The role of noise modeling in the estimation of resting-state brain effective connectivity. Issue 15 (2018)

• Record Type: Journal Article
• Authors: Prando, G.; Zorzi, M.; Bertoldo, A.; Chiuso, A.
• Is Part Of: IFAC-PapersOnLine. Volume 51:Issue 15(2018)
• Page Start: 527
• Page End: 532
• Publication Date: 2018
• Subjects: System identification -- Estimation -- filtering -- Neuroscience; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2018.09.206
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Causal relations among neuronal populations of the brain are studied through the so-called effective connectivity (EC) network. This is estimated from EEG or fMRI measurements, by inverting a generative model of the corresponding data. It is clear that the goodness of the estimated network heavily depends on the modeling assumptions. In this present paper we consider the EC estimation problem using fMRI data in resting-state condition. Specifically, we investigate on how to model endogenous fluctuations driving the neuronal activity.