Title :
Inferring causal connectivity in epileptogenic zone using directed information
Author :
Malladi, Rakesh ; Kalamangalam, Giridhar P. ; Tandon, Nitin ; Aazhang, Behnaam
Author_Institution :
Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA
Abstract :
Directed information, an information theoretic quantity, is developed in this paper to infer the causal connectivity from electrocorticography (ECoG) recordings of an epileptic patient. The causal connectivity can be used to infer the optimal electrodes for electrical stimulation based treatments of epilepsy. A parametric estimator for directed information between two ECoG signals is also proposed. The estimator estimates entropy and causally conditioned entropy and their difference is the estimate of DI. The estimator is then applied to ECoG data recorded from the electrodes in the epileptogenic zone (EZ) in two patients with focal epilepsy to learn the changes in causal connectivity during seizures.
Keywords :
bioelectric phenomena; biomedical electrodes; causality; electroencephalography; entropy; inference mechanisms; medical computing; medical disorders; neurophysiology; patient treatment; DI estimation; causal connectivity change; causal connectivity inference; causally conditioned entropy estimation; directed information; electrical stimulation based treatment; electrocorticography; epilepsy treatment; epileptic patient ECoG recording; epileptogenic zone; focal epilepsy patient EZ; information theoretic quantity; optimal electrode; parametric estimator; seizure; Channel estimation; Electrical stimulation; Electrodes; Entropy; Epilepsy; Measurement; Uncertainty; Directed information; ECoG; causal connectivity; entropy; epilepsy;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178084