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Journal Articles Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference Year : 2010

Detecting causal interdependence in simulated neural signals based on pairwise and multivariate analysis.

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Abstract

Our objective is to analyze EEG signals recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different phases are observed during the seizure process, including a fast onset activity (FOA). We aim to determine how cerebral structures get involved during this FOA, in particular whether some structure can "drive" some other structures. This paper focuses on a linear Granger causality based measure to detect causal relation of interdependence in multivariate signals generated by a physiology-based model of coupled neuronal populations. When coupling between signals exists, statistical analysis supports the relevance of this index for characterizing the information flow and its direction among neuronal populations.
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inserm-00540501 , version 1 (03-12-2010)

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Chufeng Yang, Régine Le Bouquin Jeannes, Gérard Faucon, Fabrice Wendling. Detecting causal interdependence in simulated neural signals based on pairwise and multivariate analysis.. Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2010, 1, pp.162-5. ⟨10.1109/IEMBS.2010.5627241⟩. ⟨inserm-00540501⟩
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