Study on the mechanisms of seizure-like events suppression effect by electrical stimulation using a microelectrode array

Spatial and amplitude dynamics of neurostimulation: Insights from the acute intrahippocampal kainate seizure mouse model

OBJECTIVE

Neurostimulation is an emerging treatment for patients with drug-resistant epilepsy, which is used to suppress, prevent, and terminate seizure activity. Unfortunately, after implantation and despite best clinical practice, most patients continue to have persistent seizures even after years of empirical optimization. The objective of this study is to determine optimal spatial and amplitude properties of neurostimulation in inhibiting epileptiform activity in an acute hippocampal seizure model.

METHODS

We performed high-throughput testing of high-frequency focal brain stimulation in the acute intrahippocampal kainic acid mouse model of status epilepticus. We evaluated combinations of six anatomic targets and three stimulus amplitudes.

RESULTS

We found that the spike-suppressive effects of high-frequency neurostimulation are highly dependent on the stimulation amplitude and location, with higher amplitude stimulation being significantly more effective. Epileptiform spiking activity was significantly reduced with ipsilateral 250 μA stimulation of the CA1 and CA3 hippocampal regions with 21.5% and 22.2% reductions, respectively. In contrast, we found that spiking frequency and amplitude significantly increased with stimulation of the ventral hippocampal commissure. We further found spatial differences with broader effects from CA1 versus CA3 stimulation.

SIGNIFICANCE

These findings demonstrate that the effects of therapeutic neurostimulation in an acute hippocampal seizure model are highly dependent on the location of stimulation and stimulus amplitude. We provide a platform to optimize the anti-seizure effects of neurostimulation, and demonstrate that an exploration of the large electrical parameter and location space can improve current modalities for treating epilepsy.

PLAIN LANGUAGE SUMMARY

In this study, we tested how electrical pulses in the brain can help control seizures in mice. We found that the electrode's placement and the stimulation amplitude had a large effect on outcomes. Some brain regions, notably nearby CA1 and CA3, responded positively with reduced seizure-like activities, while others showed increased activity. These findings emphasize that choosing the right spot for the electrode and adjusting the strength of electrical pulses are both crucial when considering neurostimulation treatments for epilepsy.

Ultrasound neuromodulation of cultured hippocampal neurons

Ultrasound is becoming an emerging and promising method for neuromodulation due to its advantage of noninvasiveness and its high spatial resolution. However, the underlying principles of ultrasound neuromodulation have not yet been elucidated. We have herein developed a new in vitro setup to study the ultrasonic neuromodulation, and examined various parameters of ultrasound to verify the effective conditions to evoke the neural activity. Neurons were stimulated with 0.5 MHz center frequency ultrasound, and the action potentials were recorded from rat hippocampal neural cells cultured on microelectrode arrays. As the intensity of ultrasound increased, the neuronal activity also increased. There was a notable and significant increase in both the spike rate and the number of bursts at 50% duty cycle, 1 kHz pulse repetition frequency, and the acoustic intensities of 7.6 W/cm2 and 3.8 W/cm2 in terms of spatial-peak pulse-average intensity and spatial-peak temporal-average intensity, respectively. In addition, the impact of ultrasonic neuromodulation was assessed in the presence of a gamma-aminobutyric acid A (GABAA) receptor antagonist to exclude the effect of activated inhibitory neurons. Interestingly, it is noteworthy that the predominant neuromodulatory effects of ultrasound disappeared when the GABAA blocker was introduced, suggesting the potential of ultrasonic stimulation specifically targeting inhibitory neurons. The experimental setup proposed herein could serve as a useful tool for the clarification of the mechanisms underlying the electrophysiological effects of ultrasound.

Spatial and Amplitude Dynamics of Neurostimulation: Insights from the Acute Intrahippocampal Kainate Seizure Mouse Model

Objective

Neurostimulation is an emerging treatment for patients with medically refractory epilepsy, which is used to suppress, prevent, and terminate seizure activity. Unfortunately, after implantation and despite best clinical practice, most patients continue to have persistent seizures even after years of empirical optimization. The objective of this study is to determine optimal spatial and amplitude properties of neurostimulation in inhibiting epileptiform activity in an acute hippocampal seizure model.

Methods

We performed high-throughput testing of high-frequency focal brain stimulation in the acute intrahippocampal kainic acid mouse model of temporal lobe epilepsy. We evaluated combinations of six anatomic targets and three stimulus amplitudes.

Results

We found that the spike-suppressive effects of high-frequency neurostimulation are highly dependent on the stimulation amplitude and location, with higher amplitude stimulation being significantly more effective. Epileptiform spiking activity was significantly reduced with ipsilateral 250 μA stimulation of the CA1 and CA3 hippocampal regions with 21.5% and 22.2% reductions, respectively. In contrast, we found that spiking frequency and amplitude significantly increased with stimulation of the ventral hippocampal commissure. We further found spatial differences with broader effects from CA1 versus CA3 stimulation.

Significance

These findings demonstrate that the effects of therapeutic neurostimulation in an acute hippocampal seizure model are highly dependent on the location of stimulation and stimulus amplitude. We provide a platform to optimize the anti-seizure effects of neurostimulation, and demonstrate that an exploration of the large electrical parameter and location space can improve current modalities for treating epilepsy.

Key Points

Evaluated spatial and temporal parameters of neurostimulation in a mouse model of acute seizuresBrief bursts of high-frequency (100 Hz) stimulation effectively interrupted epileptiform activity.The suppressive effect was highly dependent on stimulation amplitude and was maximal at the ipsilateral CA1 and CA3 regions.Pro-excitatory effects were identified with high-amplitude high-frequency stimulation at the ventral hippocampal commissure and contralateral CA1.

Artificial Intelligence and Computational Approaches for Epilepsy

Studies on treatment of epilepsy have been actively conducted in multiple avenues, but there are limitations in improving its efficacy due to between-subject variability in which treatment outcomes vary from patient to patient. Accordingly, there is a growing interest in precision medicine that provides accurate diagnosis for seizure types and optimal treatment for an individual epilepsy patient. Among these approaches, computational studies making this feasible are rapidly progressing in particular and have been widely applied in epilepsy. These computational studies are being conducted in two main streams: 1) artificial intelligence-based studies implementing computational machines with specific functions, such as automatic diagnosis and prognosis prediction for an individual patient, using machine learning techniques based on large amounts of data obtained from multiple patients and 2) patient-specific modeling-based studies implementing biophysical in-silico platforms to understand pathological mechanisms and derive the optimal treatment for each patient by reproducing the brain network dynamics of the particular patient per se based on individual patient's data. These computational approaches are important as it can integrate multiple types of data acquired from patients and analysis results into a single platform. If these kinds of methods are efficiently operated, it would suggest a novel paradigm for precision medicine.

Familiarity Detection and Memory Consolidation in Cortical Assemblies

Humans have a large capacity of recognition memory (Dudai, 1997), a fundamental property of higher-order brain functions such as abstraction and generalization (Vogt and Magnussen, 2007). Familiarity is the first step towards recognition memory. We have previously demonstrated using unsupervised neural network simulations that familiarity detection of complex patterns emerges in generic cortical microcircuits with bidirectional synaptic plasticity. It is therefore meaningful to conduct similar experiments on biological neuronal networks to validate these results. Studies of learning and memory in dissociated rodent neuronal cultures remain inconclusive to date. Synchronized network bursts (SNBs) that occur spontaneously and periodically have been speculated to be an intervening factor. By optogenetically stimulating cultured cortical networks with random dot movies (RDMs), we were able to reduce the occurrence of SNBs, after which an ability for familiarity detection emerged: previously seen patterns elicited higher firing rates than novel ones. Differences in firing rate were distributed over the entire network, suggesting that familiarity detection is a system level property. We also studied the change in SNB patterns following familiarity encoding. Support vector machine (SVM) classification results indicate that SNBs may be facilitating memory consolidation of the learned pattern. In addition, using a novel network connectivity probing method, we were able to trace the change in synaptic efficacy induced by familiarity encoding, providing insights on the long-term impact of having SNBs in the cultures.

Prediction of the Seizure Suppression Effect by Electrical Stimulation via a Computational Modeling Approach

In this paper, we identified factors that can affect seizure suppression via electrical stimulation by an integrative study based on experimental and computational approach. Preferentially, we analyzed the characteristics of seizure-like events (SLEs) using our previous in vitro experimental data. The results were analyzed in two groups classified according to the size of the effective region, in which the SLE was able to be completely suppressed by local stimulation. However, no significant differences were found between these two groups in terms of signal features or propagation characteristics (i.e., propagation delays, frequency spectrum, and phase synchrony). Thus, we further investigated important factors using a computational model that was capable of evaluating specific influences on effective region size. In the proposed model, signal transmission between neurons was based on two different mechanisms: synaptic transmission and the electrical field effect. We were able to induce SLEs having similar characteristics with differentially weighted adjustments for the two transmission methods in various noise environments. Although the SLEs had similar characteristics, their suppression effects differed. First of all, the suppression effect occurred only locally where directly received the stimulation effect in the high noise environment, but it occurred in the entire network in the low noise environment. Interestingly, in the same noise environment, the suppression effect was different depending on SLE propagation mechanism; only a local suppression effect was observed when the influence of the electrical field transmission was very weak, whereas a global effect was observed with a stronger electrical field effect. These results indicate that neuronal activities synchronized by a strong electrical field effect respond more sensitively to partial changes in the entire network. In addition, the proposed model was able to predict that stimulation of a seizure focus region is more effective for suppression. In conclusion, we confirmed the possibility of a computational model as a simulation tool to analyze the efficacy of deep brain stimulation (DBS) and investigated the key factors that determine the size of an effective region in seizure suppression via electrical stimulation.