Modeling the hemodynamic response to brain activation.

By Richard B. Buxton, Kâmil Uludag, David J. Dubowitz, Thomas T. Liu. NeuroImage, 2004

1,225 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/ae20e2f0bd1d52b52d9c75a087f5944c31cd99da

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In Cognitive Neuroscience

In Radiology, Nuclear Medicine and Imaging

Citations in the corpus

Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest (2008, background): “Increases in neuronal activity induce an increase in the local CBF, which exceeds the increase in oxygen consumption [Fox and Raichle, 1986; Hoge et al., 1999], resulting in lowered deoxyhemoglobin content and increased BOLD signals [Buxton et al., 2004].”
Comparing hemodynamic models with DCM (2007, neutral): “…0 = 25 s − 1 is the slope of the relation between the intravascular 3 Subsequent work by Mandeville et al. (1999) indicated that this approximation may not be perfect for transient BOLD responses, and Buxton et al. (2004) offered a more complex formulation of viscoelastic effects on blood outflow.”
The Global Signal in fMRI: Nuisance or Information? (2017, neutral): “A common choice is to compute the percent BOLD signal change from some baseline value, as the percent signal change has a meaningful connection with brain physiology (Buxton et al., 2004).”
Building a Science of Individual Differences from fMRI. (2016, background): “Factors such as vasodilatory signaling, blood vessel stiffness, neurovascular coupling delay, venous transit time and the time constant of autoregulatory feedback contribute to this variability [48,49]; these factors are known to be particularly affected by ageing and disease [50].”
An integrative model for neuronal activity-induced signal changes for gradient and spin echo functional imaging (2009, methodology): “The model is similar to other previously proposed models (e.g. Buxton et al., 2004; He and Yablonskiy, 2007; Hoogenraad et al., 2001; Lu et al., 2004; van Zijl et al., 1998), but is more comprehensive as it is valid for magnetic field strengths from 1.5 T up to 16.4 T for both GRE and SE.”
Diffusion MRI at 25: Exploring brain tissue structure and function (2012, background): “…understood (Iadecola and Nedergaard, 2007; Magistretti and Pellerin, 1999) and the BOLD signal depends on several parameters, so its biophysical link with neuronal activation is not straightforward (Buxton et al., 1998, 2004; Malonek et al., 1997; Sirotin and Das, 2009; Van Zijl et al., 1998).”
Statistical analysis of fNIRS data: A comprehensive review (2014, neutral): “…(BOLD) response measured by functional magnetic resonance imaging (fMRI), which is a nonlinear function of oxygen level and cerebral blood flow (Buxton et al., 2004), a direct measurement of oxygen concentration in fNIRS can provide a potential way to unveil the mechanism of complicated…”
A NIRS-fMRI investigation of prefrontal cortex activity during a working memory task (2013, neutral): “The BOLD signal of fMRI has relatively accurate spatial information and is proportional to the hemodynamic changes that can be measured using NIRS (Buxton et al., 2004; Toronov et al., 2003).”
A visual analytics approach to understanding cycling behaviour (2012, neutral): “The set of all possible hypotheses for a given task, which we call S H , can be inﬁnite (Muggleton, 1995).”
Coordinate-based ALE meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty (2009, methodology): “Neuroimaging using fMRI and PET is based on hemodynamic changes initiated by vasodilatory mediators released by cortical and subcortical grey matter under increased computational and metabolic demand [Buxton et al., 2004; Fox and Raichle, 1986; Logothetis, 2003].”
Comparing Dynamic Causal Models using AIC, BIC and Free Energy (2012, methodology): “In DCM, neuronal activity gives rise to fMRI signals via an extended Balloon model (Buxton et al., 2004) and BOLD signal model (Stephan et al., 2007) for each region.”
Comparing Families of Dynamic Causal Models (2010, methodology): “In DCM, neuronal activity gives rise to fMRI activity by a dynamic process described by an extended Balloon model”
Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1 (2006, background): “To a degree, the difference in ratios can be accounted for by the nonlinear relationship between the BOLD signal and CBF, and by the BOLD ceiling (saturation) effec”
Electrophysiological Imaging of Brain Activity and Connectivity – Challenges and Opportunities (2011, background): “Such a linear HRF serves as an approximation for the cascading interplay between neuronal cellular activities and a complex of the metabolic demand, blood flow, and oxygen [73], [74], with influences from the astrocytes [75].”