Shell microelectrode arrays (MEAs) for brain organoids.
Ontology highlight
ABSTRACT:
SUBMITTER: Huang Q
PROVIDER: S-EPMC9385157 | biostudies-literature | 2022 Aug
REPOSITORIES: biostudies-literature
Publications
Shell microelectrode arrays (MEAs) for brain organoids.
Huang Qi Q Tang Bohao B Romero July Carolina JC Yang Yuqian Y Elsayed Saifeldeen Khalil SK Pahapale Gayatri G Lee Tien-Jung TJ Morales Pantoja Itzy E IE Han Fang F Berlinicke Cynthia C Xiang Terry T Solazzo Mallory M Hartung Thomas T Qin Zhao Z Caffo Brian S BS Smirnova Lena L Gracias David H DH
Science advances 20220817 33
Brain organoids are important models for mimicking some three-dimensional (3D) cytoarchitectural and functional aspects of the brain. Multielectrode arrays (MEAs) that enable recording and stimulation of activity from electrogenic cells offer notable potential for interrogating brain organoids. However, conventional MEAs, initially designed for monolayer cultures, offer limited recording contact area restricted to the bottom of the 3D organoids. Inspired by the shape of electroencephalography ca ...[more]
Similar Datasets
Project description:AbstractStudies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.Impact statementHuman cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research.Graphical abstractSupplementary informationThe online version contains supplementary material available at 10.1557/s43577-022-00282-w.
| S-EPMC9474390 | biostudies-literature
Project description:3D printing involves the use of photopolymerizable resins, which are toxic and typically have incompatible properties with materials such as polystyrene (PS), which present limitations for biomedical applications. We present a method to dramatically improve the poor adhesion between the PS insulative layer on 3D printed Microelectrode Array (MEA) substrates by functionalizing the resin surface with polydopamine (PDA), a mussel-inspired surface chemistry derivative. A commercial 3D printing prepolymer resin, FormLabs Clear (FLC), was printed using a digital light processing (DLP) printer and then surface functionalized with PDA by alkali-induced aqueous immersion deposition and self-polymerization. It was observed that the adhesion of the PS to FLC was improved due to the precision emanating from the DLP method and further improved after the functionalization of DLP printed substrates with PDA at 1, 12, and 24 h time intervals. The adhesion of PS was evaluated through scotch tape peel testing and instron measurements of planar substrates and incubation testing with qualitative analysis of printed culture wells. The composition and topology of the samples were studied to understand how the properties of the surface change after PDA functionalization and how this contributes to the overall improvement in PS adhesion. Furthermore, the surface energies at each PDA deposition time were calculated from contact angle studies as it related to adhesion. Finally, biocompatibility assays of the newly modified surfaces were performed using mouse cardiac cells (HL-1) to demonstrate the biocompatibility of the PDA functionalization process. PDA surface functionalization of 3D DLP printed FLC resin resulted in a dramatic improvement of thin film PS adhesion and proved to be a biocompatible solution for improving additive manufacturing processes to realize biosensors such as in vitro MEAs.
| S-EPMC9493467 | biostudies-literature
Project description:Thin-film polymer microelectrode arrays (MEAs) facilitate the high-resolution neural recording with its superior mechanical compliance. However, the densely packed electrodes and interconnects along with the ultra-thin polymeric encapsulation/substrate layers give rise to non-negligible crosstalk, which could result in severe interference in the neural signal recording. Due to the lack of standardized characterization or modeling of crosstalk in neural electrode arrays, to date, crosstalk in polymer MEAs remains poorly understood. In this work, the crosstalk between two adjacent polymer microelectrodes is measured experimentally and modeled using equivalent circuits. Importantly, this study demonstrated a two-well measuring platform and systematically characterized the crosstalk in polymer microelectrodes with true isolation of the victim channel and precise control of its grounding condition. A simple, unified equation from detailed circuit modeling was proposed to calculate the crosstalk in different environments. Finite element analysis (FEA) analysis was conducted further to explore the crosstalk in more aggressively scaled polymer electrode threads. In addition to standardizing neural electrode array crosstalk characterization, this study not only reveals the dependence of the crosstalk in polymer MEAs on a variety of key device parameters but also provides general guidelines for the design of thin polymer MEAs for high-quality neural signal recording.
| S-EPMC8361849 | biostudies-literature
Project description:Extracellular recordings by means of high-density microelectrode arrays (HD-MEAs) have become a powerful tool to resolve subcellular details of single neurons in active networks grown from dissociated cells. To extend the application of this technology to slice preparations, we developed models describing how extracellular signals, produced by neuronal cells in slices, are detected by microelectrode arrays. The models help to analyze and understand the electrical-potential landscape in an in vitro HD-MEA-recording scenario based on point-current sources. We employed two modeling schemes, (i) a simple analytical approach, based on the method of images (MoI), and (ii) an approach, based on finite-element methods (FEM). We compared and validated the models with large-scale, high-spatiotemporal-resolution recordings of slice preparations by means of HD-MEAs. We then developed a model-based localization algorithm and compared the performance of MoI and FEM models. Both models provided accurate localization results and a comparable and negligible systematic error, when the point source was in saline, a condition similar to cell-culture experiments. Moreover, the relative random error in the x-y-z-localization amounted only up to 4.3% for z-distances up to 200 μm from the HD-MEA surface. In tissue, the systematic errors of both, MoI and FEM models were significantly higher, and a pre-calibration was required. Nevertheless, the FEM values proved to be closer to the tissue experimental results, yielding 5.2 μm systematic mean error, compared to 22.0 μm obtained with MoI. These results suggest that the medium volume or "saline height", the brain slice thickness and anisotropy, and the location of the reference electrode, which were included in the FEM model, considerably affect the extracellular signal and localization performance, when the signal source is at larger distance to the array. After pre-calibration, the relative random error of the z-localization in tissue was only 3% for z-distances up to 200 μm. We then applied the model and related detailed understanding of extracellular recordings to achieve an electrically-guided navigation of a stimulating micropipette, solely based on the measured HD-MEA signals, and managed to target spontaneously active neurons in an acute brain slice for electroporation.
| S-EPMC6349853 | biostudies-literature
Project description:Microelectrode arrays are invaluable tools for investigating the electrophysiological behaviour of neuronal networks with high spatiotemporal precision. In recent years, it has become increasingly common to functionalize such electrodes with highly porous platinum to increase their effective surface area, and hence their signal-to-noise ratio. Although such functionalization significantly improves the electrochemical performance of the electrodes, the impact of various electrode morphologies on biocompatibility and electrophysiological performance in cell cultures remains poorly understood. In this study, we introduce reproducible protocols for depositing highly porous platinum with varying morphologies on microelectrodes designed for neural cell cultures. We also evaluate the impact of morphology and electrode size on the signal-to-noise ratio in recordings from rat cortical neurons cultured on these electrodes. Our results indicate that electrodes with a uniform layer of highly nanoporous platinum offer the best trade-off between biocompatibility, electrochemical, and electrophysiological performance. While more microporous electrodes exhibited lower impedance, nanoporous electrodes detected higher extracellular signal amplitudes from neurons, suggesting reduced distance between perisomatic neuronal areas and the electrodes. Additionally, these nanoporous electrodes showed fewer thickness variations at their edges compared to the more porous electrodes. Such edges can be mechanically broken off during cell culturing and contribute to long-term cytotoxic effects, which is highly undesirable. We hope this work will contribute to better standardization in creating and utilizing nanoporous platinum microelectrodes for neuroscience applications. Improving the accessibility and reproducibility of this technology is crucial for enhancing the quality of electrophysiological data and advancing our understanding of neuronal network function and dysfunction.
| S-EPMC11841673 | biostudies-literature
Project description:Neurons release neurotransmitters such as glutamate to communicate with each other and to coordinate brain functioning. As increased glutamate release is indicative of neuronal maturation and activity, a system that can measure glutamate levels over time within the same tissue and/or culture system is highly advantageous for neurodevelopmental investigation. To address such challenges, we develop for the first time a convenient method to realize functionalized borosilicate glass capillaries with nanostructured texture as an electrochemical biosensor to detect glutamate release from cerebral organoids generated from human embryonic stem cells (hESC) that mimic various brain regions. The biosensor shows a clear catalytic activity toward the oxidation of glutamate with a sensitivity of 93 ± 9.5 nA·µM-1·cm-2. It was found that the enzyme-modified microelectrodes can detect glutamate in a wide linear range from 5 µM to 0.5 mM with a limit of detection (LOD) down to 5.6 ± 0.2 µM. Measurements were performed within the organoids at different time points and consistent results were obtained. This data demonstrates the reliability of the biosensor as well as its usefulness in measuring glutamate levels across time within the same culture system.
| S-EPMC5872062 | biostudies-literature
Project description:High-density microelectrode arrays can be used to record extracellular action potentials from hundreds to thousands of neurons simultaneously. Efficient spike sorters must be developed to cope with such large data volumes. Most existing spike sorting methods for single electrodes or small multielectrodes, however, suffer from the "curse of dimensionality" and cannot be directly applied to recordings with hundreds of electrodes. This holds particularly true for the standard reference spike sorting algorithm, principal component analysis-based feature extraction, followed by k-means or expectation maximization clustering, against which most spike sorters are evaluated. We present a spike sorting algorithm that circumvents the dimensionality problem by sorting local groups of electrodes independently with classical spike sorting approaches. It is scalable to any number of recording electrodes and well suited for parallel computing. The combination of data prewhitening before the principal component analysis-based extraction and a parameter-free clustering algorithm obviated the need for parameter adjustments. We evaluated its performance using surrogate data in which we systematically varied spike amplitudes and spike rates and that were generated by inserting template spikes into the voltage traces of real recordings. In a direct comparison, our algorithm could compete with existing state-of-the-art spike sorters in terms of sensitivity and precision, while parameter adjustment or manual cluster curation was not required. NEW & NOTEWORTHY We present an automatic spike sorting algorithm that combines three strategies to scale classical spike sorting techniques for high-density microelectrode arrays: 1) splitting the recording electrodes into small groups and sorting them independently; 2) clustering a subset of spikes and classifying the rest to limit computation time; and 3) prewhitening the spike waveforms to enable the use of parameter-free clustering. Finally, we combined these strategies into an automatic spike sorter that is competitive with state-of-the-art spike sorters.
| S-EPMC6314465 | biostudies-literature
Project description:A microelectrode array (MEA) is a configuration of multiple electrodes that enables the concurrent targeting of multiple sites for extracellular recording and stimulation. By utilizing light pulses or electrical stimulations, MEA recordings unveil the complex patterns of electrical activities that arise from the signaling processes within the retinal network. Here, we present a stepwise approach for using microelectrode arrays (MEAs) for recording action potentials from the mouse retina in response to electrical and light stimuli. We provide detailed techniques accompanied by description of a custom optical system, example recordings, troubleshooting guidelines, and data processing methods including spike sorting and code resources for analyzing light and electrical responses. The comprehensive nature of this paper aims to guide researchers in utilizing MEAs effectively for investigating retinal functionality. In particular, it can be easy to have a MEA experiment fail, but hard to identify the source of the failure. This paper is meant to demystify that process. It includes:•A description of MEA setup, recording, and spike data validation.•A troubleshooting guide for common failure modes in MEA recordings from mouse retina.•Spike detection and sorting to precisely extract distinctive action potential.
| S-EPMC10834997 | biostudies-literature
Project description:BackgroundAlthough GABA is the major inhibitory neurotransmitter in the CNS, quantifying in vivo GABA levels has been challenging. The ability to co-monitor both GABA and the major excitatory neurotransmitter, glutamate, would be a powerful tool in both research and clinical settings.New methodCeramic-based microelectrode arrays (MEAs) were used to quantify gamma-aminobutyric acid (GABA) by employing a dual-enzyme reaction scheme including GABase and glutamate oxidase (GluOx). Glutamate was simultaneously quantified on adjacent recording sites coated with GluOx alone. Endogenous glutamate was subtracted from the combined GABA and glutamate signal to yield a pure GABA concentration.ResultsElectrode sensitivity to GABA in conventional, stirred in vitro calibrations at pH 7.4 did not match the in vivo sensitivity due to diffusional losses. Non-stirred calibrations in agarose or stirred calibrations at pH 8.6 were used to match the in vivo GABA sensitivity. In vivo data collected in the rat brain demonstrated feasibility of the GABA/glutamate MEA including uptake of locally applied GABA, KCl-evoked GABA release and modulation of endogenous GABA with vigabatrin.Comparison with existing methodsImplantable enzyme-coated microelectrode arrays have better temporal and spatial resolution than existing off-line methods. However, interpretation of results can be complicated due to the multiple recording site and dual enzyme approach.ConclusionsThe initial in vitro and in vivo studies supported that the new MEA configuration may be a viable platform for combined GABA and glutamate measures in the CNS extending the previous reports to in vivo GABA detection. The challenges of this approach are emphasized.
| S-EPMC6924626 | biostudies-literature
Project description:Indirect electrochemical methods are a powerful tool for synthetic chemistry because they allow for the optimization of chemical selectivity in a reaction while maintaining the advantages of electrochemistry in terms of sustainability. Recently, we have found that such methods provide a handle for not only the synthesis of complex molecules, but also the construction of complex, addressable molecular surfaces. In this effort, the indirect electrochemical methods enable the placement or synthesis of molecules by any electrode or set of electrodes in a microelectrode array. The success of these surface-based reactions are typically evaluated with the use of fluorescence labelling studies. However, these fluorescence-based evaluations can be misleading. While they are excellent for determining that a reaction has occurred in a site-selective fashion on an array, they do not provide information on whether that reaction is the one desired or how well it worked. We describe here how the use of a "safety-catch" linker strategy allows for a more accurate assessment of reaction quality on an array, and then use that capability to illustrate how the use of transition metal mediated cross-coupling reactions on an array prevent unwanted background reactions that can occur on a polymer-coated electrode surface. The method enables a unique level of quality control for array-based transformations.
| S-EPMC10914339 | biostudies-literature