."Analysis of single-unit activity and local field potential in human mesial temporal lobe epilepsy

S KOCHEN, COORDINADORA ET COL

Congreso; 32 ND INTERNACIONAL EPILEPSY CONGRESS; 2017

ILAE

Intracranial electroencephalography is the common clinical diagnosis protocol to identify the epileptogenic zone for surgical treatment of drug resistant epilepsy patients. Analyse simultaneous recordings with clinical macro- (cM) and research micro-electrodes (rM) allows us to obtain a better understanding at microscale of how neural network works before and during epileptic seizures. We registered brain activity from cM and rM (AdTech,USA) implanted bilaterally in amygdala and hippocampus of two patients with bilateral mesial-temporal epilepsy, following clinical criteria. Recordings were obtained from 96 microelectrodes located at Seizure-Onset-Zone (SOZ;n=32), ipsilateral but outside of SOZ (n=16) and contralateral to SOZ (n=48). It was noted that the detection and clustering techniques are very sensitive to noise background, which is ten-fold increased during seizures. This noisy increase may involve a bad estimation of detection threshold, causing a fake low in FR due to a misdetection of spikes. A way to overcome this drawback is analyse the firing rate (FR) of neurons whose spikes exceeds at least 5 times the amplitude of noise during seizure. We ensure only analyse seizures (n=8) that showed LFPs with single-unit (SU) and/or multiunit extracellular activity (MU) during ictal period, and at least within 5 min before seizure onset (SO). We also analyse and characterize the LFP dynamics using techniques to estimate correlation, spectral density, slop phase and phase modulation index, as well as the correlation between the LFP dynamics and FR of SU and MU. Data is still being analysed, however, the preliminary results described 84% of neurons (128/152) showing different types of seizure-related firing patterns prior to or following the SO depending on each brain region.Further analyses are needed to generate an adaptive threshold method that follow the dynamics of the seizure and improve the spike detection during epileptic seizures which allows us a better understand of epileptogenic network.