As more papers are published and the body of knowledge increases, it becomes difficult to maintain a sense of overview and recognize relations between discussed topics. In order to assist neuroscientists with their task of finding unexplored relations between brain diseases, the DatAR project provides a topic model which allows neuroscientists to see at a glance which brain diseases are semantically similar and thus likely correlated. However, this topic model lacks the ability to explain why and how these brain diseases are semantically similar. We set out to design the Brain Disease Co-occurrence Explorer (BDCE), a 3D visualization which visualizes the number of co-occurrences between two brain diseases and any other brain topic in literature, with co-occurrence defined as two topics mentioned in the same sentence or body of text. We design two iterations of the BDCE, the first of which is evaluated by interviewing two experts in the field of 3D data visualization and immersive analytics. Based on the results from these interviews, we improve upon the design and perform user evaluations of the final iteration with participants from a neuroscience background or different related biology field. The user evaluations show that the BDCE is capable of explaining the topic model and encouraging further investigation into potentially interesting relations between brain diseases. Finally, we propose some avenues for future research regarding additional BDCE features, different visualization designs for visualizing co-occurrences in 3D space and improvements to our number visualization style.