Astrocytic gliotransmission as a pathway for stable stimulation of post-synaptic spiking: Implications for working memory

The brain consists not only of neurons but also of non-neuronal cells, including astrocytes. Recent discoveries in neuroscience suggest that astrocytes directly regulate neuronal activity by releasing gliotransmitters such as glutamate. In this paper, we consider a biologically plausible mathematical model of a tripartite neuron-astrocyte network. We study the stability of the nonlinear astrocyte dynamics, as well as its role in regulating the firing rate of the post-synaptic neuron. We show that astrocytes enable storing neuronal information temporarily. Motivated by recent findings on the role of astrocytes in explaining mechanisms of working memory, we numerically verify the utility of our analysis in showing the possibility of two competing theories of persistent and sparse neuronal activity of working memory.Comment: IFAC World Congress (2023

From multiscale biophysics to digital twins of tissues and organs: future opportunities for in silico pharmacology

With many advancements in in silico biology in recent years, the paramount challenge is to translate the accumulated knowledge into exciting industry partnerships and clinical applications. Achieving models that characterize the link of molecular interactions to the activity and structure of a whole organ are termed multiscale biophysics. Historically, the pharmaceutical industry has worked well with in silico models by leveraging their prediction capabilities for drug testing. However, the needed higher fidelity and higher resolution of models for efficient prediction of pharmacological phenomenon dictates that in silico approaches must account for the verifiable multiscale biophysical phenomena, as a spatial and temporal dimension variation for different processes and models. The collection of different multiscale models for different tissues and organs can compose digital twin solutions towards becoming a service for researchers, clinicians, and drug developers. Our paper has two main goals: 1) To clarify to what extent detailed single- and multiscale modeling has been accomplished thus far, we provide a review on this topic focusing on the biophysics of epithelial, cardiac, and brain tissues; 2) To discuss the present and future role of multiscale biophysics in in silico pharmacology as a digital twin solution by defining a roadmap from simple biophysical models to powerful prediction tools. Digital twins have the potential to pave the way for extensive clinical and pharmaceutical usage of multiscale models and our paper shows the basic fundamentals and opportunities towards their accurate development enabling the quantum leaps of future precise and personalized medical software.Comment: 30 pages, 10 figures, 1 tabl

Larger Connection Radius Increases Hub Astrocyte Number in a 3D Neuron-Astrocyte Network Model

Astrocytes – a prominent glial cell type in the brain – form networks that tightly interact with the brain’s neuronal circuits. Thus, it is essential to study the modes of such interaction if we aim to understand how neural circuits process information. Thereby, calcium elevations, the primary signal in astrocytes, propagate to the adjacent neighboring cells and directly regulate neuronal communication. It is mostly unknown how the astrocyte network topology influences neuronal activity. Here, we used a computational model to simulate planar and 3D neuron-astrocyte networks with varying topologies. We investigated the number of active nodes, the shortest path, and the mean degree. Furthermore, we applied a graph coloring analysis that highlights the network organization between different network structures. With the increase of the maximum distance between two connected astrocytes, the information flow is more centralized to the most connected cells. Our results suggest that activity-dependent plasticity and the topology of brain areas might alter the amount of astrocyte controlled synapses

Astrocytic control in in vitro and simulated neuron-astrocyte networks

acceptedVersionPeer reviewe

Astrocytes in modulating subcellular, cellular and intercellular molecular neuronal communication

Astrocytes are one of the most abundant cell types in our brain. They modulate the brain homeostasis and play a role in the synaptic signalling and thus the molecular propagation inside the brain. Moreover, they form communication networks that co-localise with the neuronal networks with comparable topological complexity. There is an increasing piece of evidence that astrocytes are important in plasticity and learning from the level of the single synapse to the entire network. Moreover, several diseases are molecular communications on different scales from the synaptic to network level.acceptedVersionPeer reviewe

Astrocytes Exhibit a Protective Role in Neuronal Firing Patterns under Chemically Induced Seizures in Neuron-Astrocyte Co-Cultures.

Astrocytes and neurons respond to each other by releasing transmitters, such as γ-aminobutyric acid (GABA) and glutamate, that modulate the synaptic transmission and electrochemical behavior of both cell types. Astrocytes also maintain neuronal homeostasis by clearing neurotransmitters from the extracellular space. These astrocytic actions are altered in diseases involving malfunction of neurons, e.g., in epilepsy, Alzheimer's disease, and Parkinson's disease. Convulsant drugs such as 4-aminopyridine (4-AP) and gabazine are commonly used to study epilepsy in vitro. In this study, we aim to assess the modulatory roles of astrocytes during epileptic-like conditions and in compensating drug-elicited hyperactivity. We plated rat cortical neurons and astrocytes with different ratios on microelectrode arrays, induced seizures with 4-AP and gabazine, and recorded the evoked neuronal activity. Our results indicated that astrocytes effectively counteracted the effect of 4-AP during stimulation. Gabazine, instead, induced neuronal hyperactivity and synchronicity in all cultures. Furthermore, our results showed that the response time to the drugs increased with an increasing number of astrocytes in the co-cultures. To the best of our knowledge, our study is the first that shows the critical modulatory role of astrocytes in 4-AP and gabazine-induced discharges and highlights the importance of considering different proportions of cells in the cultures

Simulation of developing human neuronal cell networks

BACKGROUND: Microelectrode array (MEA) is a widely used technique to study for example the functional properties of neuronal networks derived from human embryonic stem cells (hESC-NN). With hESC-NN, we can investigate the earliest developmental stages of neuronal network formation in the human brain. METHODS: In this paper, we propose an in silico model of maturating hESC-NNs based on a phenomenological model called INEX. We focus on simulations of the development of bursts in hESC-NNs, which are the main feature of neuronal activation patterns. The model was developed with data from developing hESC-NN recordings on MEAs which showed increase in the neuronal activity during the investigated six measurement time points in the experimental and simulated data. RESULTS: Our simulations suggest that the maturation process of hESC-NN, resulting in the formation of bursts, can be explained by the development of synapses. Moreover, spike and burst rate both decreased at the last measurement time point suggesting a pruning of synapses as the weak ones are removed. CONCLUSIONS: To conclude, our model reflects the assumption that the interaction between excitatory and inhibitory neurons during the maturation of a neuronal network and the spontaneous emergence of bursts are due to increased connectivity caused by the forming of new synapses.BioMed Central open acces

Combined Experimental and System-Level Analyses Reveal the Complex Regulatory Network of miR-124 during Human Neurogenesis

Non-coding RNAs regulate many biological processes including neurogenesis. The brain-enriched miR-124 has been assigned as a key player of neuronal differentiation via its complex but little understood regulation of thousands of annotated targets. To systematically chart its regulatory functions, we used CRISPR/Cas9 gene editing to disrupt all six miR-124 alleles in human induced pluripotent stem cells. Upon neuronal induction, miR-124-deleted cells underwent neurogenesis and became functional neurons, albeit with altered morphology and neurotransmitter specification. Using RNA-induced-silencing-complex precipitation, we identified 98 high-confidence miR-124 targets, of which some directly led to decreased viability. By performing advanced transcription-factor-network analysis, we identified indirect miR-124 effects on apoptosis, neuronal subtype differentiation, and the regulation of previously uncharacterized zinc finger transcription factors. Our data emphasize the need for combined experimental- and system-level analyses to comprehensively disentangle and reveal miRNA functions, including their involvement in the neurogenesis of diverse neuronal cell types found in the human brain

Analyse und Simulation von Konzentrations-Wirkungskurven auf Grundlage von Multielektroden-Neurochip-Experimenten

Thema Die Dissertation ist aus dem Themengebiet der Computational Neuroscience, die sich mit der Untersuchung der Informationsverarbeitung im neuronalen System beschäftigt, entstanden. In diesem Forschungsbereich gehören in vitro Multielektroden-Arrays (MEAs) zu den wichtigsten Hilfsmitteln, um die neuronalen Signale aufzuzeichnen. Die MEA-Neurochip-Technologie soll die Untersuchung der Wirkungen und Nebenwirkungen von neuroaktiven Substanzen in einer frühen Phase der pharmakologischen Produktentwicklung unterstützen, so dass ein High-Throughput-Screening von pharmakologischen Kandidaten ermöglicht wird. Somit kann zum Beispiel nach einer Behandlungsstrategie für neurodegenerative Erkrankungen gesucht werden. Zielstellung Das konkrete Ziel der Dissertation ist die Untersuchung von Konzentrations-Wirkungskurven (KWK) sowohl in Experimenten als auch in Simulationen. KWK stellen die konzentrationsabhängige Wirkung von neuroaktiven Substanzen auf verschiedene Merkmale der neuronalen Aktivität dar. Sie spiegeln unterschiedliche Wirkmechanismen der Substanzen an Rezeptoren wider. Damit helfen KWK das Zusammenspiel der verschiedenen Rezeptorwirkungen von neuroaktiven Substanzen qualitativ und quantitativ zu erfassen. Des Weiteren wird die Veränderung der Grundfrequenzen nach Zugabe einer neuroaktiven Substanz untersucht. Methoden Im Rahmen der Dissertation wurden mit CRCFitting (CRC = concentration-response curve) und dem INEX-Modell zwei Software-Module entwickelt, implementiert und getestet sowie zur Auswertung von Daten genutzt: 1) Das Softwaremodul CRCFitting ermöglicht die automatisierte Berechnung von KWK, die Bewertung der Güte dieser Berechnung und die Bestimmung von neuen Merkmalen aus den KWK. Insbesondere entfällt bei der KWK-Berechnung jegliche händische Festlegung von Parameterbereichen oder Startwerten. Ein weiterer großer Vorteil ist die automatisierte Bestimmung der Phasigkeit einer KWK; diese Phasigkeit entspricht unterschiedlichen Rezeptorwirkungen einer Substanz. 2) Das Simulationstool INEX beruht als Simulationstool auf einem Modell spikender Neurone. Ein inhomogener Poissonprozess simuliert das Spiken und die synaptische Wirkung entsteht durch exzitatorische (enthemmende) und inhibitorische (hemmende) Synapsen. Dieses Modell zeichnet sich durch seine Schnelligkeit in der Simulation aus, weshalb auch große Netzwerke mit 10.000 Neuronen und mehr simuliert werden können. Das INEX-Modell ermöglicht es außerdem, unterschiedliche Vernetzungsgrade einer Neuronenpopulation sowie das Verhältnis des Anteils inhibitorischer zum Anteil exzitatorischer Neuronen zu untersuchen. Des Weiteren wurde mittels des an der TU Clausthal entwickelten Tools „SpikeTrain-Analysator“ multiplikative Frequenzleistungsspektren aus den Spiketrains mehrerer neuronaler Kulturen vor und nach Zugabe einer neuroaktiven Substanz berechnet. Ergebnisse Die automatisierte Berechnung von KWK und die nachfolgende Bestimmung von Merkmalen für die Substanzen erlauben es, eine Substanz aufgrund dieser Merkmale mit hoher Sensitivität zu identifizieren. Der „SpikeTrain-Analysator" zeigt eine Spindelbildung der Frequenzdifferenz-leistungsspektren bei Experimenten mit Agmatin auf. Das INEX-Modell ist gut geeignet, um neuronale Aktivität, wie sie bei MEA-Neurochip-Experimenten beobachtet wird, zu simulieren. Dies wird qualitativ und quantitativ nachgewiesen. Vereint werden die beiden im Rahmen der Dissertation entwickelten Tools in der Simulation von KWK durch das INEX-Modell, um schließlich zu zeigen, wie verschiedene Rezeptorwirkungen unterschiedliche KWK entstehen lassen.Topic The dissertation is part of the subject area of Computational Neuroscience, which has the focus on the investigation of information processing in neuronal systems. In this research area, in vitro multielectrode arrays (MEAs) are a widely used tool to record neuronal signals. The MEA neurochip technology supports the analysis of response and side effects of neuro-active substances in an early phase of pharmacological product development to allow a high-throughput screening of potential pharmacological drugs. Hence, a screening for therapeutic strategies of neurodegenerative diseases is possible. Objectives The concrete aim of the dissertation is the investigation of concentration-response curves (CRC) in experiments as well as in simulations. CRCs are the concentration-depended responses of neuro-active substances to various features of the neuronal activity. They reflect different mechanisms of action of substances at the receptor sides. Thus, CRCs capture qualitatively and quantitively the interplay of different receptor responses of neuro-active substances. Moreover, the change of the base frequencies after the application of a neuro-active substance is investigated. Methods Within the scope of the dissertation, two software modules, the CRCFitting (CRC = concentration-response curve) toolbox and the INEX model, were developed, implemented and tested as well as used for data analysis. 1) The software module CRCFitting enables the automatized computation of CRCs, the assessment of the goodness of fit and the calculation of new features from CRCs. Particularly, the manual definition of parameter ranges and starting values is not required. An additional advantage is the automatized definition of the number of phases of a CRC; this number corresponds to diverse receptor responses of one substance. 2) The simulation tool INEX is based on a model of spiking neurons. An inhomogeneous Poisson process simulates the spiking and the synaptic response originating from excitatory and inhibitory synapses. The model is characterized by short run times, so that large networks with 10,000 neurons and more can be simulated. The INEX model allows additionally different connectivity percentages and the change of the portion of inhibitory and excitatory neurons. Moreover, using the tool „SpikeTrain-Analysator“ developed at TU Clausthal, multiplicative frequency power spectra are calculated from spike trains obtained from several neuronal cultures before and after adding a neuro-active substance. Results The automatized computation of CRCs and the following calculation of features allow an identification of a substance with high sensitivity. The „SpikeTrain-Analysator“ shows a spindle formation of the frequency power spectra in experiments with agmatine. The INEX model is well suitable to simulate neuronal activity as observed in MEA neurochip experiments which was proved qualitatively and quantitatively. The two within the scope of the thesis developed tools are combined in simulations of CRCs using the INEX model to show how different receptor responses result in diverse CRCs