Slow moving neural source in the epileptic hippocampus can mimic progression of human seizures

Controlling the local extracellular electric field can suppress the generation and propagation of seizures and spikes in the hippocampus

OBJECTIVE

Neural activity such as theta waves, epileptic spikes and seizures can cross a physical transection using electric fields thus propagating by ephaptic coupling and independently of synaptic transmission. Recruitment of neurons in epilepsy occurs in part due to electric field coupling in addition to synaptic mechanisms. Hence, controlling the local electric field could suppress or cancel the generation of these epileptic events.

METHODS

4-aminopyridine (4-AP) was used to induce spontaneous epileptic spikes and seizures in longitudinal hippocampal slices in-vitro. Two extracellular recording electrodes were placed in the tissue, one at the edge of the slice on the temporal side at the focus of the epileptic activity and the other on the septal side to record the propagation. Two stimulating electrodes were placed outside the slice at the edge of the focal zone. An extracellular voltage clamp circuit maintained the voltage within the focus at 0V with respect to the bath ground.

RESULTS

Experiments showed that 100 % of the epileptic activity originated at the temporal region and propagated to the septal region of the slices thereby establishing the existence of a focus in the temporal end of the tissue. The clamp achieved 100 % suppression of all seizure activity in the tissue with current amplitudes between 70 and 250 nA. No spikes or seizures were observed in either the focus or the septal region when the clamp was "on". When the clamp was turned off, both the spikes and seizure events recovered immediately.

CONCLUSIONS

The experiments show that controlling the extracellular voltage within a focus can prevent the generation and the propagation of epileptiform activity from the focus with very low amplitudes currents.

Modeling seizure networks in neuron-glia cultures using microelectrode arrays

Epilepsy is a common neurological disorder, affecting over 65 million people worldwide. Unfortunately, despite resective surgery, over 30 % of patients with drug-resistant epilepsy continue to experience seizures. Retrospective studies considering connectivity using intracranial electrocorticography (ECoG) obtained during neuromonitoring have shown that treatment failure is likely driven by failure to consider critical components of the seizure network, an idea first formally introduced in 2002. However, current studies only capture snapshots in time, precluding the ability to consider seizure network development. Over the past few years, multiwell microelectrode arrays have been increasingly used to study neuronal networks in vitro. As such, we sought to develop a novel in vitro MEA seizure model to allow for study of seizure networks. Specifically, we used 4-aminopyridine (4-AP) to capture hyperexcitable activity, and then show increased network changes after 2 days of chronic treatment. We characterize network changes using functional connectivity measures and a novel technique using dimensionality reduction. We find that 4-AP successfully captures persistently elevated mean firing rate and significant changes in underlying connectivity patterns. We believe this affords a robust in vitro seizure model from which longitudinal network changes can be studied, laying groundwork for future studies exploring seizure network development.

EEG Signal Epilepsy Detection With a Weighted Neighbor Graph Representation and Two-Stream Graph-Based Framework

Epilepsy is one of the most common neurological diseases. Clinically, epileptic seizure detection is usually performed by analyzing electroencephalography (EEG) signals. At present, deep learning models have been widely used for single-channel EEG signal epilepsy detection, but this method is difficult to explain the classification results. Researchers have attempted to solve interpretive problems by combining graph representation of EEG signals with graph neural network models. Recently, the combination of graph representations and graph neural network (GNN) models has been increasingly applied to single-channel epilepsy detection. By this methodology, the raw EEG signal is transformed to its graph representation, and a GNN model is used to learn latent features and classify whether the data indicates an epileptic seizure episode. However, existing methods are faced with two major challenges. First, existing graph representations tend to have high time complexity as they generally require each vertex to traverse all other vertices to construct a graph structure. Some of them also have high space complexity for being dense. Second, while separate graph representations can be derived from a single-channel EEG signal in both time and frequency domains, existing GNN models for epilepsy detection can learn from a single graph representation, which makes it hard to let the information from the two domains complement each other. For addressing these challenges, we propose a Weighted Neighbour Graph (WNG) representation for EEG signals. Reducing the redundant edges of the existing graph, WNG can be both time and space-efficient, and as informative as its less efficient counterparts. We then propose a two-stream graph-based framework to simultaneously learn features from WNG in both time and frequency domain. Extensive experiments demonstrate the effectiveness and efficiency of the proposed methods.

Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies

The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research.

Multiple Sources of Fast Traveling Waves during Human Seizures: Resolving a Controversy

During human seizures, organized waves of voltage activity rapidly sweep across the cortex. Two contradictory theories describe the source of these fast traveling waves: either a slowly advancing narrow region of multiunit activity (an ictal wavefront) or a fixed cortical location. Limited observations and different analyses prevent resolution of these incompatible theories. Here we address this disagreement by combining the methods and microelectrode array recordings (N = 11 patients, 2 females, N = 31 seizures) from previous human studies to analyze the traveling wave source. We find, inconsistent with both existing theories, a transient relationship between the ictal wavefront and traveling waves, and multiple stable directions of traveling waves in many seizures. Using a computational model that combines elements of both existing theories, we show that interactions between an ictal wavefront and fixed source reproduce the traveling wave dynamics observed in vivo We conclude that combining both existing theories can generate the diversity of ictal traveling waves.SIGNIFICANCE STATEMENT The source of voltage discharges that propagate across cortex during human seizures remains unknown. Two candidate theories exist, each proposing a different discharge source. Support for each theory consists of observations from a small number of human subject recordings, analyzed with separately developed methods. How the different, limited data and different analysis methods impact the evidence for each theory is unclear. To resolve these differences, we combine the unique, human microelectrode array recordings collected separately for each theory and analyze these combined data with a unified approach. We show that neither existing theory adequately describes the data. We then propose a new theory that unifies existing proposals and successfully reproduces the voltage discharge dynamics observed in vivo.

Neural recruitment by ephaptic coupling in epilepsy

OBJECTIVE

One of the challenges in treating patients with drug-resistant epilepsy is that the mechanisms of seizures are unknown. Most current interventions are based on the assumption that epileptic activity recruits neurons and progresses by synaptic transmission. However, several experimental studies have shown that neural activity in rodent hippocampi can propagate independently of synaptic transmission. Recent studies suggest these waves are self-propagating by electric field (ephaptic) coupling. In this study, we tested the hypothesis that neural recruitment during seizures can occur by electric field coupling.

METHODS

4-Aminopyridine was used in both in vivo and in vitro preparation to trigger seizures or epileptiform activity. A transection was made in the in vivo hippocampus and in vitro hippocampal and cortical slices to study whether the induced seizure activity can recruit neurons across the gap. A computational model was built to test whether ephaptic coupling alone can account for neural recruitment across the transection. The model prediction was further validated by in vitro experiments.

RESULTS

Experimental results show that electric fields generated by seizure-like activity in the hippocampus both in vitro and in vivo can recruit neurons locally and through a transection of the tissue. The computational model suggests that the neural recruitment across the transection is mediated by electric field coupling. With in vitro experiments, we show that a dielectric material can block the recruitment of epileptiform activity across a transection, and that the electric fields measured within the gap are similar to those predicted by model simulations. Furthermore, this nonsynaptic neural recruitment is also observed in cortical slices, suggesting that this effect is robust in brain tissue.

SIGNIFICANCE

These results indicate that ephaptic coupling, a nonsynaptic mechanism, can underlie neural recruitment by a small electric field generated by seizure activity and could explain the low success rate of surgical transections in epilepsy patients.

Role of paroxysmal depolarization in focal seizure activity

We analyze the role of inhibition in sustaining focal epileptic seizure activity. We review ongoing seizure activity at the mesoscopic scale that can be observed with microelectrode arrays as well as at the macroscale of standard clinical EEG. We provide clinical, experimental, and modeling data to support the hypothesis that paroxysmal depolarization (PD) is a critical component of the ictal machinery. We present dual-patch recordings in cortical cultures showing reduced synaptic transmission associated with presynaptic occurrence of PD, and we find that the PD threshold is cell size related. We further find evidence that optically evoked PD activity in parvalbumin neurons can promote propagation of neuronal excitation in neocortical networks in vitro. Spike sorting results from microelectrode array measurements around ictal wave propagation in human focal seizures demonstrate a strong increase in putative inhibitory firing with an approaching excitatory wave, followed by a sudden reduction of firing at passage. At the macroscopic level, we summarize evidence that this excitatory ictal wave activity is strongly correlated with oscillatory activity across a centimeter-sized cortical network. We summarize Wilson-Cowan-type modeling showing how inhibitory function is crucial for this behavior. Our findings motivated us to develop a network motif of neurons in silico, governed by a reduced version of the Hodgkin-Huxley formalism, to show how feedforward, feedback, PD, and local failure of inhibition contribute to observed dynamics across network scales. The presented multidisciplinary evidence suggests that the PD not only is a cellular marker or epiphenomenon but actively contributes to seizure activity.NEW & NOTEWORTHY We present mechanisms of ongoing focal seizures across meso- and macroscales of microelectrode array and standard clinical recordings, respectively. We find modeling, experimental, and clinical evidence for a dual role of inhibition across these scales: local failure of inhibition allows propagation of a mesoscopic ictal wave, whereas inhibition elsewhere remains intact and sustains macroscopic oscillatory activity. We present evidence for paroxysmal depolarization as a mechanism behind this dual role of inhibition in shaping ictal activity.

Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks

Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highlight how major advances in neuroscience tool development now enable multi-scale investigation of fundamental questions to resolve the currently controversial understanding of seizure networks. These findings will provide essential insight into what has emerged as a disconnect between the different levels of investigation and identify new targets and treatment options.

Self-propagating, non-synaptic epileptiform activity recruits neurons by endogenous electric fields

It is well documented that synapses play a significant role in the transmission of information between neurons. However, in the absence of synaptic transmission, neural activity has been observed to continue to propagate. Previous studies have shown that propagation of epileptiform activity takes place in the absence of synaptic transmission and gap junctions and is outside the range of ionic diffusion and axonal conduction. Computer simulations indicate that electric field coupling could be responsible for the propagation of neural activity under pathological conditions such as epilepsy. Electric fields can modulate neuronal membrane voltage, but there is no experimental evidence suggesting that electric field coupling can mediate self-regenerating propagation of neural activity. Here we examine the role of electric field coupling by eliminating all forms of neural communications except electric field coupling with a cut through the neural tissue. We show that 4-AP induced activity generates an electric field capable of recruiting neurons on the distal side of the cut. Experiments also show that applied electric fields with amplitudes similar to endogenous values can induce propagating waves. Finally, we show that canceling the electrical field at a given point can block spontaneous propagation. The results from these in vitro electrophysiology experiments suggest that electric field coupling is a critical mechanism for non-synaptic neural propagation and therefore could contribute to the propagation of epileptic activity in the brain.

Slow periodic activity in the longitudinal hippocampal slice can self-propagate non-synaptically by a mechanism consistent with ephaptic coupling

KEY POINTS

Slow periodic activity can propagate with speeds around 0.1 m s-1 and be modulated by weak electric fields. Slow periodic activity in the longitudinal hippocampal slice can propagate without chemical synaptic transmission or gap junctions, but can generate electric fields which in turn activate neighbouring cells. Applying local extracellular electric fields with amplitude in the range of endogenous fields is sufficient to modulate or block the propagation of this activity both in the in silico and in the in vitro models. Results support the hypothesis that endogenous electric fields, previously thought to be too small to trigger neural activity, play a significant role in the self-propagation of slow periodic activity in the hippocampus. Experiments indicate that a neural network can give rise to sustained self-propagating waves by ephaptic coupling, suggesting a novel propagation mechanism for neural activity under normal physiological conditions.

ABSTRACT

Slow oscillations are a standard feature observed in the cortex and the hippocampus during slow wave sleep. Slow oscillations are characterized by low-frequency periodic activity (<1 Hz) and are thought to be related to memory consolidation. These waves are assumed to be a reflection of the underlying neural activity, but it is not known if they can, by themselves, be self-sustained and propagate. Previous studies have shown that slow periodic activity can be reproduced in the in vitro preparation to mimic in vivo slow oscillations. Slow periodic activity can propagate with speeds around 0.1 m s-1 and be modulated by weak electric fields. In the present study, we show that slow periodic activity in the longitudinal hippocampal slice is a self-regenerating wave which can propagate with and without chemical or electrical synaptic transmission at the same speeds. We also show that applying local extracellular electric fields can modulate or even block the propagation of this wave in both in silico and in vitro models. Our results support the notion that ephaptic coupling plays a significant role in the propagation of the slow hippocampal periodic activity. Moreover, these results indicate that a neural network can give rise to sustained self-propagating waves by ephaptic coupling, suggesting a novel propagation mechanism for neural activity under normal physiological conditions.