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PhD Guido Nolte | Understanding Phase Amplitude Coupling from Bi-spectral Analysis

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Dr Uku Vainik | Unifying the many neurocognitive traits associated with obesity: Uncontrolled Eating

Many eating-related psychological constructs have been proposed to explain obesity and over-eating. However, these constructs, including food addiction, disinhibition, hedonic hunger, emotional eating, binge eating, and the like all have similar definitions, emphasising loss of control over intake. As questionnaires measuring the constructs correlate strongly (r>0.5) with each other, we propose that these constructs should be reconsidered to be part of a single broad phenotype: Uncontrolled Eating (UE). Such an approach enables reviewing and meta-analysing evidence obtained with each individual questionnaire. Here, we describe robust associations between UE, body mass index (BMI), food intake, psychological traits, and brain systems. Reviewing cross-sectional and longitudinal data, we show that UE is phenotypically and genetically intertwined with BMI and food intake. We also review evidence on how three independent psychological constructs may contribute to UE: heightened food reward sensitivity, lower self-control, and higher negative affect. UE mediates all three constructs’ associations with BMI and food intake. Finally, we review and meta-analyse brain systems subserving UE: namely, (i) the dopamine mesolimbic circuit associated with reward sensitivity, (ii) frontal cognitive networks sustaining dietary self-control, and (iii) the hypothalamus-pituitary-adrenal axis, amygdala and hippocampus supporting stress reactivity. While there are limits to the explanatory and predictive power of the UE phenotype, we conclude that treating different eating-related constructs as a single concept, UE, enables drawing robust conclusions on the relationship between food intake and BMI, psychological variables, and brain structure and function. [mehr]

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Prof. Ralf Deichmann | MR Imaging methods for measuring brain tissue parameters: Technical challenges and applications

There is an increasing number of research studies that are based on quantitative MR imaging (qMRI) techniques for the direct mapping of brain tissue properties. The parameters most frequently mapped are the water content or proton density (PD) and the relaxation times (T1, T2, T2*). An important application of qMRI is the construction of synthetic anatomical data sets with novel contrasts. In clinical studies, the careful evaluation of qMRI data allows for the detection of diffuse pathologies in normal appearing brain tissue. However, the design of reliable mapping methods is technically challenging as various secondary effects have to be compensated for to avoid a residual bias in the data. In the presentation, some of the most prominent qMRI techniques will be shortly described. There will be a special focus on the application of qMRI in clinical research, in particular for Tumour Imaging, in Multiple Sclerosis (MS) and in Epilepsy. [mehr]

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Dr Stephanie Wong | A new framework for conceptualizing symptoms in frontotemporal dementia: From animal models to the clinic

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