Accurate signal-source localization in brain slices by means of high-density microelectrode arrays

Abstract 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 mo...

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Autores principales:	Marie Engelene J. Obien, Andreas Hierlemann, Urs Frey
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2019
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4a0d62514a8e4af99be935eda99ee59a
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spelling	oai:doaj.org-article:4a0d62514a8e4af99be935eda99ee59a2021-12-02T15:09:59ZAccurate signal-source localization in brain slices by means of high-density microelectrode arrays10.1038/s41598-018-36895-y2045-2322https://doaj.org/article/4a0d62514a8e4af99be935eda99ee59a2019-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-36895-yhttps://doaj.org/toc/2045-2322Abstract 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.Marie Engelene J. ObienAndreas HierlemannUrs FreyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 9, Iss 1, Pp 1-19 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Marie Engelene J. Obien Andreas Hierlemann Urs Frey Accurate signal-source localization in brain slices by means of high-density microelectrode arrays
description	Abstract 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.
format	article
author	Marie Engelene J. Obien Andreas Hierlemann Urs Frey
author_facet	Marie Engelene J. Obien Andreas Hierlemann Urs Frey
author_sort	Marie Engelene J. Obien
title	Accurate signal-source localization in brain slices by means of high-density microelectrode arrays
title_short	Accurate signal-source localization in brain slices by means of high-density microelectrode arrays
title_full	Accurate signal-source localization in brain slices by means of high-density microelectrode arrays
title_fullStr	Accurate signal-source localization in brain slices by means of high-density microelectrode arrays
title_full_unstemmed	Accurate signal-source localization in brain slices by means of high-density microelectrode arrays
title_sort	accurate signal-source localization in brain slices by means of high-density microelectrode arrays
publisher	Nature Portfolio
publishDate	2019
url	https://doaj.org/article/4a0d62514a8e4af99be935eda99ee59a
work_keys_str_mv	AT marieengelenejobien accuratesignalsourcelocalizationinbrainslicesbymeansofhighdensitymicroelectrodearrays AT andreashierlemann accuratesignalsourcelocalizationinbrainslicesbymeansofhighdensitymicroelectrodearrays AT ursfrey accuratesignalsourcelocalizationinbrainslicesbymeansofhighdensitymicroelectrodearrays
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Accurate signal-source localization in brain slices by means of high-density microelectrode arrays

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