Learning to self-regulate the balance of stress-related large-scale brain networks: Effects on brain activation during tasks of higher cognitive functions & vigilance

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dc.contributor.advisorKrause, Florian
dc.contributor.advisorKohn, Nils
dc.contributor.authorYoldas, Rengin
dc.date.issued2022-08-26
dc.description.abstractThe dynamic activation balance in large-scale brain networks such as the executive control network (ECN) and the salience network (SN), in response to stress seem to be maladapted in stress-related psychopathologies. This led to the idea to train individuals in voluntary neurofeedback-based self-regulation of the activation balance in the SN and ECN. This approach could teach them a skill that can be used to influence those networks’ dynamic activation shifts during and after stress. Using neurofeedback training with real-time functional Magnetic Resonance Imaging (rtfMRI), the current study implemented a paradigm teaching participants to voluntarily self-regulate the activation balance of the SN and ECN. Neural activation patterns during cognitive task performance after self-regulation periods were analysed, in order to assess if the effects of the self-regulation influence not only neural activation during the regulation but also afterwards during performance in various cognitive tasks. The involvement of the ECN in higher-order executive cognitive functions lead to the hypothesis that previous regulation to ECN would enhance task-related neural activation during a working memory task (n-back). The same effect was hypothesized for regulation to SN with respect to task-related neural activation during the oddball task, due to the increases in regions associated with the SN during the highly vigilant state in the initial response-phase to stress. The results of the random-effects analysis showed that participants were able to self-regulate the activation balance towards especially SN, without receiving any feedback. Further activation patterns during the tasks resembled activation patterns that were found in previous fMRI studies of the oddball and n-back task. However, no results supporting a modulation effect on neural activation during the tasks was observable for either task. Assuming that the size of the desired effect is smaller than expected, a follow-up fixed-effects analysis was performed. The results for this analysis, indicated amongst others 1) that prior regulation towards ECN as well as SN resulted in higher task-related activation patterns in comparison to prior resting phases, 2) that the regulation towards ECN resulted in more task-related activation during the n-back task and 3) that the regulation towards SN resulted in more task-related activation during the oddball task. Although, the results of the second analyses provided more support of the hypotheses they are only valid for the current sample. Nevertheless, they provide evidence that prior self-regulation of activation balance in stress-related brain networks affects cognitive performance. These findings support the potential of neurofeedback training as a tool to build resilience as well as targeting the maladapted activation balance of large-scale brain networks in stress-related psychopathologies.
dc.identifier.urihttps://theses.ubn.ru.nl/handle/123456789/14757
dc.language.isoen
dc.thesis.facultyFaculteit der Sociale Wetenschappen
dc.thesis.specialisationspecialisations::Faculteit der Sociale Wetenschappen::Researchmaster Cognitive Neuroscience::Researchmaster Cognitive Neuroscience
dc.thesis.studyprogrammestudyprogrammes::Faculteit der Sociale Wetenschappen::Researchmaster Cognitive Neuroscience
dc.thesis.typeResearchmaster
dc.titleLearning to self-regulate the balance of stress-related large-scale brain networks: Effects on brain activation during tasks of higher cognitive functions & vigilance
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