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- W4300697790 abstract "Causal relations among neuronal populations of the brain are studied through the so-called effective connectivity (EC) network. The latter 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 underlying 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." @default.
- W4300697790 created "2022-10-04" @default.
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- W4300697790 date "2018-02-13" @default.
- W4300697790 modified "2023-09-26" @default.
- W4300697790 title "The role of noise modeling in the estimation of resting-state brain effective connectivity" @default.
- W4300697790 doi "https://doi.org/10.48550/arxiv.1802.05533" @default.
- W4300697790 hasPublicationYear "2018" @default.
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