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Nanopatterned Nafion microelectrode arrays for in vitro cardiac electrophysiology.

ABSTRACT: In this study, we report nanopatterned Nafion microelectrode arrays for in vitro cardiac electrophysiology. With the aim of defining sophisticated Nafion nanostructures with highly ionic conductivity, fabrication parameters such as Nafion concentration and curing temperature were optimized. By increasing curing temperature and Nafion concentration, we were able to control the replication fidelity of Nafion nanopatterns when copied from a PDMS master mold. We also found that cross-sectional morphology and ion current density of nanopatterned Nafion strongly depends on the fabrication parameters. To investigate this dependency, current-voltage analysis was conducted using organic electrochemical transistors (OECT) overlaid with patterned Nafion substrates. Nanopatterned Nafion was found to allow higher ion current densities than unpatterned surfaces. Furthermore, higher curing temperatures were found to render Nafion layers with higher ion/electrical transfer properties. To optimize nanopattern dimensions, electrical current flows, and film uniformity, a final configuration consisting of 5% nanopatterned Nafion cured at 65°C was chosen. Multielectrode arrays (MEAs) were then covered with optimized Nafion nanopatterns and used for electrophysiological analysis of two types of induced pluripotent stem cell-derived cardiomyocytes (iPSCs-CMs). These data highlight the suitability of nanopatterned Nafion, combined with MEAs, for enhancing the cellular environment of iPSC-CMs for use in electrophysiological analysis in vitro.

SUBMITTER: Choi JS

PROVIDER: S-EPMC7688058 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Nanopatterned Nafion microelectrode arrays for <i>in vitro</i> cardiac electrophysiology.

Choi Jong Seob JS Smith Alec S T AST Williams Nisa P NP Matsubara Tatsuya T Choi Minji M Kim Joon-Wan JW Kim Hyung Jin HJ Choi Seungkeun S Kim Deok-Ho DH

Advanced functional materials 20200422 25

In this study, we report nanopatterned Nafion microelectrode arrays for in vitro cardiac electrophysiology. With the aim of defining sophisticated Nafion nanostructures with highly ionic conductivity, fabrication parameters such as Nafion concentration and curing temperature were optimized. By increasing curing temperature and Nafion concentration, we were able to control the replication fidelity of Nafion nanopatterns when copied from a PDMS master mold. We also found that cross-sectional morph ...[more]

PMID: 33244297

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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.

Dataset Information

Nanopatterned Nafion microelectrode arrays for in vitro cardiac electrophysiology.

Publications

Nanopatterned Nafion microelectrode arrays for <i>in vitro</i> cardiac electrophysiology.

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