Nonlinear temporal dynamics of the cerebral blood flow response

Miller, Karla L.; Luh, Wen‐Ming; Liu, Thomas T.; Martı́nez, Antı́gona; Obata, Takayuki; Wong, Eric C.; Frank, Lawrence R.; Buxton, Richard B.

doi:10.1002/hbm.1020

Cited by 185 publications

(129 citation statements)

References 33 publications

(48 reference statements)

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“…5. The BOLD response typically exhibits a temporal nonlinearity such that an appropriately shifted and added response to a brief stimulus over-predicts the true response to an extended stimulus (Birn et al, 2001;Boynton et al, 1996;Friston et al, 1998;Glover, 1999;Miller et al, 2001;Robson et al, 1998;Vasquez and Noll, 1998). This temporal nonlinearity is most pronounced when the brief stimulus is less than about 4 s and the extended stimulus is longer than 6 s. Comparing short and long duration stimuli that are both longer than about 4 s, the temporal nonlinearity is reduced.…”

Section: Experimental Characterization Of the Hemodynamic Responsementioning

confidence: 99%

“…The two sources of nonlinearity can be distinguished experimentally by whether the nonlinearity is present in just the BOLD response or in both the BOLD and CBF responses. For example, Miller et al (2001) found that both visual and motor cortices exhibited a nonlinear BOLD response, but only the visual cortex showed a nonlinear CBF response.…”

Section: Transients Of the Bold Responsementioning

confidence: 99%

“…These two sources of nonlinearity interact in an interesting way (Miller et al, 2001). If the neural nonlinearity is strong, then the flow response to even a short duration stimulus is strong.…”

Section: Transients Of the Bold Responsementioning

confidence: 99%

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Modeling the hemodynamic response to brain activation

et al. 2004

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Neural activity in the brain is accompanied by changes in cerebral blood flow (CBF) and blood oxygenation that are detectable with functional magnetic resonance imaging (fMRI) techniques. In this paper, recent mathematical models of this hemodynamic response are reviewed and integrated. Models are described for: (1) the blood oxygenation level dependent (BOLD) signal as a function of changes in cerebral oxygen extraction fraction (E) and cerebral blood volume (CBV); (2) the balloon model, proposed to describe the transient dynamics of CBV and deoxyhemoglobin (Hb) and how they affect the BOLD signal; (3) neurovascular coupling, relating the responses in CBF and cerebral metabolic rate of oxygen (CMRO 2 ) to the neural activity response; and (4) a simple model for the temporal nonlinearity of the neural response itself. These models are integrated into a mathematical framework describing the steps linking a stimulus to the measured BOLD and CBF responses. Experimental results examining transient features of the BOLD response (post-stimulus undershoot and initial dip), nonlinearities of the hemodynamic response, and the role of the physiologic baseline state in altering the BOLD signal are discussed in the context of the proposed models. Quantitative modeling of the hemodynamic response, when combined with experimental data measuring both the BOLD and CBF responses, makes possible a more specific and quantitative assessment of brain physiology than is possible with standard BOLD imaging alone. This approach has the potential to enhance numerous studies of brain function in development, health, and disease. D

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Section: Experimental Characterization Of the Hemodynamic Responsementioning

confidence: 99%

Section: Transients Of the Bold Responsementioning

confidence: 99%

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Modeling the hemodynamic response to brain activation

et al. 2004

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“…A large increase in CBF is not accompanied by a proportionally large increase in BOLD signal change due to the washing out of all the deoxyhemoglobin in the venous vasculature. 13,14 This mismatch is a matter of concern, as motor execution is a fundamental paradigm for many BOLD fMRI studies and is of clinical relevance in the prognosis of neurologic disorders such as Parkinson's disease. 15,16 To date, the matter remains open to debate.…”

Section: Introductionmentioning

confidence: 99%

BOLD Consistently Matches Electrophysiology in Human Sensorimotor Cortex at Increasing Movement Rates: A Combined 7T fMRI and ECoG Study on Neurovascular Coupling

Siero

Hermes

Hoogduin

et al. 2013

J Cereb Blood Flow Metab

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Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is widely used to measure human brain function and relies on the assumption that hemodynamic changes mirror the underlying neuronal activity. However, an often reported saturation of the BOLD response at high movement rates has led to the notion of a mismatch in neurovascular coupling. We combined BOLD fMRI at 7T and intracranial electrocorticography (ECoG) to assess the relationship between BOLD and neuronal population activity in human sensorimotor cortex using a motor task with increasing movement rates. Though linear models failed to predict BOLD responses from the task, the measured BOLD and ECoG responses from the same tissue were in good agreement. Electrocorticography explained almost 80% of the mismatch between measured-and model-predicted BOLD responses, indicating that in human sensorimotor cortex, a large portion of the BOLD nonlinearity with respect to behavior (movement rate) is well predicted by electrophysiology. The results further suggest that other reported examples of BOLD mismatch may be related to neuronal processes, rather than to neurovascular uncoupling.

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“…However, there are many reports of nonlinearity in haemodynamic responses in the literature (e.g. Ances et al, 2000;Huettel and McCarthy, 2000;Miller et al, 2001;Pfeuffer et al, 2003;Vazquez and Noll, 1998), and so it is unlikely that a simple linear convolution model (LCM) is general.…”

Section: Introductionmentioning

confidence: 99%

Long Duration Stimuli and Nonlinearities in the Neural–Haemodynamic Coupling

Martindale

Berwick

Martin

et al. 2005

J Cereb Blood Flow Metab

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Recent studies have shown that the haemodynamic responses to brief (o2 secs) stimuli can be well characterised as a linear convolution of neural activity with a suitable haemodynamic impulse response. In this paper, we show that the linear convolution model cannot predict measurements of blood flow responses to stimuli of longer duration (42 secs), regardless of the impulse response function chosen. Modifying the linear convolution scheme to a nonlinear convolution scheme was found to provide a good prediction of the observed data. Whereas several studies have found a nonlinear coupling between stimulus input and blood flow responses, the current modelling scheme uses neural activity as an input, and thus implies nonlinearity in the coupling between neural activity and blood flow responses. Neural activity was assessed by current source density analysis of depthresolved evoked field potentials, while blood flow responses were measured using laser Doppler flowmetry. All measurements were made in rat whisker barrel cortex after electrical stimulation of the whisker pad for 1 to 16 secs at 5 Hz and 1.2 mA (individual pulse width 0.3 ms).

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Nonlinear temporal dynamics of the cerebral blood flow response

Cited by 185 publications

References 33 publications

Modeling the hemodynamic response to brain activation

Modeling the hemodynamic response to brain activation

BOLD Consistently Matches Electrophysiology in Human Sensorimotor Cortex at Increasing Movement Rates: A Combined 7T fMRI and ECoG Study on Neurovascular Coupling

Long Duration Stimuli and Nonlinearities in the Neural–Haemodynamic Coupling

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