Progressive alterations in electrophysiological and epileptic network properties during the development of temporal lobe epilepsy in rats

Abstract

ObjectiveRefractory temporal lobe epilepsy (TLE) with recurring seizures causing continuing pathological changes in neural reorganization. There is an incomplete understanding of how spatiotemporal electrophysiological characteristics changes during the development of TLE. Long-term multi-site epilepsy patients’ data is hard to obtain. Thus, our study relied on animal models to reveal the changes in electrophysiological and epileptic network characteristics systematically. MethodsLong-term local field potentials (LFPs) were recorded over a period of 1 to 4 months from 6 pilocarpine-treated TLE rats. We compared variations of seizure onset zone (SOZ), seizure onset pattern (SOP), the latency of seizure onsets, and functional connectivity network from 10-channel LFPs between the early and late stages. Moreover, three machine learning classifiers trained by early-stage data were used to test seizure detection performance in the late stage. ResultsCompared to the early stage, the earliest seizure onset was more frequently detected in hippocampus areas in the late stage. The latency of seizure onsets between electrodes became shorter. Low-voltage fast activity (LVFA) was the most common SOP and the proportion of it increased in the late stage. Different brain states were observed during seizures using Granger causality (GC). Moreover, seizure detection classifiers trained by early-stage data were less accurate when tested in late-stage data. SignificanceNeuromodulation especially closed-loop deep brain stimulation (DBS) is effective in the treatment of refractory TLE. Although the frequency or amplitude of the stimulation is generally adjusted in existing closed-loop DBS devices in clinical usage, the adjustment rarely considers the pathological progression of chronic TLE. This suggests that an important factor affecting the therapeutic effect of neuromodulation may have been overlooked. The present study reveals time-varying electrophysiological and epileptic network properties in chronic TLE rats and indicates that classifiers of seizure detection and neuromodulation parameters might be designed to adapt to the current state dynamically with the progression of epilepsy.