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dc.contributor.advisorManning, Patrick
dc.contributor.advisorDeRidder, Dirk
dc.contributor.advisorSutherland, Wayne
dc.contributor.authorRoss, Samantha Courtney
dc.date.available2018-10-12T03:08:30Z
dc.date.copyright2018
dc.identifier.citationRoss, S. C. (2018). Quantitative Electroencephalogram Neuroimaging in Obesity (Thesis, Doctor of Philosophy). University of Otago. Retrieved from http://hdl.handle.net/10523/8433en
dc.identifier.urihttp://hdl.handle.net/10523/8433
dc.description.abstractEfforts to understand and treat obesity come from a wide range of disciplines. Neuroimaging in obesity is typically performed with fMRI and PET, which are indirect measures of neural activity. EEG is a direct measure of neuronal activity that can contribute valuable information to obesity research. There are few prior EEG studies in obesity and these have used various protocols including resting state and food response measurements. AIM The purpose of the current study was to compare fasting and postprandial brain activity between matched obese and lean women. The effect of acute weight loss on brain activity in obese women and differences between obese women after weight loss and lean women was also to be determined. A secondary aim was to compare brain activity in obese women with high and low Yale Food Addiction Scale scores, indicating addictive tendencies, and those with and without the Taq1A allele, which is related to dopaminergic signalling. METHODS Thirty-five otherwise healthy obese (BMI≥30) women were recruited as part of a larger weight loss study and 35 age-matched lean (BMI<25) women were recruited from the general public. Participants completed a meal response protocol involving the recording of resting state EEG and measurement of appetite-related variables. The obese subjects then underwent a 4 week very low-calorie diet resulting in ≥5% weight loss and the meal protocol repeated. Quantitative EEG was used to compare whole brain and region of interest activity as well as network connectivity. The regions analysed had been previously identified as related to obesity and are associated with processing of internal signals, behavioural control and reward. RESULTS Quantitative EEG analysis revealed an overall reduction of alpha and beta signalling in obesity-related regions of the brain in obese compared to lean individuals. This was found at both fasting and peak satiety (45 min after the meal). This data was adjusted for insulin resistance as it was inversely correlated with brain activity. Following this adjustment, differences in alpha and beta current density between obese and lean women were no longer significant. During the meal there was also a significant 3.7-fold larger increase in alpha 1 signalling in the right temporo-parietal junction in the obese compared to lean women. In the presence of the Taq1A allele, obese women had significantly lower alpha 1 and alpha 2 signalling compared with lean women. Yale Food Addiction Scale score did not appear to differentiate brain activity in the obese women. Loss of an average of 7.3kg body weight in the obese women was accompanied by small significant changes in several bands across all regions of interest. The pattern of significantly lower alpha and beta signalling compared to lean women remained. CONCLUSIONS These findings indicate that the obese women are processing interoceptive and reward information related to food consumption differently to lean women. This may impede predictive processing regarding the adequate amount of food intake required to maintain body weight, resulting in overeating to ensure enough calories are consumed. Insulin resistance and Taq1A-related dopaminergic signalling may play a role in this.
dc.language.isoen
dc.publisherUniversity of Otago
dc.rightsAll items in OUR Archive are provided for private study and research purposes and are protected by copyright with all rights reserved unless otherwise indicated.
dc.subjectobesity
dc.subjectqeeg
dc.subjectneuroimaging
dc.titleQuantitative Electroencephalogram Neuroimaging in Obesity
dc.typeThesis
dc.date.updated2018-10-12T02:36:33Z
dc.language.rfc3066en
thesis.degree.disciplineMedicine
thesis.degree.nameDoctor of Philosophy
thesis.degree.grantorUniversity of Otago
thesis.degree.levelDoctoral
otago.interloanno
otago.openaccessAbstract Only
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