Exploring neural directed interactions with transfer entropy based on an adaptive kernel density estimator.

Kai Zuo (1, 2) , Jean-Jacques Bellanger (3) , Chunfeng Yang (1, 2) , Huazhong Shu (1, 2) , Regine Le Bouquin Jeannes (3)

1 LIST - Laboratory of Image Science and Technology [Nanjing]
2 CRIBS - Centre de Recherche en Information Biomédicale sino-français
3 LTSI - Laboratoire Traitement du Signal et de l'Image

This paper aims at estimating causal relationships between signals to detect flow propagation in autoregressive and physiological models. The main challenge of the ongoing work is to discover whether neural activity in a given structure of the brain influences activity in another area during epileptic seizures. This question refers to the concept of effective connectivity in neuroscience, i.e. to the identification of information flows and oriented propagation graphs. Past efforts to determine effective connectivity rooted to Wiener causality definition adapted in a practical form by Granger with autoregressive models. A number of studies argue against such a linear approach when nonlinear dynamics are suspected in the relationship between signals. Consequently, nonlinear nonparametric approaches, such as transfer entropy (TE), have been introduced to overcome linear methods limitations and promoted in many studies dealing with electrophysiological signals. Until now, even though many TE estimators have been developed, further improvement can be expected. In this paper, we investigate a new strategy by introducing an adaptive kernel density estimator to improve TE estimation.

Mots clés: bioelectric phenomena; brain models; causality; electroencephalography; entropy; medical signal detection; neurophysiology; nonlinear dynamical systems; stochastic processes

Domaines: Ingénierie biomédicale; Traitement du signal et de l'image [eess.SP]; Traitement du signal et de l'image [eess.SP]

Kai Zuo, Jean-Jacques Bellanger, Chunfeng Yang, Huazhong Shu, Regine Le Bouquin Jeannes. Exploring neural directed interactions with transfer entropy based on an adaptive kernel density estimator.. Conference proceedings : .. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2013, 2013, pp.4342-5. ⟨10.1109/EMBC.2013.6610507⟩. ⟨hal-00881459⟩