Susanne Greiner

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The Attention Deficit Hyperactivity Disorder (ADHD) affects the school-age population and has large social costs. The scientific community is still lacking a pathophysiological model of the disorder and there are no objective biomarkers to support the diagnosis. In 2011 the ADHD-200 Consortium provided a rich, heterogeneous neuroimaging dataset aimed at(More)
Humans learn to trust each other by evaluating the outcomes of repeated interpersonal interactions. However, available prior information on the reputation of traders may alter the way outcomes affect learning. Our functional magnetic resonance imaging study is the first to allow the direct comparison of interaction-based and prior-based learning. Twenty(More)
Machine learning techniques are increasingly adopted in computer-aided diagnosis. Evaluation methods for classification results that are based on the study of one or more metrics can be unable to distinguish between cases in which the classifier is discriminating the classes from cases in which it is not. In the binary setting, such circumstances can be(More)
Brain connectivity studies aim at describing the connections within the brain. Diffusion and functional MRI techniques provide different kinds of information to understand brain connectivity non-invasively. Fiber tract segmentation is the task of identifying pathways of neuronal axons connecting different brain areas from MRI data. In this work we propose a(More)
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