Abstracts

Multiplicity of Seizure Dynamotypes in Individual Epilepsy Contributes to the Propagation of the Seizure: A Retrospective Study Including Rats and Clinical Patients

Abstract number : 2.055
Submission category : 3. Neurophysiology / 3F. Animal Studies
Year : 2021
Submission ID : 1825909
Source : www.aesnet.org
Presentation date : 12/5/2021 12:00:00 PM
Published date : Nov 22, 2021, 06:51 AM

Authors :
Christophe Bernard, PhD - INSERM UMR_S 1106, Institut de Neuroscience des Systemes - INS; Mitsuyoshi Nakatani - Aix Marseille University; Izumi Toyoda – Department of Neurology/Neurosurgery – UC Davis School of Veterinary Medicine; Francesca Pizzo – Department of Clinical Neurophysiology and Epileptology – AMPM, Timon hospital; Paul S Buckmaster – Department of Neurology and Neurological Sciences – Stanford University; Fabrice Bartolomei – Department of Clinical Neurophysiology and Epileptology – APHM, Timone hospital

Rationale: The classification and propagation patterns of epileptic seizures can provide practical information for the treatment of epilepsy. Among the 16 possible classifications of ictal onset and offset based on seizure dynamics, the saddle node/homoclinic (SN/SH), which is characterized by ictal Direct Current (DC) shift, seems to be predominant across species. We predicted that individuals with epilepsy may express different types of seizures and different propagation patterns during the ictal period. We tested these hypotheses using data from an experimental model of temporal lobe epilepsy and from patients with intractable partial epilepsy.

Methods: We enrolled 10 male Sprague-Dawley rats treated with pilocarpine (380 mg/kg, i.p.), which developed spontaneous epileptic seizures. We also employed 12 patients who showed more than 5 seizures during Stereo-electroencephalography (SEEG) implantation from 2017 to 2018 at Timone Hospital. EEG was obtained with a Microdrive with bandpass filter (0.1-Hz) and sampling rate 2-kHz for rats, whereas with 256‐ channel Deltamed system, at a 256-, 1024‐ or 2048-Hz sampling frequency and high-pass filter of 0.16-Hz for clinical patients. Each seizure was classified based upon the type of onset (SN, SNIC, SupH, or SubH) and offset (SH, SNIC SupH, or FLC). We evaluated i) seizure duration, ii) the amplitude of ictal DC shift (only for animal data), iii) the number of brain regions which exceeded the defined threshold of low gamma (Lγ: 30-50 Hz) power during seizure propagation. We tested whether these factors are different between the seizures starting from SN onset and other onsets.

Results: A total of 8 rats with 405 seizures and 12 patients with 216 seizures were included. In line with our hypotheses, we confirmed the existence of several types of seizures in individual animals and patients. In rats, the most common form of seizure (approximately 50% for each animal) is characterized by a DC shift at onset, whereas in human, approximately 25% of seizures showed SN onset. The duration of seizures with SN onset showed inverse proportion to the amplitude of ictal DC shift in rats. Despite the fact that EEG attenuation often follow SN onset, the group comparison show that abnormal EEG patterns represented by Lγ easily propagated to wider area in SN onset seizures. Similar results were also found in patients in terms of the relationships between onset types and seizure duration/propagation pattern. Although we did not find clear relationships between conscious level and seizure onset types, it is possible that Sz duration may be also affected by the presence or absence of consciousness.

Conclusions: The most frequent form of seizures with ictal DC shift (SN onset) is characterized by faster propagation to surrounding regions, and a duration that is inversely proportional to the amplitude of the DC shift at onset.

Funding: Please list any funding that was received in support of this abstract.: The research reported herein was supported by the funding from the European Union’s Horizon 2020 framework program for research and innovation under grant agreement No. 765549.

Neurophysiology