Spatiotemporal BOLD dynamics from a poroelastic hemodynamic model.

A quantitative theory is developed for the relationship between stimulus and the resulting blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) signal, including both spatial and temporal dynamics for the first time. The brain tissue is modeled as a porous elastic medium, whose interconnected pores represent the vasculature. The model explicitly incorporates conservation of blood mass, interconversion of oxygenated and deoxygenated hemoglobin, force balance within the blood and of blood pressure with vessel walls, and blood flow modulation due to neuronal activity. In appropriate limits it is shown to reproduce prior Balloon models of hemodynamic response, which do not include spatial variations. The regime of validity of such models is thereby clarified by elucidating their assumptions, and when these break down, for example when voxel sizes become small.

[1]  N. Logothetis,et al.  Negative functional MRI response correlates with decreases in neuronal activity in monkey visual area V1 , 2006, Nature Neuroscience.

[2]  J. Bear Dynamics of Fluids in Porous Media , 1975 .

[3]  H. Duvernoy,et al.  Cortical blood vessels of the human brain , 1981, Brain Research Bulletin.

[4]  R. Higdon Absorbing boundary conditions for difference approximations to the multi-dimensional wave equation , 1986 .

[5]  Karl J. Friston Regulation of rCBF by diffusible signals: An analysis of constraints on diffusion and elimination , 1995 .

[6]  G. Carmignoto,et al.  Astrocyte control of synaptic transmission and neurovascular coupling. , 2006, Physiological reviews.

[7]  H. H. Lipowsky,et al.  Microvascular Rheology and Hemodynamics , 2005, Microcirculation.

[8]  N. Logothetis,et al.  Neurophysiological investigation of the basis of the fMRI signal , 2001, Nature.

[9]  Karl J. Friston,et al.  Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics , 2000, NeuroImage.

[10]  Thomas E. Nichols,et al.  Non-white noise in fMRI: Does modelling have an impact? , 2006, NeuroImage.

[11]  J. C. Jimenez,et al.  Nonlinear local electrovascular coupling. I: A theoretical model , 2006, Human brain mapping.

[12]  J. Mayhew,et al.  A Model of the Dynamic Relationship between Blood Flow and Volume Changes during Brain Activation , 2004, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[13]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[14]  Peter A. Robinson,et al.  BOLD responses to stimuli: Dependence on frequency, stimulus form, amplitude, and repetition rate , 2006, NeuroImage.

[15]  A. Grinvald,et al.  Compartment-Resolved Imaging of Activity-Dependent Dynamics of Cortical Blood Volume and Oximetry , 2005, The Journal of Neuroscience.

[16]  G L Shulman,et al.  INAUGURAL ARTICLE by a Recently Elected Academy Member:A default mode of brain function , 2001 .

[17]  Karl J. Friston,et al.  Comparing hemodynamic models with DCM , 2007, NeuroImage.

[18]  R. Buxton,et al.  Dynamics of blood flow and oxygenation changes during brain activation: The balloon model , 1998, Magnetic resonance in medicine.

[19]  Karl J. Friston,et al.  Dynamic causal modelling , 2003, NeuroImage.

[20]  W. Gibson,et al.  Origins of blood volume change due to glutamatergic synaptic activity at astrocytes abutting on arteriolar smooth muscle cells. , 2008, Journal of theoretical biology.

[21]  R. Buxton,et al.  A Model for the Coupling between Cerebral Blood Flow and Oxygen Metabolism during Neural Stimulation , 1997, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[22]  D. Nair About being BOLD , 2005, Brain Research Reviews.

[23]  Emery N. Brown,et al.  Nonstationary noise estimation in functional MRI , 2005, NeuroImage.

[24]  N. Harel,et al.  Blood capillary distribution correlates with hemodynamic-based functional imaging in cerebral cortex. , 2002, Cerebral cortex.

[25]  M. Raichle,et al.  The Effects of Changes in PaCO2 Cerebral Blood Volume, Blood Flow, and Vascular Mean Transit Time , 1974, Stroke.

[26]  B. Rosen,et al.  Evidence of a Cerebrovascular Postarteriole Windkessel with Delayed Compliance , 1999, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[27]  Thomas T. Liu,et al.  Discrepancies between BOLD and flow dynamics in primary and supplementary motor areas: application of the balloon model to the interpretation of BOLD transients , 2004, NeuroImage.

[28]  D. Griffiths Introduction to Electrodynamics , 2017 .

[29]  Stephen A. Billings,et al.  A three-compartment model of the hemodynamic response and oxygen delivery to brain , 2005, NeuroImage.

[30]  M. Fox,et al.  Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging , 2007, Nature Reviews Neuroscience.

[31]  M. C. Angulo,et al.  Neuron-to-astrocyte signaling is central to the dynamic control of brain microcirculation , 2003, Nature Neuroscience.

[32]  N. Logothetis,et al.  Spatial Specificity of BOLD versus Cerebral Blood Volume fMRI for Mapping Cortical Organization , 2007, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[33]  B. Conrad,et al.  Dynamics of regional cerebral blood flow for various visual stimuli , 2004, Experimental Brain Research.

[34]  Y. Fung,et al.  Biomechanics: Mechanical Properties of Living Tissues , 1981 .

[35]  D. Acheson Elementary Fluid Dynamics , 1990 .