A NIRS–fMRI investigation of prefrontal cortex activity during a working memory task

Sato, Hiroki; Yahata, Noriaki; Funane, Tsukasa; Takizawa, Ryu; Katura, Takusige; Atsumori, Hirokazu; Nishimura, Yukika; Kinoshita, Akihide; Kiguchi, Masashi; Koizumi, Hideaki; Fukuda, Masato; Kasai, Kiyoto

doi:10.1016/j.neuroimage.2013.06.043

Cited by 294 publications

(213 citation statements)

References 62 publications

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“…The results indicate a high correlation between groups for fNIRS and fMRI signals in an integration area of the temporal lobe and the correlation between the signals is in-line with that shown before in concurrent fMRI/fNIRS studies 3 . Figure 9 indicates that fNIRS activity in the temporal lobe is not only cortical in nature with differential oxy-and deoxyHb chromofore absorbance, but also that activity in the temporal lobe is quite different from that seen in the frontal lobe does not correlate with fMRI activity in the temporal lobe.…”

Section: Representative Resultssupporting

confidence: 90%

“…These results and the results of previous studies investigating concurrent fNIRS/fMRI imaging procedures confirm a high correlation between the signals as theoretically predicted [1][2][3] . One limitation to the interpretation of the data presented here is that we were unable to utilize newer techniques in optimization of NIRS recording that show it is possible to increase the resolution of the individual channel data using high density recordings.…”

Section: Representative Resultssupporting

confidence: 90%

“…Long-term goals include development of a tool to study not only motor learning paradigms but also serve to confirm the appropriateness of fNIRS for a wider variety of tasks that are not possible to perform in a naturalistic fashion using traditional methods. fNIRS activity has previously been shown to be highly correlated (r = 0.77-0.94) for homologous regions with fMRI BOLD (blood oxygen level dependent) signal recordings in limited studies which measured concurrent fNIRS and fMRI functional activity using classic psychological and simple finger tapping paradigms [1][2][3] . The results of these studies confirm fNIRS is valid and reliable to determine cortical activity associated with a reduced environmental task compatible with fMRI.…”

Section: Introductionmentioning

confidence: 99%

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fMRI Validation of fNIRS Measurements During a Naturalistic Task

Noah

Ono

Nomoto

et al. 2015

JoVE

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We present a method to compare brain activity recorded with near-infrared spectroscopy (fNIRS) in a dance video game task to that recorded in a reduced version of the task using fMRI (functional magnetic resonance imaging). Recently, it has been shown that fNIRS can accurately record functional brain activities equivalent to those concurrently recorded with functional magnetic resonance imaging for classic psychophysical tasks and simple finger tapping paradigms. However, an often quoted benefit of fNIRS is that the technique allows for studying neural mechanisms of complex, naturalistic behaviors that are not possible using the constrained environment of fMRI. Our goal was to extend the findings of previous studies that have shown high correlation between concurrently recorded fNIRS and fMRI signals to compare neural recordings obtained in fMRI procedures to those separately obtained in naturalistic fNIRS experiments. Specifically, we developed a modified version of the dance video game Dance Dance Revolution (DDR) to be compatible with both fMRI and fNIRS imaging procedures. In this methodology we explain the modifications to the software and hardware for compatibility with each technique as well as the scanning and calibration procedures used to obtain representative results. The results of the study show a task-related increase in oxyhemoglobin in both modalities and demonstrate that it is possible to replicate the findings of fMRI using fNIRS in a naturalistic task. This technique represents a methodology to compare fMRI imaging paradigms which utilize a reduced-world environment to fNIRS in closer approximation to naturalistic, full-body activities and behaviors. Further development of this technique may apply to neurodegenerative diseases, such as Parkinson's disease, late states of dementia, or those with magnetic susceptibility which are contraindicated for fMRI scanning.

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Section: Representative Resultssupporting

confidence: 90%

Section: Representative Resultssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

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fMRI Validation of fNIRS Measurements During a Naturalistic Task

Noah

Ono

Nomoto

et al. 2015

JoVE

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“…52 Briefly, in the WM (which had an identical delayed-response paradigm), each trial started with a 1.5-s presentation of the target stimuli ("target" hereafter) on a PC display screen, which was followed by a delay of 7 s. A probe stimulus ("probe" hereafter) was then presented for 2.0 s or until the participant responded. The participant responded by pressing a button on a handheld pad connected to the PC.…”

Section: Tasksmentioning

confidence: 99%

“…52 For the calculation of y 1 and y 2 , no temporal offset for the transient phase was set. For calculation of y 1 , the task periods of the four-item condition for WM and right-hand tapping condition for TAP of all repetitions were used.…”

Section: Discrimination Between Deep-and Shallow-layer Functional Neamentioning

confidence: 99%

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

et al. 2015

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Abstract. It has been reported that a functional near-infrared spectroscopy (fNIRS) signal can be contaminated by extracerebral contributions. Many algorithms using multidistance separations to address this issue have been proposed, but their spatial separation performance has rarely been validated with simultaneous measurements of fNIRS and functional magnetic resonance imaging (fMRI). We previously proposed a method for discriminating between deep and shallow contributions in fNIRS signals, referred to as the multidistance independent component analysis (MD-ICA) method. In this study, to validate the MD-ICA method from the spatial aspect, multidistance fNIRS, fMRI, and laser-Doppler-flowmetry signals were simultaneously obtained for 12 healthy adult males during three tasks. The fNIRS signal was separated into deep and shallow signals by using the MD-ICA method, and the correlation between the waveforms of the separated fNIRS signals and the gray matter blood oxygenation level-dependent signals was analyzed. A three-way analysis of variance (signal depth × Hb kind × task) indicated that the main effect of fNIRS signal depth on the correlation is significant [F ð1;1286Þ ¼ 5.34, p < 0.05]. This result indicates that the MD-ICA method successfully separates fNIRS signals into spatially deep and shallow signals, and the accuracy and reliability of the fNIRS signal will be improved with the method. © The Authors. 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.

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Neuroergonomics

Ayaz

Dehais

2021

Handbook of Human Factors and Ergonomics

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A NIRS–fMRI investigation of prefrontal cortex activity during a working memory task

Cited by 294 publications

References 62 publications

fMRI Validation of fNIRS Measurements During a Naturalistic Task

fMRI Validation of fNIRS Measurements During a Naturalistic Task

Concurrent fNIRS-fMRI measurement to validate a method for separating deep and shallow fNIRS signals by using multidistance optodes

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