Astrocyte- neuron interaction as a mechanism responsible for generation of neural synchrony: a study based on modeling and experiments

Interpreting the rich dialogue between astrocytes and neurons: An overview in Rett syndrome

Rett syndrome (RTT) is a severe neurodevelopmental disorder primarily affecting females, with an incidence of 1 in 10,000 live births. It is caused mainly by de novo mutations in the X-linked MECP2 gene, which encodes methyl-CpG binding protein 2 (Mecp2), a key epigenetic regulator. MECP2 mutations have profound impacts on neurons, which exhibit morphological, synaptic and functional impairments. However, more recent evidence highlights a crucial role of astrocytes in RTT pathogenesis. Indeed, RTT astrocytes exhibit structural and functional impairments, failing to support neuronal growth and function through non-cell autonomous mechanisms. Studies reveal that MECP2 deficient astrocytes secrete abnormal factors that impair neuronal growth and synaptic function. Furthermore, they show dysregulated calcium signalling, disrupted glutamate and potassium homeostasis, and increased inflammatory responses, all of which contribute to neuronal dysfunction. Understanding these neuron-astrocyte interactions may offer novel therapeutic targets for RTT. In the review we aim at presenting the current knowledge of astrocyte-neuron crosstalk in RTT, describing the different mechanisms highlighted so far through which MECP2 mutant astrocytes impair neurons. Finally, we discuss existing and prospective methodological approaches for investigating cell-to-cell communication in RTT.

Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source

Perception of voice means acoustic electric conversion in the auditory system, and changes of external magnetic field can affect the neural activities by taming the channel current via some field components including memristor and Josephson junction. Combination of two capacitors via an electric component is effective to describe the physical property of artificial cell membrane, which is often used to reproduce the characteristic of electric activities in cell membrane. Involvement of two capacitive variables for two capacitors in the neural circuit can discern the effect of field diversity in the media in two sides of the cell membrane in theoretical way. A Josephson junction is used to couple a piezoelectric neural circuit composed of two capacitors, one inductor and one nonlinear resistor. Field energy is mainly kept in the capacitive and inductive components, and it is obtained and converted into dimensionless energy function. The Hamilton energy function in an equivalent auditory neuron is verified by using the Helmholtz theorem. Noisy excitation on the neural circuit can be detected via the Josephson junction channel and similar stochastic resonance is detected by regulating the noise intensity, as a result, the average energy reaches a peak value under stochastic resonance. An adaptive law controls the bifurcation parameter, which is relative to the membrane property, and energy shift controls the mode selection during continuous growth of the bifurcation parameter. That is, external energy injection derived from acoustic wave or magnetic field will control the energy level, and then suitable firing patterns are controlled effectively.

Astroglial gap junctions strengthen hippocampal network activity by sustaining afterhyperpolarization via KCNQ channels

Throughout the brain, astrocytes form networks mediated by gap junction channels that promote the activity of neuronal ensembles. Although their inputs on neuronal information processing are well established, how molecular gap junction channels shape neuronal network patterns remains unclear. Here, using astroglial connexin-deficient mice, in which astrocytes are disconnected and neuronal bursting patterns are abnormal, we show that astrocyte networks strengthen bursting activity via dynamic regulation of extracellular potassium levels, independently of glutamate homeostasis or metabolic support. Using a facilitation-depression model, we identify neuronal afterhyperpolarization as the key parameter underlying bursting pattern regulation by extracellular potassium in mice with disconnected astrocytes. We confirm this prediction experimentally and reveal that astroglial network control of extracellular potassium sustains neuronal afterhyperpolarization via KCNQ voltage-gated K+ channels. Altogether, these data delineate how astroglial gap junctions mechanistically strengthen neuronal population bursts and point to approaches for controlling aberrant activity in neurological diseases.

Breathing cluster in complex neuron-astrocyte networks

Brain activities are featured by spatially distributed neural clusters of coherent firings and a spontaneous slow switching of the clusters between the coherent and incoherent states. Evidences from recent in vivo experiments suggest that astrocytes, a type of glial cell regarded previously as providing only structural and metabolic supports to neurons, participate actively in brain functions by regulating the neural firing activities, yet the underlying mechanism remains unknown. Here, introducing astrocyte as a reservoir of the glutamate released from the neuron synapses, we propose the model of the complex neuron-astrocyte network, and investigate the roles of astrocytes in regulating the cluster synchronization behaviors of networked chaotic neurons. It is found that a specific set of neurons on the network are synchronized and form a cluster, while the remaining neurons are kept as desynchronized. Moreover, during the course of network evolution, the cluster is switching between the synchrony and asynchrony states in an intermittent fashion, henceforth the phenomenon of "breathing cluster." By the method of symmetry-based analysis, we conduct a theoretical investigation on the synchronizability of the cluster. It is revealed that the contents of the cluster are determined by the network symmetry, while the breathing of the cluster is attributed to the interplay between the neural network and the astrocyte. The phenomenon of breathing cluster is demonstrated in different network models, including networks with different sizes, nodal dynamics, and coupling functions. The findings shed light on the cellular mechanism of astrocytes in regulating neural activities and give insights into the state-switching of the neocortex.

Purinergic signaling mediates neuroglial interactions to modulate sighs

Sighs prevent the collapse of alveoli in the lungs, initiate arousal under hypoxic conditions, and are an expression of sadness and relief. Sighs are periodically superimposed on normal breaths, known as eupnea. Implicated in the generation of these rhythmic behaviors is the preBötzinger complex (preBötC). Our experimental evidence suggests that purinergic signaling is necessary to generate spontaneous and hypoxia-induced sighs in a mouse model. Our results demonstrate that driving calcium increases in astrocytes through pharmacological methods robustly increases sigh, but not eupnea, frequency. Calcium imaging of preBötC slices corroborates this finding with an increase in astrocytic calcium upon application of sigh modulators, increasing intracellular calcium through g-protein signaling. Moreover, photo-activation of preBötC astrocytes is sufficient to elicit sigh activity, and this response is blocked with purinergic antagonists. We conclude that sighs are modulated through neuron-glia coupling in the preBötC network, where the distinct modulatory responses of neurons and glia allow for both rhythms to be independently regulated.

The computational power of the human brain

At the end of the 20th century, analog systems in computer science have been widely replaced by digital systems due to their higher computing power. Nevertheless, the question keeps being intriguing until now: is the brain analog or digital? Initially, the latter has been favored, considering it as a Turing machine that works like a digital computer. However, more recently, digital and analog processes have been combined to implant human behavior in robots, endowing them with artificial intelligence (AI). Therefore, we think it is timely to compare mathematical models with the biology of computation in the brain. To this end, digital and analog processes clearly identified in cellular and molecular interactions in the Central Nervous System are highlighted. But above that, we try to pinpoint reasons distinguishing in silico computation from salient features of biological computation. First, genuinely analog information processing has been observed in electrical synapses and through gap junctions, the latter both in neurons and astrocytes. Apparently opposed to that, neuronal action potentials (APs) or spikes represent clearly digital events, like the yes/no or 1/0 of a Turing machine. However, spikes are rarely uniform, but can vary in amplitude and widths, which has significant, differential effects on transmitter release at the presynaptic terminal, where notwithstanding the quantal (vesicular) release itself is digital. Conversely, at the dendritic site of the postsynaptic neuron, there are numerous analog events of computation. Moreover, synaptic transmission of information is not only neuronal, but heavily influenced by astrocytes tightly ensheathing the majority of synapses in brain (tripartite synapse). At least at this point, LTP and LTD modifying synaptic plasticity and believed to induce short and long-term memory processes including consolidation (equivalent to RAM and ROM in electronic devices) have to be discussed. The present knowledge of how the brain stores and retrieves memories includes a variety of options (e.g., neuronal network oscillations, engram cells, astrocytic syncytium). Also epigenetic features play crucial roles in memory formation and its consolidation, which necessarily guides to molecular events like gene transcription and translation. In conclusion, brain computation is not only digital or analog, or a combination of both, but encompasses features in parallel, and of higher orders of complexity.

Astrocytic modulation of neuronal signalling

Neuronal signalling is a key element in neuronal communication and is essential for the proper functioning of the CNS. Astrocytes, the most prominent glia in the brain play a key role in modulating neuronal signalling at the molecular, synaptic, cellular, and network levels. Over the past few decades, our knowledge about astrocytes and their functioning has evolved from considering them as merely a brain glue that provides structural support to neurons, to key communication elements. Astrocytes can regulate the activity of neurons by controlling the concentrations of ions and neurotransmitters in the extracellular milieu, as well as releasing chemicals and gliotransmitters that modulate neuronal activity. The aim of this review is to summarise the main processes through which astrocytes are modulating brain function. We will systematically distinguish between direct and indirect pathways in which astrocytes affect neuronal signalling at all levels. Lastly, we will summarize pathological conditions that arise once these signalling pathways are impaired focusing on neurodegeneration.

Parameter Inference for an Astrocyte Model using Machine Learning Approaches

Astrocytes are the largest subset of glial cells and perform structural, metabolic, and regulatory functions. They are directly involved in the communication at neuronal synapses and the maintenance of brain homeostasis. Several disorders, such as Alzheimer's, epilepsy, and schizophrenia, have been associated with astrocyte dysfunction. Computational models on various spatial levels have been proposed to aid in the understanding and research of astrocytes. The difficulty of computational astrocyte models is to fastly and precisely infer parameters. Physics informed neural networks (PINNs) use the underlying physics to infer parameters and, if necessary, dynamics that can not be observed. We have applied PINNs to estimate parameters for a computational model of an astrocytic compartment. The addition of two techniques helped with the gradient pathologies of the PINNS, the dynamic weighting of various loss components and the addition of Transformers. To overcome the issue that the neural network only learned the time dependence but did not know about eventual changes of the input stimulation to the astrocyte model, we followed an adaptation of PINNs from control theory (PINCs). In the end, we were able to infer parameters from artificial, noisy data, with stable results for the computational astrocyte model.

Information Encoding in Bursting Spiking Neural Network Modulated by Astrocytes

We investigated a mathematical model composed of a spiking neural network (SNN) interacting with astrocytes. We analysed how information content in the form of two-dimensional images can be represented by an SNN in the form of a spatiotemporal spiking pattern. The SNN includes excitatory and inhibitory neurons in some proportion, sustaining the excitation-inhibition balance of autonomous firing. The astrocytes accompanying each excitatory synapse provide a slow modulation of synaptic transmission strength. An information image was uploaded to the network in the form of excitatory stimulation pulses distributed in time reproducing the shape of the image. We found that astrocytic modulation prevented stimulation-induced SNN hyperexcitation and non-periodic bursting activity. Such homeostatic astrocytic regulation of neuronal activity makes it possible to restore the image supplied during stimulation and lost in the raster diagram of neuronal activity due to non-periodic neuronal firing. At a biological point, our model shows that astrocytes can act as an additional adaptive mechanism for regulating neural activity, which is crucial for sensory cortical representations.

Connectome-based biophysics models of Alzheimer's disease diagnosis and prognosis

With the increasing prevalence of Alzheimer's disease (AD) among aging populations and the limited therapeutic options available to slow or reverse its progression, the need has never been greater for improved diagnostic tools for identifying patients in the preclinical and prodomal phases of AD. Biophysics models of the connectome-based spread of amyloid-beta (Aβ) and microtubule-associated protein tau (τ) have enjoyed recent success as tools for predicting the time course of AD-related pathological changes. However, given the complex etiology of AD, which involves not only connectome-based spread of protein pathology but also the interactions of many molecular and cellular players over multiple spatiotemporal scales, more robust, complete biophysics models are needed to better understand AD pathophysiology and ultimately provide accurate patient-specific diagnoses and prognoses. Here we discuss several areas of active research in AD whose insights can be used to enhance the mathematical modeling of AD pathology as well as recent attempts at developing improved connectome-based biophysics models. These efforts toward a comprehensive yet parsimonious mathematical description of AD hold great promise for improving both the diagnosis of patients at risk for AD and our mechanistic understanding of how AD progresses.

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.

Controlling synchronization of gamma oscillations by astrocytic modulation in a model hippocampal neural network

Recent in vitro and in vivo experiments demonstrate that astrocytes participate in the maintenance of cortical gamma oscillations and recognition memory. However, the mathematical understanding of the underlying dynamical mechanisms remains largely incomplete. Here we investigate how the interplay of slow modulatory astrocytic signaling with fast synaptic transmission controls coherent oscillations in the network of hippocampal interneurons that receive inputs from pyramidal cells. We show that the astrocytic regulation of signal transmission between neurons improves the firing synchrony and extends the region of coherent oscillations in the biologically relevant values of synaptic conductance. Astrocyte-mediated potentiation of inhibitory synaptic transmission markedly enhances the coherence of network oscillations over a broad range of model parameters. Astrocytic regulation of excitatory synaptic input improves the robustness of interneuron network gamma oscillations induced by physiologically relevant excitatory model drive. These findings suggest a mechanism, by which the astrocytes become involved in cognitive function and information processing through modulating fast neural network dynamics.

Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays

Recent advances in the field of cellular reprogramming have opened a route to studying the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, HD-MEAs are used in vitro to characterize and compare human induced-pluripotent-stem-cell-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinson's disease and amyotrophic lateral sclerosis. Reproducible electrophysiological network, single-cell and subcellular metrics are used for phenotype characterization and drug testing. Metrics, such as burst shape and axonal velocity, enable the distinction of healthy and diseased neurons. The HD-MEA metrics can also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, it is shown that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes.

Modulation of Astrocytes on Mode Selection of Neuron Firing Driven by Electromagnetic Induction

Both of astrocytes and electromagnetic induction are magnificent to modulate neuron firing by introducing feedback currents to membrane potential. An improved astro-neuron model considering both of the two factors is employed to investigate their different roles in modulation. The mixing mode, defined by combination of period bursting and depolarization blockage, characterizes the effect of astrocytes. Mixing mode and period bursting alternatively appear in parameter space with respect to the amplitude of feedback current on neuron from astrocyte modulation. However, magnetic flux obviously plays a role of neuron firing inhibition. It not only repels the mixing mode but also suppresses period bursting. The mixing mode becomes period bursting mode and even resting state when astrocytes are hyperexcitable. Abnormal activities of astrocytes are capable to induce depolarization blockage to compose the mixing mode together with bursting mode. But electromagnetic induction shows its strong ability of inhibition of neuron firing, which is also illustrated in the bifurcation diagram. Indeed, the combination of the two factors and appropriate choice of parameters show the great potential to control disorder of neuron firing like epilepsy.

Dynamic Transitions in Neuronal Network Firing Sustained by Abnormal Astrocyte Feedback

Astrocytes play a crucial role in neuronal firing activity. Their abnormal state may lead to the pathological transition of neuronal firing patterns and even induce seizures. However, there is still little evidence explaining how the astrocyte network modulates seizures caused by structural abnormalities, such as gliosis. To explore the role of gliosis of the astrocyte network in epileptic seizures, we first established a direct astrocyte feedback neuronal network model on the basis of the hippocampal CA3 neuron-astrocyte model to simulate the condition of gliosis when astrocyte processes swell and the feedback to neurons increases in an abnormal state. We analyzed the firing pattern transitions of the neuronal network when astrocyte feedback starts to change via increases in both astrocyte feedback intensity and the connection probability of astrocytes to neurons in the network. The results show that as the connection probability and astrocyte feedback intensity increase, neuronal firing transforms from a nonepileptic synchronous firing state to an asynchronous firing state, and when astrocyte feedback starts to become abnormal, seizure-like firing becomes more severe and synchronized; meanwhile, the synchronization area continues to expand and eventually transforms into long-term seizure-like synchronous firing. Therefore, our results prove that astrocyte feedback can regulate the firing of the neuronal network, and when the astrocyte network develops gliosis, there will be an increase in the induction rate of epileptic seizures.

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.

An efficient neuron-astrocyte differentiation protocol from human embryonic stem cell-derived neural progenitors to assess chemical-induced developmental neurotoxicity

Human embryonic stem cell neuronal differentiation models provide promising in vitro tools for the prediction of developmental neurotoxicity of chemicals. Such models mimic essential elements of human relevant neuronal development, including the differentiation of a variety of brain cell types and their neuronal network formation as evidenced by specific gene and protein biomarkers. However, the reproducibility and lengthy culture duration of cell models present drawbacks and delay regulatory implementation. Here we present a relatively short and robust protocol to differentiate H9-derived neural progenitor cells (NPCs) into a neuron-astrocyte co-culture. When frozen-stored NPCs were re-cultured and induced into neuron-astrocyte differentiation, they showed gene- and protein expression typical for these cells, and most notably they exhibited spontaneous electrical activity within three days of culture as measured by a multi-well micro-electrode array. Modulating the ratio of astrocytes and neurons through different growth factors including glial cell line-derived neurotrophic factor (GDNF), brain-derived neurotrophic factor (BDNF), and ciliary neurotrophic factor (CNTF) did not compromise the ability to develop spontaneous electrical activity. This robust neuronal differentiation model may serve as a functional component of a testing strategy for unravelling mechanisms of developmental neurotoxicity.

The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging

Biological aging is a complex process involving multiple biological processes. These can be understood theoretically though considering them as individual networks-e.g., epigenetic networks, cell-cell networks (such as astroglial networks), and population genetics. Mathematical modeling allows the combination of such networks so that they may be studied in unison, to better understand how the so-called "seven pillars of aging" combine and to generate hypothesis for treating aging as a condition at relatively early biological ages. In this review, we consider how recent progression in mathematical modeling can be utilized to investigate aging, particularly in, but not exclusive to, the context of degenerative neuronal disease. We also consider how the latest techniques for generating biomarker models for disease prediction, such as longitudinal analysis and parenclitic analysis can be applied to as both biomarker platforms for aging, as well as to better understand the inescapable condition. This review is written by a highly diverse and multi-disciplinary team of scientists from across the globe and calls for greater collaboration between diverse fields of research.

Multi-lineage Human iPSC-Derived Platforms for Disease Modeling and Drug Discovery

Human induced pluripotent stem cells (hiPSCs) provide a powerful platform for disease modeling and have unlocked new possibilities for understanding the mechanisms governing human biology, physiology, and genetics. However, hiPSC-derivatives have traditionally been utilized in two-dimensional monocultures, in contrast to the multi-systemic interactions that influence cells in the body. We will discuss recent advances in generating more complex hiPSC-based systems using three-dimensional organoids, tissue-engineering, microfluidic organ-chips, and humanized animal systems. While hiPSC differentiation still requires optimization, these next-generation multi-lineage technologies can augment the biomedical researcher's toolkit and enable more realistic models of human tissue function.

A Computational Model of Interactions Between Neuronal and Astrocytic Networks: The Role of Astrocytes in the Stability of the Neuronal Firing Rate

Recent research in neuroscience indicates the importance of tripartite synapses and gliotransmission mediated by astrocytes in neuronal system modulation. Although the astrocyte and neuronal network functions are interrelated, they are fundamentally different in their signaling patterns and, possibly, the time scales at which they operate. However, the exact nature of gliotransmission and the effect of the tripartite synapse function at the network level are currently elusive. In this paper, we propose a computational model of interactions between an astrocyte network and a neuron network, starting from tripartite synapses and spanning to a joint network level. Our model focuses on a two-dimensional setup emulating a mixed in vitro neuron-astrocyte cell culture. The model depicts astrocyte-released gliotransmitters exerting opposing effects on the neurons: increasing the release probability of the presynaptic neuron while hyperpolarizing the post-synaptic one at a longer time scale. We simulated the joint networks with various levels of astrocyte contributions and neuronal activity levels. Our results indicate that astrocytes prolong the burst duration of neurons, while restricting hyperactivity. Thus, in our model, the effect of astrocytes is homeostatic; the firing rate of the network stabilizes to an intermediate level independently of neuronal base activity. Our computational model highlights the plausible roles of astrocytes in interconnected astrocytic and neuronal networks. Our simulations support recent findings in neurons and astrocytes in vivo and in vitro suggesting that astrocytic networks provide a modulatory role in the bursting of the neuronal network.

Vascular and non-vascular contributors to memory reduction during traumatic brain injury

Traumatic brain injury (TBI) is an increasing health problem. It is a complex, progressive disease that consists of many factors affecting memory. Studies have shown that increased blood-brain barrier (BBB) permeability initiates pathological changes in neuro-vascular network but the role of cerebrovascular dysfunction and its mediated mechanisms associated with memory reduction during TBI are still not well understood. Changes in BBB, inflammation, extravasation of blood plasma components, activation of neuroglia lead to neurodegeneration. Extravasated proteins such as amyloid-beta, fibrinogen, and cellular prion protein may form degradation resistant complexes that can lead to neuronal dysfunction and degeneration. They also have the ability to activate astrocytes, and thus, can be involved in memory impairment. Understanding the triggering mechanisms and the places they originate in vasculature or in extravascular tissue may help to identify potential therapeutic targets to ameliorate memory reduction during TBI. The goal of this review is to discuss conceptual mechanisms that lead to short-term memory reduction during non-severe TBI considering distinction between vascular and non-vascular effects on neurons. Some aspects of these mechanisms need to be confirmed further. Therefore, we hope that the discussion presented bellow may lead to experiments that may clarify the triggering mechanisms of memory reduction after head trauma.

Human iPSC-derived neuronal models for in vitro neurotoxicity assessment

Neurotoxicity testing still relies on ethically debated, expensive and time consuming in vivo experiments, which are unsuitable for high-throughput toxicity screening. There is thus a clear need for a rapid in vitro screening strategy that is preferably based on human-derived neurons to circumvent interspecies translation. Recent availability of commercially obtainable human induced pluripotent stem cell (hiPSC)-derived neurons and astrocytes holds great promise in assisting the transition from the current standard of rat primary cortical cultures to an animal-free alternative. We therefore composed several hiPSC-derived neuronal models with different ratios of excitatory and inhibitory neurons in the presence or absence of astrocytes. Using immunofluorescent stainings and multi-well micro-electrode array (mwMEA) recordings we demonstrate that these models form functional neuronal networks that become spontaneously active. The differences in development of spontaneous neuronal activity and bursting behavior as well as spiking patterns between our models confirm the importance of the presence of astrocytes. Preliminary neurotoxicity assessment demonstrates that these cultures can be modulated with known seizurogenic compounds, such as picrotoxin (PTX) and endosulfan, and the neurotoxicant methylmercury (MeHg). However, the chemical-induced effects on different parameters for neuronal activity, such as mean spike rate (MSR) and mean burst rate (MBR), may depend on the ratio of inhibitory and excitatory neurons. Our results thus indicate that hiPSC-derived neuronal models must be carefully designed and characterized prior to large-scale use in neurotoxicity screening.

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.

Digital Implementation of the Two-Compartmental Pinsky-Rinzel Pyramidal Neuron Model

It is believed that brain-like computing system can be achieved by the fusion of electronics and neuroscience. In this way, the optimized digital hardware implementation of neurons, primary units of nervous system, play a vital role in neuromorphic applications. Moreover, one of the main features of pyramidal neurons in cortical areas is bursting activities that has a critical role in synaptic plasticity. The Pinsky-Rinzel model is a nonlinear two-compartmental model for CA3 pyramidal cell that is widely used in neuroscience. In this paper, a modified Pinsky-Rinzel pyramidal model is proposed by replacing its complex nonlinear equations with piecewise linear approximation. Next, a digital circuit is designed for the simplified model to be able to implement on a low-cost digital hardware, such as field-programmable gate array (FPGA). Both original and proposed models are simulated in MATLAB and next digital circuit simulated in Vivado is compared to show that obtained results are in good agreement. Finally, the results of physical implementation on FPGA are also illustrated. The presented circuit advances preceding designs with regards to the ability to replicate essential characteristics of different firing responses including bursting and spiking in the compartmental model. This new circuit has various applications in neuromorphic engineering, such as developing new neuroinspired chips.

The role of neuron-glia interactions in the emergence of ultra-slow oscillations

Ultra-slow cortical oscillatory activity of 1-100 mHz has been recorded in human by electroencephalography and in dissociated cultures of cortical rat neurons, but the underlying mechanisms remain to be elucidated. This study presents a computational model of ultra-slow oscillatory activity based on the interaction between neurons and astrocytes. We predict that the frequency of these oscillations closely depends on activation of astrocytes in the network, which is reflected by oscillations of their intracellular calcium concentrations with periods between tens of seconds and minutes. An increase of intracellular calcium in astrocytes triggers the release of adenosine triphosphate from these cells which may alter transmission at nearby synapses by increasing or decreasing neurotransmitter release. These results provide theoretical support for the emerging awareness of astrocytes as active players in the regulation of neural activity and identify neuron-astrocyte interactions as a potential primary mechanism for the emergence of ultra-slow cortical oscillations.

Human induced pluripotent stem cell (hiPSC)-derived neurons respond to convulsant drugs when co-cultured with hiPSC-derived astrocytes

Accurate risk assessment for drug-induced seizure is expected to be performed before entering clinical studies because of its severity and fatal damage to drug development. Induced pluripotent stem cell (iPSC) technology has allowed the use of human neurons and glial cells in toxicology studies. Recently, several studies showed the advantage of co-culture system of human iPSC (hiPSC)-derived neurons with rodent/human primary astrocytes regarding neuronal functions. However, the application of hiPSC-derived neurons for seizure risk assessment has not yet been fully addressed, and not at all when co-cultured with hiPSC-derived astrocytes. Here, we characterized hiPSC-derived neurons co-cultured with hiPSC-derived astrocytes to discuss how hiPSC-derived neurons are useful to assess seizure risk of drugs. First, we detected the frequency of spikes and synchronized bursts hiPSC-derived neurons when co-cultured with hiPSC-derived astrocytes for 8 weeks. This synchronized burst was suppressed by the treatment with 6-cyano-7-nitroquinoxaline-2,3-dione, α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) receptor antagonist, and D-(-)-2-amino-5-phosphonopentanoic acid, an N-Methyl-d-aspartate (NMDA) receptor antagonist. These data suggested that co-cultured hiPSC-derived neurons formed synaptic connections mediated by AMPA and NMDA receptors. We also demonstrated that co-cultured hiPSC-derived neurons showed epileptiform activity upon treatment with gabazine or kaliotoxin. Finally, we performed single-cell transcriptome analysis in hiPSC-derived neurons and found that hiPSC-derived astrocytes activated the pathways involved in the activities of AMPA and NMDA receptor functions, neuronal polarity, and axon guidance in hiPSC-derived neurons. These data suggested that hiPSC-derived astrocytes promoted the development of action potential, synaptic functions, and neuronal networks in hiPSC-derived neurons, and then these functional alterations result in the epileptiform activity in response to convulsant drugs. Our study indicates the possibility that co-culture system of hiPSC-derived neurons with hiPSC-derived astrocytes could be useful in the risk assessment of drug-induced seizure.

Understanding the role of astrocytic GABA in simulated neural networks

Astrocytes actively influence the behavior of the surrounding neuronal network including changes of the synaptic plasticity and neuronal excitability. These dynamics are altered in diseases like Alzheimer's, where the release of the gliotransmitter GABA is increased by affected, so called reactive astrocytes. In this paper, we aim to simulate a neural network with altered astrocytic GABA release. Therefore, we use our developed neuron-astrocyte model, called INEXA, which includes astrocyte controlled tripartite synapses and the astrocyte-astrocyte interaction. Our results show that GABA released by astrocytes may be responsible for synchronous inhibition of postsynaptic neurons. With increased GABA inhibition, the spike and burst rate decreased while the burst duration and spikes per burst remain similar. To our knowledge, it is the first time that the effect of this gliotransmitter to the neural network was simulated.

Astrocytic modulation of neuronal excitability through K+ spatial buffering

The human brain contains two major cell populations, neurons and glia. While neurons are electrically excitable and capable of discharging short voltage pulses known as action potentials, glial cells are not. However, astrocytes, the prevailing subtype of glia in the cortex, are highly connected and can modulate the excitability of neurons by changing the concentration of potassium ions in the extracellular environment, a process called K⁺ clearance. During the past decade, astrocytes have been the focus of much research, mainly due to their close association with synapses and their modulatory impact on neuronal activity. It has been shown that astrocytes play an essential role in normal brain function including: nitrosative regulation of synaptic release in the neocortex, synaptogenesis, synaptic transmission and plasticity. Here, we discuss the role of astrocytes in network modulation through their K⁺ clearance capabilities, a theory that was first raised 50 years ago by Orkand and Kuffler. We will discuss the functional alterations in astrocytic activity that leads to aberrant modulation of network oscillations and synchronous activity.

From in silico astrocyte cell models to neuron-astrocyte network models: A review

The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons.

Paper-based patterned 3D neural cultures as a tool to study network activity on multielectrode arrays

High-throughput platform targeting activity patterns of 3D neural cultures with arbitrary topology, by combining network-wide intracellular and local extracellular signals.

A new bio-inspired stimulator to suppress hyper-synchronized neural firing in a cortical network

Hyper-synchronous neural oscillations are the character of several neurological diseases such as epilepsy. On the other hand, glial cells and particularly astrocytes can influence neural synchronization. Therefore, based on the recent researches, a new bio-inspired stimulator is proposed which basically is a dynamical model of the astrocyte biophysical model. The performance of the new stimulator is investigated on a large-scale, cortical network. Both excitatory and inhibitory synapses are also considered in the simulated spiking neural network. The simulation results show that the new stimulator has a good performance and is able to reduce recurrent abnormal excitability which in turn avoids the hyper-synchronous neural firing in the spiking neural network. In this way, the proposed stimulator has a demand controlled characteristic and is a good candidate for deep brain stimulation (DBS) technique to successfully suppress the neural hyper-synchronization.

Microcircuits in respiratory rhythm generation: commonalities with other rhythm generating networks and evolutionary perspectives

Rhythmicity is critical for the generation of rhythmic behaviors and higher brain functions. This review discusses common mechanisms of rhythm generation, including the role of synaptic inhibition and excitation, with a focus on the mammalian respiratory network. This network generates three phases of breathing and is highly integrated with brain regions associated with numerous non-ventilatory behaviors. We hypothesize that during evolution multiple rhythmogenic microcircuits were recruited to accommodate the generation of each breathing phase. While these microcircuits relied primarily on excitatory mechanisms, synaptic inhibition became increasingly important to coordinate the different microcircuits and to integrate breathing into a rich behavioral repertoire that links breathing to sensory processing, arousal, and emotions as well as learning and memory.

The role of astrocyte mitochondria in differential regional susceptibility to environmental neurotoxicants: tools for understanding neurodegeneration

In recent decades, there has been a significant expansion in our understanding of the role of astrocytes in neuroprotection, including spatial buffering of extracellular ions, secretion of metabolic coenzymes, and synaptic regulation. Astrocytic neuroprotective functions require energy, and therefore require a network of functional mitochondria. Disturbances to astrocytic mitochondrial homeostasis and their ability to produce ATP can negatively impact neural function. Perturbations in astrocyte mitochondrial function may accrue as the result of physiological aging processes or as a consequence of neurotoxicant exposure. Hydrophobic environmental neurotoxicants, such as 1,3-dinitrobenzene and α-chlorohydrin, cause regionally specific spongiform lesions mimicking energy deprivation syndromes. Astrocyte involvement includes mitochondrial damage that either precedes or is accompanied by neuronal damage. Similarly, environmental neurotoxicants that are implicated in the etiology of age-related neurodegenerative conditions cause regionally specific damage in the brain. Based on the regioselective nature of age-related neurodegenerative lesions, chemically induced models of regioselective lesions targeting astrocyte mitochondria can provide insight into age-related susceptibilities in astrocyte mitochondria. Most of the available research to date focuses on neuronal damage in cases of age-related neurodegeneration; however, there is a body of evidence that supports a central mechanistic role for astrocyte mitochondria in the expression of neural injury. Regional susceptibility to neuronal damage induced by aging by exposure to neurotoxicants may be a reflection of highly variable regional energy requirements. This review identifies region-specific vulnerabilities in astrocyte mitochondria in examples of exposure to neurotoxicants and in age-related neurodegeneration.

The Impact of Neuroimmune Alterations in Autism Spectrum Disorder

Autism spectrum disorder (ASD) involves a complex interplay of both genetic and environmental risk factors, with immune alterations and synaptic connection deficiency in early life. In the past decade, studies of ASD have substantially increased, in both humans and animal models. Immunological imbalance (including autoimmunity) has been proposed as a major etiological component in ASD, taking into account increased levels of pro-inflammatory cytokines observed in postmortem brain from patients, as well as autoantibody production. Also, epidemiological studies have established a correlation of ASD with family history of autoimmune diseases; associations with major histocompatibility complex haplotypes and abnormal levels of immunological markers in the blood. Moreover, the use of animal models to study ASD is providing increasing information on the relationship between the immune system and the pathophysiology of ASD. Herein, we will discuss the accumulating literature for ASD, giving special attention to the relevant aspects of factors that may be related to the neuroimmune interface in the development of ASD, including changes in neuroplasticity.

Neuron-glia networks: integral gear of brain function

Astrocytes, the most abundant glial cell in the brain, play critical roles in metabolic and homeostatic functions of the Nervous System; however, their participation in coding information and cognitive processes has been largely ignored. The strategic position of astrocyte processes facing synapses and the astrocyte ability to uptake neurotransmitters and release neuroactive substances, so-called “gliotransmitters”, provide the scenario for prolific neuron-astrocyte signaling. From studies at single-cell level to animal behavior, recent advances in technology and genetics have revealed the impact of astrocyte activity in brain function from cellular and synaptic physiology, neuronal circuits to behavior. The present review critically discusses the consequences of astrocyte signaling on synapses and networks, as well as its impact on neuronal information processing, showing that some crucial brain functions arise from the coordinated activity of neuron-glia networks.

A digital neurmorphic circuit for a simplified model of astrocyte dynamics

Recent neurophysiologic findings have shown that astrocytes (the most abundant type of glial cells) are active partners in neural information processing and regulate the synaptic transmission dynamically. Motivated by these findings, in the present research, a digital neuromorphic circuit to implement the astrocyte dynamics is developed. To model the dynamics of the intracellular Ca(2+) waves produced by astrocytes, we utilize a simplified model which considers the main physiological pathways of neuron-astrocyte interactions. Next, a digital circuit for the astrocyte dynamic is proposed which is simulated using ModelSim and finally, it is implemented in hardware on the ZedBoard. The results of hardware synthesis, FPGA implementations are in agreement with MATLAB and ModelSim simulations and confirm that the proposed digital astrocyte is suitable for applications in reconfigurable neuromorphic devices which implement biologically brain circuits.

Astrocyte-neuron interactions: from experimental research-based models to translational medicine

In this chapter, we review the principal astrocyte functions and the interactions between neurons and astrocytes. We then address how the experimentally observed functions have been verified in computational models and review recent experimental literature on astrocyte-neuron interactions. Benefits of computational neuroscience work are highlighted through selected studies with neurons and astrocytes by analyzing the existing models qualitatively and assessing the relevance of these models to experimental data. Common strategies to mathematical modeling and computer simulation in neuroscience are summarized for the nontechnical reader. The astrocyte-neuron interactions are then further illustrated by examples of some neurological and neurodegenerative diseases, where the miscommunication between glia and neurons is found to be increasingly important.

The role of astrocytes in the regulation of synaptic plasticity and memory formation

Astrocytes regulate synaptic transmission and play a role in the formation of new memories, long-term potentiation (LTP), and functional synaptic plasticity. Specifically, astroglial release of glutamate, ATP, and cytokines likely alters the survivability and functioning of newly formed connections. Among these pathways, regulation of glutamate appears to be most directly related to the promotion of LTP, which is highly dependent on the synchronization of synaptic receptors through the regulation of excitatory postsynaptic potentials. Moreover, regulation of postsynaptic glutamate receptors, particularly AMPA receptors, is dependent on signaling by ATP synthesized in astrocytes. Finally, cytokine signaling is also implicated in regulating LTP, but is likely most important in plasticity following tissue damage. Despite the role of these signaling factors in regulating LTP and functional plasticity, an integrative model of these factors has not yet been elucidated. In this review, we seek to summarize the current body of evidence on astrocytic mechanisms for regulation of LTP and functional plasticity, and provide an integrative model of the processes.

Information transmission in a neuron-astrocyte coupled model

A coupled model containing two neurons and one astrocyte is constructed by integrating Hodgkin-Huxley neuronal model and Li-Rinzel calcium model. Based on this hybrid model, information transmission between neurons is studied numerically. Our results show that when the successive spikes are produced in neuron 1 (N1), the bursting-like spikes (BLSs) occur in two neurons simultaneously during the spikes being transferred to neuron 2 (N2). The existence of the astrocyte and a higher expression level of mGluRs facilitate the occurrence of BLSs, but the rate of occurrence is not sensitive to the parameters. Furthermore, time delay τ occurs during the information transmission, and τ is almost independent of the effect of the astrocyte. Additionally, we found that low coupling strength may result in the distortion of the information, and this distortion is also proven to be almost independent of the astrocyte.

A phase plane analysis of neuron-astrocyte interactions

Intensive experimental studies have shown that astrocytes are active partners in modulation of synaptic transmission. In the present research, we study neuron-astrocyte signaling using a biologically inspired model of one neuron synapsing one astrocyte. In this model, the firing dynamics of the neuron is described by the Morris-Lecar model and the Ca(2+) dynamics of a single astrocyte explained by a functional model introduced by Postnov and colleagues. Using the coupled neuron-astrocyte model and based on the results of the phase plane analyses, it is demonstrated that the astrocyte is able to activate the silent neuron or change the neuron spiking frequency through bidirectional communication. This suggests that astrocyte feedback signaling is capable of modulating spike transmission frequency by changing neuron spiking frequency. This effect is described by a saddle-node on invariant circle bifurcation in the coupled neuron-astrocyte model. In this way, our results suggest that the neuron-astrocyte crosstalk has a fundamental role in producing diverse neuronal activities and therefore enhances the information processing capabilities of the brain.