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静息态血流动力学反应函数估计对自主神经系统波动的敏感性。

Sensitivity of the resting-state haemodynamic response function estimation to autonomic nervous system fluctuations.

作者信息

Wu Guo-Rong, Marinazzo Daniele

机构信息

Key Laboratory of Cognition and Personality, Faculty of Psychology, Southwest University, Chongqing 400715, China Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium

Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium.

出版信息

Philos Trans A Math Phys Eng Sci. 2016 May 13;374(2067). doi: 10.1098/rsta.2015.0190.

Abstract

The haemodynamic response function (HRF) is a key component of the blood oxygen level-dependent (BOLD) signal, providing the mapping between neural activity and the signal measured with functional magnetic resonance imaging (fMRI). Most of the time the HRF is associated with task-based fMRI protocols, in which its onset is explicitly included in the design matrix. On the other hand, the HRF also mediates the relationship between spontaneous neural activity and the BOLD signal in resting-state protocols, in which no explicit stimulus is taken into account. It has been shown that resting-state brain dynamics can be characterized by looking at sparse BOLD 'events', which can be retrieved by point process analysis. These events can be then used to retrieve the HRF at rest. Crucially, cardiac activity can also induce changes in the BOLD signal, thus affecting both the number of these events and the estimation of the haemodynamic response. In this study, we compare the resting-state haemodynamic response retrieved by means of a point process analysis, taking the cardiac fluctuations into account. We find that the resting-state HRF estimation is significantly modulated in the brainstem and surrounding cortical areas. From the analysis of two high-quality datasets with different temporal and spatial resolution, and through the investigation of intersubject correlation, we suggest that spontaneous point process response durations are associated with the mean interbeat interval and low-frequency power of heart rate variability in the brainstem.

摘要

血流动力学响应函数(HRF)是血氧水平依赖(BOLD)信号的关键组成部分,它在神经活动与功能磁共振成像(fMRI)测量的信号之间建立映射关系。大多数情况下,HRF与基于任务的fMRI协议相关,在该协议中,其起始点被明确纳入设计矩阵。另一方面,HRF在静息态协议中也介导自发神经活动与BOLD信号之间的关系,在静息态协议中不考虑明确的刺激。研究表明,静息态脑动力学可以通过观察稀疏的BOLD“事件”来表征,这些事件可以通过点过程分析来检索。然后可以使用这些事件来检索静息态下的HRF。至关重要的是,心脏活动也会引起BOLD信号的变化,从而影响这些事件的数量以及血流动力学响应的估计。在本研究中,我们通过点过程分析来比较考虑心脏波动后检索到的静息态血流动力学响应。我们发现,脑干和周围皮质区域的静息态HRF估计受到显著调制。通过对两个具有不同时间和空间分辨率的高质量数据集的分析,并通过对受试者间相关性的研究,我们表明自发点过程响应持续时间与脑干中心率变异性的平均心动间期和低频功率相关。

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本文引用的文献

1
Retrieving the Hemodynamic Response Function in resting state fMRI: Methodology and application.
Annu Int Conf IEEE Eng Med Biol Soc. 2015;2015:6050-3. doi: 10.1109/EMBC.2015.7319771.
2
A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures.
Sci Data. 2015 Jan 20;2:140054. doi: 10.1038/sdata.2014.54. eCollection 2015.
4
Resting-state functional MR imaging: a new window to the brain.
Radiology. 2014 Jul;272(1):29-49. doi: 10.1148/radiol.14132388.
5
Fear from the heart: sensitivity to fear stimuli depends on individual heartbeats.
J Neurosci. 2014 May 7;34(19):6573-82. doi: 10.1523/JNEUROSCI.3507-13.2014.
7
Physiological noise in brainstem FMRI.
Front Hum Neurosci. 2013 Oct 4;7:623. doi: 10.3389/fnhum.2013.00623. eCollection 2013.
8
Methods to detect, characterize, and remove motion artifact in resting state fMRI.
Neuroimage. 2014 Jan 1;84:320-41. doi: 10.1016/j.neuroimage.2013.08.048. Epub 2013 Aug 29.
9
10
Dynamic functional connectivity: promise, issues, and interpretations.
Neuroimage. 2013 Oct 15;80:360-78. doi: 10.1016/j.neuroimage.2013.05.079. Epub 2013 May 24.

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