Ring-shaped neuronal networks: a platform to study persistent activity

Three-Dimensional Cell Drawing Technique in Hydrogel Using Micro Injection System

Fabrication of three-dimensional tissues using living cells is a promised approach for drug screening experiment and in vitro disease modeling. To study a physiological neuronal function, three-dimensional cell patterning and construction of neuronal cell network were required. In this study, we proposed a three-dimensional cell drawing methodology in hydrogel to construct the three-dimensional neuronal cell network. PC-12 cells, which were used as neuronal cell differentiation model, were dispensed into a collagen hydrogel using a micro injector with a three-dimensional position control. To maintain the three-dimensional position of cells, atelocollagen was kept at sol-gel transition state during cell dispensing. As the results, PC-12 cells were patterned in the atelocollagen gel to form square pattern with different depth. In the patterned cellular lines, PC-12 cells elongated neurites and form a continuous cellular network in the atelocollagen gel. It was suggested that our three-dimensional cell drawing technology has potentials to reconstruct three-dimensional neuronal networks for an investigation of physiological neuronal functions.

Multi-curvature micropatterns unveil distinct calcium and mitochondrial dynamics in neuronal networks

Tangential curvatures are a key geometric feature of tissue folds in the human cerebral cortex. In the brain, these smoother and firmer bends are called gyri and sulci and form distinctive curved tissue patterns imposing a mechanical stimulus on neuronal networks. This stimulus is hypothesized to be essential for proper brain cell function but lacks in most standard neuronal cell assays. A variety of soft lithographic micropatterning techniques can be used to integrate round geometries in cell assays. Most microfabricated patterns, however, focus only on a small set of defined curvatures. In contrast, curvatures in the brain span a wide physical range, leaving it unknown which precise role distinct curvatures may play on neuronal cell signaling. Here we report a hydrogel-based multi-curvature design consisting of over twenty bands of distinct parallel curvature ranges to precisely engineer neuronal networks' growth and signaling under patterns of arcs. Monitoring calcium and mitochondrial dynamics in primary rodent neurons grown over two weeks in the multi-curvature patterns, we found that static calcium signaling was locally attenuated under higher curvatures (k > 0.01 μm-1). In contrast, to randomize growth, transient calcium signaling showed higher synchronicity when neurons formed networks in confined multi-curvature patterns. Additionally, we found that mitochondria showed lower motility under high curvatures (k > 0.01 μm-1) than under lower curvatures (k < 0.01 μm-1). Our results demonstrate how sensitive neuronal cell function may be linked and controlled through specific curved geometric features. Furthermore, the hydrogel-based multi-curvature design possesses high compatibility with various surfaces, allowing a flexible integration of geometric features into next-generation neuro devices, cell assays, tissue engineering, and implants.

Collective dynamics of neuronal activities in various modular networks

Modularity is a key feature of structural and functional brain networks. However, the association between the structure and function of modular brain networks has not been revealed. We constructed three types of modular cortical networks in vitro and investigated their neuronal activities. The modular networks comprising 4, 3, or 2 modules were constructed using polydimethylsiloxane (PDMS) microstructures fabricated directly on a multi-electrode array (MEA) without transfer. The 4-module network had the strongest modular connectivity, followed by the 3-module and 2-module networks. To investigate how neuronal activities were affected by the modular network structure, spontaneous neuronal activities were recorded on different days in vitro and analyzed based on spike amplitudes, network bursts, and the propagation properties of individual spikes. Different characteristics were observed depending on the network topology and modular connectivity. Moreover, when an electrode was stimulated by biphasic voltage pulses, bursts were elicited for the 4-module network, whereas spikes were elicited for the 3-module and 2-module networks. Direct fabrication of the PDMS microstructures on the MEA without transfer allows microscale construction of modular networks and high-density functional recording; therefore, the technique utilizing the PDMS microstructures can be applied to the systematic study of the dynamics of modular neuronal networks in vitro.

Correlative light and electron microscopy for complex cellular structures on PDMS substrates with coded micro-patterns

Fluorescence light microscopy (FLM) is commonly used for localizing specific cellular and subcellular targets. Electron microscopy (EM), on the other hand, can reveal ultrastructural details of cellular architectures beyond the limit of optical resolution. Correlative light and electron microscopy (CLEM) that combines the two techniques has proven valuable in various cell biological applications that require both specificity and resolution. Here, we report an efficient and easy-to-use CLEM system, and its applications in studying neuronal synapses. The system utilizes patterned symbols to encode coordinates on micro-fabricated polydimethylsiloxane (PDMS) substrates, on which dissociated primary hippocampal neurons grow and form synaptic connections. After imaging and localizing specifically labeled synapses with FLM, samples are embedded in resin blocks and sectioned for EM analysis. The patterned symbols on PDMS substrates provide coordinate information, allowing efficient co-registration between FLM and EM images with high precision. A custom-developed software package achieves automated EM image collection, FLM/EM alignment, and EM navigation. With this CLEM system, we have obtained high quality electron tomograms of fluorescently labeled synapses along dendrites of hippocampal neurons and analyzed docking statistics of synaptic vesicles (SVs) in different subtypes of excitatory synapses. This technique provides an efficient approach to combine functional studies with ultrastructural analysis of heterogeneous neuronal synapses, as well as other subcellular structures in general.

Engineered 3D vascular and neuronal networks in a microfluidic platform

Neurovascular coupling plays a key role in the pathogenesis of neurodegenerative disorders including motor neuron disease (MND). In vitro models provide an opportunity to understand the pathogenesis of MND, and offer the potential for drug screening. Here, we describe a new 3D microvascular and neuronal network model in a microfluidic platform to investigate interactions between these two systems. Both 3D networks were established by co-culturing human embryonic stem (ES)-derived MN spheroids and endothelial cells (ECs) in microfluidic devices. Co-culture with ECs improves neurite elongation and neuronal connectivity as measured by Ca2+ oscillation. This improvement was regulated not only by paracrine signals such as brain-derived neurotrophic factor secreted by ECs but also through direct cell-cell interactions via the delta-notch pathway, promoting neuron differentiation and neuroprotection. Bi-directional signaling was observed in that the neural networks also affected vascular network formation under perfusion culture. This in vitro model could enable investigations of neuro-vascular coupling, essential to understanding the pathogenesis of neurodegenerative diseases including MNDs such as amyotrophic lateral sclerosis.

Live-Cell, Label-Free Identification of GABAergic and Non-GABAergic Neurons in Primary Cortical Cultures Using Micropatterned Surface

Excitatory and inhibitory neurons have distinct roles in cortical dynamics. Here we present a novel method for identifying inhibitory GABAergic neurons from non-GABAergic neurons, which are mostly excitatory glutamatergic neurons, in primary cortical cultures. This was achieved using an asymmetrically designed micropattern that directs an axonal process to the longest pathway. In the current work, we first modified the micropattern geometry to improve cell viability and then studied the axon length from 2 to 7 days in vitro (DIV). The cell types of neurons were evaluated retrospectively based on immunoreactivity against GAD67, a marker for inhibitory GABAergic neurons. We found that axons of non-GABAergic neurons grow significantly longer than those of GABAergic neurons in the early stages of development. The optimal threshold for identifying GABAergic and non-GABAergic neurons was evaluated to be 110 μm at 6 DIV. The method does not require any fluorescence labelling and can be carried out on live cells. The accuracy of identification was 98.2%. We confirmed that the high accuracy was due to the use of a micropattern, which standardized the development of cultured neurons. The method promises to be beneficial both for engineering neuronal networks in vitro and for basic cellular neuroscience research.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Local polymer replacement for neuron patterning and in situ neurite guidance

By locally dispensing poly-L-lysine (PLL) molecules with a FluidFM onto a protein and cell resistant poly-L-lysine-graft-polyethylene glycol (PLL-g-PEG) coated substrate, the antifouling layer can be replaced under the tip aperture by the cell adhesive PLL. We used this approach for guiding the adhesion and axonal outgrowth of embryonic hippocampal neurons in situ. Cultures of hippocampal neurons were chosen because they mostly contain pyramidal neurons. The hippocampus is known to be involved in memory formation, and the stages of network development are well characterized, which is an asset to fundamental research. After fabricating diffuse PLL spots with 10-250 μm diameter, seeded hippocampal cells stick preferentially onto the spots migrating toward the spot center along the PLL gradient. Cell clusters were formed depending on the lateral size of the PLL dots and the density of seeded cells. In a second step of this protocol, the FluidFM is used to connect in situ the obtained clusters. The outgrowth of neurites, which are known to grow preferentially on adhesive substrates, is tailored by writing PLL lines. Antibody staining confirms that the outgrowing neurites are mostly axons, while the activity of the neurons is assessed by a calcium indicator, proving cell viability. The calcium signal intensity of two actively interconnected clusters showed to be correlated, corroborating the formation of vectored and polarized interconnections.

Modeling the formation process of grouping stimuli sets through cortical columns and microcircuits to feature neurons

A computational model of a self-structuring neuronal net is presented in which repetitively applied pattern sets induce the formation of cortical columns and microcircuits which decode distinct patterns after a learning phase. In a case study, it is demonstrated how specific neurons in a feature classifier layer become orientation selective if they receive bar patterns of different slopes from an input layer. The input layer is mapped and intertwined by self-evolving neuronal microcircuits to the feature classifier layer. In this topical overview, several models are discussed which indicate that the net formation converges in its functionality to a mathematical transform which maps the input pattern space to a feature representing output space. The self-learning of the mathematical transform is discussed and its implications are interpreted. Model assumptions are deduced which serve as a guide to apply model derived repetitive stimuli pattern sets to in vitro cultures of neuron ensembles to condition them to learn and execute a mathematical transform.

Microfluidic approaches for gene delivery and gene therapy

Recent advances in microfluidics have created new and exciting prospects for gene delivery and therapy. The micro-scaled environment within microfluidic systems enables precise control and optimization of multiple processes and techniques used in gene transfection and the production of gene and drug transporters. Traditional non-viral gene transfection methods, such as electroporation, microinjection and optical gene transfection, are improved from the use of innovative microfluidic systems. Additionally, microfluidic systems have also made the production of many viral and non-viral vectors controlled, automated, and reproducible. In summary, the development and application of microfluidic systems are producing increased efficiency in gene delivery and promise improved gene therapy results.

Organs-on-a-chip: a focus on compartmentalized microdevices

Advances in microengineering technologies have enabled a variety of insights into biomedical sciences that would not have been possible with conventional techniques. Engineering microenvironments that simulate in vivo organ systems may provide critical insight into the cellular basis for pathophysiologies, development, and homeostasis in various organs, while curtailing the high experimental costs and complexities associated with in vivo studies. In this article, we aim to survey recent attempts to extend tissue-engineered platforms toward simulating organ structure and function, and discuss the various approaches and technologies utilized in these systems. We specifically focus on microtechnologies that exploit phenomena associated with compartmentalization to create model culture systems that better represent the in vivo organ microenvironment.

Engineered neuronal circuits: a new platform for studying the role of modular topology

Neuron–glia cultures serve as a valuable model system for exploring the bio-molecular activity of single cells. Since neurons in culture can be conveniently recorded with great fidelity from many sites simultaneously, it has long been suggested that uniform cultured neurons may also be used to investigate network-level mechanisms pertinent to information processing, activity propagation, memory, and learning. But how much of the functionality of neural circuits can be retained in vitro remains an open question. Recent studies utilizing patterned networks suggest that they provide a most useful platform to address fundamental questions in neuroscience. Here we review recent efforts in the realm of patterned networks’ activity investigations. We give a brief overview of the patterning methods and experimental approaches commonly employed in the field, and summarize the main results reported in the literature. The general picture that emerges from these reports indicates that patterned networks with uniform connectivity do not exhibit unique activity patterns. Rather, their activity is very similar to that of unpatterned uniform networks. However, by breaking the connectivity homogeneity, using a modular architecture, it is possible to introduce pronounced topology-related gating and delay effects. These findings suggest that patterned cultured networks may serve as a new platform for studying the role of modularity in neuronal circuits.