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Currently, little is known about the spatial distribution of white matter hyperintensities (WMH) in the brain of patients with Systemic Lupus erythematosus (SLE). Previous lesion markers, such as number and volume, ignore the strategic location of WMH. The goal of this work was to develop a fully-automated method to identify predominant patterns of WMH across WM tracts based on cluster analysis. A total of 221 SLE patients with and without neuropsychiatric symptoms from two different sites were included in this study. WMH segmentations and lesion locations were acquired automatically. Cluster analysis was performed on the WMH distribution in 20 WM tracts. Our pipeline identified five distinct clusters with predominant involvement of the forceps major, forceps minor, as well as right and left anterior thalamic radiations and the right inferior fronto-occipital fasciculus. The patterns of the affected WM tracts were consistent over the SLE subtypes and sites. Our approach revealed distinct and robust tract-based WMH patterns within SLE patients. This method could provide a basis, to link the location of WMH with clinical symptoms. Furthermore, it could be used for other diseases characterized by presence of WMH to investigate both the clinical relevance of WMH and underlying pathomechanism in the brain.

Although vast research has been conducted concerning gambling behavior this is the first study combining behavioral and functional magnetic resonance imaging (fMRI) data while using the Cambridge Gambling Task (CGT). We tested 20 healthy right-handed men and chose an event-related design to allow for precise temporal separation of gambling stages. In the color decision stage participants had to guess whether a yellow token was hidden behind red or blue boxes presented in varying color ratios, then stake wagers during the bet decision stage. In the final stage the outcome (won or lost) was presented. Analyzing the blood-oxygenation level-dependent (BOLD) contrasts in the decision stages we found increases of activation in brain areas involved in decision making, working memory and learning, when participants bet on the majority choice. During the outcome stage increased brain activation was found in parts of the reward system and areas involved in decision making and impulse control, when winning. When losing, activation increased in areas involved in risk aversion and management of uncertainties. When participants lost unexpectedly (i.e. lost although they bet on the majority), increased activation was found in the insula, compared to winning expectedly. The more unexpectedly participants won the higher the increase of brain activation in parts of the reward system and areas involved in executive functions. Our study gives an extensive overview of brain areas involved in different stages of gambling and during various outcomes, with corresponding behavioral data (e.g. speed and quality of decision making) illustrating underlying tendencies.