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.

SigMate: A MATLAB-based Neuronal Signal Processing Tool

MAHMUD, MUFTI;BERTOLDO, ALESSANDRA;GIRARDI, STEFANO;MASCHIETTO, MARTA;VASSANELLI, STEFANO
2010

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.
Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE EMBC2010)
9781424441235
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/2437682
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