Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI

By Rasmus M. Birn, J. B. Diamond, Monica A. Smith, Peter A. Bandettini. NeuroImage, 2006

1,425 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/750158e6f2b1ed750a3e56596d9572f6679d99f6

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Citations in the corpus

Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging (2007, background): “and physiological fluctuations, such as cardiac or respiratory activity, account for a significant fraction of spontaneous BOLD variance in human dat”
The Restless Brain (2011, positive): “Although some worried that this ﬁnding might be of cardiac or respiratory origin (Birn et al., 2006; Chang et al., 2009; Wise et al., 2004), it has become clear that this activity, now uniquely seen with fMRI BOLD imaging, is indeed of fundamental importance for brain function as neurophysiologists…”
The Oscillating Brain: Complex and Reliable (2009, background): “Finally, an increasing number of studies have drawn attention to the potential artifactual contributions of cardiac and respiratory-related processes to LFO amplitude measures (Bianciardi et al., 2009; Birn et al., 2006; Chang et al., 2009; van Buuren et al., 2009; Yan et al., 2009).”
Spatiotemporal dynamics of low frequency BOLD fluctuations in rats and humans (2010, neutral): “However, it is possible that physiological noise may alter the spatial spread of the pattern, as suggested by the reduction in spatial extent of correlation caused by regression of respiratory contribution (Birn et al., 2006).”
Awake reactivation of emotional memory traces through hippocampal-neocortical interactions (2016, neutral): “heart rate frequency, heart rate variability, (raw) abdominal circumference, respiratory frequency, respiratory amplitude, and respiration volume per unit time (RVT; Birn et al., 2006), yielding a total of 26 RETROICOR regressors.”
Global Signal Regression Strengthens Association between Resting-State Functional Connectivity and Behavior (2019, neutral): “The global signal is associated with head motion, respiration and cardiac rhythms (Birn et al., 2006; Power et al., 2014; 2017; Liu et al., 2017).”
The resting brain: unconstrained yet reliable. (2009, background): “…and the validity of negative correlations (Skudlarski et al. 2008), others studies suggest global signal correction as a reasonable alternative to direct measurement and subsequent removal of physiological cardiac and respiratory signals (Fox et al. 2005; Birn et al. 2006; Hampson et al. 2006).”
Mind wandering and attention during focused meditation: A fine-grained temporal analysis of fluctuating cognitive states (2012, neutral): “This study also provides a method in which first person subjective information can be used in fMRI paradigms to reveal a finely detailed picture of cognitive states as they fluctuate in real time.”
Sources and implications of whole-brain fMRI signals in humans (2016, methodology): “…those studies have linked breathing patterns at rest to fMRI signal changes across much of the brain, with Wise and colleagues reporting modulation in gray and white matter (Wise et al., 2004) and more recent studies emphasizing gray matter changes (Birn et al., 2006, 2008; Chang and Glover, 2009).”
Clinical applications of the functional connectome (2013, neutral): “For example, patterns of functional connectivity derived from respiratory signals have been shown to resemble those typically observed in the default network (Birn et al., 2006, 2008a).”
A Brain-Wide Study of Age-Related Changes in Functional Connectivity. (2015, background): “The global signal is assumed to reflect a combination of resting-state fluctuations, physiological noise (e.g., respiratory and cardiac noise), and other noise signals (Birn et al. 2006).”
Methods for cleaning the BOLD fMRI signal (2016, neutral): “Although this effect can be clearly observed in response to a hypercapnic or breath-holding challenge (Bright et al., 2009; Bulte et al., 2012; Kastrup et al., 1998, 1999a, 1999b; Li et al., 1999), it also naturally occurs during normal breathing where subtle variations in the depth and rate of brea”
A component based noise correction method (CompCor) for BOLD and perfusion based fMRI (2007, methodology): “A recent adaptation for BOLD-based imaging employs additional regressors describing variations in respiratory volume (Birn et al., 2006).”
The respiration response function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration (2008, methodology): “…the fluctuations in breathing during rest generally occur at similar frequencies (∼0.03 Hz) and in similar brain regions as those implicated in resting-state default-mode network activity (Birn et al., 2006; Modarreszadeh and Bruce, 1994; Van den Aardweg and Karemaker, 2002; Wise et al., 2004).”
Exploring the brain network: a review on resting-state fMRI functional connectivity. (2010, methodology): “cardiac oscillations (Birn et al., 2006; Birn et al., 2008; Chang et al., 2009; Shmueli et al., 2007; Wise et al., 2004) or whether these correlations originate from co-activation in the underlying spontaneous neuronal activation patterns of these regions, measured through a hemodynamic response fun”