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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer
2010
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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. |
format | Online Article Text |
id | pubmed-4038021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Springer |
record_format | MEDLINE/PubMed |
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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