SigMate: A MATLAB-based neuronal signal processing tool
- PMID: 21096329
- DOI: 10.1109/IEMBS.2010.5626747
SigMate: A MATLAB-based neuronal signal processing tool
Abstract
Advances in neuronal probe technology to record brain activity have posed a significant challenge in performing necessary processing and analysis of the recorded data. To be able to infer meaningful conclusions from the recorded signals through these probes, sophisticated signal processing and analysis tools are required. This paper presents a MATLAB-based novel tool, 'SigMate', capable of performing various processing and analysis incorporating the available standard tools and our in-house custom tools. The present features include, data display (2D and 3D), baseline correction, stimulus artifact removal, noise characterization, file operations (file splitter, file concatenator, and file column rearranger), latency estimation, determination of cortical layer activation order, spike detection, spike sorting, and are gradually growing. This tool has been tested extensively for the recordings using the standard micropipettes as well as implantable neural probes based on EOSFETs (Electrolyte-Oxide-Semiconductor Field Effect Transistors) and will be made available to the community shortly.
Similar articles
-
SigMate: a Matlab-based automated tool for extracellular neuronal signal processing and analysis.J Neurosci Methods. 2012 May 30;207(1):97-112. doi: 10.1016/j.jneumeth.2012.03.009. Epub 2012 Apr 10. J Neurosci Methods. 2012. PMID: 22513383
-
NeuroQuest: a comprehensive analysis tool for extracellular neural ensemble recordings.J Neurosci Methods. 2012 Feb 15;204(1):189-201. doi: 10.1016/j.jneumeth.2011.10.027. Epub 2011 Nov 10. J Neurosci Methods. 2012. PMID: 22101141 Free PMC article.
-
Neural Parallel Engine: A toolbox for massively parallel neural signal processing.J Neurosci Methods. 2018 May 1;301:18-33. doi: 10.1016/j.jneumeth.2018.03.004. Epub 2018 Mar 9. J Neurosci Methods. 2018. PMID: 29530617
-
Approaches for the efficient extraction and processing of biopotentials in implantable neural interfacing microsystems.Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:5855-9. doi: 10.1109/IEMBS.2011.6091448. Annu Int Conf IEEE Eng Med Biol Soc. 2011. PMID: 22255671 Review.
-
A review on cluster estimation methods and their application to neural spike data.J Neural Eng. 2018 Jun;15(3):031003. doi: 10.1088/1741-2552/aab385. Epub 2018 Mar 2. J Neural Eng. 2018. PMID: 29498353 Review.
Cited by
-
Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and Challenges.Front Neurosci. 2016 Jun 2;10:248. doi: 10.3389/fnins.2016.00248. eCollection 2016. Front Neurosci. 2016. PMID: 27313507 Free PMC article. Review.
-
Robot-Embodied Neuronal Networks as an Interactive Model of Learning.Open Neurol J. 2017 Sep 30;11:39-47. doi: 10.2174/1874205X01711010039. eCollection 2017. Open Neurol J. 2017. PMID: 29151990 Free PMC article.
-
SANTIA: a Matlab-based open-source toolbox for artifact detection and removal from extracellular neuronal signals.Brain Inform. 2021 Jul 20;8(1):14. doi: 10.1186/s40708-021-00135-3. Brain Inform. 2021. PMID: 34283328 Free PMC article.