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Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds

Functional optical topography (OT) measures the changes in oxygenated and deoxygenated hemoglobin (HbO(2), HHb) across multiple brain sites which occur in response to neuronal activation of the cerebral cortex. However, identification of areas of cortical activation is a complex task due to intrinsi...

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Detalles Bibliográficos
Autores principales: Tachtsidis, Ilias, Koh, Peck H., Stubbs, Charlotte, Elwell, Clare E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038021/
https://www.ncbi.nlm.nih.gov/pubmed/20204798
http://dx.doi.org/10.1007/978-1-4419-1241-1_34
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author Tachtsidis, Ilias
Koh, Peck H.
Stubbs, Charlotte
Elwell, Clare E.
author_facet Tachtsidis, Ilias
Koh, Peck H.
Stubbs, Charlotte
Elwell, Clare E.
author_sort Tachtsidis, Ilias
collection PubMed
description Functional optical topography (OT) measures the changes in oxygenated and deoxygenated hemoglobin (HbO(2), HHb) across multiple brain sites which occur in response to neuronal activation of the cerebral cortex. However, identification of areas of cortical activation is a complex task due to intrinsic physiological noise and systemic interference and careful statistical analysis is therefore required. A total of 10 young healthy adults were studied. The activation paradigm comprised of anagrams followed by finger tapping. 12 channels of the OT system were positioned over the frontal cortex and 12 channels over the motor cortex while the systemic physiology (mean blood pressure (MBP), heart rate (HR), scalp flux) was simultaneously monitored. Analysis was done using the functional Optical Signal Analysis (fOSA) software and Statistical Parametric Mapping (SPM), where we utilized two approaches: (i) using only HbO(2) as a regressor in the general linear model (GLM) and (ii) using all of the explanatory variables (HbO(2), MBP, HR and scalp flux) as regressors. Group analysis using SPM showed significant correlation in a large number of OT channels between HbO(2) and systemic regressors; however no differences in activation areas were seen between the two approaches.
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spelling pubmed-40380212014-06-02 Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds Tachtsidis, Ilias Koh, Peck H. Stubbs, Charlotte Elwell, Clare E. Adv Exp Med Biol Article Functional optical topography (OT) measures the changes in oxygenated and deoxygenated hemoglobin (HbO(2), HHb) across multiple brain sites which occur in response to neuronal activation of the cerebral cortex. However, identification of areas of cortical activation is a complex task due to intrinsic physiological noise and systemic interference and careful statistical analysis is therefore required. A total of 10 young healthy adults were studied. The activation paradigm comprised of anagrams followed by finger tapping. 12 channels of the OT system were positioned over the frontal cortex and 12 channels over the motor cortex while the systemic physiology (mean blood pressure (MBP), heart rate (HR), scalp flux) was simultaneously monitored. Analysis was done using the functional Optical Signal Analysis (fOSA) software and Statistical Parametric Mapping (SPM), where we utilized two approaches: (i) using only HbO(2) as a regressor in the general linear model (GLM) and (ii) using all of the explanatory variables (HbO(2), MBP, HR and scalp flux) as regressors. Group analysis using SPM showed significant correlation in a large number of OT channels between HbO(2) and systemic regressors; however no differences in activation areas were seen between the two approaches. Springer 2010 /pmc/articles/PMC4038021/ /pubmed/20204798 http://dx.doi.org/10.1007/978-1-4419-1241-1_34 Text en
spellingShingle Article
Tachtsidis, Ilias
Koh, Peck H.
Stubbs, Charlotte
Elwell, Clare E.
Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds
title Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds
title_full Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds
title_fullStr Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds
title_full_unstemmed Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds
title_short Functional optical topography analysis using Statistical Parametric Mapping (SPM) methodology with and without physiological confounds
title_sort functional optical topography analysis using statistical parametric mapping (spm) methodology with and without physiological confounds
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4038021/
https://www.ncbi.nlm.nih.gov/pubmed/20204798
http://dx.doi.org/10.1007/978-1-4419-1241-1_34
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