An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection

Abstract Intrinsic Optical Signal (IOS) imaging has been used extensively to examine activity-related changes within the cerebral cortex. A significant technical challenge with IOS imaging is the presence of large noise, artefact components and periodic interference. Signal processing is therefore i...

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Autores principales:	J. A. Turley, K. Zalewska, M. Nilsson, F. R. Walker, S. J. Johnson
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/256fd4dc9ae5474793548f07416c579a
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spelling	oai:doaj.org-article:256fd4dc9ae5474793548f07416c579a2021-12-02T12:31:55ZAn analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection10.1038/s41598-017-06864-y2045-2322https://doaj.org/article/256fd4dc9ae5474793548f07416c579a2017-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-06864-yhttps://doaj.org/toc/2045-2322Abstract Intrinsic Optical Signal (IOS) imaging has been used extensively to examine activity-related changes within the cerebral cortex. A significant technical challenge with IOS imaging is the presence of large noise, artefact components and periodic interference. Signal processing is therefore important in obtaining quality IOS imaging results. Several signal processing techniques have been deployed, however, the performance of these approaches for IOS imaging has never been directly compared. The current study aims to compare signal processing techniques that can be used when quantifying stimuli-response IOS imaging data. Data were gathered from the somatosensory cortex of mice following piezoelectric stimulation of the hindlimb. The effectiveness of each technique to remove noise and extract the IOS signal was compared for both spatial and temporal responses. Careful analysis of the advantages and disadvantages of each method were carried out to inform the choice of signal processing for IOS imaging. We conclude that spatial Gaussian filtering is the most effective choices for improving the spatial IOS response, whilst temporal low pass and bandpass filtering produce the best results for producing temporal responses when periodic stimuli are an option. Global signal regression and truncated difference also work well and do not require periodic stimuli.J. A. TurleyK. ZalewskaM. NilssonF. R. WalkerS. J. JohnsonNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-14 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q J. A. Turley K. Zalewska M. Nilsson F. R. Walker S. J. Johnson An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
description	Abstract Intrinsic Optical Signal (IOS) imaging has been used extensively to examine activity-related changes within the cerebral cortex. A significant technical challenge with IOS imaging is the presence of large noise, artefact components and periodic interference. Signal processing is therefore important in obtaining quality IOS imaging results. Several signal processing techniques have been deployed, however, the performance of these approaches for IOS imaging has never been directly compared. The current study aims to compare signal processing techniques that can be used when quantifying stimuli-response IOS imaging data. Data were gathered from the somatosensory cortex of mice following piezoelectric stimulation of the hindlimb. The effectiveness of each technique to remove noise and extract the IOS signal was compared for both spatial and temporal responses. Careful analysis of the advantages and disadvantages of each method were carried out to inform the choice of signal processing for IOS imaging. We conclude that spatial Gaussian filtering is the most effective choices for improving the spatial IOS response, whilst temporal low pass and bandpass filtering produce the best results for producing temporal responses when periodic stimuli are an option. Global signal regression and truncated difference also work well and do not require periodic stimuli.
format	article
author	J. A. Turley K. Zalewska M. Nilsson F. R. Walker S. J. Johnson
author_facet	J. A. Turley K. Zalewska M. Nilsson F. R. Walker S. J. Johnson
author_sort	J. A. Turley
title	An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
title_short	An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
title_full	An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
title_fullStr	An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
title_full_unstemmed	An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
title_sort	analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/256fd4dc9ae5474793548f07416c579a
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An analysis of signal processing algorithm performance for cortical intrinsic optical signal imaging and strategies for algorithm selection

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