Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy

Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can...

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Main Authors:	Caldwell, Matthew, Scholkmann, Felix, Wolf, Ursula, Wolf, Martin, Elwell, Clare, Tachtsidis, Ilias
Format:	Online
Language:	English
Published:	Academic Press 2016
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139986/

id	pubmed-5139986
recordtype	oai_dc
spelling	pubmed-51399862016-12-12 Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy Caldwell, Matthew Scholkmann, Felix Wolf, Ursula Wolf, Martin Elwell, Clare Tachtsidis, Ilias Article Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, ‘BrainSignals’. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors. Academic Press 2016-12 /pmc/articles/PMC5139986/ /pubmed/27591921 http://dx.doi.org/10.1016/j.neuroimage.2016.08.058 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Caldwell, Matthew Scholkmann, Felix Wolf, Ursula Wolf, Martin Elwell, Clare Tachtsidis, Ilias
spellingShingle	Caldwell, Matthew Scholkmann, Felix Wolf, Ursula Wolf, Martin Elwell, Clare Tachtsidis, Ilias Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
author_facet	Caldwell, Matthew Scholkmann, Felix Wolf, Ursula Wolf, Martin Elwell, Clare Tachtsidis, Ilias
author_sort	Caldwell, Matthew
title	Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
title_short	Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
title_full	Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
title_fullStr	Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
title_full_unstemmed	Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
title_sort	modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy
description	Haemodynamics-based neuroimaging is widely used to study brain function. Regional blood flow changes characteristic of neurovascular coupling provide an important marker of neuronal activation. However, changes in systemic physiological parameters such as blood pressure and concentration of CO2 can also affect regional blood flow and may confound haemodynamics-based neuroimaging. Measurements with functional near-infrared spectroscopy (fNIRS) may additionally be confounded by blood flow and oxygenation changes in extracerebral tissue layers. Here we investigate these confounds using an extended version of an existing computational model of cerebral physiology, ‘BrainSignals’. Our results show that confounding from systemic physiological factors is able to produce misleading haemodynamic responses in both positive and negative directions. By applying the model to data from previous fNIRS studies, we demonstrate that such potentially deceptive responses can indeed occur in at least some experimental scenarios. It is therefore important to record the major potential confounders in the course of fNIRS experiments. Our model may then allow the observed behaviour to be attributed among the potential causes and hence reduce identification errors.
publisher	Academic Press
publishDate	2016
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5139986/
_version_	1613760083108298752

Modelling confounding effects from extracerebral contamination and systemic factors on functional near-infrared spectroscopy

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