SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals

Fabietti, M. ORCID: 0000-0003-3093-5985, Mahmud, M. ORCID: 0000-0002-2037-8348, Lotfi, A. ORCID: 0000-0002-5139-6565, Kaiser, M.S., Averna, A., Guggenmos, D.J., Nudo, R.J., Chiappalone, M. and Chen, J., 2021. SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals. Brain Informatics, 8: 14. ISSN 2198-4018

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Abstract

Neuronal signals generally represent activation of the neuronal networks and give insights into brain functionalities. They are considered as fingerprints of actions and their processing across different structures of the brain. These recordings generate a large volume of data that are susceptible to noise and artifacts. Therefore, the review of these data to ensure high quality by automatically detecting and removing the artifacts is imperative. Toward this aim, this work proposes a custom-developed automatic artifact removal toolbox named, SANTIA (SigMate Advanced: a Novel Tool for Identification of Artifacts in Neuronal Signals). Developed in Matlab, SANTIA is an open-source toolbox that applies neural network-based machine learning techniques to label and train models to detect artifacts from the invasive neuronal signals known as local field potentials.

Item Type: Journal article
Publication Title: Brain Informatics
Creators: Fabietti, M., Mahmud, M., Lotfi, A., Kaiser, M.S., Averna, A., Guggenmos, D.J., Nudo, R.J., Chiappalone, M. and Chen, J.
Publisher: Springer Science and Business Media LLC
Date: 20 July 2021
Volume: 8
ISSN: 2198-4018
Identifiers:
NumberType
10.1186/s40708-021-00135-3DOI
1456979Other
Rights: © The Author(s) 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Divisions: Schools > School of Science and Technology
Record created by: Laura Ward
Date Added: 16 Aug 2021 14:06
Last Modified: 16 Aug 2021 14:06
URI: http://irep.ntu.ac.uk/id/eprint/43993

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