Abstract
Functional magnetic resonance imaging (fMRI) measures brain activity by detecting the blood-oxygen-level dependent (BOLD) response to neural activity. The BOLD response depends on the neurovascular coupling, which connects cerebral blood flow, cerebral blood volume, and deoxyhemoglobin level to neuronal activity. The exact mechanisms behind this neurovascular coupling are not yet fully investigated. There are at least three different ways in which these mechanisms are being discussed. Firstly, mathematical models involving the so-called Balloon model describes the relation between oxygen metabolism, cerebral blood volume, and cerebral blood flow. However, the Balloon model does not describe cellular and biochemical mechanisms. Secondly, the metabolic feedback hypothesis, which is based on experimental findings on metabolism associated with brain activation, and thirdly, the neurotransmitter feed-forward hypothesis which describes intracellular pathways leading to vasoactive substance release. Both the metabolic feedback and the neurotransmitter feed-forward hypotheses have been extensively studied, but only experimentally. These two hypotheses have never been implemented as mathematical models. Here we investigate these two hypotheses by mechanistic mathematical modeling using a systems biology approach; these methods have been used in biological research for many years but never been applied to the BOLD response in fMRI. In the current work, model structures describing the metabolic feedback and the neurotransmitter feed-forward hypotheses were applied to measured BOLD responses in the visual cortex of 12 healthy volunteers. Evaluating each hypothesis separately shows that neither hypothesis alone can describe the data in a biologically plausible way. However, by adding metabolism to the neurotransmitter feed-forward model structure, we obtained a new model structure which is able to fit the estimation data and successfully predict new, independent validation data. These results open the door to a new type of fMRI analysis that more accurately reflects the true neuronal activity.
Highlights
Functional magnetic resonance imaging measures brain activity by detecting associated changes in blood oxygenation through the blood-oxygen-level dependent (BOLD) response
The initial dip is hypothesized to reflect an increased cerebral metabolic rate of oxygen (CMRO2) that is followed by an increase of dHb content in the blood. (ii) At 6–8 s after the stimulus, the BOLD response peaks as a result of increased cerebral blood volume (CBV) and/ or increased cerebral blood flow (CBF). (iii) After the peak, the BOLD response decays and shows a post-peak undershoot before returning to baseline
We have presented mathematical modeling of the mechanisms underlying the BOLD response in Functional magnetic resonance imaging (fMRI), based on the metabolic feedback and the neurotransmitter feed-forward hypotheses, extensively discussed in the literature [15][16][29]
Summary
Functional magnetic resonance imaging (fMRI) measures brain activity by detecting associated changes in blood oxygenation through the blood-oxygen-level dependent (BOLD) response. The BOLD response reflects neuronal activity through the neurovascular coupling [2], the mechanisms causing the response are still not fully understood. We investigate these mechanisms by mathematical modeling using a systems biology approach. (iii) After the peak, the BOLD response decays and shows a post-peak undershoot before returning to baseline. The mechanisms controlling these processes (i-iii) remain unresolved, and there are at least three different approaches to understand these mechanisms
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