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Objective Resting-state functional magnetic resonance imaging (rs-fMRI) has become an essential measure to investigate the human brain’s spontaneous activity and intrinsic functional connectivity. Several studies including our own previous work have shown that the brain controls the regulation of energy expenditure and food intake behavior. Accordingly, we expected different metabolic states to influence connectivity and activity patterns in neuronal networks. Methods The influence of hunger and satiety on rs-fMRI was investigated using three connectivity models (local connectivity, global connectivity and amplitude rs-fMRI signals). After extracting the connectivity parameters of 90 brain regions for each model, we used sequential forward floating selection strategy in conjunction with a linear support vector machine classifier and permutation tests to reveal which connectivity model differentiates best between metabolic states (hunger vs. satiety). Results We found that the amplitude of rs-fMRI signals is slightly more precise than local and global connectivity models in order to detect resting brain changes during hunger and satiety with a classification accuracy of 81%. Conclusion The amplitude of rs-fMRI signals serves as a suitable basis for machine learning based classification of brain activity. This opens up the possibility to apply this combination of algorithms to similar research questions, such as the characterization of brain states (e.g., sleep stages) or disease conditions (e.g., Alzheimer’s disease, minimal cognitive impairment).

To study the interplay of metabolic state (hungry vs. satiated) and glucose administration (including hormonal modulation) on brain function, resting-state functional magnetic resonance imaging (rs-fMRI) and blood samples were obtained in 24 healthy normal-weight men in a repeated measurement design. Participants were measured twice: once after a 36 h fast (except water) and once under satiation (three meals/day for 36 h). During each session, rs-fMRI and hormone concentrations were recorded before and after a 75 g oral dose of glucose. We calculated the amplitude map from blood-oxygen-level-dependent (BOLD) signals by using the fractional amplitude of low-frequency fluctuation (fALFF) approach for each volunteer per condition. Using multiple linear regression analysis (MLRA) the interdependence of brain activity, plasma insulin and blood glucose was investigated. We observed a modulatory impact of fasting state on intrinsic brain activity in the posterior cingulate cortex (PCC). Strikingly, differences in plasma insulin levels between hunger and satiety states after glucose administration at the time of the scan were negatively related to brain activity in the posterior insula and superior frontal gyrus (SFG), while plasma glucose levels were positively associated with activity changes in the fusiform gyrus. Furthermore, we could show that changes in plasma insulin enhanced the connectivity between the posterior insula and SFG. Our results indicate that hormonal signals like insulin alleviate an acute hemostatic energy deficit by modifying the homeostatic and frontal circuitry of the human brain.

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IntroductionDifferent metabolic conditions can affect what and how much we eat. Hormones of glucose metabolism and adipokines such as adiponectin take part in the control of these decisions and energy balance of the body. However, a comprehensive understanding of how these endocrine and metabolic factors influence food intake has not been reached. We hypothesised that the amount of food a person consumes differs substantially after a fasting period even after the energy deficit was partially removed by glucose ingestion and endocrine signals like insulin and C-peptide indicated a high glucose metabolic status. Furthermore, the macronutrient composition of the consumed food and a possible association with adiponectin under the influence of glucose ingestion was assessed.MethodsIn a within-subject design, 24 healthy males participated in both a fasting (42 h) and control (non-fasting) condition. A total of 20 blood samples from each subject were collected during each condition to assess serum levels of adiponectin, insulin, C-peptide, cortisol and ACTH. At the end of each condition food intake was measured with an ad libitum buffet after the acute energy deficit was compensated using a carbohydrate-rich drink.ResultsThe total amount of caloric intake and single macronutrients was higher after the fasting intervention after replenishment with glucose. All recorded hormone levels, except for adiponectin, were significantly different for at least one of the study intervals. The relative proportions of the macronutrient composition of the consumed food were stable in both conditions under the influence of glucose ingestion. In the non-fasting condition, the relative amount of protein intake correlated with adiponectin levels during the experiment.Discussion and conclusionAn anabolic glucose metabolism after glucose ingestion following a fasting intervention did not even out energy ingestion compared to a control group with regular food intake and glucose ingestion. Anorexigenic hormones like insulin in this context were not able despite higher levels than in the control condition to ameliorate the drive for food intake to normal or near normal levels. Relative macronutrient intake remains stable under these varying metabolic conditions and glucose influence. Serum adiponectin levels showed a positive association with the relative protein intake in the non-fasting condition under the influence of glucose although adiponectin levels overall did not differ in between the conditions.