Cargando…
Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays
Transparent and flexible materials are attractive for a wide range of emerging bioelectronic applications. These include neural interfacing devices for both recording and stimulation, where low electrochemical electrode impedance is valuable. Here the conducting polymer poly(3,4-ethylenedioxythiophe...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377407/ https://www.ncbi.nlm.nih.gov/pubmed/30783610 http://dx.doi.org/10.1523/ENEURO.0187-18.2018 |
_version_ | 1783395735550558208 |
---|---|
author | Donahue, Mary J. Kaszas, Attila Turi, Gergely F. Rózsa, Balázs Slézia, Andrea Vanzetta, Ivo Katona, Gergely Bernard, Christophe Malliaras, George G. Williamson, Adam |
author_facet | Donahue, Mary J. Kaszas, Attila Turi, Gergely F. Rózsa, Balázs Slézia, Andrea Vanzetta, Ivo Katona, Gergely Bernard, Christophe Malliaras, George G. Williamson, Adam |
author_sort | Donahue, Mary J. |
collection | PubMed |
description | Transparent and flexible materials are attractive for a wide range of emerging bioelectronic applications. These include neural interfacing devices for both recording and stimulation, where low electrochemical electrode impedance is valuable. Here the conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is used to fabricate electrodes that are small enough to allow unencumbered optical access for imaging a large cell population with two-photon (2P) microscopy, yet provide low impedance for simultaneous high quality recordings of neural activity in vivo. To demonstrate this, pathophysiological activity was induced in the mouse cortex using 4-aminopyridine (4AP), and the resulting electrical activity was detected with the PEDOT:PSS-based probe while imaging calcium activity directly below the probe area. The induced calcium activity of the neuronal network as measured by the fluorescence change in the cells correlated well with the electrophysiological recordings from the cortical grid of PEDOT:PSS microelectrodes. Our approach provides a valuable vehicle for complementing classical high temporal resolution electrophysiological analysis with optical imaging. |
format | Online Article Text |
id | pubmed-6377407 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-63774072019-02-19 Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays Donahue, Mary J. Kaszas, Attila Turi, Gergely F. Rózsa, Balázs Slézia, Andrea Vanzetta, Ivo Katona, Gergely Bernard, Christophe Malliaras, George G. Williamson, Adam eNeuro Methods/New Tools Transparent and flexible materials are attractive for a wide range of emerging bioelectronic applications. These include neural interfacing devices for both recording and stimulation, where low electrochemical electrode impedance is valuable. Here the conducting polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) is used to fabricate electrodes that are small enough to allow unencumbered optical access for imaging a large cell population with two-photon (2P) microscopy, yet provide low impedance for simultaneous high quality recordings of neural activity in vivo. To demonstrate this, pathophysiological activity was induced in the mouse cortex using 4-aminopyridine (4AP), and the resulting electrical activity was detected with the PEDOT:PSS-based probe while imaging calcium activity directly below the probe area. The induced calcium activity of the neuronal network as measured by the fluorescence change in the cells correlated well with the electrophysiological recordings from the cortical grid of PEDOT:PSS microelectrodes. Our approach provides a valuable vehicle for complementing classical high temporal resolution electrophysiological analysis with optical imaging. Society for Neuroscience 2018-01-10 /pmc/articles/PMC6377407/ /pubmed/30783610 http://dx.doi.org/10.1523/ENEURO.0187-18.2018 Text en Copyright © 2018 Donahue et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Methods/New Tools Donahue, Mary J. Kaszas, Attila Turi, Gergely F. Rózsa, Balázs Slézia, Andrea Vanzetta, Ivo Katona, Gergely Bernard, Christophe Malliaras, George G. Williamson, Adam Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays |
title | Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays |
title_full | Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays |
title_fullStr | Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays |
title_full_unstemmed | Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays |
title_short | Multimodal Characterization of Neural Networks Using Highly Transparent Electrode Arrays |
title_sort | multimodal characterization of neural networks using highly transparent electrode arrays |
topic | Methods/New Tools |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377407/ https://www.ncbi.nlm.nih.gov/pubmed/30783610 http://dx.doi.org/10.1523/ENEURO.0187-18.2018 |
work_keys_str_mv | AT donahuemaryj multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT kaszasattila multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT turigergelyf multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT rozsabalazs multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT sleziaandrea multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT vanzettaivo multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT katonagergely multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT bernardchristophe multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT malliarasgeorgeg multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays AT williamsonadam multimodalcharacterizationofneuralnetworksusinghighlytransparentelectrodearrays |