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Xenon pressure dependence on the synchronized burst inhibition of rat cortical neuronal network cultured on multi-electrode arrays.

ABSTRACT: Mature rat cortical neuronal networks cultured on multi-electrode arrays (MEAs) are known to show spontaneous synchronized bursts accompanied by independent single spikes. The spontaneous synchronized bursts can be inhibited by Xe gas. In this study, we adjust the Xe gas pressure to control the amount of Xe in a neuron-cultured MEA medium. We show that the synchronized bursts cease completely within several minutes by applying Xe gas at partial pressures above 0.3 MPa. After depressurizing and purging with fresh air, the synchronized bursts recover to their original frequency. Thus, we confirmed that Xe acts as a network-activity inhibitor of the cultured neuronal network on MEAs. But below 0.3 MPa, the synchronized bursts are inhibited only partially, depending on the Xe partial pressure. Based on the partial-pressure influence on the change of the neuronal network activities, we find the critical concentration of Xe for the inhibition effect to be approximately 9.5 mM, a value above which more than 90% of the synchronized burst activity is inhibited. Further systematic observations with Xe-air mixed gases show that pressurized air with a small amount of Xe suppresses the inhibition of synchronized bursts, suggesting an air component that can accelerate the synchronized bursts.

SUBMITTER: Uchida T

PROVIDER: S-EPMC6084913 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundCortical cultures grown long-term on multi-electrode arrays (MEAs) are frequently and extensively used as models of cortical networks in studies of neuronal firing activity, neuropharmacology, toxicology and mechanisms underlying synaptic plasticity. However, in contrast to the predominantly asynchronous neuronal firing activity exhibited by intact cortex, electrophysiological activity of mature cortical cultures is dominated by spontaneous epileptiform-like global burst events which hinders their effective use in network-level studies, particularly for neurally-controlled animat ('artificial animal') applications. Thus, the identification of culture features that can be exploited to produce neuronal activity more representative of that seen in vivo could increase the utility and relevance of studies that employ these preparations. Acetylcholine has a recognised neuromodulatory role affecting excitability, rhythmicity, plasticity and information flow in vivo although its endogenous production by cortical cultures and subsequent functional influence upon neuronal excitability remains unknown.ResultsConsequently, using MEA electrophysiological recording supported by immunohistochemical and RT-qPCR methods, we demonstrate for the first time, the presence of intrinsic cholinergic neurons and significant, endogenous cholinergic tone in cortical cultures with a characterisation of the muscarinic and nicotinic components that underlie modulation of spontaneous neuronal activity. We found that tonic muscarinic ACh receptor (mAChR) activation affects global excitability and burst event regularity in a culture age-dependent manner whilst, in contrast, tonic nicotinic ACh receptor (nAChR) activation can modulate burst duration and the proportion of spikes occurring within bursts in a spatio-temporal fashion.ConclusionsWe suggest that the presence of significant endogenous cholinergic tone in cortical cultures and the comparability of its modulatory effects to those seen in intact brain tissues support emerging, exploitable commonalities between in vivo and in vitro preparations. We conclude that experimental manipulation of endogenous cholinergic tone could offer a novel opportunity to improve the use of cortical cultures for studies of network-level mechanisms in a manner that remains largely consistent with its functional role.

Project description:Nowadays, in vitro three-dimensional (3D) neuronal networks are becoming a consolidated experimental model to overcome most of the intrinsic limitations of bi-dimensional (2D) assemblies. In the 3D environment, experimental evidence revealed a wider repertoire of activity patterns, characterized by a modulation of the bursting features, than the one observed in 2D cultures. However, it is not totally clear and understood what pushes the neuronal networks towards different dynamical regimes. One possible explanation could be the underlying connectivity, which could involve a larger number of neurons in a 3D rather than a 2D space and could organize following well-defined topological schemes. Driven by experimental findings, achieved by recording 3D cortical networks organized in multi-layered structures coupled to Micro-Electrode Arrays (MEAs), in the present work we developed a large-scale computational network model made up of leaky integrate-and-fire (LIF) neurons to investigate possible structural configurations able to sustain the emerging patterns of electrophysiological activity. In particular, we investigated the role of the number of layers defining a 3D assembly and the spatial distribution of the connections within and among the layers. These configurations give rise to different patterns of activity that could be compared to the ones emerging from real in vitro 3D neuronal populations. Our results suggest that the introduction of three-dimensionality induced a global reduction in both firing and bursting rates with respect to 2D models. In addition, we found that there is a minimum number of layers necessary to obtain a change in the dynamics of the network. However, the effects produced by a 3D organization of the cells is somewhat mitigated if a scale-free connectivity is implemented in either one or all the layers of the network. Finally, the best matching of the experimental data is achieved supposing a 3D connectivity organized in structured bundles of links located in different areas of the 2D network.

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Xenon pressure dependence on the synchronized burst inhibition of rat cortical neuronal network cultured on multi-electrode arrays.

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