Literature DB >> 22713670

A NIRS-fMRI study of resting state network.

Shuntaro Sasai1, Fumitaka Homae, Hama Watanabe, Akihiro T Sasaki, Hiroki C Tanabe, Norihiro Sadato, Gentaro Taga.   

Abstract

Resting state functional connectivity, which is defined as temporal correlation of spontaneous activity between diverse brain regions, has been reported to form resting state networks (RSNs), consisting of a specific set of brain regions, based on functional magnetic resonance imaging (fMRI). Recently, studies using near-infrared spectroscopy (NIRS) reported that NIRS signals also show temporal correlation between different brain regions. The local relationship between NIRS and fMRI signals has been examined by simultaneously recording these signals when participants perform tasks or respond to stimuli. However, the NIRS-fMRI signal relationship during the resting state has been reported only between NIRS signals obtained within limited regions and whole brain fMRI signals. Therefore, it remains unclear whether NIRS signals obtained at diverse regions correlate with regional fMRI signals close to the NIRS measurement channels, especially in relation to the RSNs. In this study, we tested whether the signals measured by these different modalities during the resting state have the consistent characteristics of the RSNs. Specifically, NIRS signals during the resting state were acquired over the frontal, temporal, and occipital cortices while whole brain fMRI data was simultaneously recorded. First, by projecting the NIRS channel positions over the cerebral cortical surface, we identified the most likely anatomical locations of all NIRS channels used in the study. Next, to investigate the regional signal relationship between NIRS and fMRI, we calculated the cross-correlation between NIRS signals and fMRI signals in the brain regions adjacent to each NIRS channel. For each NIRS channel, we observed the local maxima of correlation coefficients between NIRS and fMRI signals within a radius of 2 voxels from the projection point. Furthermore, we also found that highly correlated voxels with the NIRS signal were mainly localized within brain tissues for all NIRS channels, with the exception of 2 frontal channels. Finally, by calculating the correlation between NIRS signals at a channel and whole brain fMRI signals, we observed that NIRS signals correlate with fMRI signals not only within brain regions adjacent to NIRS channels but also within distant brain regions constituting RSNs, such as the dorsal attention, fronto-parietal control, and default mode networks. These results support the idea that NIRS signals obtained at several cortical regions during the resting state mainly reflect regional spontaneous hemodynamic fluctuations that originate from spontaneous cortical activity, and include information that characterizes the RSNs. Because NIRS is relatively easy to use and a less physically demanding neuroimaging technique, our findings should facilitate a broad application of this technique to examine RSNs, especially for clinical populations and conditions unsuitable for fMRI.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22713670     DOI: 10.1016/j.neuroimage.2012.06.011

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  49 in total

1.  Greater contribution of cerebral than extracerebral hemodynamics to near-infrared spectroscopy signals for functional activation and resting-state connectivity in infants.

Authors:  Tsukasa Funane; Fumitaka Homae; Hama Watanabe; Masashi Kiguchi; Gentaro Taga
Journal:  Neurophotonics       Date:  2014-09-02       Impact factor: 3.593

Review 2.  How Does Experience Shape Early Development? Considering the Role of Top-Down Mechanisms.

Authors:  L L Emberson
Journal:  Adv Child Dev Behav       Date:  2017-02-07

3.  Functional near-infrared spectroscopy evidence for the development of topological asymmetry between hemispheric brain networks from childhood to adulthood.

Authors:  Lin Cai; Qi Dong; Mengjing Wang; Haijing Niu
Journal:  Neurophotonics       Date:  2019-05-08       Impact factor: 3.593

Review 4.  Hemodynamic correlates of cognition in human infants.

Authors:  Richard N Aslin; Mohinish Shukla; Lauren L Emberson
Journal:  Annu Rev Psychol       Date:  2014-09-22       Impact factor: 24.137

5.  Synchronous multiscale neuroimaging environment for critically sampled physiological analysis of brain function: hepta-scan concept.

Authors:  Vesa Korhonen; Tuija Hiltunen; Teemu Myllylä; Xindi Wang; Jussi Kantola; Juha Nikkinen; Yu-Feng Zang; Pierre LeVan; Vesa Kiviniemi
Journal:  Brain Connect       Date:  2014-09-26

Review 6.  Default mode network as a potential biomarker of chemotherapy-related brain injury.

Authors:  Shelli R Kesler
Journal:  Neurobiol Aging       Date:  2014-05-15       Impact factor: 4.673

7.  Resting state connectivity patterns with near-infrared spectroscopy data of the whole head.

Authors:  Sergio L Novi; Renato B M L Rodrigues; Rickson C Mesquita
Journal:  Biomed Opt Express       Date:  2016-06-06       Impact factor: 3.732

8.  Increased prefrontal cortex connectivity during cognitive challenge assessed by fNIRS imaging.

Authors:  Frigyes Samuel Racz; Peter Mukli; Zoltan Nagy; Andras Eke
Journal:  Biomed Opt Express       Date:  2017-07-25       Impact factor: 3.732

9.  Cerebral time domain-NIRS: reproducibility analysis, optical properties, hemoglobin species and tissue oxygen saturation in a cohort of adult subjects.

Authors:  Giacomo Giacalone; Marta Zanoletti; Davide Contini; Rebecca Re; Lorenzo Spinelli; Luisa Roveri; Alessandro Torricelli
Journal:  Biomed Opt Express       Date:  2017-10-12       Impact factor: 3.732

10.  Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

Authors:  Yoshiya Moriguchi; Takamasa Noda; Kosei Nakayashiki; Yohei Takata; Shiori Setoyama; Shingo Kawasaki; Yoshihiko Kunisato; Kazuo Mishima; Kazuyuki Nakagome; Takashi Hanakawa
Journal:  Hum Brain Mapp       Date:  2017-07-19       Impact factor: 5.038

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