In the past decade, the fast and transient coupling and uncoupling of functionally related brain regions into networks has received much attention in cognitive neuroscience. Empirical tools to study network coupling include functional magnetic resonance imaging (fMRI)-based functional and/or effective connectivity, and electroencephalography (EEG)/magnetoencephalography-based measures of neuronal synchronization. Here we use simultaneously recorded EEG and fMRI to assess whether fMRI-based connectivity and frequency-specific EEG power are related. Using data collected during resting state, we studied whether posterior EEG alpha power fluctuations are correlated with connectivity within the visual network and between the visual cortex and the rest of the brain. The results show that when alpha power increases, BOLD connectivity between the primary visual cortex and occipital brain regions decreases and that the negative relation of the visual cortex with the anterior/medial thalamus decreases and the ventral–medial prefrontal cortex is reduced in strength. These effects were specific for the alpha band, and not observed in other frequency bands. The decreased connectivity within the visual system may indicate an enhanced functional inhibition during a higher alpha activity. This higher inhibition level also attenuates long-range intrinsic functional antagonism between the visual cortex and the other thalamic and cortical regions. Together, these results illustrate that power fluctuations in posterior alpha oscillations result in local and long-range neural connectivity changes.
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Abstract: INTRODUCTION: Resting energy expenditure (REE) is expected to be higher in athletes because of their relatively high fat free mass (FFM). Therefore, REE predictive equation for recreational athletes may be required. The aim of this study was to validate existing REE predictive equations and to develop a new recreational athlete specific equation.
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Background: When the resting energy expenditure (REE) of overweight and obese adolescents cannot be measured by indirect calorimetry, it has to be predicted with an equation. Objective: The aim of this study was to examine the validity of published equations for REE compared with indirect calorimetry in overweight and obese adolescents. Design: Predictive equations based on weight, height, sex, age, fatfree mass (FFM), and fat mass were compared with measured REE. REE was measured by indirect calorimetry, and body composition was measured by dual-energy X-ray absorptiometry. The accuracy of the REE equations was evaluated on the basis of the percentage of adolescents predicted within 10% of REE measured, the mean percentage difference between predicted and measured values (bias), and the root mean squared prediction error (RMSE). Results: Forty-three predictive equations (of which 12 were based on FFM) were included. Validation was based on 70 girls and 51 boys with a mean age of 14.5 y and a mean (6SD) body mass index SD score of 2.93 6 0.45. The percentage of adolescents with accurate predictions ranged from 74% to 12% depending on the equation used. The most accurate and precise equation for these adolescents was the Molnar equation (accurate predictions: 74%; bias: –1.2%; RMSE: 174 kcal/d). The often-used Schofield-weight equation for age 10–18 y was not accurate (accurate predictions: 50%; bias: +10.7%; RMSE: 276 kcal/d). Conclusions: Indirect calorimetry remains the method of choice for REE in overweight and obese adolescents. However, the sex-specific Molnar REE prediction equation appears to be the most accurate for overweight and obese adolescents aged 12–18 y. This trial was registered at www.trialregister.nl with the Netherlands Trial Register as ISRCTN27626398.
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While the creation of an energy deficit (ED) is required for weight loss, it is well documented that actual weight loss is generally lower than what expected based on the initially imposed ED, a result of adaptive mechanisms that are oppose to initial ED to result in energy balance at a lower set-point. In addition to leading to plateauing weight loss, these adaptive responses have also been implicated in weight regain and weight cycling (add consequences). Adaptions occur both on the intake side, leading to a hyperphagic state in which food intake is favored (elevated levels of hunger, appetite, cravings etc.), as well as on the expenditure side, as adaptive thermogenesis reduces energy expenditure through compensatory reductions in resting metabolic rate (RMR), non-exercise activity expenditure (NEAT) and the thermic effect of food (TEF). Two strategies that have been utilized to improve weight loss outcomes include increasing dietary protein content and increasing energy flux during weight loss. Preliminary data from our group and others demonstrate that both approaches - especially when combined - have the capacity to reduce the hyperphagic response and attenuate reductions in energy expenditure, thereby minimizing the adaptive mechanisms implicated in plateauing weight loss, weight regain and weight cycling. Past research has largely focused on one specific component of energy balance (e.g. hunger or RMR) rather than assessing the impact of these strategies on all components of energy balance. Given that all components of energy balance are strongly connected with each other and therefore can potentially negate beneficial impacts on one specific component, the primary objective of this application is to use a comprehensive approach that integrates all components of energy balance to quantify the changes in response to a high protein and high energy flux, alone and in combination, during weight loss (Fig 1). Our central hypothesis is that a combination of high protein intake and high energy flux will be most effective at minimizing both metabolic and behavioral adaptations in several components of energy balance such that the hyperphagic state and adaptive thermogenesis are attenuated to lead to superior weight loss results and long-term weight maintenance.
