A NIRS-fMRI study of resting state network

被引:121
作者
Sasai, Shuntaro [1 ,2 ]
Homae, Fumitaka [3 ]
Watanabe, Hama
Sasaki, Akihiro T. [2 ,4 ,5 ]
Tanabe, Hiroki C. [4 ,5 ]
Sadato, Norihiro [4 ,5 ,6 ]
Taga, Gentaro
机构
[1] Univ Tokyo, Grad Sch Educ, Div Phys & Hlth Educ, Bunkyo Ku, Tokyo 1130033, Japan
[2] Japan Soc Promot Sci, Chiyoda Ku, Tokyo 1028472, Japan
[3] Tokyo Metropolitan Univ, Dept Language Sci, Hachioji, Tokyo 1920397, Japan
[4] Natl Inst Nat Sci, Natl Inst Physiol Sci, Dept Cerebral Res, Div Cerebral Integrat, Okazaki, Aichi 4448585, Japan
[5] Grad Univ Adv Studies Sokendai, Dept Physiol Sci, Okazaki, Aichi 4448585, Japan
[6] Japan Sci & Technol Agcy, Res Inst Sci & Technol Soc, Chiyoda Ku, Tokyo 1020076, Japan
关键词
Resting state; Functional connectivity; Resting state network; Default mode network; Simultaneous NIRS-fMRI recording; Spontaneous hemodynamic fluctuation; NEAR-INFRARED SPECTROSCOPY; INDEPENDENT COMPONENT ANALYSIS; BRAINS DEFAULT NETWORK; LEVEL-DEPENDENT SIGNAL; FUNCTIONAL CONNECTIVITY; BLOOD OXYGENATION; FRONTAL-CORTEX; MOTOR CORTEX; BOLD SIGNAL; SPONTANEOUS FLUCTUATIONS;
D O I
10.1016/j.neuroimage.2012.06.011
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
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. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:179 / 193
页数:15
相关论文
共 102 条
[1]   Meeting of minds: the medial frontal cortex and social cognition [J].
Amodio, DM ;
Frith, CD .
NATURE REVIEWS NEUROSCIENCE, 2006, 7 (04) :268-277
[2]   Network Anticorrelations, Global Regression, and Phase-Shifted Soft Tissue Correction [J].
Anderson, Jeffrey S. ;
Druzgal, T. Jason ;
Lopez-Larson, Melissa ;
Jeong, Eun-Kee ;
Desai, Krishnaji ;
Yurgelun-Todd, Deborah .
HUMAN BRAIN MAPPING, 2011, 32 (06) :919-934
[3]   A fast diffeomorphic image registration algorithm [J].
Ashburner, John .
NEUROIMAGE, 2007, 38 (01) :95-113
[4]   Investigations into resting-state connectivity using independent component analysis [J].
Beckmann, CF ;
DeLuca, M ;
Devlin, JT ;
Smith, SM .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY B-BIOLOGICAL SCIENCES, 2005, 360 (1457) :1001-1013
[5]  
Benjamini Y, 2001, ANN STAT, V29, P1165
[6]   FUNCTIONAL CONNECTIVITY IN THE MOTOR CORTEX OF RESTING HUMAN BRAIN USING ECHO-PLANAR MRI [J].
BISWAL, B ;
YETKIN, FZ ;
HAUGHTON, VM ;
HYDE, JS .
MAGNETIC RESONANCE IN MEDICINE, 1995, 34 (04) :537-541
[7]   The brain's default network - Anatomy, function, and relevance to disease [J].
Buckner, Randy L. ;
Andrews-Hanna, Jessica R. ;
Schacter, Daniel L. .
YEAR IN COGNITIVE NEUROSCIENCE 2008, 2008, 1124 :1-38
[8]   Unrest at rest: Default activity and spontaneous network correlations [J].
Buckner, Randy L. ;
Vincent, Justin L. .
NEUROIMAGE, 2007, 37 (04) :1091-1096
[9]   Self-projection and the brain [J].
Buckner, Randy L. ;
Carroll, Daniel C. .
TRENDS IN COGNITIVE SCIENCES, 2007, 11 (02) :49-57
[10]   Revisiting the Foundations of Network Analysis [J].
Butts, Carter T. .
SCIENCE, 2009, 325 (5939) :414-416