Title of article :
Online analysis of local field potentials for seizure detection in freely moving rats
Author/Authors :
Zare, Meysam Department of Physiology - Faculty of Medical Sciences - Tarbiat Modares University, Tehran , Nazari, Milad Department of Technology - Electrical Engineering - Sharif University, Tehran , Shojaei, Amir Department of Brain and Cognitive Science - Cell Science Research Center - Royan Institute for Stem Cell Biology and Technology - ACECR, Tehran , Raoufy, Mohammad Reza Department of Physiology - Faculty of Medical Sciences - Tarbiat Modares University, Tehran , Mirnajafi-Zadeh, Javad Institute for Brain Sciences and Cognition - Tarbiat Modares University, Tehran - Department of Physiology - Faculty of Medical Sciences - Tarbiat Modares University, Tehran
Pages :
5
From page :
173
To page :
177
Abstract :
Objective(s): Seizure detection during online recording of electrophysiological parameters is very important in epileptic patients. In the present study, online analysis of field potential recordings was used for detecting spontaneous seizures in epileptic animals. Materials and Methods: Epilepsy was induced in rats by pilocarpine injection. During the chronic period of the pilocarpine model, local field potential (LFP) recording was run for at least 24 hr. At the same time, video monitoring of the animals was done to determine the real time of seizure occurrence. Both power and sample entropy of LFP were used for online analysis. Results: Obtained results showed that changes in LFP power are a better index for seizure detection. In addition, when we used one hundred consecutive epochs (each epoch equals 10 ms) of LFP for data analysis, the best detection was achieved. Conclusion: It may be suggested that power is a suitable parameter for online analysis of LFP in order to detect the spontaneous seizures correctly.
Keywords :
Entropy , Local field potentials , Pilocarpine , Power , Seizure detection
Journal title :
Astroparticle Physics
Serial Year :
2020
Record number :
2487024
Link To Document :
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