共 60 条
Resting-state networks representation of the global phenomena
被引:0
作者:
Amemiya, Shiori
[1
]
Takao, Hidemasa
[1
]
Hanaoka, Shouhei
[1
]
Abe, Osamu
[1
]
机构:
[1] Univ Tokyo, Grad Sch Med, Dept Radiol, Tokyo, Japan
关键词:
resting-state functional magnetic resonance imaging;
hemodynamic response function;
cerebrovascular perfusion;
blood oxygenation level-dependency;
neurovascular coupling;
INDEPENDENT COMPONENT ANALYSIS;
NEAR-INFRARED SPECTROSCOPY;
CEREBRAL-BLOOD-FLOW;
FUNCTIONAL CONNECTIVITY;
HEMODYNAMIC-RESPONSES;
TEMPORAL DYNAMICS;
CONCURRENT FMRI;
VISUAL-CORTEX;
FLUCTUATIONS;
SIGNAL;
D O I:
10.3389/fnins.2023.1220848
中图分类号:
Q189 [神经科学];
学科分类号:
071006 ;
摘要:
Resting-state functional magnetic resonance imaging (rsfMRI) has been widely applied to investigate spontaneous neural activity, often based on its macroscopic organization that is termed resting-state networks (RSNs). Although the neurophysiological mechanisms underlying the RSN organization remain largely unknown, accumulating evidence points to a substantial contribution from the global signals to their structured synchronization. This study further explored the phenomenon by taking advantage of the inter- and intra-subject variations of the time delay and correlation coefficient of the signal timeseries in each region using the global mean signal as the reference signal. Consistent with the hypothesis based on the empirical and theoretical findings, the time lag and correlation, which have consistently been proven to represent local hemodynamic status, were shown to organize networks equivalent to RSNs. The results not only provide further evidence that the local hemodynamic status could be the direct source of the RSNs' spatial patterns but also explain how the regional variations in the hemodynamics, combined with the changes in the global events' power spectrum, lead to the observations. While the findings pose challenges to interpretations of rsfMRI studies, they further support the view that rsfMRI can offer detailed information related to global neurophysiological phenomena as well as local hemodynamics that would have great potential as biomarkers.
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