Synchronous high-frequency oscillations in inhibitory-dominant network motifs consisting of three dentate gyrus-CA3 systems

The seizure classification of focal epilepsy based on the network motif analysis

Due to the complexity of focal epilepsy and its risk for transiting to the generalized epilepsy, the development of reliable classification methods to accurately predict and classify focal and generalized seizures is critical for the clinical management of patients with epilepsy. In order to holistically understand the seizure propagation behavior of focal epilepsy, we propose a three-node motif reduced network by respectively simplifying the focal region, surrounding healthy region and their critical regions as the single node. Because three-node motif can richly characterize information evolutions, the motif analysis method could comprehensively investigate the seizure behavior of focal epilepsy. Firstly, we define a new seizure propagation marker value to capture the seizure onsets and intensity. Based on the three-node motif analysis, it is shown that the focal seizure and spreading can be categorized as inhibitory seizure, focal seizure, focal-critical seizure and generalized seizures, respectively. The four types of seizures correspond to specific modal types respectively, reflecting the strong correlation between seizure behavior and information flow evolution. In addition, it is found that the intensity difference of outflow and inflow information from the critical node (connection heterogeneity) and the excitability of the critical node significantly affected the distribution and transition of the four seizure types. In particular, the method of local linear stability analysis also verifies the effectiveness of four types of seizures classification. In sum, this paper computationally confirms the complex dynamic behavior of focal seizures, and the study of criticality is helpful to propose novel seizure control strategies.

Dynamic effects of miR-20a-5p on hippocampal ripple energy after status epilepticus in rats

To determine the dynamic effects of miR-20a-5p on hippocampal ripple energy in rats after status epilepticus (SE). A lithium pilocarpine (LiCl-PILO)-induced rat model of status epilepticus (SE) was established, and the rats were divided into the normal control (Control, CTL), epileptic control (PILO), valproic acid (VPA + PILO), miR-20a-5p overexpression lentivirus vector (miR + PILO), sponges blocking lentivirus vector (Sponges + PILO), and scramble sequence negative control (Scramble + PILO) groups (n = 6). Electroencephalograms (EEGs) were used to analyze changes in hippocampal ripple energy before and after SE. Quantitative polymerase chain reaction (q-PCR) analysis showed that miR-20a-5p levels gradually increased after miR-20a-5p overexpression lentivirus vector injection into the lateral ventricle, and the miR-20a-5p levels were significantly higher than that in CTL group on days 7 and 36 (P < 0.001). The miR-20a-5p levels decreased significantly on days 7 and 36 after blocking by sponges lentivirus vector injected into the lateral ventricle (P < 0.001). After injection of PILO, the average ripple energy expression in each group gradually increased, and reached the peak before chloral hydrate injection (compared with 1 day before SE, P < 0.05). The ripple energy in the VPA + PILO and Sponges + PILO groups was significantly lower than that in the PILO group at 60 min and 70 min after PILO injection and before chloral hydrate injection (P < 0.05), and maintained lower until 2 h after chloral hydrate injection in VPA + PILO (P < 0.05). Compared with the VPA + PILO group, the mean ripple energy of the Sponges + PILO group had no difference at all time points (P ≥ 0.05). After SE, ripple distribution of space and energy is closely related to the occurrence of epilepsy. Inhibition of miR20a-5p expression can downregulate ripple oscillation energy during seizure.

Effect of gap junction blockers on hippocampal ripple energy expression in rats with status epilepticus

OBJECTIVES

To study the effect of gap junction blockers, quinine (QUIN) and carbenoxolone (CBX), on hippocampal ripple energy expression in rats with status epilepticus (SE).

METHODS

A total of 24 rats were randomly divided into four groups: model, QUIN, valproic acid (VPA), and CBX (n=6 each). A rat model of SE induced by lithium-pilocarpine (PILO) was prepared. The QUIN, VPA, and CBX groups were given intraperitoneal injection of QUIN (50 mg/kg), VPA by gavage (200 mg/kg), and intraperitoneal injection of CBX (50 mg/kg) respectively, at 3 days before PILO injection. Electroencephalography was used to analyze the change in hippocampal ripple energy before and after modeling, as well as before and after chloral hydrate injection to control seizures.

RESULTS

Ripple expression was observed in the hippocampal CA1, CA3, and dentate gyrus regions of normal rats. After 10 minutes of PILO injection, all groups had a gradual increase in mean ripple energy expression compared with 1 day before modeling, with the highest expression level before chloral hydrate injection in the model, VPA and CBX groups (P<0.05). The QUIN group had the highest expression level of mean ripple energy 60 minutes after PILO injection. The mean ripple energy returned to normal levels in the three intervention groups immediately after chloral hydrate injection, while in the model group, the mean ripple energy returned to normal levels 1 hour after chloral hydrate injection. The mean ripple energy remained normal till to day 3 after SE in the four groups. The changing trend of maximum ripple energy was similar to that of mean ripple energy.

CONCLUSIONS

The change in ripple energy can be used as a quantitative indicator for early warning of seizures, while it cannot predict seizures in the interictal period. Gap junction blockers can reduce ripple energy during seizures.

Effects of brain-derived neurotrophic factor and noise on transitions in temporal lobe epilepsy in a hippocampal network

Brain-derived neurotrophic factor (BDNF) has recently been implicated in the modulation of receptor activation leading to dynamic state transitions in temporal lobe epilepsy (TLE). In addition, the crucial role of neuronal noise in these transitions has been studied in electrophysiological experiments. However, the precise role of these factors during seizure generation in TLE is not known. Building on a previously proposed model of an epileptogenic hippocampal network, we included the actions of BDNF-regulated receptors and intrinsic noise. We found that the effects of both BDNF and noise can increase the activation of N-methyl-D-aspartate receptors leading to excessive C a 2 + flux, which induces abnormal fast spiking and bursting. Our results indicate that the combined effects have a strong influence on the seizure-generating network, resulting in higher firing frequency and amplitude. As correlations between firing increase, the synchronization of the entire network increases, a marker of the ictogenic transitions from normal to seizures-like dynamics. Our work on the effects of BDNF dynamics in a noisy environment might lead to an improved model-based understanding of the pathological mechanisms in TLE.