Online analysis of local field potentials for seizure detection in freely moving rats

Document Type: Original Article

Authors

1 Department of Physiology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

2 Department of Technology, Electrical Engineering, Sharif University, Tehran

3 Department of Brain and Cognitive Sciences, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR, Tehran, Iran

4 Institute for Brain Sciences and Cognition, Tarbiat Modares University, Tehran, Iran

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


1. Christensen J, Vestergaard M, Pedersen MG, Pedersen CB, Olsen J, Sidenius P. Incidence and prevalence of epilepsy in Denmark. Epilepsy Res 2007; 76:60–65.
2. Herman ST. Epilepsy after brain insult: targeting epileptogenesis. Neurology 2002; 59:21-26.
3. Chang BS, Lowenstein DH. Epilepsy. N Engl J Med 2003; 349:1257–1266.
4. Kwan P, Brodie MJ. Early identification of refractory epilepsy. N Engl J Med 2000; 342:314–319.
5. Sillanpaa M, Jalava M, Kaleva O, Shinnar S. Long-term prognosis of seizures with onset in childhood. N Engl J Med 1998; 338:1715–1722.
6. Scorza FA, Arida RM, Naffah-Mazzacoratti MdG, Scerni DA, Calderazzo L, Cavalheiro EA. The pilocarpine model of epilepsy: what have we learned? An Acad Bras Cienc 2009; 81:345–365.
7. Cendes F, Andermann F, Gloor P, Evans A, Jones-Gotman M, Watson C et al. MRI volumetric measurement of amygdala and hippocampus in temporal lobe epilepsy. Neurology 1993; 43:719–725.
8. Boulton AA, editor. Neurophysiological Techniques: Applications to Neural Systems. Totowa, NJ: Humana Press; 1991.
9. Kajikawa Y, Schroeder CE. How local is the local field potential? Neuron 2011; 72:847–858.
10. Kile KB, Tian N, Durand DM. Low frequency stimulation decreases seizure activity in a mutation model of epilepsy. Epilepsia 2010; 51:1745–1753.
11. Ramgopal S, Thome-Souza S, Jackson M, Kadish NE, Sánchez Fernández I, Klehm J et al. Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy. Epilepsy Behav 2014; 37:291–307.
12. Elliott RE, Morsi A, Tanweer O, Grobelny B, Geller E, Carlson C et al. Efficacy of vagus nerve stimulation over time: review of 65 consecutive patients with treatment-resistant epilepsy treated with VNS 10 years. Epilepsy Behav 2011; 20:478–483.
13. Morrell M. Brain stimulation for epilepsy: Can scheduled or responsive neurostimulation stop seizures? Curr Opin Neurol 2006; 19:164–168.
14. Rashid S, Pho G, Czigler M, Werz MA, Durand DM. Low frequency stimulation of ventral hippocampal commissures reduces seizures in a rat model of chronic temporal lobe epilepsy. Epilepsia 2012; 53:147–156.
15. Hodaie M, Wennberg RA, Dostrovsky JO, Lozano AM. Chronic anterior thalamus stimulation for intractable epilepsy. Epilepsia 2002; 43:603–608.
16. Pavlova MK, Shea SA, Bromfield EB. Day/night patterns of focal seizures. Epilepsy Behav 2004; 5:44–49.
17. Good LB, Sabesan S, Marsh ST, Tsakalis K, Treiman D, Iasemidis L. Control of synchronization of brain dynamics leads to control of epileptic seizures in rodents. Int J Neural Syst 2009; 19:173–196.
18. Sun FT, Morrell MJ. The RNS System: Responsive cortical stimulation for the treatment of refractory partial epilepsy. Expert Rev Med Devices 2014; 11:563–572.
19. Fisher RS, Velasco AL. Electrical brain stimulation for epilepsy. Nat Rev Neurol 2014; 10:261–270.
20. Schad A, Schindler K, Schelter B, Maiwald T, Brandt A, Timmer J et al. Application of a multivariate seizure detection and prediction method to non-invasive and intracranial long-term EEG recordings. Clin Neurophysiol 2008; 119:197–211.
21. Aarabi A, Fazel-Rezai R, Aghakhani Y. A fuzzy rule-based system for epileptic seizure detection in intracranial EEG. Clin Neurophysiol 2009; 120:1648–1657.
22. Salam M, Sawan M, Nguyen D. Low-power implantable device for onset detection and subsequent treatment of epileptic seizures: A review. J Helthc Eng 2010; 1:169–184.
23. Salam MT, Sawan M, Dang KN. A novel low-power-implantable epileptic seizure-onset detector. IEEE Trans Biomed Circuits Syst 2011; 5:568–578.
24. Safi-Harb M, Salam MT, Nguyen DK, Sawan M. An implantable seizure-onset detector based on a dual-path single-window count-based technique for closed-loop applications. IEEE J Emerg. Sel. Topics Circuits Syst. 2011; 1:603–612.
25. Racine RJ. Modification of seizure activity by electrical stimulation: II. Motor seizure. Electroencephalography and Clinical Neurophysiology 1972; 32:281–294.
26. Toyoda I, Bower MR, Leyva F, Buckmaster PS. Early activation of ventral hippocampus and subiculum during spontaneous seizures in a rat model of temporal lobe epilepsy. J Neurosci 2013; 33:11100–11115.
27. Imtiaz SA, Logesparan L, Rodriguez-Villegas E. Performance-power consumption tradeoff in wearable epilepsy monitoring systems. IEEE J Biomed Health Inform 2015; 19:1019–1028.
28. Jouny CC, Bergey GK. Characterization of early partial seizure onset: Frequency, complexity and entropy. Clin Neurophysiol 2012; 123:658–669.
29. Novak V, Reeves AL, Novak P, Low PA, Sharbrough FW. Time-frequency mapping of R-R interval during complex partial seizures of temporal lobe origin. J Auton Nerv Syst 1999; 77:195–202.
30. Acharya UR, Fujita H, Sudarshan VK, Bhat S, Koh JE. Application of entropies for automated diagnosis of epilepsy using EEG signals: A review. Knowledge-based systems 2015; 88:85–96.
31. Song Y, Crowcroft J, Zhang J. Automatic epileptic seizure detection in EEGs based on optimized sample entropy and extreme learning machine. J Neurosci Methods 2012; 210:132–146.
32. Ghasemi Z, Naderi N, Shojaei A, Ahmadirad N, Raoufy MR, Mirnajafi-Zadeh J. Low frequency electrical stimulation attenuated the epileptiform activity-induced changes in action potential features in hippocampal CA1 pyramidal neurons. Cell J 2018; 20:355–360.