Deep neural networks have led to state-of-the-art results in many medical imaging tasks including Alzheimer’s disease (AD) detection based on structural magnetic resonance imaging (MRI) data. However, the network decisions are often perceived as being highly non-transparent making it difficult to apply these algorithms in clinical routine. In this study, we propose using layer-wise relevance […]

Parkinson’s disease (PD) is the second most frequent neurodegenerative disease worldwide and the availability of early biomarkers and novel biotargets represents an urgent medical need. The main pathogenetic hallmark of PD is the specific loss of nigral dopaminergic neurons, in which mitochondrial dysfunction plays a crucial role. Mitochondrial proteases are central to the maintenance of […]

Abstract Concreteness ratings are frequently used in a variety of disciplines to operationalize differences between concrete and abstract words and concepts. However, most ratings studies present items in isolation, thereby overlooking the potential polysemy of words. Consequently, ratings for polysemous words may be conflated, causing a threat to the validity of concreteness‐ratings studies. This is […]