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Neural inhibition can explain negative BOLD responses: A mechanistic modelling and fMRI study
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 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, Center for Medical Image Science and Visualization (CMIV). Linköping University, Faculty of Medicine and Health Sciences.
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Medicine and Health Sciences.
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2017 (English)In: NeuroImage, ISSN 1053-8119, E-ISSN 1095-9572, Vol. 158, p. 219-231Article 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. Vol. 158, p. 219-231
Keywords [en]
fMRI; Neurovascular coupling; GABA; glutamate; Cerebral blood flow; Blood oxygen level dependent response; Hemodynamic response; Systems biology
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-141844DOI: 10.1016/j.neuroimage.2017.07.002ISI: 000411450600021PubMedID: 28687518Scopus ID: 2-s2.0-85022231713OAI: oai:DiVA.org:liu-141844DiVA, id: diva2:1147966
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: 2018-01-25Bibliographically approved
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. p. 68
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: 2018-01-25Bibliographically approved

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Witt, Suzanne Tyson

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Sten, SebastianLundengård, KarinWitt, Suzanne TysonCedersund, GunnarElinder, FredrikEngström, Maria
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