Synaptic inhibition and pathologic hyperexcitability through enhanced neuron-astrocyte interaction: a modeling study

Analysis of Network Models with Neuron-Astrocyte Interactions

Neural networks, composed of many neurons and governed by complex interactions between them, are a widely accepted formalism for modeling and exploring global dynamics and emergent properties in brain systems. In the past decades, experimental evidence of computationally relevant neuron-astrocyte interactions, as well as the astrocytic modulation of global neural dynamics, have accumulated. These findings motivated advances in computational glioscience and inspired several models integrating mechanisms of neuron-astrocyte interactions into the standard neural network formalism. These models were developed to study, for example, synchronization, information transfer, synaptic plasticity, and hyperexcitability, as well as classification tasks and hardware implementations. We here focus on network models of at least two neurons interacting bidirectionally with at least two astrocytes that include explicitly modeled astrocytic calcium dynamics. In this study, we analyze the evolution of these models and the biophysical, biochemical, cellular, and network mechanisms used to construct them. Based on our analysis, we propose how to systematically describe and categorize interaction schemes between cells in neuron-astrocyte networks. We additionally study the models in view of the existing experimental data and present future perspectives. Our analysis is an important first step towards understanding astrocytic contribution to brain functions. However, more advances are needed to collect comprehensive data about astrocyte morphology and physiology in vivo and to better integrate them in data-driven computational models. Broadening the discussion about theoretical approaches and expanding the computational tools is necessary to better understand astrocytes' roles in brain functions.

Transition behavior of the seizure dynamics modulated by the astrocyte inositol triphosphate noise

Epilepsy is a neurological disorder with recurrent seizures, which convey complex dynamical characteristics including chaos and randomness. Until now, the underlying mechanism has not been fully elucidated, especially the bistable property beneath the epileptic random induction phenomena in certain conditions. Inspired by the recent finding that astrocyte GTPase-activating protein (G-protein)-coupled receptors could be involved in stochastic epileptic seizures, we proposed a neuron-astrocyte network model, incorporating the noise of the astrocytic second messenger, inositol triphosphate (IP3) that is modulated by G-protein-coupled receptor activation. Based on this model, we have statistically analyzed the transitions of epileptic seizures by performing repeatable simulation trials. Our simulation results show that the increase in the IP3 noise intensity induces depolarization-block epileptic seizures together with an increase in neuronal firing frequency, consistent with corresponding experiments. Meanwhile, the bistable states of the seizure dynamics were present under certain noise intensities, during which the neuronal firing pattern switches between regular sparse spiking and epileptic seizure states. This random presence of epileptic seizures is absent when the noise intensity continues to increase, accompanying with an increase in the epileptic depolarization block duration. The simulation results also shed light on the fact that calcium signals in astrocytes play significant roles in the pattern formations of the epileptic seizure. Our results provide a potential pathway for understanding the epileptic randomness in certain conditions.

A Computational Model to Investigate GABA-Activated Astrocyte Modulation of Neuronal Excitation

Gamma-aminobutyric acid (GABA) is critical for proper neural network function and can activate astrocytes to induce neuronal excitability; however, the mechanism by which astrocytes transform inhibitory signaling to excitatory enhancement remains unclear. Computational modeling can be a powerful tool to provide further understanding of how GABA-activated astrocytes modulate neuronal excitation. In the present study, we implemented a biophysical neuronal network model to investigate the effects of astrocytes on excitatory pre- and postsynaptic terminals following exposure to increasing concentrations of external GABA. The model completely describes the effects of GABA on astrocytes and excitatory presynaptic terminals within the framework of glutamatergic gliotransmission according to neurophysiological findings. Utilizing this model, our results show that astrocytes can rapidly respond to incoming GABA by inducing Ca²⁺ oscillations and subsequent gliotransmitter glutamate release. Elevation in GABA concentrations not only naturally decreases neuronal spikes but also enhances astrocytic glutamate release, which leads to an increase in astrocyte-mediated presynaptic release and postsynaptic slow inward currents. Neuronal excitation induced by GABA-activated astrocytes partly counteracts the inhibitory effect of GABA. Overall, the model helps to increase knowledge regarding the involvement of astrocytes in neuronal regulation using simulated bath perfusion of GABA, which may be useful for exploring the effects of GABA-type antiepileptic drugs.

Computational Models for Calcium-Mediated Astrocyte Functions

The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus, we would like to emphasize that only via reproducible research are we able to build better computational models for astrocytes, which truly advance science. Our study is the first to characterize in detail the biophysical and biochemical mechanisms that have been modeled for astrocytes.

A Theoretical Study on the Role of Astrocytic Activity in Neuronal Hyperexcitability by a Novel Neuron-Glia Mass Model

Recent experimental evidence on the clustering of glutamate and GABA transporters on astrocytic processes surrounding synaptic terminals pose the question of the functional relevance of the astrocytes in the regulation of neural activity. In this perspective, we introduce a new computational model that embeds recent findings on neuron-astrocyte coupling at the mesoscopic scale intra- and inter-layer local neural circuits. The model consists of a mass model for the neural compartment and an astrocyte compartment which controls dynamics of extracellular glutamate and GABA concentrations. By arguments based on bifurcation theory, we use the model to study the impact of deficiency of astrocytic glutamate and GABA uptakes on neural activity. While deficient astrocytic GABA uptake naturally results in increased neuronal inhibition, which in turn results in a decreased neuronal firing, deficient glutamate uptake by astrocytes may either decrease or increase neuronal firing either transiently or permanently. Given the relevance of neuronal hyperexcitability (or lack thereof) in the brain pathophysiology, we provide biophysical conditions for the onset identifying different physiologically relevant regimes of operation for astrocytic uptake transporters.

Astrocytes as new targets to improve cognitive functions

Astrocytes are now viewed as key elements of brain wiring as well as neuronal communication. Indeed, they not only bridge the gap between metabolic supplies by blood vessels and neurons, but also allow fine control of neurotransmission by providing appropriate signaling molecules and insulation through a tight enwrapping of synapses. Recognition that astroglia is essential to neuronal communication is nevertheless fairly recent and the large body of evidence dissecting such role has focused on the synaptic level by identifying neuro- and gliotransmitters uptaken and released at synaptic or extrasynaptic sites. Yet, more integrated research deciphering the impact of astroglial functions on neuronal network activity have led to the reasonable assumption that the role of astrocytes in supervising synaptic activity translates in influencing neuronal processing and cognitive functions. Several investigations using recent genetic tools now support this notion by showing that inactivating or boosting astroglial function directly affects cognitive abilities. Accordingly, brain diseases resulting in impaired cognitive functions have seen their physiopathological mechanisms revisited in light of this primary protagonist of brain processing. We here provide a review of the current knowledge on the role of astrocytes in cognition and in several brain diseases including neurodegenerative disorders, psychiatric illnesses, as well as other conditions such as epilepsy. Potential astroglial therapeutic targets are also discussed.

Quantifying altered long-term potentiation in the CA1 hippocampus

Long-term potentiation (LTP) of synaptic transmission is a widely accepted model of learning and memory. In vitro brain slice techniques were used to investigate the effects of cortical-spreading depression and picrotoxin, an antagonist of the gamma-aminobutyric acid A (GABA(A)) receptor, on the tetanus-induced long-term potentiation of field excitatory postsynaptic potentials. Cortical-spreading depression is involved in glutamate desensitization; on the other hand, GABA(A) antagonists could increase postsynaptic excitability. This study shows that picrotoxin effectively induced long-term potentiation with 142.25 ± 4.18% of the baseline in the picrotoxin group (n = 8) versus 134.36 ± 2.35% of the baseline in the control group (n = 10). In group with picrotoxin applied to CSD, we obtained the smallest magnitude of LTP (120.15 ± 3.73% of the baseline, n = 8). These results suggest that picrotoxin could increase hippocampal activity and LTP; on the contrary, CSD reduced LTP magnitude. In addition, the results also suggest that the decay rate of post-tetanic potentiation has a direct relationship with LTP. Moreover, data were interpreted by nonlinear least squares quantifying, and LTP could also be quantified. The nonlinear attribute of LTP had an influence on the fitting, with respect to increasing the accuracy of the parameters and the compatibility of combination of stimuli that produce LTP.

Oral Uncaria rhynchophylla (UR) reduces kainic acid-induced epileptic seizures and neuronal death accompanied by attenuating glial cell proliferation and S100B proteins in rats

AIM OF THE STUDY

Epilepsy is a common clinical syndrome with recurrent neuronal discharges in cerebral cortex and hippocampus. Here we aim to determine the protective role of Uncaria rhynchophylla (UR), an herbal drug belong to Traditional Chinese Medicine (TCM), on epileptic rats.

MATERIALS AND METHODS

To address this issue, we tested the effect of UR on kainic acid (KA)-induced epileptic seizures and further investigate the underlying mechanisms.

RESULTS

Oral UR successfully decreased neuronal death and discharges in hippocampal CA1 pyramidal neurons. The population spikes (PSs) were decreased from 4.1 ± 0.4 mV to 2.1 ± 0.3 mV in KA-induced epileptic seizures and UR-treated groups, respectively. Oral UR protected animals from neuronal death induced by KA treatment (from 34 ± 4.6 to 191.7 ± 48.6 neurons/field) through attenuating glial cell proliferation and S100B protein expression but not GABAA and TRPV1 receptors.

CONCLUSIONS

The above results provide detail mechanisms underlying the neuroprotective action of UR on KA-induced epileptic seizure in hippocampal CA1 neurons.

Computational modeling of paroxysmal depolarization shifts in neurons induced by the glutamate release from astrocytes

Recent experimental studies have shown that astrocytes respond to external stimuli with a transient increase of the intracellular calcium concentration or can exhibit self-sustained spontaneous activity. Both evoked and spontaneous astrocytic calcium oscillations are accompanied by exocytosis of glutamate caged in astrocytes leading to paroxysmal depolarization shifts (PDS) in neighboring neurons. Here, we present a simple mathematical model of the interaction between astrocytes and neurons that is able to numerically reproduce the experimental results concerning the initiation of the PDS. The timing of glutamate release from the astrocyte is studied by means of a combined modeling of a vesicle cycle and the dynamics of SNARE-proteins. The neuronal slow inward currents (SICs), induced by the astrocytic glutamate and leading to PDS, are modeled via the activation of presynaptic glutamate receptors. The dependence of the bidirectional communication between neurons and astrocytes on the concentration of glutamate transporters is analyzed, as well. Our numerical results are in line with experimental findings showing that astrocyte can induce synchronous PDSs in neighboring neurons, resulting in a transient synchronous spiking activity.

Modeling synaptic transmission of the tripartite synapse

The tripartite synapse denotes the junction of a pre- and postsynaptic neuron modulated by a synaptic astrocyte. Enhanced transmission probability and frequency of the postsynaptic current-events are among the significant effects of the astrocyte on the synapse as experimentally characterized by several groups. In this paper we provide a mathematical framework for the relevant synaptic interactions between neurons and astrocytes that can account quantitatively for both the astrocytic effects on the synaptic transmission and the spontaneous postsynaptic events. Inferred from experiments, the model assumes that glutamate released by the astrocytes in response to synaptic activity regulates store-operated calcium in the presynaptic terminal. This source of calcium is distinct from voltage-gated calcium influx and accounts for the long timescale of facilitation at the synapse seen in correlation with calcium activity in the astrocytes. Our model predicts the inter-event interval distribution of spontaneous current activity mediated by a synaptic astrocyte and provides an additional insight into a novel mechanism for plasticity in which a low fidelity synapse gets transformed into a high fidelity synapse via astrocytic coupling.

fMRI MODELS OF DENDRITIC AND ASTROCYTIC NETWORKS

In order to elucidate the relationships between hierarchical structures within the neocortical neuropil and the information carried by an ensemble of neurons encompassing a single voxel, it is essential to predict through volume conductor modeling LFPs representing average extracellular potentials, which are expressed in terms of interstitial potentials of individual cells in networks of gap-junctionally connected astrocytes and synaptically connected neurons. These relationships have been provided and can then be used to investigate how the underlying neuronal population activity can be inferred from the measurement of the BOLD signal through electrovascular coupling mechanisms across the blood-brain barrier. The importance of both synaptic and extrasynaptic transmission as the basis of electrophysiological indices triggering vascular responses between dendritic and astrocytic networks, and sequential configurations of firing patterns in composite neural networks is emphasized. The purpose of this review is to show how fMRI data may be used to draw conclusions about the information transmitted by individual neurons in populations generating the BOLD signal.