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dc.contributor.authorBeresniewicz, Justyna
dc.date.accessioned2023-02-27T10:25:07Z
dc.date.available2023-02-27T10:25:07Z
dc.date.issued2023-03-10
dc.date.submitted2023-02-19T12:40:41.244Z
dc.identifiercontainer/c1/ba/c4/56/c1bac456-7cf7-44da-97d1-3d374e1a86b1
dc.identifier.isbn9788230864524
dc.identifier.isbn9788230854082
dc.identifier.urihttps://hdl.handle.net/11250/3054149
dc.description.abstractHjernen er organisert i ulike funksjonelle og strukturelle nettverk. Til tross for omfattende forskning, er fremdeles ikke funksjonen og dynamikken i slike nettverk godt forstått. En økt innsikt kan være avgjørende for å forstå symptomer, og mekanismene som kontrollerer disse, hos pasienter med psykiske lidelser som schizofreni. Avhandlingen omfatter tre studier som hver adresserer ulike delmål i forskningen. Den første studien undersøker endringer i strukturelle nettverk hos en gruppe pasienter med schizofreni. Studien viser på gruppenivå at det er dels utbredte strukturelle forskjeller i hvit substans hos pasienter med schizofreni som opplever hørselshallusinasjoner sammenlignet med pasienter som ikke opplever disse hallusinasjonen. For å undersøke mulig samsvarende funksjonelle endringer har det vært behov for først å utvikle en ny tilnærming for å måle forskjeller i dynamikken mellom hjernens nettverk i hvile (DMN) og i aktiv oppgaveløsing av krevende kognitive oppgaver (EMN) hos en gruppe friske frivillige deltakere. I korte trekk, ble tre ulike visuelle, kognitive oppgaver presentert for deltakerne gjennom et fMRI blokk design. Resultatene i studien viste en antikorrelasjon i tid i områder som er involvert i henholdsvis hvile (DMN) og aktiv tilstand (EMN). For å gjøre undersøkelser hos pasienter med psykiske lidelser mindre tidkrevende, beskrives i avhandlingen også en studie som undersøker om hvileområder i hjernen (DMN) som er aktivert nettopp som del av en fMRI blokk design studier overlapper med en tilleggsundersøkelse med femminutters kontinuerlig hvile («resting state»). Sammenligningen er også interessant fra et mer basalforskningsperspektiv fordi en rask endring mellom aktiv tilstand og hvile kanskje bedre reflekterer en realistisk hviletilstand enn den kontinuerlige undersøkelsen som i dag representerer «gullstandarden» i denne type forskning. Resultatene fra studien viste stor grad av overlapp mellom aktiverte områder og at den foreslåtte tilnærmingen dermed kan ha et stort potensial i videre undersøkelser. I sum beskriver forskningen i avhandlingen muligheter for å undersøke strukturelle og funksjonelle nettverk hos pasienter med psykiske lidelser. Avhandlingen viser første resultater hos pasienter med schizofreni som strukturelle forskjeller i hvit substans mellom pasientgrupper avhengig om de opplever hørselshallusinasjoner eller ikke. Slike undersøkelser kan og bør komplementeres med undersøkelser av funksjonelle nettverk slik som foreslått i de andre studiene i avhandlingen, og i sum bidra til et godt rammeverk for videre undersøkelser hos pasienter.en_US
dc.description.abstractThe human brain is organized in various networks both functionally and structurally. However, despite the extensive research on brain connectivity, which was made possible due to the development of in vivo brain imaging techniques, the neuroscientific field is still far from fully comprehending networks function and dynamics. Detailed knowledge about the relationship between various brain networks is essential for understanding the function of the healthy brain. However, many studies on mental disorders such as schizophrenia suggest that it might be caused by abnormal brain network functioning and structural aberrations. Therefore, the knowledge of the brain network's dynamics and structure might be critical for revealing the underpinnings of mental disorders such as schizophrenia. The presented thesis had three main goals, resulting in three structural and functional imaging studies. Firstly, the brain's structural connectivity affected by schizophrenia has been investigated to determine the nature and extent of its changes. Hence, Diffusion Tensor Imaging (DTI) and tract-based spatial statistics (TBSS) were employed to explore white matter differences between subtypes of schizophrenia patients compared to healthy controls. This study revealed widespread FA-value reduction in the hallucinating schizophrenia subjects' white matter compared to non-hallucinating ones. Since widespread aberrations of the white matter should affect the function of the large-scale brain networks, the second goal was to explore the two main functional brain networks, Default Mode Network (DMN) and Extrinsic Mode Network (EMN). This is because dysfunction of DMN and EMN networks has been previously suggested to be significant for the generation of symptoms of schizophrenia disorder, such as Auditory Verbal Hallucinations (AVH). Since the concept of EMN is relatively new and not yet deeply explored, and additionally protocol used in that study has not been previously utilized to study EMN and DMN, it was first necessary to test the design in a group of healthy participants. This study used the novel protocol based on the classic block design fMRI experiment with three different visual tasks: mental rotation, working memory, and mental arithmetic. The results of study II proved the existence of the EMN that is anti-correlated with the DMN and is domain-general. Lastly, the neuroimaging studies of the participants suffering from mental disorders such as schizophrenia require relatively short and effective examination protocols. Therefore, the last project investigated both similarities and differences in DMN activity between two experimental designs: block design and resign state. A classic block design experiment would be a good candidate for the investigation reflecting the fluctuating activity of the brain during typical daily activity. The results of Study III showed that the activity of the DMN was generally similar in the two experiments, though with some discrepancies. These differences were in the DMN architecture itself and concerning the relations of the DMN with other brain networks. These findings, in combination with the results of study number two suggest that the block design experiment could be the most effective for studying the function of the brain in schizophrenia. The studies incorporated in that thesis add to the current findings on the white matter alterations in schizophrenia disorder and contribute to a better understanding of the function and dynamics of the large-scale brain networks: EMN and DMN. Last but not least, the performed studies give a good background for future clinical studies on schizophrenia disorder.en_US
dc.language.isoengen_US
dc.publisherThe University of Bergenen_US
dc.relation.haspartPaper I: Beresniewicz, J., Craven, A. R., Hugdahl, K., Løberg, E.-M., Kroken, R. A., Johnsen, E., & Grüner, R. (2021). White matter microstructural differences between hallucinating and non-hallucinating schizophrenia spectrum patients. Diagnostics, 11(1), 139. The article is available at: <a href=" https://hdl.handle.net/11250/2762604" target="blank">https://hdl.handle.net/11250/2762604</a>en_US
dc.relation.haspartPaper II: Riemer, F., Grüner, R., Beresniewicz, J., Kazimierczak, K., Ersland, L., & Hugdahl, K. (2020). Dynamic switching between intrinsic and extrinsic mode networks as demands change from passive to active processing. Scientific Reports, 10, 21463. The article is available at: <a href=" https://hdl.handle.net/11250/2753299" target="blank">https://hdl.handle.net/11250/2753299</a>en_US
dc.relation.haspartPaper III: Beresniewicz J. , Riemer F., Kazimierczak K., Ersland L., Hugdahl K., Grüner R. Similarities and differences between intermittent and continuous resting-state fMRI. The article is not available in BORA.en_US
dc.rightsIn copyright
dc.rights.urihttp://rightsstatements.org/page/InC/1.0/
dc.titleStructural and functional largescale brain network dynamics: Examples from mental disordersen_US
dc.typeDoctoral thesisen_US
dc.date.updated2023-02-19T12:40:41.244Z
dc.rights.holderCopyright the Author. All rights reserveden_US
dc.description.degreeDoktorgradsavhandling
fs.unitcode17-32-0


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