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Although motor imagery is widely used for motor learning in rehabilitation and sports training, the underlying mechanisms are still poorly understood. Based on fMRI data sets acquired with very high temporal resolution (300 ms) under motor execution and imagery conditions, we utilized Dynamic Causal Modeling (DCM) to determine effective connectivity(More)
Resting-state data sets contain coherent fluctuations unrelated to neural processes originating from residual motion artefacts, respiration and cardiac action. Such confounding effects may introduce correlations and cause an overestimation of functional connectivity strengths. In this study we applied several multidimensional linear regression approaches to(More)
Social anxiety disorder patients suffer from excessive anxious responses in social interaction leading to avoidance behavior and social impairment. Although the amygdala has a central role in perception and processing of threatening cues, little is known about the involved networks and corresponding dysfunctions in social anxiety. Therefore, this study aims(More)
Previous studies suggest organizing effects of sex hormones on brain structure during early life and puberty, yet little is known about the adult period. The aim of the present study was to elucidate the role of 17beta-estradiol, progesterone, and testosterone on cortical sex differences in grey matter volume (GM) of the adult human brain. To assess sexual(More)
Reflecting one's mental self is a fundamental process for evaluating the personal relevance of life events and for moral decision making and future envisioning. Although the corresponding network has been receiving growing attention, the driving neurochemical mechanisms of the default mode network (DMN) remain unknown. Here we combined positron emission(More)
OBJECTIVE Independent component analysis (ICA) has proven its applicability in both standard and resting-state fMRI. While there is consensus on single-subject ICA methodology, the extension to group ICA is more complex and a number of approaches have been suggested. Currently, two software packages are most frequently used for ICA group analysis: (1) GIFT(More)
Escitalopram the S-enantiomer of the racemate citalopram, is clinically more effective than citalopram in the treatment of major depressive disorder. However, the precise mechanism by which escitalopram achieves superiority over citalopram is yet to be determined. It has been hypothesized that the therapeutically inactive R-enantiomer competes with the(More)
The serotonin system plays an important role in the neural processing of anxiety. The involvement of the main inhibitory serotonergic receptor, the serotonin-1A (5-HT1A) subtype, in dysfunctional forms of anxiety has been supported by findings from a wide range of preclinical research and clinical trials, including treatment studies, genetic research, and(More)
Area-specific and stimulation-dependent changes of human brain activation by selective serotonin reuptake inhibitors (SSRI) are an important issue for improved understanding of treatment mechanisms, given the frequent prescription of these drugs in depression and anxiety disorders. The aim of this neuroimaging study was to investigate differences in(More)
Exploratory analysis of functional MRI data allows activation to be detected even if the time course differs from that which is expected. Independent Component Analysis (ICA) has emerged as a powerful approach, but current extensions to the analysis of group studies suffer from a number of drawbacks: they can be computationally demanding, results are(More)