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

Wu, Guo-Rong; Marinazzo, Daniele

doi:10.1098/rsta.2015.0190

Cited by 29 publications

(30 citation statements)

References 66 publications

(108 reference statements)

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“…To minimize any HRF delay effect, we used a blind‐deconvolution technique for BOLD‐fMRI signals to eliminate confounders, based on temporal precedence ( https://github.com/compneuro-da/rsHRF) (Wu et al, ). During the resting state, BOLD‐fMRI data were obtained by inspecting the discrete events that resulted in relatively large amplitude BOLD signal peaks, usually called spontaneous BOLD “events” (Liu & Duyn, ; Wu & Marinazzo, ). These events can then be used to retrieve the region‐specific HRF at rest.…”

Section: Methodsmentioning

confidence: 99%

Exploring the functional connectome in white matter

Biswal

Wang

et al. 2019

Human Brain Mapping

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A major challenge in neuroscience is understanding how brain function emerges from the connectome. Most current methods have focused on quantifying functional connectomes in gray‐matter (GM) signals obtained from functional magnetic resonance imaging (fMRI), while signals from white‐matter (WM) have generally been excluded as noise. In this study, we derived a functional connectome from WM resting‐state blood‐oxygen‐level‐dependent (BOLD)‐fMRI signals from a large cohort (n = 488). The WM functional connectome exhibited weak small‐world topology and nonrandom modularity. We also found a long‐term (i.e., over 10 months) topological reliability, with topological reproducibility within different brain parcellation strategies, spatial distance effect, global and cerebrospinal fluid signals regression or not. Furthermore, the small‐worldness was positively correlated with individuals' intelligence values (r = .17, pcorrected = .0009). The current findings offer initial evidence using WM connectome and present additional measures by which to uncover WM functional information in both healthy individuals and in cases of clinical disease.

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Section: Methodsmentioning

confidence: 99%

Exploring the functional connectome in white matter

Biswal

Wang

et al. 2019

Human Brain Mapping

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“…In order to establish the relationship between the hemodynamic response function (HRF) and scMRI, a method for estimating HRF offset and width in resting-state fMRI data (Wu, Liao, Stramaglia, Ding, et al, 2013; Wu & Marinazzo, 2016) for a given voxel, based on various spontaneous point process events, was fitted across all 361 ROIs and 17 network time series.…”

Section: Methodsmentioning

confidence: 99%

“…In order to establish the relationship between the hemodynamic response function (HRF) and scMRI, a method for estimating HRF offset and width in resting-state fMRI data (Wu, Liao, Stramaglia, Ding, et al, 2013;Wu & Marinazzo, 2016) Barch et al (2013). A brief description of each measure can be found in the Supporting Information related to this article.…”

Section: Methodsmentioning

confidence: 99%

Sustained versus instantaneous connectivity differentiates cognitive functions of processing speed and episodic memory

King

Anderson

2018

Human Brain Mapping

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Synchrony of brain activity over time describes the functional connectivity between brain regions but does not address the temporal component of this relationship. We propose a complementary method of analysis by introducing the width of cross-correlation curves between functional MRI (fMRI) time series as a metric of the relative duration of synchronous activity between brain regions, or "sustained connectivity". Using resting-state fMRI, cognitive, and demographics data from 1,003 subjects included in the Human Connectome Project, we find that sustained connectivity is a reproducible trait in individuals, heritable, more transient in females, and shows changes with age in early adulthood. Sustained connectivity in sensory brain regions is specifically associated with differences in processing speed across subjects, particularly in men. In contrast, traditional functional connectivity was correlated with a measure of episodic memory, but not with processing speed. Individual differences in hemodynamic response function (HRF) are closely approximated by sustained connectivity and width of the HRF is also correlated with processing speed across individuals, suggesting that variability in hemodynamic response may be influenced by transient versus sustained neural activity rather than simply differences in vascularity and signal transduction. Sustained connectivity may provide new opportunities to study brain dynamics in clinical populations.

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“…1 Most studies assume a standard whole-brain canonical HRF during analysis (typically made of 2 gamma functions), although previous works show HRF variability for different brain regions and across subjects. [2][3][4][5] The variability of non-neural components of HRF across the brain as well as across individuals 2,3 is problematic. Since only neural activity is of interest in most fMRI studies, interpretation of fMRI findings is often clouded because of the aforementioned non-neural sources of variability in fMRI.…”

Section: Introductionmentioning

confidence: 99%

Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity

Rangaprakash

Marinazzo

et al. 2018

Magnetic Resonance in Med

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

Abstract: One contribution of 16 to a theme issue 'Uncovering brain-heart information through advanced signal and image processing' . Subject Areas:statistics, computational biology

Cited by 29 publications

References 66 publications

Exploring the functional connectome in white matter

Exploring the functional connectome in white matter

Sustained versus instantaneous connectivity differentiates cognitive functions of processing speed and episodic memory

Hemodynamic response function (HRF) variability confounds resting‐state fMRI functional connectivity

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