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Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy

Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, al...

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Autores principales: Abdalmalak, Androu, Novi, Sergio L., Kazazian, Karnig, Norton, Loretta, Benaglia, Tatiana, Slessarev, Marat, Debicki, Derek B., Lawrence, Keith St., Mesquita, Rickson C., Owen, Adrian M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957952/
https://www.ncbi.nlm.nih.gov/pubmed/35350556
http://dx.doi.org/10.3389/fnins.2022.803297
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author Abdalmalak, Androu
Novi, Sergio L.
Kazazian, Karnig
Norton, Loretta
Benaglia, Tatiana
Slessarev, Marat
Debicki, Derek B.
Lawrence, Keith St.
Mesquita, Rickson C.
Owen, Adrian M.
author_facet Abdalmalak, Androu
Novi, Sergio L.
Kazazian, Karnig
Norton, Loretta
Benaglia, Tatiana
Slessarev, Marat
Debicki, Derek B.
Lawrence, Keith St.
Mesquita, Rickson C.
Owen, Adrian M.
author_sort Abdalmalak, Androu
collection PubMed
description Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO(2) could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest.
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spelling pubmed-89579522022-03-28 Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy Abdalmalak, Androu Novi, Sergio L. Kazazian, Karnig Norton, Loretta Benaglia, Tatiana Slessarev, Marat Debicki, Derek B. Lawrence, Keith St. Mesquita, Rickson C. Owen, Adrian M. Front Neurosci Neuroscience Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO(2) could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest. Frontiers Media S.A. 2022-03-08 /pmc/articles/PMC8957952/ /pubmed/35350556 http://dx.doi.org/10.3389/fnins.2022.803297 Text en Copyright © 2022 Abdalmalak, Novi, Kazazian, Norton, Benaglia, Slessarev, Debicki, Lawrence, Mesquita and Owen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Abdalmalak, Androu
Novi, Sergio L.
Kazazian, Karnig
Norton, Loretta
Benaglia, Tatiana
Slessarev, Marat
Debicki, Derek B.
Lawrence, Keith St.
Mesquita, Rickson C.
Owen, Adrian M.
Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy
title Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy
title_full Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy
title_fullStr Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy
title_full_unstemmed Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy
title_short Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy
title_sort effects of systemic physiology on mapping resting-state networks using functional near-infrared spectroscopy
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8957952/
https://www.ncbi.nlm.nih.gov/pubmed/35350556
http://dx.doi.org/10.3389/fnins.2022.803297
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