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Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Department of Clinical and Experimental Medicine, Division of Cell Biology.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences.
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2016 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, no 6, e1004971Article in journal (Refereed) Published
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Abstract [en]

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.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2016. Vol. 12, no 6, e1004971
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-130437DOI: 10.1371/journal.pcbi.1004971ISI: 000379349700045PubMedID: 27310017OAI: oai:DiVA.org:liu-130437DiVA: diva2:951161
Note

Funding Agencies|Swedish Research council [2014-6249]; Knut and Alice Wallenbergs foundation, KAW [2013.0076]; Research council of Southeast Sweden [FORSS-481691]; Linkoping University

Available from: 2016-08-06 Created: 2016-08-05 Last updated: 2017-11-08
In thesis
1. Mechanistic modelling - a BOLD response to the fMRI information loss problem
Open this publication in new window or tab >>Mechanistic modelling - a BOLD response to the fMRI information loss problem
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Functional Magnetic Resonance Imaging (fMRI) is a common technique for imaging brain activity in humans. However, the fMRI signal stems from local changes in oxygen level rather than from neuronal excitation. The change in oxygen level is referred to as the Blood Oxygen Level Dependent (BOLD) response, and is connected to neuronal excitation and the BOLD response are connected by the neurovascular coupling. The neurons affect the oxygen metabolism, blood volume and blood flow, and this in turn controls the shape of the BOLD response. This interplay is complex, and therefore fMRI analysis often relies on models. However, none of the previously existing models are based on the intracellular mechanisms of the neurovascular coupling. Systems biology is a relatively new field where mechanistic models are used to integrate data from many different parts of a system in order to holistically analyze and predict system properties. This thesis presents a new framework for analysis of fMRI data, based on mechanistic modelling of the neurovascular coupling, using systems biology methods.

 Paper I presents the development of the first intracellular signaling model of the neurovascular coupling. Using models, a feed-forward and a feedback hypothesis are tested against each other. The resulting model can mechanistically explain both the initial dip, the main response and the post-peak undershoot of the BOLD response. It is also fitted to estimation data from the visual cortex and validated against variations in frequency and intensity of the stimulus. In Paper II, I present a framework for separating activity from noise by investigating the influence of the astrocytes on the blood vessels via release of vasoactive sub- stances, using observability analysis. This new method can recognize activity in both measured and simulated data, and separate differences in stimulus strength in simulated data. Paper III investigates the effects of the positive allosteric GABA modulator diazepam on working memory in healthy adults. Both positive and negative BOLD was measured during a working memory task, and activation in the cingulate cortex was negatively correlated to the plasma concentration of diazepam. In this area, the BOLD response had decreased below baseline in test subjects with >0.01 mg/L diazepam in the blood. Paper IV expands the model presented in Paper I with a GABA mechanism so that it can describe neuronal inhibition and the negative BOLD response. Sensitization of the GABA receptors by diazepam was added, which enabled the model to explain how changes to the BOLD response described in Paper III could occur without a change in the balance between the GABA and glutamate concentrations.

The framework presented herein may serve as the basis for a new method for identification of both brain activity and useful potential biomarkers for brain diseases and disorders, which will bring us a deeper understanding of the functioning of the human brain.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. 68 p.
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1591
National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-142870 (URN)10.3384/diss.diva-142870 (DOI)9789176854419 (ISBN)
Public defence
2017-11-30, Hugo Theorell, Campus US, Linköping, 13:15 (English)
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Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2017-11-08Bibliographically approved

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Lundengård, KarinCedersund, GunnarSten, SebastianElinder, FredrikEngström, Maria

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