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A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection
Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy (fNIRS)...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848231/ https://www.ncbi.nlm.nih.gov/pubmed/33536888 http://dx.doi.org/10.3389/fnhum.2020.606238 |
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author | Zhang, Jiang Zhang, Jingyue Ren, Houhua Liu, Qihong Du, Zhengcong Wu, Lan Sai, Liyang Yuan, Zhen Mo, Site Lin, Xiaohong |
author_facet | Zhang, Jiang Zhang, Jingyue Ren, Houhua Liu, Qihong Du, Zhengcong Wu, Lan Sai, Liyang Yuan, Zhen Mo, Site Lin, Xiaohong |
author_sort | Zhang, Jiang |
collection | PubMed |
description | Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy (fNIRS) signals was proposed to examine the brain activation difference between the spontaneous deceptive behavior and controlled behavior. The power value produced by the model was applied to quantify the activity energy of brain regions, which can serve as a neuromarker for deception detection. Interestingly, the power analysis results generated from the Welch spectrum estimation method demonstrated that the spontaneous deceptive behavior elicited significantly higher power than that from the controlled behavior in the prefrontal cortex. Meanwhile, the power findings also showed significant difference between the spontaneous deceptive behavior and controlled behavior, indicating that the reward system was only involved in the deception. The proposed power analysis method for processing fNIRS data provides us an additional insight to understand the cognitive mechanism of deception. |
format | Online Article Text |
id | pubmed-7848231 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-78482312021-02-02 A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection Zhang, Jiang Zhang, Jingyue Ren, Houhua Liu, Qihong Du, Zhengcong Wu, Lan Sai, Liyang Yuan, Zhen Mo, Site Lin, Xiaohong Front Hum Neurosci Neuroscience Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy (fNIRS) signals was proposed to examine the brain activation difference between the spontaneous deceptive behavior and controlled behavior. The power value produced by the model was applied to quantify the activity energy of brain regions, which can serve as a neuromarker for deception detection. Interestingly, the power analysis results generated from the Welch spectrum estimation method demonstrated that the spontaneous deceptive behavior elicited significantly higher power than that from the controlled behavior in the prefrontal cortex. Meanwhile, the power findings also showed significant difference between the spontaneous deceptive behavior and controlled behavior, indicating that the reward system was only involved in the deception. The proposed power analysis method for processing fNIRS data provides us an additional insight to understand the cognitive mechanism of deception. Frontiers Media S.A. 2021-01-18 /pmc/articles/PMC7848231/ /pubmed/33536888 http://dx.doi.org/10.3389/fnhum.2020.606238 Text en Copyright © 2021 Zhang, Zhang, Ren, Liu, Du, Wu, Sai, Yuan, Mo and Lin. http://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 Zhang, Jiang Zhang, Jingyue Ren, Houhua Liu, Qihong Du, Zhengcong Wu, Lan Sai, Liyang Yuan, Zhen Mo, Site Lin, Xiaohong A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection |
title | A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection |
title_full | A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection |
title_fullStr | A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection |
title_full_unstemmed | A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection |
title_short | A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection |
title_sort | look into the power of fnirs signals by using the welch power spectral estimate for deception detection |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848231/ https://www.ncbi.nlm.nih.gov/pubmed/33536888 http://dx.doi.org/10.3389/fnhum.2020.606238 |
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