liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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.ORCID iD: 0000-0001-9386-0568
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.
Show others and affiliations
2016 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 12, no 6, article id e1004971Article in journal (Refereed) Published
Resource type
Text
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, article id 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, id: 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: 2020-08-14
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)
Opponent
Supervisors
Available from: 2017-11-08 Created: 2017-11-08 Last updated: 2024-01-10Bibliographically approved
2. Mathematical modeling of neurovascular coupling
Open this publication in new window or tab >>Mathematical modeling of neurovascular coupling
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The brain is critically dependent on the continuous supply of oxygen and glucose, which is carried and delivered by blood. When a brain region is activated, metabolism of these substrates increases rapidly, but is quickly offset by a substantially higher increase in blood flow to that region, resulting in a brief oversupply of these substrates. This phenomenon is referred to as functional hyperemia, and forms the foundation of functional neuroimaging techniques such as functional Magnetic Resonance Imaging (fMRI), which captures a Blood Oxygen Level-Dependent (BOLD) signal. fMRI exploits these BOLD signals to infer brain activity, an approach that has revolutionized the research of brain function over the last 30 years. Due to the indirect nature of this measure, a deeper understanding of the connection between brain activity and hemodynamic changes — a neurovascular coupling (NVC) — is essential in order to fully interpret such functional imaging data. NVC connects the synaptic activity of neurons with local changes in cerebral blood flow, cerebral blood volume, and cerebral metabolism of oxygen, through a complex signaling network, consisting of multiple different brain cells which release a myriad of distinct vasoactive messengers with specific vascular targets. To aid with this complexity, mathematical modeling can provide vital help using methods and tools from the field of Systems Biology. Previous models of the NVC exist, conventionally describing quasi-phenomenological steps translating neuronal activity into hemodynamic changes. However, no mechanistic mathematical model that describe the known intracellular mechanisms or hypotheses underlying the NVC, and which can account for a wide variety of NVC related measurements, currently exists. Therefore, in this thesis, we apply a Systems Biology approach to develop such intracellular mechanisms based models using in vivo experimental data consisting of different NVC related measures in rodents, primates, and humans.

Paper I investigates two widely discussed hypotheses describing the NVC: the metabolic feedback hypothesis, and the vasoactive feed-forward hypothesis. We illustrate through multiple model rejections that only a model describing a combination of the two hypotheses can capture the qualitative features of the BOLD signal, as measured in humans. This combined model can describe data used for training, as well as predict independent validation data not previously seen by the model before.

Paper II extends this model to describe the negative BOLD response, where the blood oxygenation drops below basal levels, which is commonly observed in clinical and cognitive studies. The model explains the negative BOLD response as the result of neuronal inhibition, describing and adequately predicting experimental data from two different experiments.

In Paper III, we develop a first model including the cell-specific contributions of GABAergic interneurons and pyramidal neurons to functional hyperemia, using data of optogenetic and sensory stimuli in rodents for both awake and anesthesia conditions. The model captures the effect of the anesthetic as purely acting on the neuronal level if a Michaelis-Menten expression is included, and it also correctly predicts data from experiments with different pharmacological inhibitors.

Finally, in Paper IV, we extend the model in Paper III to describe and predict a majority of the relevant hemodynamic NVC measures using data from rodents, primates, and humans. The model suggests an explanation for observed bi-modal behaviors, and can be used to generate new insights regarding the underpinnings of other complicated observed behaviors. This model constitutes the most complete mechanistic model of the NVC to date.

This new model-based understanding opens the door for a more integrative approach to the analysis of neuroimaging data, with potential applications in both basic science and in the clinic.

Abstract [sv]

Hjärnan kräver, för att bevara sin normala funktion, en kontinuerlig tillströmning av metaboliter så som syre och glukos, som bärs och levereras av blodomloppet. När ett hjärnområde aktiveras ökar förbrukningen av dessa metaboliter kvickt. Detta kompenseras snabbt för igenom att blodtillförseln till hjärnområdet ökar, vilket temporärt ökar syresättningen av blodet i det aktiverade hjärnområdet under flera sekunder, långt efter att aktiviteten avtagit. Detta fenomen utgör grunden för flera av de icke-invasiva tekniker som idag används för att kartlägga hjärnans funktion i både människor och djur. Ett exempel är funktionell magnetresonanstomografi (fMRI) som mäter lokala förändringar av syrehalten i hjärnan och använder detta som en markör för att lokalisera aktiverade hjärnområden. Användningen av fMRI har revolutionerat hjärnforskningen sedan den introducerades för 30 år sedan, men då tekniken indirekt mäter hjärnaktivitet genom syrehalten i blodet är det viktigt att förstå den serie av händelser som sker mellan ökad hjärnaktivitet och ökad blodtillförsel till hjärnområdet: den neurovaskulära kopplingen.

Den neurovaskulära kopplingen förbinder den elektriska aktiviteten i nervceller med lokala förändringar i blodflöde, blodvolym och metabolism av syre, genom ett komplext biokemiskt system av olika typer av hjärnceller som utsöndrar substanser som påverkar blodkärlen. För att uppnå en ökad förståelse för hur sådana komplexa biologiska system fungerar kan man använda sig av matematisk modellering och skapa en datormodell över systemet, som är en huvudgren inom forskningsområdet Systembiologi. I denna avhandling har vi utvecklat en serie av matematiska modeller som beskriver och undersöker de intracellulära biokemiska signalvägar som den neurovaskulära kopplingen består av, genom att använda oss av olika typer av experimentell data insamlat i flera olika arter: möss, apor och människor.

Artikel 1 undersöker två av de vanligast förekommande hypoteserna som beskriver den neurovaskulära kopplingen. Vi visar med hjälp av modellerna att varje hypotes var för sig inte kan förklara fMRI-data insamlad i människa, men en kombination av de två hypoteserna kan. Denna kombinerade modell kan även korrekt förutsäga hur mätdata bör se ut för olika fall den aldrig tidigare fått se.

Artikel 2 utökar denna modell till att även beskriva scenarion där syrehalten i blodet minskar på grund av att aktiviteten i hjärnområdet hämmas. Denna hämning fyller en viktig funktion då den reglerar aktiviteten i olika hjärnområden så att andra hjärnområden inte hindras från att utföra olika uppgifter.

Artikel 3 beskriver en ny typ av matematisk modell för den neurovaskulära kopplingen, som kan särskilja olika nervcellers bidrag till regleringen av blodkärlen. Detta är möjligt igenom experimentell data som genererats med hjälp av optogenetik, där en ljuskänslig jonkanal uttrycks i specifika typer av nervceller i möss. Med hjälp av en ljuspuls kan man då aktivera olika typer av nervceller var för sig. Modellen kan även beskriva hur narkosmedel förändrar den funktionella kärlregleringen, samt förutsäga effekten av olika typer av biokemiska hämmare.

I Artikel 4 utökas denna modell till att kunna beskriva och förutsäga experimentell data från de allra flesta tillgängliga mätmetoder som används för att undersöka den neurovaskulära kopplingen. Denna modell bidrar med insikter om hur olika typer av observerade fenomen uppstår på olika nivåer av signaleringskedjan.

Denna nya modellbaserade förståelse kring den neurovaskulära kopplingen ger möjlighet till en djupare analys av experimentell data relaterad till hjärnans funktion, med både kliniska och forskningsrelaterade tillämpningar.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2020. p. 108
Series
Linköping University Medical Dissertations, ISSN 0345-0082 ; 1742
National Category
Neurosciences Physiology and Anatomy
Identifiers
urn:nbn:se:liu:diva-167806 (URN)10.3384/diss.diva-167806 (DOI)9789179298388 (ISBN)
Public defence
2020-09-11, Online through YouTube (contact malin.sundberg@liu.se) and Hasselquistsalen, Building 511, Campus US, 09:00 (English)
Opponent
Supervisors
Available from: 2020-08-19 Created: 2020-08-09 Last updated: 2025-02-10Bibliographically approved

Open Access in DiVA

fulltext(3310 kB)359 downloads
File information
File name FULLTEXT01.pdfFile size 3310 kBChecksum SHA-512
7a0362ab936589b2020896cb49dfc27429e68b4fcbc398c431a469d2d4b15badc1dc99fdb307202ceb2dbb5b095004fb2d5cc554804f4ccca4b638d370971e91
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Authority records

Lundengård, KarinCedersund, GunnarSten, SebastianElinder, FredrikEngström, Maria

Search in DiVA

By author/editor
Lundengård, KarinCedersund, GunnarSten, SebastianElinder, FredrikEngström, Maria
By organisation
Division of Radiological SciencesFaculty of Medicine and Health SciencesCenter for Medical Image Science and Visualization (CMIV)Department of Biomedical EngineeringFaculty of Science & EngineeringDivision of Cell BiologyDepartment of Medical and Health Sciences
In the same journal
PloS Computational Biology
Bioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
Total: 359 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 606 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf