Neuron to Astrocyte Communication via Cannabinoid Receptors Is Necessary for Sustained Epileptiform Activity in Rat Hippocampus

Astrocytes are integral functional components of synapses, regulating transmission and plasticity. They have also been implicated in the pathogenesis of epilepsy, although their precise roles have not been comprehensively characterized. Astrocytes integrate activity from neighboring synapses by responding to neuronally released neurotransmitters such as glutamate and ATP. Strong activation of astrocytes mediated by these neurotransmitters can promote seizure-like activity by initiating a positive feedback loop that induces excessive neuronal discharge. Recent work has demonstrated that astrocytes express cannabinoid 1 (CB1) receptors, which are sensitive to endocannabinoids released by nearby pyramidal cells. In this study, we tested whether this mechanism also contributes to epileptiform activity. In a model of 4-aminopyridine induced epileptic-like activity in hippocampal slice cultures, we show that pharmacological blockade of astrocyte CB1 receptors did not modify the initiation, but significantly reduced the maintenance of epileptiform discharge. When communication in astrocytic networks was disrupted by chelating astrocytic calcium, this CB1 receptor-mediated modulation of epileptiform activity was no longer observed. Thus, endocannabinoid signaling from neurons to astrocytes represents an additional significant factor in the maintenance of epileptiform activity in the hippocampus

Bistable, Irregular Firing and Population Oscillations in a Modular Attractor Memory Network

Attractor neural networks are thought to underlie working memory functions in the cerebral cortex. Several such models have been proposed that successfully reproduce firing properties of neurons recorded from monkeys performing working memory tasks. However, the regular temporal structure of spike trains in these models is often incompatible with experimental data. Here, we show that the in vivo observations of bistable activity with irregular firing at the single cell level can be achieved in a large-scale network model with a modular structure in terms of several connected hypercolumns. Despite high irregularity of individual spike trains, the model shows population oscillations in the beta and gamma band in ground and active states, respectively. Irregular firing typically emerges in a high-conductance regime of balanced excitation and inhibition. Population oscillations can produce such a regime, but in previous models only a non-coding ground state was oscillatory. Due to the modular structure of our network, the oscillatory and irregular firing was maintained also in the active state without fine-tuning. Our model provides a novel mechanistic view of how irregular firing emerges in cortical populations as they go from beta to gamma oscillations during memory retrieval

Interpretation of intracerebral-EEG epileptic spikes from detailed modeling of neural networks

Abstract-This paper deals with the interpretation of the macroscopic features of epileptic spikes recorded in human hippocampus based on a neural network model of the CA1 subfield. The network consists of principal cells (pyramidal neurons) and local interneurons and uses GABAergic and glutamatergic synapses. For pyramidal cells, this paper introduces a novel two-compartment model that was developed using published data and our own experimental data (intracellular recordings, in vitro). For interneurons, singlecompartment models published elsewhere were implemented. The forward problem was solved to calculate the local field potential generated by the network. Our results show that: i) the ‘reduced ’ model approach allows for simulations including a relatively large number of cells, ii) for appropriate changes in model-parameters (related to synaptic transmission), the model can generate “spike ” events that closely resemble actual epileptic spikes and iii) some features of spike shape (amplitude, duration) can be explained by the degree of excitatory and inhibitory drive to pyramidal cells. computational modeling; hippocampus; CA1; local field potentials; epilpetic spikes I

Energy deprivation transiently enhances rhythmic inhibitory events in the CA3 hippocampal network in vitro

Oxygen glucose deprivation (OGD) leads to rapid suppression of synaptic transmission. Here we describe an emergence of rhythmic activity at 8 to 20 Hz in the CA3 subfield of hippocampal slice cultures occurring for a few minutes prior to the OGD-induced cessation of evoked responses. These oscillations, dominated by inhibitory events, represent network activity, as they were abolished by tetrodotoxin. They were also completely blocked by the GABAergic antagonist picrotoxin, and strongly reduced by the glutamatergic antagonist NBQX. Applying CPP to block NMDA receptors had no effect and neither did UBP302, an antagonist of GluK1-containing kainate receptors. The gap junction blocker mefloquine disrupted rhythmicity. Simultaneous whole-cell voltage-clamp recordings from neighboring or distant CA3 pyramidal cells revealed strong cross-correlation of the incoming rhythmic activity. Interneurons in the CA3 area received similar correlated activity. Interestingly, oscillations were much less frequently observed in the CA1 area. These data, together with the observation that the recorded activity consists primarily of inhibitory events, suggest that CA3 interneurons are important for generating these oscillations. This transient increase in inhibitory network activity during OGD may represent a mechanism contributing to the lower vulnerability to ischemic insults of the CA3 area as compared to the CA1 area

Electrophysiological Biomarkers of Epilepsy

In patients being evaluated for epilepsy and in animal models of epilepsy, electrophysiological recordings are carried to capture seizures to determine the existence of epilepsy. Electroencephalography recordings from the scalp, or sometimes directly from the brain, are also used to locate brain areas where seizure begins, and in surgical treatment help plan the area for resection. As seizures are unpredictable and can occur infrequently, ictal recordings are not ideal in terms of time, cost, or risk when, for example, determining the efficacy of existing or new anti-seizure drugs, evaluating potential anti-epileptogenic interventions, or for prolonged intracerebral electrode studies. Thus, there is a need to identify and validate other electrophysiological biomarkers of epilepsy that could be used to diagnose, treat, cure, and prevent epilepsy. Electroencephalography recordings in the epileptic brain contain other interictal electrophysiological disturbances that can occur more frequently than seizures, such as interictal spikes (IIS) and sharp waves, and from invasive studies using wide bandwidth recording and small diameter electrodes, the discovery of pathological high-frequency oscillations (HFOs) and microseizures. Of IIS, HFOs, and microseizures, a significant amount of recent research has focused on HFOs in the pathophysiology of epilepsy. Results from studies in animals with epilepsy and presurgical patients have consistently found a strong association between HFOs and epileptogenic brain tissue that suggest HFOs could be a potential biomarker of epileptogenicity and epileptogenesis. Here, we discuss several aspects of HFOs, as well as IIS and microseizures, and the evidence that supports their role as biomarkers of epilepsy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s13311-014-0259-0) contains supplementary material, which is available to authorized users