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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.ORCID iD: 0000-0001-9386-0568
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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: 2020-08-14Bibliographically 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)
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
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: 2020-09-01Bibliographically approved

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Witt, Suzanne Tyson

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