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Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging

Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated ([Formula: see text]) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activat...

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Autores principales: Sutoko, Stephanie, Chan, Yee Ling, Obata, Akiko, Sato, Hiroki, Maki, Atsushi, Numata, Takashi, Funane, Tsukasa, Atsumori, Hirokazu, Kiguchi, Masashi, Tang, Tong Boon, Li, Yingwei, Frederick, Blaise deB, Tong, Yunjie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Society of Photo-Optical Instrumentation Engineers 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326259/
https://www.ncbi.nlm.nih.gov/pubmed/30662924
http://dx.doi.org/10.1117/1.NPh.6.1.015001
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author Sutoko, Stephanie
Chan, Yee Ling
Obata, Akiko
Sato, Hiroki
Maki, Atsushi
Numata, Takashi
Funane, Tsukasa
Atsumori, Hirokazu
Kiguchi, Masashi
Tang, Tong Boon
Li, Yingwei
Frederick, Blaise deB
Tong, Yunjie
author_facet Sutoko, Stephanie
Chan, Yee Ling
Obata, Akiko
Sato, Hiroki
Maki, Atsushi
Numata, Takashi
Funane, Tsukasa
Atsumori, Hirokazu
Kiguchi, Masashi
Tang, Tong Boon
Li, Yingwei
Frederick, Blaise deB
Tong, Yunjie
author_sort Sutoko, Stephanie
collection PubMed
description Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated ([Formula: see text]) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activation. However, systemic physiological artifacts (i.e., nonneuronal) likely occur also in overlapping frequency bands. We measured peripheral photoplethysmogram (PPG) signal concurrently with fNIRS (at prefrontal region) to extract the low-frequency oscillations (LFOs) as systemic noise regressors. We investigated three main points in this study: (1) the relationship between prefrontal fNIRS and peripheral PPG signals; (2) the denoising potential using these peripheral LFOs, and (3) the innovative ways to avoid the false-positive result in fNIRS studies. We employed spatial working memory (WM) and control tasks (e.g., resting state) to illustrate these points. Our results showed: (1) correlation between signals from prefrontal fNIRS and peripheral PPG is region-dependent. The high correlation with peripheral ear signal (i.e., [Formula: see text]) occurred mainly in frontopolar regions in both spatial WM and control tasks. This may indicate the finding of task-dependent effect even in peripheral signals. We also found that the PPG recording at the ear has a high correlation with prefrontal fNIRS signal than the finger signals. (2) The systemic noise was reduced by 25% to 34% on average across regions, with a maximum of 39% to 58% in the highly correlated frontopolar region, by using these peripheral LFOs as noise regressors. (3) By performing the control tasks, we confirmed that the statistically significant activation was observed in the spatial WM task, not in the controls. This suggested that systemic (and any other) noises unlikely violated the major statistical inference. (4) Lastly, by denoising using the task-related signals, the significant activation of region-of-interest was still observed suggesting the manifest task-evoked response in the spatial WM task.
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spelling pubmed-63262592020-01-09 Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging Sutoko, Stephanie Chan, Yee Ling Obata, Akiko Sato, Hiroki Maki, Atsushi Numata, Takashi Funane, Tsukasa Atsumori, Hirokazu Kiguchi, Masashi Tang, Tong Boon Li, Yingwei Frederick, Blaise deB Tong, Yunjie Neurophotonics Research Papers Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated ([Formula: see text]) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activation. However, systemic physiological artifacts (i.e., nonneuronal) likely occur also in overlapping frequency bands. We measured peripheral photoplethysmogram (PPG) signal concurrently with fNIRS (at prefrontal region) to extract the low-frequency oscillations (LFOs) as systemic noise regressors. We investigated three main points in this study: (1) the relationship between prefrontal fNIRS and peripheral PPG signals; (2) the denoising potential using these peripheral LFOs, and (3) the innovative ways to avoid the false-positive result in fNIRS studies. We employed spatial working memory (WM) and control tasks (e.g., resting state) to illustrate these points. Our results showed: (1) correlation between signals from prefrontal fNIRS and peripheral PPG is region-dependent. The high correlation with peripheral ear signal (i.e., [Formula: see text]) occurred mainly in frontopolar regions in both spatial WM and control tasks. This may indicate the finding of task-dependent effect even in peripheral signals. We also found that the PPG recording at the ear has a high correlation with prefrontal fNIRS signal than the finger signals. (2) The systemic noise was reduced by 25% to 34% on average across regions, with a maximum of 39% to 58% in the highly correlated frontopolar region, by using these peripheral LFOs as noise regressors. (3) By performing the control tasks, we confirmed that the statistically significant activation was observed in the spatial WM task, not in the controls. This suggested that systemic (and any other) noises unlikely violated the major statistical inference. (4) Lastly, by denoising using the task-related signals, the significant activation of region-of-interest was still observed suggesting the manifest task-evoked response in the spatial WM task. Society of Photo-Optical Instrumentation Engineers 2019-01-09 2019-01 /pmc/articles/PMC6326259/ /pubmed/30662924 http://dx.doi.org/10.1117/1.NPh.6.1.015001 Text en © The Authors. https://creativecommons.org/licenses/by/3.0/ Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
spellingShingle Research Papers
Sutoko, Stephanie
Chan, Yee Ling
Obata, Akiko
Sato, Hiroki
Maki, Atsushi
Numata, Takashi
Funane, Tsukasa
Atsumori, Hirokazu
Kiguchi, Masashi
Tang, Tong Boon
Li, Yingwei
Frederick, Blaise deB
Tong, Yunjie
Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
title Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
title_full Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
title_fullStr Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
title_full_unstemmed Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
title_short Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
title_sort denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging
topic Research Papers
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6326259/
https://www.ncbi.nlm.nih.gov/pubmed/30662924
http://dx.doi.org/10.1117/1.NPh.6.1.015001
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