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Application of Spike Sorting Algorithm to Neuronal Signals Originated from Boron Doped Diamond Micro-Electrode Arrays

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F20%3A00531509" target="_blank" >RIV/67985823:_____/20:00531509 - isvavai.cz</a>

  • Alternative codes found

    RIV/68378271:_____/20:00531509 RIV/68407700:21460/20:00342360

  • Result on the web

    <a href="http://www.biomed.cas.cz/physiolres/pdf/2020/69_529.pdf" target="_blank" >http://www.biomed.cas.cz/physiolres/pdf/2020/69_529.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.33549/physiolres.934366" target="_blank" >10.33549/physiolres.934366</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Application of Spike Sorting Algorithm to Neuronal Signals Originated from Boron Doped Diamond Micro-Electrode Arrays

  • Original language description

    In this work we report on the implementation of methods for data processing signals from microelectrode arrays (MEA) and the application of these methods for signals originated from two types of MEAs to detect putative neurons and sort them into subpopulations. We recorded electrical signals from firing neurons using titanium nitride (TiN) and boron doped diamond (BDD) MEAs. In previous research, we have shown that these methods have the capacity to detect neurons using commercially-available TiN-MEAs. We have managed to cultivate and record hippocampal neurons for the first time using a newly developed custom-made multichannel BDD-MEA with 20 recording sites. We have analysed the signals with the algorithms developed and employed them to inspect firing bursts and enable spike sorting. We did not observe any significant difference between BDD- and TiN-MEAs over the parameters, which estimated spike shape variability per each detected neuron. This result supports the hypothesis that we have detected real neurons, rather than noise, in the BDD-MEA signal. BDD materials with suitable mechanical, electrical and biocompatibility properties have a large potential in novel therapies for treatments of neural pathologies, such as deep brain stimulation in Parkinson's disease.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • Project

    <a href="/en/project/GA17-15319S" target="_blank" >GA17-15319S: Diamond based microelectrode arrays for dual mode neural recording</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Physiological Research

  • ISSN

    0862-8408

  • e-ISSN

  • Volume of the periodical

    69

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    8

  • Pages from-to

    529-536

  • UT code for WoS article

    000551270100018

  • EID of the result in the Scopus database

    2-s2.0-85088495161