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JMLR
2011

Causal Time Series Analysis of Functional Magnetic Resonance Imaging Data

8 years 11 months ago
Causal Time Series Analysis of Functional Magnetic Resonance Imaging Data
This review focuses on dynamic causal analysis of functional magnetic resonance (fMRI) data to infer brain connectivity from a time series analysis and dynamical systems perspective. Causal influence is expressed in the Wiener-Akaike-Granger-Schweder (WAGS) tradition and dynamical systems are treated in a state space modeling framework. The nature of the fMRI signal is reviewed with emphasis on the involved neuronal, physiological and physical processes and their modeling as dynamical systems. In this context, two streams of development in modeling causal brain connectivity using fMRI are discussed: time series approaches to causality in a discrete time tradition and dynamic systems and control theory approaches in a continuous time tradition. This review closes with discussion of ongoing work and future perspectives on the integration of the two approaches.
Alard Roebroeck, Anil K. Seth, Pedro A. Valdes-Sos
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2011
Where JMLR
Authors Alard Roebroeck, Anil K. Seth, Pedro A. Valdes-Sosa
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