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Mechanistic modelling - a BOLD response to the fMRI information loss problem
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
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: urn:nbn:se:liu:diva-142870DOI: 10.3384/diss.diva-142870ISBN: 9789176854419 (print)OAI: oai:DiVA.org:liu-142870DiVA: diva2:1155527
Public defence
2017-11-30, Hugo Theorell, Campus US, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2017-11-08Bibliographically approved
List of papers
1. Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI
Open this publication in new window or tab >>Mechanistic Mathematical Modeling Tests Hypotheses of the Neurovascular Coupling in fMRI
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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
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
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:liu:diva-130437 (URN)10.1371/journal.pcbi.1004971 (DOI)000379349700045 ()27310017 (PubMedID)
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
2. Positive Allosteric Modulator of GABA Lowers BOLD Responses in the Cingulate Cortex
Open this publication in new window or tab >>Positive Allosteric Modulator of GABA Lowers BOLD Responses in the Cingulate Cortex
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2016 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 3Article in journal (Refereed) Published
Abstract [en]

Knowledge about the neural underpinnings of the negative blood oxygen level dependent (BOLD) responses in functional magnetic resonance imaging (fMRI) is still limited. We hypothesized that pharmacological GABAergic modulation attenuates BOLD responses, and that blood concentrations of a positive allosteric modulator of GABA correlate inversely with BOLD responses in the cingulate cortex. We investigated whether or not pure task-related negative BOLD responses were co-localized with pharmacologically modulated BOLD responses. Twenty healthy adults received either 5 mg diazepam or placebo in a double blind, randomized design. During fMRI the subjects performed a working memory task. Results showed that BOLD responses in the cingulate cortex were inversely correlated with diazepam blood concentrations; that is, the higher the blood diazepam concentration, the lower the BOLD response. This inverse correlation was most pronounced in the pregenual anterior cingulate cortex and the anterior mid-cingulate cortex. For subjects with diazepam plasma concentration > 0.1 mg/L we observed negative BOLD responses with respect to fixation baseline. There was minor overlap between cingulate regions with task-related negative BOLD responses and regions where the BOLD responses were inversely correlated with diazepam concentration. We interpret that the inverse correlation between the BOLD response and diazepam was caused by GABA-related neural inhibition. Thus, this study supports the hypothesis that GABA attenuates BOLD responses in fMRI. The minimal overlap between task-related negative BOLD responses and responses attenuated by diazepam suggests that these responses might be caused by different mechanisms.

Place, publisher, year, edition, pages
San Francisco, CA, United States: Public Library of Science, 2016
Keyword
quantitative magnetic resonance imaging; brain tissue modeling; myelin; edema; T-1 relaxation; T-2 relaxation; proton density
National Category
Neurosciences
Identifiers
urn:nbn:se:liu:diva-126192 (URN)10.1371/journal.pone.0148737 (DOI)000371434500011 ()26930498 (PubMedID)
Note

Funding agencies: Linkoping University; County Council of Ostergotland

Available from: 2016-03-18 Created: 2016-03-18 Last updated: 2017-11-08Bibliographically approved
3. Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study
Open this publication in new window or tab >>Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study
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2017 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 158, 219-231 p.Article in journal (Refereed) Published
Abstract [en]

Functional magnetic resonance imaging (fMRI) of hemodynamic changes captured in the blood oxygen level-dependent (BOLD) response contains information of brain activity. The BOLD response is the result of a complex neurovascular coupling and comes in at least two fundamentally different forms: a positive and a negative deflection. Because of the complexity of the signaling, mathematical modelling can provide vital help in the data analysis. For the positive BOLD response, there are plenty of mathematical models, both physiological and phenomenological. However, for the negative BOLD response, no physiologically based model exists. Here, we expand our previously developed physiological model with the most prominent mechanistic hypothesis for the negative BOLD response: the neural inhibition hypothesis. The model was trained and tested on experimental data containing both negative and positive BOLD responses from two studies: 1) a visual-motor task and 2) a workin-gmemory task in conjunction with administration of the tranquilizer diazepam. Our model was able to predict independent validation data not used for training and provides a mechanistic underpinning for previously observed effects of diazepam. The new model moves our understanding of the negative BOLD response from qualitative reasoning to a quantitative systems-biology level, which can be useful both in basic research and in clinical use.

Place, publisher, year, edition, pages
Elsevier, 2017
Keyword
fMRI; Neurovascular coupling; GABA; glutamate; Cerebral blood flow; Blood oxygen level dependent response; Hemodynamic response; Systems biology
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:liu:diva-141844 (URN)10.1016/j.neuroimage.2017.07.002 (DOI)000411450600021 ()28687518 (PubMedID)2-s2.0-85022231713 (Scopus ID)
Note

Funding Agencies|Swedish Research Council [20146249]; Knut and Alice Wallenbergs foundation, KAW [2013.0076]; Research council of Southeast Sweden [FORSS-481691]; Linkoping University local funds

Available from: 2017-10-09 Created: 2017-10-09 Last updated: 2017-11-08Bibliographically approved

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