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. 2016 May 13;374(2067):20150190.
doi: 10.1098/rsta.2015.0190.

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

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

Guo-Rong Wu et al. Philos Trans A Math Phys Eng Sci. .

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.

Keywords: cardiac fluctuations; functional magnetic resonance imaging; haemodynamic response; point process; resting state.

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Figures

Figure 1.
Figure 1.
Spatial distribution of voxelwise adjusted R-squared values for different cardiac fluctuations in different TRs. First column: formula imageformula image. Second column: formula imageformula image. Third column: formula imageformula image. MP, motion parameter. (Online version in colour.)
Figure 2.
Figure 2.
Median maps of HRF parameters (first, fourth, sixth, seventh rows) and BOLD s.d./mean/CV (second, third, fifth rows) across subjects (pre-processed by DRCTN). (Online version in colour.)
Figure 3.
Figure 3.
Main effect on HRF parameters of four cardiac fluctuation correction models with different pre-processing procedures (repeated-measures ANOVA F-value, p<0.05, FWE correction). CTR, DCTRN; RCT, DRCTN; TRC, DTRCN. (Online version in colour.)
Figure 4.
Figure 4.
Correlation maps between HRV and HRF parameters (p<0.05, FWE correction). Top: TR=0.645 s. Middle and bottom: TR=2.5 s (SDNN, LF). The warm (cool) colour denotes positive (negative) T-value. (Online version in colour.)

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