dc.contributor.author | Sjuls, Guro Stensby | |
dc.contributor.author | Specht, Karsten | |
dc.date.accessioned | 2023-01-13T13:38:40Z | |
dc.date.available | 2023-01-13T13:38:40Z | |
dc.date.issued | 2022-12-13 | |
dc.description.abstract | Introduction: Replicability has become an increasing focus within the scientific communities with the ongoing
‘‘replication crisis.’’ One area that appears to struggle with unreliable results is resting-state functional magnetic
resonance imaging (rs-fMRI). Therefore, the current study aimed at improving the knowledge of endogenous
factors that contribute to inter-individual variability.
Methods: Arterial blood pressure (BP), body mass, hematocrit, and glycated hemoglobin were investigated as
potential sources of between-subject variability in rs-fMRI, in healthy individuals. Whether changes in restingstate networks (rs-networks) could be attributed to variability in the blood-oxygen-level-dependent (BOLD)-
signal, changes in neuronal activity, or both was of special interest. Within-subject parameters were estimated
by utilizing dynamic-causal modeling, as it allows to make inferences on the estimated hemodynamic
(BOLD-signal dynamics) and neuronal parameters (effective connectivity) separately.
Results: The results of the analyses imply that BP and body mass can cause between-subject and between-group
variability in the BOLD-signal and that all the included factors can affect the underlying connectivity.
Discussion: Given the results of the current and previous studies, rs-fMRI results appear to be susceptible to a range of
factors, which is likely to contribute to the low degree of replicability of these studies. Interestingly, the highest degree
of variability seems to appear within the much-studied default mode network and its connections to other networks. | en_US |
dc.identifier.citation | Sjuls, Specht. Variability in Resting-State Functional Magnetic Resonance Imaging: The Effect of Body Mass, Blood Pressure, Hematocrit, and Glycated Hemoglobin on Hemodynamic and Neuronal Parameters. Brain Connectivity. 2022;12(10):870-882 | en_US |
dc.identifier.cristinID | FRIDAID 2102057 | |
dc.identifier.doi | 10.1089/brain.2021.0125 | |
dc.identifier.issn | 2158-0014 | |
dc.identifier.issn | 2158-0022 | |
dc.identifier.uri | https://hdl.handle.net/10037/28217 | |
dc.language.iso | eng | en_US |
dc.publisher | Mary Ann Liebert, Inc. | en_US |
dc.relation.journal | Brain Connectivity | |
dc.rights.accessRights | openAccess | en_US |
dc.rights.holder | Copyright 2022 The Author(s) | en_US |
dc.rights.uri | https://creativecommons.org/licenses/by-nc/4.0 | en_US |
dc.rights | Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) | en_US |
dc.title | Variability in Resting-State Functional Magnetic Resonance Imaging: The Effect of Body Mass, Blood Pressure, Hematocrit, and Glycated Hemoglobin on Hemodynamic and Neuronal Parameters | en_US |
dc.type.version | publishedVersion | en_US |
dc.type | Journal article | en_US |
dc.type | Tidsskriftartikkel | en_US |
dc.type | Peer reviewed | en_US |