy. Institute of Advanced Biomedical Technologies, "G.d'Annunzio" University, Chieti, Italy.
authors: Pierpaolo
authors: P
authors: Croce
authors: Alessio
authors: A
authors: Basti
authors: Laura
authors: L
authors: Marzetti
authors: Filippo
authors: F
authors: Zappasodi
authors: Cosimo Del
authors: CD
authors: Gratta
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002560:Cerebrovascular Circulation / Q000502:physiology; D003198:Computer Simulation; D004569:Electroencephalography / Q000706:statistics & numerical data*; D005240:Feasibility Studies; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D008959:Models, Neurological; D009010:Monte Carlo Method; D009424:Nervous System Physiological Phenomena; D059629:Signal-To-Noise Ratio