Despite the extensive use of in-vitro models for neuroscientific investigations and notwithstanding the growing field of network electrophysiology, all studies on cultured cells devoted to elucidate neurophysiological mechanisms and computational properties, are based on 2D neuronal networks. These networks are usually grown onto specific rigid substrates (also with embedded electrodes) and lack of most of the constituents of the in-vivo like environment: cell morphology, cell-to-cell interaction and neuritic outgrowth in all directions. Cells in a brain region develop in a 3D space and interact with a complex multi-cellular environment and extracellular matrix. Under this perspective, 3D networks coupled to micro-transducer arrays, represent a new and powerful in-vitro model capable of better emulating in-vivo physiology. In this work, we present a new experimental paradigm constituted by 3D hippocampal networks coupled to Micro-Electrode-Arrays (MEAs) and we show how the features of the recorded network dynamics differ from the corresponding 2D network model. Further development of the proposed 3D in-vitro model by adding embedded functionalized scaffolds might open new prospects for manipulating, stimulating and recording the neuronal activity to elucidate neurophysiological mechanisms and to design bio-hybrid microsystems.

Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness S a affects networks topology. In the low nano-meter range, S a = 0–30 nm, information increases with S a. Moreover, we found that energy density of a network of cells correlates to the topology of that network. This reinforces the view that information, energy and surface nano-topography are tightly inter-connected and should not be neglected when studying cell-cell interaction in neural tissue repair and regeneration.

Due to their small dimensions, electrophysiology on thin and intricate axonal branches in support of understanding their role in normal and diseased brain function poses experimental challenges. To reduce experimental complexity, we coupled microelectrode arrays (MEAs) to bi-level microchannel devices for the long-term in vitro tracking of axonal morphology and activity with high spatiotemporal resolution. Our model allowed the long-term multisite recording from pure axonal branches in a microscopy-compatible environment. Compartmentalizing the network structure into interconnected subpopulations simplified access to the locations of interest. Electrophysiological data over 95 days in vitro (DIV) showed an age-dependent increase of axonal conduction velocity, which was positively correlated with, but independent of evolving burst activity over time. Conduction velocity remained constant at chemically increased network activity levels. In contrast, low frequency (1 Hz, 180 repetitions) electrical stimulation of axons or network subpopulations evoked amplitude-dependent direct (5–35 ms peri-stimulus) and polysynaptic (35–1,000 ms peri-stimulus) activity with temporarily (<35 ms) elevated propagation velocities along the perisomatic branches. Furthermore, effective stimulation amplitudes were found to be significantly lower (>250 mV) in microchannels when compared with those reported for unconfined cultures (>800 mV). The experimental paradigm may lead to new insights into stimulation-induced axonal plasticity.

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Abscisic acid (ABA), a long known phytohormone, has been recently demonstrated to be present also in humans, where it targets cells of the innate immune response, mesenchymal and hemopoietic stem cells and cells involved in the regulation of systemic glucose homeostasis. LANCL2, a peripheral membrane protein, is the mammalian ABA receptor. We show that N-terminal glycine myristoylation causes LANCL2 localization to the plasmamembrane and to cytoplasmic membrane vesicles, where it interacts with the α subunit of a Gi protein and starts the ABA signaling pathway via activation of adenylate cyclase. Demyristoylation of LANCL2 by chemical or genetic means triggers its nuclear translocation. Nuclear enrichment of native LANCL2 is also induced by ABA treatment. Therefore human LANCL2 is a non-transmembrane G protein-coupled receptor susceptible to hormone-induced nuclear translocation.

During development, axons of neurons in the mammalian central nervous system lose their ability to regenerate. To study the regeneration process, axons of mouse hippocampal neurons were partially damaged by an UVA laser dissector system. The possibility to deliver very low average power to the sample reduced the collateral thermal damage and allowed studying axonal regeneration of mouse neurons during early days in vitro. Force spectroscopy measurements were performed during and after axon ablation with a bead attached to the axonal membrane and held in an optical trap. With this approach, we quantified the adhesion of the axon to the substrate and the viscoelastic properties of the membrane during regeneration. The reorganization and regeneration of the axon was documented by long-term live imaging. Here we demonstrate that BDNF regulates neuronal adhesion and favors the formation of actin waves during regeneration after axonal lesion.

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Currently, large-scale networks derived from dissociated neurons growing and developing in vitro on extracellular micro-transducer devices are the gold-standard experimental model to study basic neurophysiological mechanisms involved in the formation and maintenance of neuronal cell assemblies. However, in vitro studies have been limited to the recording of the electrophysiological activity generated by bi-dimensional (2D) neural networks. Nonetheless, given the intricate relationship between structure and dynamics, a significant improvement is necessary to investigate the formation and the developing dynamics of three-dimensional (3D) networks. In this work, a novel experimental platform in which 3D hippocampal or cortical networks are coupled to planar Micro-Electrode Arrays (MEAs) is presented. 3D networks are realized by seeding neurons in a scaffold constituted of glass microbeads (30-40 µm in diameter) on which neurons are able to grow and form complex interconnected 3D assemblies. In this way, it is possible to design engineered 3D networks made up of 5-8 layers with an expected final cell density. The increasing complexity in the morphological organization of the 3D assembly induces an enhancement of the electrophysiological patterns displayed by this type of networks. Compared with the standard 2D networks, where highly stereotyped bursting activity emerges, the 3D structure alters the bursting activity in terms of duration and frequency, as well as it allows observation of more random spiking activity. In this sense, the developed 3D model more closely resembles in vivo neural networks.