2020
DOI: 10.3389/fnins.2020.00167
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Differences in Net Information Flow and Dynamic Connectivity Metrics Between Physically Active and Inactive Subjects Measured by Functional Near-Infrared Spectroscopy (fNIRS) During a Fatiguing Handgrip Task

Abstract: Urquhart et al. Dynamic fNIRS Metrics During Handgrip resulting in delayed fatigue onset and enhanced performance. The dynamic cortical network metrics quantified in this work for young, healthy subjects provides baseline measurements to guide future work on older individuals and persons with impaired cardiovascular health.

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Cited by 14 publications
(10 citation statements)
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References 72 publications
(145 reference statements)
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“…Several methods were used in neuroimaging studies to determine the coupling direction between neural signals, such as Granger causality analysis (GCA) (Granger, 1969; Im et al, 2010; Jiang et al, 2015), phase transfer entropy (PTE) (Cao, Wang, Liu, & Alexandrakis, 2018; Hillebrand et al, 2016; Lobier, Siebenhühner, Palva, & Palva, 2014; Urquhart, Wang, Liu, Fadel, & Alexandrakis, 2020; Wang et al, 2017), permutation conditional mutual information (Abásolo, Escudero, Hornero, Gómez, & Espino, 2008; Hall & Sarkar, 2011; Li & Ouyang, 2010; Liang, Liang, Wang, Ouyang, & Li, 2015; Wen et al, 2016), and so on. In this study, the GCA method was used, because the GCA is easy to implement, and has been widely used in previous fNIRS studies to estimate the causal relationship between fNIRS time series data, such as cooperation (Cui et al, 2012), teaching (Pan, Novembre, Song, Li, & Hu, 2018), and imitation (Holper, Scholkmann, & Wolf, 2012).…”
Section: Methodsmentioning
confidence: 99%
“…Several methods were used in neuroimaging studies to determine the coupling direction between neural signals, such as Granger causality analysis (GCA) (Granger, 1969; Im et al, 2010; Jiang et al, 2015), phase transfer entropy (PTE) (Cao, Wang, Liu, & Alexandrakis, 2018; Hillebrand et al, 2016; Lobier, Siebenhühner, Palva, & Palva, 2014; Urquhart, Wang, Liu, Fadel, & Alexandrakis, 2020; Wang et al, 2017), permutation conditional mutual information (Abásolo, Escudero, Hornero, Gómez, & Espino, 2008; Hall & Sarkar, 2011; Li & Ouyang, 2010; Liang, Liang, Wang, Ouyang, & Li, 2015; Wen et al, 2016), and so on. In this study, the GCA method was used, because the GCA is easy to implement, and has been widely used in previous fNIRS studies to estimate the causal relationship between fNIRS time series data, such as cooperation (Cui et al, 2012), teaching (Pan, Novembre, Song, Li, & Hu, 2018), and imitation (Holper, Scholkmann, & Wolf, 2012).…”
Section: Methodsmentioning
confidence: 99%
“…The results of the frequency-domain analysis showed a significant higher power content in the neurogenic band for the Corrugator and Nose Tip with respect to the muscle ROIs (Exercised and Nonexercised Legs), as shown in Figure 4 . The neurogenic band is associated with nerve activation [ 36 ], hence it may be possible that the higher activity for this band in the facial ROIs could reflect the state of fatigue. This hypothesis was further corroborated by the significant correlation between RPE and the power content of this band for the Nose Tip ( Table 1 ).…”
Section: Discussionmentioning
confidence: 99%
“…The origin of this system is in the center of the chin. Four reference points are obtained at the nasion (Nz), right preauricular points (AR), left preauricular points (AL), and central zero (Cz) [ 71 ]. The positions of the fNIRS sources and detectors were obtained according to the origin and the four reference points.…”
Section: Methodsmentioning
confidence: 99%