Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics.

By Karl J. Friston, Andrea Mechelli, Robert Turner, Cathy J. Price. NeuroImage, 2000

1,185 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging

View Paper: https://www.semanticscholar.org/paper/b9824126cf637ae2c205a509f3c3a12dac52800e

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Citations in the corpus

Modeling the Impact of Lesions in the Human Brain (2009, methodology): “Simulated BOLD signals were computed by using a nonlinear hemodynamic model as previously described [8,10,26].”
Dynamic causal modelling (2003, methodology): “Four of these are of secondary importance and correspond to the state variables of the hemodynamic model presented in Friston et al. (2000).”
The Statistical Analysis of fMRI Data. (2008, methodology): “We differentiate between nonlinear physiological-based models, such as the Balloon model (Buxton, Wong and Frank, 1998; Friston et al., 2000; Riera et al., 2004), which describes the dynamics of cerebral blood volume and deoxygenation and their effects on the resulting BOLD signal, and models that…”
Optimization of experimental design in fMRI: a general framework using a genetic algorithm (2003, methodology): “The prewhitening approach yields the most efficient estimator of ␤ with colored noise, but leads to biased estimates of ␴ 2 if the estimate of the noise autocorrelation is inaccurate (Friston et al., 2000a).”
Understanding DCM: Ten simple rules for the clinician (2013, positive): “This results in a proportional increase in flow into the region with concomitant changes in blood volume and deoxyhaemoglobin content, causing the observed change in BOLD response (Buxton et al., 1998; Friston et al., 2000).”
Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering (2011, methodology): “The hemodynamic model 100 (Friston et al., 2000) links neuronal activity to flow and subsumes the balloon-windkessel model (Buxton et al., 1998; Mandeville et al., 1999), linking flow to observed fMRI signals.”
Population dynamics: Variance and the sigmoid activation function (2008, methodology): “The kernels were computed as described in the appendix of Friston et al. (2000).”
Bayesian Model Selection for Group Studies (2009, neutral): “This is also known as the Laplace approximation, a full treatment of which can be found in Friston et al. (2007). For any approximation to the conditional density, the free-energy bound on the log-evidence can be re-written as a mixture of accuracy and complexity:”
Constrained linear basis sets for HRF modelling using Variational Bayes (2004, methodology): “In Friston et al. (2000), they derive Volterra kernels from the balloon model (Buxton et al., 1998) and fit them to empirically found Volterra kernels from the frequentist inferred GLM of Friston et al. (1998b).”
The Virtual Brain: a simulator of primate brain network dynamics (2013, methodology): “The BOLD monitor is based on Buxton and Frank (1997) and Friston et al. (2000).”
A guide to group effective connectivity analysis, part 1: First level analysis with DCM for fMRI (2019, background): “Empirical estimates have shown κ to have a half-life of around 1 s (Friston et al., 2000), placing it in the correct range to be mediated by nitric oxide (NO).”
Statistical parametric mapping (2013, methodology): “Hemodynamics elicited by an impulse of neuronal activity as predicted by a dynamical biophysical model (see Friston et al 2000a for details ).”
Nonlinear Dynamic Causal Models for fMRI (2008, positive): “…regulation, τ is the mean transit time of venous blood, α is the resistance of the venous balloon, and E 0 is the resting oxygen extraction fraction (see Friston et al., 2000; Stephan et al., 2007a for details): Changes in vasodilatory signalling s: ds dt ¼ x−κs−γ f −1 ð Þ ðA1Þ Changes in blood…”
Emerging concepts for the dynamical organization of resting-state activity in the brain (2010, positive): “To more closely align the dynamics of model 1 with actual neuroimaging data, the oscillations for each node were converted to a BolD signal using the Balloon– Windkessel haemodynamic model 47 .”