in-vitro culture of human-induced pluripotent stem cells (ipsc) on high-density microelectrode array (hd-mea)

HD-MEA 上的多模态大规模神经记录和分析 

Neuronal ensembles, often termed cell assemblies, are pivotal in neural coding, facilitating intricate computations for processing multiscale neural information1,2,3. These ensembles underpin the formation of expansive neuronal networks and their nuanced microcircuits4. Such networks and their oscillatory patterns drive advanced brain functions, including perception and cognition. While extensive research has explored specific neuronal types and synaptic pathways, a deeper understanding of how neurons collaboratively form cell assemblies and influence spatiotemporal information processing across circuits and networks remains elusive5.
Acute, ex-vivo brain slices are pivotal electrophysiological tools for studying intact neural circuits, offering a controlled setting to probe oscillatory activity patterns of neural function, synaptic transmission, and connectivity, with implications in pharmacological testing and disease modeling6,7,8. This study protocol highlights two key brain circuits - the hippocampal-cortical (HC) involved in learning and memory processes9,10, and the olfactory bulb (OB) responsible for odor discrimination11,12,13. In these two regions, new functional neurons are continuously generated by adult neurogenesis throughout life in mammalian brains14. Both circuits demonstrate multidimensional dynamic neural activity patterns and inherent plasticity that participate in rewiring the existing neural network and facilitate alternative information processing strategies when required15,16.
Acute, ex-vivo brain slice models are indispensable for delving into brain functionality and understanding disease mechanisms at the microcircuit level. However, in-vitro cell cultures derived from human induced pluripotent stem cells (iPSCs) neuronal networks offer a promising avenue of translational research, seamlessly connecting findings from animal experiments to potential human clinical treatment17,18. These human-centric in-vitro assays serve as a reliable platform for assessing pharmacological toxicity, enabling precise drug screening, and furthering research into innovative cell-based therapeutic strategies19,20. Recognizing the pivotal role of the iPSC neuronal model, we have dedicated the third module of this protocol study to thoroughly investigate the functional characteristics of its derived networks and to fine-tune the associated cell culture protocols.
These electrogenic neural modules have been commonly studied using techniques like calcium (Ca2+ imaging), patch-clamp recordings, and low-density microelectrode arrays (LD-MEA). While Ca2+ imaging offers single-cell activity mapping, it is a cell-labeling-based method hindered by its low temporal resolution and challenges in long-term recordings. LD-MEAs lack spatial precision, while patch-clamp, being an invasive single-site technique and laborious, often yields a low success rate21,22,23. To address these challenges and effectively probe network-wide activity, large-scale simultaneous neural recordings have emerged as a pivotal approach for understanding the computational principles of neural dynamics underlying brain complexity and their implications in health and disease24,25.
In this JoVE protocol, we demonstrate a large-scale neural recording method based on the high-density MEA (HD-MEA) for capturing spatiotemporal neuronal activity across various brain modalities, including hippocampal and olfactory bulb circuits from ex-vivo mouse brain acute slices (Figures 1A-C) and in-vitro human iPSC-derived neuronal networks (Figures 1D-E), previously reported by our group and other colleagues26,27,28,29,30,31,32,33,34,35. The HD-MEA, built on complementary-metal-oxide-semiconductor (CMOS) technology, boasts on-chip circuitry and amplification, allowing sub-millisecond recordings across a 7mm2 array size36. This non-invasive approach captures multi-site, label-free extracellular firing patterns from thousands of neuronal ensembles simultaneously using 4096 microelectrodes at a high spatiotemporal resolution, revealing the intricate dynamics of local field potentials (LFPs) and multiunit spiking activity (MUA)26,29.
Given the vastness of the data generated by this methodology, a sophisticated analytical framework is essential, yet poses challenges37. We have developed computational tools that encompass automatic event detection, classification, graph theory, machine learning, and other advanced techniques (Figure 1F)26,29,38,39. Integrating the HD-MEA with these analytical tools, a holistic approach is devised to probe the intricate dynamics from individual cell assemblies to broader neural networks across diverse neural modalities. This combined approach deepens our grasp of the computational dynamics in normal brain functions and offers insights into anomalies present in pathological conditions28. Moreover, insights from this approach can propel advancements in brain-inspired modeling, neuromorphic computing, and neural learning algorithms. Ultimately, this method holds promise in uncovering the core mechanisms behind neural network disruptions, potentially identifying biomarkers, and guiding the creation of precise diagnostic tools and targeted treatments for neurological conditions.

作者聚焦：通过 HD-MEA 技术推进大规模神经动力学

CMOS集成高密度微电极阵列上多模态大规模神经元集成动力学的记录与分析

Watch this Scientific Journal Video about In-Vitro Culture of Human-Induced Pluripotent Stem Cells iPSC on High-Density Microelectrode Array HD-MEA at JoVE.com

在高密度微电极阵列 （HD-MEA） 上人诱导的多能干细胞 （iPSC） 的体外培养 

首先，以 HD-MEA 芯片为例。用用 96% 乙醇润湿的纸巾擦拭玻璃环的芯片。将每个装置放入引擎盖下的无菌培养皿中，并用70%乙醇填充MEA储液器。吸入乙醇后，用无菌、过滤、双蒸水清洗储液罐三次。加入一毫升预处理培养基并孵育过夜。第二天，从设备中取出预处理介质。在每个设备的有效区域涂上一毫升 PDLO。第二天，从设备中吸出 PDLO。用双蒸水清洗设备三次，并让它们在引擎盖下晾干。用无菌、过滤、双蒸水填充 35 x 10 毫米的培养皿，并将其放在芯片旁边。使用预热的培养基，将细胞悬液移液到芯片活性区域的表面上。在 37% 二氧化碳的环境中孵育芯片 5。45 分钟后，将两毫升加热至室温的培养基轻轻加入 HD-MEA 储液槽中。将芯片在 37 摄氏度和 5% 二氧化碳中孵育。

in-vitro-culture-human-induced-pluripotent-stem-cells-ipsc-on-high

Research

JoVE Journal

Neuroscience

In-Vitro Culture of Human-Induced Pluripotent Stem Cells (iPSC) on High-Density Microelectrode Array (HD-MEA)

346 次观看. 首先，以 HD-MEA 芯片为例。用用 96% 乙醇润湿的纸巾擦拭玻璃环的芯片。将每个装置放入引擎盖下的无菌培养皿中，并用70%乙醇填充MEA储液器。吸入乙醇后，用无菌、过滤、双蒸水清洗储液罐三次。加入一毫升预处理培养基并孵育过夜。第二天，从设备中取出预处理介质。在每个设备的有效区域涂上一毫升 PDLO。第二天，从设备中吸出 PDLO。用双蒸水清洗设备三次，?...

视频: 在高密度微电极阵列 （HD-MEA） 上人诱导的多能干细胞 （iPSC） 的体外培养 

Recording and Analyzing Multimodal Large-Scale Neuronal Ensemble Dynamics on CMOS-Integrated High-Density Microelectrode Array

Large-scale neuronal networks and their complex distributed microcircuits are essential to generate perception, cognition, and behavior that emerge from patterns of spatiotemporal neuronal activity. These dynamic patterns emerging from functional groups of interconnected neuronal ensembles facilitate precise computations for processing and coding multiscale neural information, thereby driving higher brain functions. To probe the computational principles of neural dynamics underlying this complexity and investigate the multiscale impact of biological processes in health and disease, large-scale simultaneous recordings have become instrumental. Here, a high-density microelectrode array (HD-MEA) is employed to study two modalities of neural dynamics - hippocampal and olfactory bulb circuits from ex-vivo mouse brain slices and neuronal networks from in-vitro cell cultures of human induced pluripotent stem cells (iPSCs). The HD-MEA platform, with 4096 microelectrodes, enables non-invasive, multi-site, label-free recordings of extracellular firing patterns from thousands of neuronal ensembles simultaneously at high spatiotemporal resolution. This approach allows the characterization of several electrophysiological network-wide features, including single/-multi-unit spiking activity patterns and local field potential oscillations. To scrutinize these multidimensional neural data, we have developed several computational tools incorporating machine learning algorithms, automatic event detection and classification, graph theory, and other advanced analyses. By supplementing these computational pipelines with this platform, we provide a methodology for studying the large, multiscale, and multimodal dynamics from cell assemblies to networks. This can potentially advance our understanding of complex brain functions and cognitive processes in health and disease. Commitment to open science and insights into large-scale computational neural dynamics could enhance brain-inspired modeling, neuromorphic computing, and neural learning algorithms. Furthermore, understanding the underlying mechanisms of impaired large-scale neural computations and their interconnected microcircuit dynamics could lead to the identification of specific biomarkers, paving the way for more accurate diagnostic tools and targeted therapies for neurological disorders.

Here, we employ HD-MEA to delve into computational dynamics of large-scale neuronal ensembles, particularly in hippocampal, olfactory bulb circuits, and human neuronal networks. Capturing spatiotemporal activity, combined with computational tools, provides insights into neuronal ensemble complexity. The method enhances understanding of brain functions, potentially identifying biomarkers and treatments for neurological disorders.

Large-scale neuronal networks and their complex distributed microcircuits are essential to generate perception, cognition, and behavior that emerge from ...

在高密度微电极阵列 （HD-MEA） 上人诱导的多能干细胞 （iPSC） 的体外培养

在高密度微电极阵列（HD-MEA）上人诱导的多能干细胞（iPSC）的体外培养