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Open Access

Peer-reviewed

Research Article

A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents

Thomas Pircher ,

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

* E-mail: thomas.pircher@fau.de

Affiliation Institute of Process Machinery and Systems Engineering, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany

https://orcid.org/0000-0001-9708-6469

⨯
Bianca Pircher,

Roles Conceptualization, Investigation, Writing – original draft, Writing – review & editing

Affiliation Department of Biology, Animal Physiology, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
⨯
Andreas Feigenspan

Roles Data curation, Funding acquisition, Supervision, Writing – review & editing

Affiliation Department of Biology, Animal Physiology, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen, Germany
⨯

A novel machine learning-based approach for the detection and analysis of spontaneous synaptic currents

Thomas Pircher,
Bianca Pircher,
Andreas Feigenspan

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Published: September 19, 2022
https://doi.org/10.1371/journal.pone.0273501

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