Networked neural spheroid by neuro-bundle mimicking nervous system created by topology effect
© Jeong et al.; licensee BioMed Central. 2015
Received: 14 January 2015
Accepted: 6 March 2015
Published: 22 March 2015
In most animals, the nervous system consists of the central nervous system (CNS) and the peripheral nervous system (PNS), the latter of which connects the CNS to all parts of the body. Damage and/or malfunction of the nervous system causes serious pathologies, including neurodegenerative disorders, spinal cord injury, and Alzheimer’s disease. Thus, not surprising, considerable research effort, both in vivo and in vitro, has been devoted to studying the nervous system and signal transmission through it. However, conventional in vitro cell culture systems do not enable control over diverse aspects of the neural microenvironment. Moreover, formation of certain nervous system growth patterns in vitro remains a challenge. In this study, we developed a deep hemispherical, microchannel-networked, concave array system and applied it to generate three-dimensional nerve-like neural bundles. The deep hemicylindrical channel network was easily fabricated by exploiting the meniscus induced by the surface tension of a liquid poly(dimethylsiloxane) (PDMS) prepolymer. Neurospheroids spontaneously aggregated in each deep concave microwell and were networked to neighboring spheroids through the deep hemicylindrical channel. Notably, two types of satellite spheroids also formed in deep hemispherical microchannels through self-aggregation and acted as an anchoring point to enhance formation of nerve-like networks with neighboring spheroids. During neural-network formation, neural progenitor cells successfully differentiated into glial and neuronal cells. These cells secreted laminin, forming an extracellular matrix around the host and satellite spheroids. Electrical stimuli were transmitted between networked neurospheroids in the resulting nerve-like neural bundle, as detected by imaging Ca2+ signals in responding cells.
KeywordsNeurospheroid Neural spheroid networking Deep hemicylindrical channel Neural bundle Nerve-like structure
The nervous system in an animal transmits signals between each organ and the brain, serving to coordinate voluntary and involuntary activities [1-3]. In most animals, the nervous system consists of the central nervous system (CNS) and peripheral nervous system (PNS), the latter of which connects the CNS to all parts of the body [3-5]. Damage and/or malfunction of the nervous system causes serious pathologies, including neurodegenerative disorders, spinal cord injury, and Alzheimer’s disease. Given its prominent functional role, the nervous system has been the continuing focus of extensive studies.
One aspect of nervous system function that attracted considerable attention is signal transmission through the system. Signals within the nervous system are transmitted by an electrochemical wave called an action potential, which travels along the nerves, composed of cylindrical bundles of fibers consisting mostly of neural axons. The signal is transmitted between nerves by small amounts of neurotransmitter molecules released at nerve junctions, termed synapses. A variety of in vitro approaches have been developed in an attempt to understand the signal transduction mechanisms of this critically important system. However, conventional in vitro cell culture plates do not provide the ability to control diverse features of the neural microenvironment, and formation of certain neuronal growth patterns that mimic those that occur in vivo remains a challenge [6-8]. Recent progress in microfluidics, including micro contact printing and micro- and nano-topology fabrication technology, have allowed the culture of neuronal cells in a well-defined microenvironment, enabling the control of neuron and glial cell structuring processes. Microscale chemical [9,10] and topological patterns have proven invaluable for the study of neuronal behavior. Representative examples of these techniques include gradient control of soluble biochemical cues [11-14], micro-engineered grooved patterns [15,16], and biochemically modified grooved substrates [17,18]. These methods have been used extensively for guiding the growth of neurons [8,15,16,19] and promoting neuro-networking [7,20]. Although these approaches yield well-defined, networked neural cultures, it remains difficult to create a neural functionality close to that of the in vivo environment because cell culture conditions are restricted to a two-dimensional (2D) surface. Three-dimensional (3D) neuro-spheroid and -bundle formation of the nervous system by culturing on controlled microstructures, which have been shown to support successful growth of neurites, have been proposed as an alternative for mimicking the in vivo microenvironment [14,21,22].
Although 2D and 3D formation in in vitro nervous systems facilitate neurite growth and networking, most such models are based on the growth of single neurons or a single cell-cell network [7,8,13,18] using primary neuro progenitor cells. However, the nervous system in the animal is created by the growth of multiple cell types, including neurons and glia, which provide structural and metabolic support. In addition, conventional neural cell culture methods have a limited ability to mimic the connections of the nervous system between one part of the body and another through fiber bundles. To this end, several studies have been performed to fabricate three-dimensional (3D) neural networks using a microwell array [7,21-23]. Although, these studies demonstrated successful formation of spheroids and neural networking, it is still challenging to create a bundle-like neural networking formation which mimics the nervous system between spheroids. To address this limit, we have demonstrated that topological factors are critical for the formation of a nervous system, and further showed that a hemicylindrical channel is more effective in guiding neural outgrowth than a rectangular channel . However, the neural bundle in this system was weakly connected through the hemicylindrical channel, and it was difficult to observe signal transmission through the bundle. For improved formation of bundle-like structures, we discovered that the channel barrier plays an important role in guiding well-defined outgrowth of multiple neurites, and quantitative studies for the barrier effect for the nervous system formation were required. In this study, we demonstrate a 3D nervous system model in which neurospheroids are networked to neighboring neurospheroids by a nerve-like network through deep hemicylindrical channels. To fabricate deep hemicylindrical channels, we introduced a method for extracting remnant poly(dimethylsiloxane) (PDMS) prepolymer from microwells and channels. The resulting concave wells supported the self-aggregation of host neurospheroids, and the deep hemicylindrical channel between concave wells provided excellent guidance of neural growth. Unlike the case for shallow hemicylindrical channels, satellite neurospheroids formed in the deep hemicylindrical channel. These satellite spheroids, guided by the deep hemicylindrical channel, played a bridging role in forming networks between host spheroids, enhancing the formation of strong nerve-like structures. To confirm this topological effect on the formation of nerve-like structures, we conducted a series of experiments comparing deep hemicylindrical channel well networking (HCWN) systems with shallow HCWN systems. These experiments demonstrated successful differentiation of neural progenitor cells to glia and neurons in the deep HCWN system. Moreover, subsequent Ca2+ imaging revealed propagation of electrical stimuli between networked host spheroids, confirming formation of functional nerve-like networks. Laminin membranes also developed around host and satellite neurospheroids during the process of neural progenitor cell differentiation. The proposed 3D nervous system could be extended to serve as a model for pathophysiological studies of the nervous system as well as nervous system diseases.
Formation of deep HCWN features through PDMS surface tension
Topological effects of shallow and deep HCWN systems on neural network formation
Topological effects of the deep HCWN system on satellite spheroid formation
ECM membrane secretion and glial cell differentiation
Neuronal signal transmission through neurite bundles
In a previous study, we compared neural network formation in a shallow hemicylindrical channel to that in a rectangular channel . Although the nerve-like network in the shallow hemicylindrical microchannel was generated randomly and was weak, we found that the hemicylindrical channel provided suitable conditions for neurite outgrowth and networking. In the current study, we compared nervous system formation in shallow and deep hemicylindrical channels to observe the barrier effect. Our results demonstrated that the deep hemicylindrical channel exerts a strong topological influence over the generation of satellite neurospheroids, enhancing guidance of neurite outgrowth and creation of a bundle-like nerve system. Cells tended to aggregate at the center of the deep microchannel (Figure 2d, orange arrowheads) forming type 2 spheroids as the shape of the deep channels is flat and presents a high barrier which prevents neuronal outgrowth. The type 1 spheroids generally appeared at the smooth interfacing area between the concave well and hemicylindrical channel (Figure 3b, c, and e, red arrowheads). These two types of satellite spheroids act as anchors to enhance neural network formation in the deep HCWN system. Although further studies of satellite spheroids are needed, such behavior of neural cells in deep HCWN plates seems to be closely related with the topology of the channel. Despite seeding cells on untreated surfaces of deep HCWN plates, neurites grew along the center of the hemicylindrical microchannels even without ECM treatment. These results show that the curvature and depth of the HCWN channels provide a topology which is advantageous for forming a well-guided network of nerves.
Interestingly, the GFAP and Nestin were expressed around the satellite spheroid and at the joint region around the host spheroid, whereas they were not expressed in the host spheroid (Figure 4 h and i). This figure suggests that some progenitor cells around satellite spheroids and at the joint region are differentiating into glial cells, while cells in host spheroids do not differentiate into glia cells. Although further study is required, this phenomenon seems to reflect the glia cells’ role during the nervous system development stage.
Microenvironments have important role for central nerve system (CNS) development and neural stem cell (NSC) differentiation , and several ECM molecules have been identified that regulate cell growth, migration and proliferation [5,16], as well as differentiation of neural progenitor cells [6,8]. Although, microstructures and biochemical materials can provide cues for growth and differentiation of neuro-progenitor cells, it is still unclear how the neuro-progenitor cells modify the environment to enhance their growth and differentiation. In this study, the deep HCWN seems to enhance the formation of host and satellite spheroids that contributed by secreting laminin, which is well known for playing an important role in neural cell outgrowth and the differentiation of neural progenitor cells , and to induce differentiation of the neural cells without any pretreatment of biochemical attractants (Figure 4c, d, and e). The self-modified environment by the secretion of laminin in the deep HCWN can facilitate the formation of well-organized neuro-bundles.
Using the deep HCWN system, we successfully developed a neural network connecting host and satellite neurospheroids. The host and satellite spheroids created at the deep HCWN structures through self-modification of the surrounding ECM environment. During network formation on the deep hemicylindrical channel network, neural progenitor cells successfully differentiated into glial and neuron cells, forming a laminin-containing scaffold around the host and satellite neurospheroids during nerve-like formation. Functional connectivity within the fabricated nerve-like network was demonstrated by monitoring transmission of an electrical stimulus using Ca2+ imaging. Furthermore, we found that satellite neurospheroids formed around the host neurospheroid on the deep hemicylindrical channel and in the center of the channel. These satellite neurospheroids act as anchoring points in the networks to play an important role in enhancing neural network formation. We expect that the proposed method will be extensively used as a brain or nervous system model for the drug screening and the physiological study.
Fabrication of master molds for deep and shallow HCWN systems
Shallow and deep HCWN plates consist of concave microwell arrays connected by a shallow (50–100 μm) or deep (~300 μm) hemicylindrical channel. HCWN plates were fabricated by first preparing a two-layered PDMS base mold consisting of cylindrical microwell arrays connected via a rectangular channel using a standard soft lithography process (Additional file 1: Figure S1a). Shallow HCWN plates were prepared by pouring PDMS prepolymer on the PDMS base mold (Figure 1a (i-ii) and Additional file 1: Figure S1b), and sweeping out PDMS prepolymer by lightly pressing the soft PDMS base mold using a glass slide (76 × 52 × 1.2 mm), as previously reported [24,26-28] (Figure 1a and Additional file 1: Figure S1b). For deep HCWN plates, the remnant PDMS prepolymer in microwells and channels was aspirated using a syringe (Figure 1a (i-iii) and Additional file 1: Figure S1c), leaving a hemicylindrical channel with a depth of approximately 300 μm–almost the same depth as the rectangular channel of the PDMS base mold. The residual PDMS prepolymer was measured using a micro balance (PAG214C, OHAUS, USA). For the measurement, the weight of PDMS base mold was measured first. The weight of PDMS base mold after prepolymer sweeping and suction was measured. By subtraction of weight of PDMS base mold, we measured the weight of remaining prepolymer after sweeping and suction. The residual PDMS prepolymer in the microwell and rectangular channel adopted a curved meniscus through surface tension, forming the deep hemicylindrical channels and concave wells. The PDMS prepolymer-formed meniscus was solidified by thermal curing on a hot plate (80°C for 1 hour) (Figure 1a (iv), and Additional file 1: Figure S1b and c (iv)). After fabrication, shallow and deep HCWN plates were replicated using SU-8 (Micro-Chem, Newton, MA, USA), and a convex SU-8 master mold was created (Additional file 1: Figure S1d and S2). Deep and shallow HCWN plates were ultimately fabricated by replicating the master mold with PDMS. The dimensions of shallow and deep HCWN systems are depicted in Figure 1d. For the deep HCWN system, the dimensions of cylindrical wells were 500 × 500 μm (diameter and depth); rectangular channels were 1 mm (length) × 200 μm (width) × 300 μm (depth) (Additional file 1: Figure S1b and c).
Preparations of neural progenitor cells
Primary neural progenitor cells were isolated from a cortical region of prenatal (embryonic day 16) rats (DBL, Incheon, South Korea), and were collected by centrifugation at 10,000 rpm for 5 minutes [23,29,30]. After collection, progenitor cells were seeded in wells of deep and shallow HCWN plates and cultured in Neurobasal media (Gibco, Lifetechnonogies, NY, USA) containing B-27 Supplement (Gibco, Lifetechnonogies, NY, USA), 0.5 mM L-glutamine, and 1% of an antibiotics solution containing 10,000 units penicillin (Gibco, Lifetechnonogies, NY, USA) and streptomycin. All procedures conformed to the standards of the Institutional Review Board of Korea University.
Cell culturing on shallow and deep HCWN plates
To seed a uniform number of cells into each concave well, we directly dropped 1 ml of a cell suspension (2.0 × 107 cells/ml) on top of each type of HCWN plate followed by repeated gentle pipetting [31,32]. When cells had settled into concave well arrays and channels (10 minutes after seeding), culture medium was gently applied to remove cells that had not settled (Additional file 1: Figure S3). The medium was replaced with fresh medium every other day.
Signal transmission between spheroids within formed neural networks was monitored by imaging Ca2+ in responding cells using the ratiometric fluorescent dye, Fura-2-AM (100 μM; loading time, 30 minutes). To test whether this Ca2+ response was evoked by neuronal action potential activity, we used tetrodotoxin (TTX), a voltage gated Na+ channel inhibitor. To block the neuronal activity, we treated the cells with TTX for at least 5 minutes using a bath application (ACSF recording solution containing TTX). Then, Ca2+ responses were measured upon electrical stimulation. In the presence of TTX, we could not see the Ca2+ response. The experimental details are now included in the method section. Cells were imaged by exciting at wavelengths of 340 and 380 nm, and collecting fluorescence at 510 nm using a CCD camera. Ca2+ concentration was determined by performing ratio calculations using Axon Imaging Workbench version 6.2 (Axon Instruments, Molecular Devices, Sunnyvale, CA, USA). To induce the neuronal activity-dependent Ca2+ responses in cells, we used the 20 Hz electrical stimulation, a subthreshold stimulation. This stimulation has been widely used to induce the neuronal activity in brain slice without causing long-term potentiation . Cells in spheres were electrically stimulated with a 20-Hz, 1-second pulse, and images were acquired at a rate of 1 images/s. The relative change in Ca2+ concentration was normalized to baseline concentration, obtained by averaging 20 images prior to stimulation.
For immunostaining, networked neurospheroids were first fixed for 20 minutes with 4% formaldehyde at 4°C, after which cells were permeabilized by incubating with phosphate-buffered saline (PBS) containing 0.1% Triton X-100 for 20 minutes at room temperature, blocked with PBS containing 3% bovine serum albumen (BSA) for 30 minutes, and then incubated with primary antibody overnight at 4°C. Neurite outgrowth was examined using a primary rabbit polyclonal antibody against the neurofilament, β-III tubulin (1:1000; Santa Cruz Biotechnology, Dallas, TX, USA), a marker of neurites. Astrocytes and neural progenitor/stem cells were examined using a primary rabbit polyclonal IgG antibody against GFAP (1:100; Santa Cruz Biotechnology, Dallas, TX, USA) and a primary anti-rat antibody against nestin (1:1000; Stemcell technologies, USA), respectively. After incubating overnight, cells were washed with PBS containing 0.1% BSA for 5 minutes, and then incubated with secondary antibodies (1:1000; Invitrogen, Carlsbad, CA, USA) for 1.5 hours at room temperature. Cells were washed again with PBS/0.1% BSA, and images were acquired with a fluorescence microscope (EVOS; Advanced Microscopy Group, Mills Creek, WA, USA) after counterstaining with 4,6-diamidino-2-phenylindole dihydrochloride (DAPI; Invitrogen).
For confirmation of laminin, day-10 networked neurospheroids on deep HCWN plates were fixed with 4% paraformaldehyde for 20 minutes at 4°C and permeabilized by incubating with PBS/0.1% Triton X-100 for 20 minutes at room temperature. Non-specific protein adsorption to cells and membranes of deep HCWN plates was blocked by incubating with PBS/0.1% BSA for 30 minutes at 4°C. Cells were then probed with anti-laminin (Abcam, Cambridge, UK) overnight at 4°C. Cells and membranes in deep HCWN plates were gently washed again with PBS/0.1% BSA and incubated with the appropriate Alexa Fluor 488- or 594- secondary antibody (Invitrogen) for 90 minutes at 4°C. Fluorescence images were obtained using a confocal laser-scanning microscope (Olympus, Japan).
Scanning electron microscopy
Concave channel network shape, extracellular matrix (ECM) membrane, and neurospheroid-integrated neural networks in the deep HCWN system were analyzed by field emission-scanning electron microscopy (FE-SEM) using a JEOL 4701 F system (JEOL Ltd., Tokyo, JAPAN). Neural networks cultured in deep or shallow HCWN plates were first fixed with 2.5% glutaraldehyde in deionized water for 1 hour, then gently washed with deionized water, and subjected to secondary fixation in 1% osmium tetroxide in deionized water for 1 hour. Fixed concave-channel neural networks were dehydrated with a series of graded ethanol (25%, 50%, 75%, 95%, and 100%), then incubated with tert-butyl alcohol at room temperature for 30 minutes (three times) and frozen at −70°C. Neural networks on deep HCWN plates were freeze-dried until the tert-butyl alcohol had evaporated, then were mounted on a specimen stub with graphite tape, coated with palladium alloy, and observed by FE-SEM.
Neurite connection and outgrowth measurements and statistical analysis
The direction and lengths of neurite outgrowths from host and satellite spheroids were measured in optical microscope images by image analysis using ImageJ (http://rsbweb.nih.gov/ij/). Neurite connections were manually determined from optical microscope images (Additional file 1: Figure S4). The statistical analysis was implemented using SPSS ver.12 (Chicago, IL, USA).
This work was supported by the Industrial Strategic Technology Development Program, the Ministry of Trade, Industry & Energy (MI, Korea) (Project No.10041923) and Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2012M3C7A1055410).
- Patrick C. Neural tissue engineering. Ann Biomed Eng. 1997;25(1):p. S-41.View ArticleGoogle Scholar
- Elenkov IJ, Wilder RL, Chrousos GP, Vizi ES, et al. The sympathetic nerve-an integrative interface between two supersystems: the brain and the immune system. Pharmacol Rev. 2000;52(4):595–638.PubMedGoogle Scholar
- Dayan P, Abbott LF. Theoretical neuroscience. Cambridge, MA: MIT Press; 2001.Google Scholar
- Maeda E, Robinson HP, Kawana A. The mechanisms of generation and propagation of synchronized bursting in developing networks of cortical neurons. J Neurosci. 1995;15(10):6834–45.PubMedGoogle Scholar
- Park J, Kim S, Park SI, Choe Y, Li J, Han A. A microchip for quantitative analysis of CNS axon growth under localized biomolecular treatments. J Neurosci Methods. 2014;221:166–74.View ArticlePubMedGoogle Scholar
- Park J, Lim E, Back S, Na H, Park Y, Sun K. Nerve regeneration following spinal cord injury using matrix metalloproteinase-sensitive, hyaluronic acid-based biomimetic hydrogel scaffold containing brain-derived neurotrophic factor. J Biomed Mater Res A. 2009;93(3):1091–9.Google Scholar
- Kato-Negishi M, Tsuda Y, Onoe H, Takeuchi S. A neurospheroid network-stamping method for neural transplantation to the brain. Biomaterials. 2010;31(34):8939–45.View ArticlePubMedGoogle Scholar
- Recknor JB, Sakaguchi DS, Mallapragada SK. Directed growth and selective differentiation of neural progenitor cells on micropatterned polymer substrates. Biomaterials. 2006;27(22):4098–108.View ArticlePubMedGoogle Scholar
- Miller RJ, Tran PB. Chemokinetics. Neuron. 2005;47(5):621–3.View ArticlePubMed CentralPubMedGoogle Scholar
- Gao Y-J, Ji R-R. Chemokines, neuronal-glial interactions, and central processing of neuropathic pain. Pharmacol Ther. 2010;126(1):56–68.View ArticlePubMed CentralPubMedGoogle Scholar
- Kapur TA, Shoichet MS. Immobilized concentration gradients of nerve growth factor guide neurite outgrowth. J Biomed Mater Res A. 2004;68(2):235–43.View ArticlePubMedGoogle Scholar
- Kothapalli CR, van Veen E, de Valence S, Chung S, Zervantonakis IK, Gertler FB, et al. A high-throughput microfluidic assay to study neurite response to growth factor gradients. Lab Chip. 2011;11(3):497–507.View ArticlePubMedGoogle Scholar
- Park JY, Kim S-K, Woo D-H, Lee E-J, Kim J-H, Lee S-H, et al. Differentiation of neural progenitor cells in a microfluidic chip-generated cytokine gradient. Stem Cells. 2009;27(11):2646–54.View ArticlePubMedGoogle Scholar
- Choi YJ, Chae S, Kim JH, Barald KF, Park JY, Lee S-H. Neurotoxic amyloid beta oligomeric assemblies recreated in microfluidic platform with interstitial level of slow flow. Sci Rep. 2013;3:1921.PubMed CentralPubMedGoogle Scholar
- Kang E, Jeong GS, Choi YY, Lee KH, Khademhosseini A, Lee S-H. Digitally tunable physicochemical coding of material composition and topography in continuous microfibres. Nat Mater. 2011;10(11):877–83.View ArticlePubMedGoogle Scholar
- Kang E, Choi YY, Chae SK, Moon J-H, Chang J-Y, Lee S-H. Microfluidic Spinning of Flat Alginate Fibers with Grooves for Cell-aligning Scaffolds. Adv Mater. 2012;24(31):4271–7.View ArticlePubMedGoogle Scholar
- Rhee SW, Taylor AM, Tu CH, Cribbs DH, Cotman CW, Jeon NL. Patterned cell culture inside microfluidic devices. Lab Chip. 2005;5(1):102–7.View ArticlePubMedGoogle Scholar
- Baek NS, Kim YH, Han YH, Lee BJ, Kim T-D, Kim S-T, et al. Facile photopatterning of polyfluorene for patterned neuronal networks. Soft Matter. 2011;7(21):10025–31.View ArticleGoogle Scholar
- Yang F, Murugan R, Wang S, Ramakrishna S. Electrospinning of nano/micro scale poly (L-lactic acid) aligned fibers and their potential in neural tissue engineering. Biomaterials. 2005;26(15):2603–10.View ArticlePubMedGoogle Scholar
- Jun SB, Hynd MR, Dowell-Mesfin N, Smith KL, Turner JN, Shain W, et al. Low-density neuronal networks cultured using patterned poly-l-lysine on microelectrode arrays. J Neurosci Methods. 2007;160(2):317–26.View ArticlePubMed CentralPubMedGoogle Scholar
- Choi YJ, Park J, Lee S-H. Size-controllable networked neurospheres as a 3D neuronal tissue model for Alzheimer’s disease studies. Biomaterials. 2013;34(12):2938–46.View ArticlePubMedGoogle Scholar
- Kato-Negishi M, Morimoto Y, Onoe H, Takeuchi S. Millimeter-Sized Neural Building Blocks for 3D Heterogeneous Neural Network Assembly. Adv Healthc Mater. 2013;2(12):1564–70.View ArticlePubMedGoogle Scholar
- Park J, Lee BK, Jeong GS, Hyun JK, Lee CJ, Lee S-H. Three-dimensional brain-on-a-chip with an interstitial level of flow and its application as an in vitro model of Alzheimer’s disease. Lab Chip. 2015;15(1):141–50.View ArticlePubMedGoogle Scholar
- Jeong GS. Networked neuro-spheres formed by topological attractants for engineering of 3-dimensional nervous system. Tissue Eng Regen Med. 2014;11(4):297–303.View ArticleGoogle Scholar
- Nurcombe V. Laminin in neural development. Pharmacol Ther. 1992;56(2):247–64.View ArticlePubMedGoogle Scholar
- Jeong GS, Jun Y, Song JH, Shin SH, Lee S-H. Meniscus induced self organization of multiple deep concave wells in a microchannel for embryoid bodies generation. Lab Chip. 2012;12(1):159–66.View ArticlePubMedGoogle Scholar
- Jeong GS, Song JH, Kang AR, Jun Y, Kim JH, Chang JY, et al. Surface Tension-mediated, Concave-microwell Arrays for Large-scale, Simultaneous Production of Homogeneously Sized Embryoid Bodies. Adv Healthc Mater. 2013;2(1):119–25.View ArticlePubMedGoogle Scholar
- Jeong GS, Lee S-H. Microfluidic spinning of grooved microfiber for guided neuronal cell culture using surface tension mediated grooved round channel. Tissue Eng Regen Med. 2014;11(4):291–6.View ArticleGoogle Scholar
- Lesuisse C, Martin LJ. Long-term culture of mouse cortical neurons as a model for neuronal development, aging, and death. J Neurobiol. 2002;51(1):9–23.View ArticlePubMedGoogle Scholar
- Qian X, Shen Q, Goderie SK, He W, Capela A, Davis AA, et al. Timing of CNS cell generation: a programmed sequence of neuron and glial cell production from isolated murine cortical stem cells. Neuron. 2000;28(1):69–80.View ArticlePubMedGoogle Scholar
- Choi YY, Chung BG, Lee DH, Khademhosseini A, Kim JH, Lee SH. Controlled-size embryoid body formation in concave microwell arrays. Biomaterials. 2010;31(15):4296–303.View ArticlePubMedGoogle Scholar
- Wong SF, No DY, Choi YY, Kim DS, Chung BG, Lee S-H. Concave microwell based size-controllable hepatosphere as a three-dimensional liver tissue model. Biomaterials. 2011;32(32):8087–96.View ArticlePubMedGoogle Scholar
- MacVicar B, Hochman D. Imaging of synaptically evoked intrinsic optical signals in hippocampal slices. J Neurosci. 1991;11(5):1458–69.PubMedGoogle Scholar
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.