2019 – The Year In Review

As the year 2019 slowly draws to a close, it is time to look back on the past 12 months.

During the last year, a lot of things happened in our institute. We started in January with approximately 41 colleagues and now we have grown to 63 colleagues. We have gained two new groups one is called “Psychoinformatics”, which focuses on the interface of neuroscience, psychology and computer science and the combination of classical experimental methodology with machine learning methods. This group is headed by Michael Hanke, who was appointed professor at the Heinrich Heine University Düsseldorf in the domain of Systematic Analysis of Brain Organization. The other one “Biomarker Development” led by Jürgen Dukart aims to identify, validate and integrate novel neuroimaging and digital biomarkers that can be applied for early detection and treatment evaluation of changes in brain organization in advanced age as well as in neurological and psychiatric diseases.

Psychoinformatics group led by Michael Hanke.

Biomarker Development group led by Jürgen Dukart.

At this point I would also like to mention that Anne Latz Anne successfully completed her doctorate with the title “Neural correlates of age-related changes in cognitive action control” this year. Moreover, Sofie Valk was selected as the winner of the SANS Poster Award for her poster on “Neurogenetic markers of personality” at the annual meeting of the Social & Affective Neuroscience Society in May.

With more than 40 published papers and highly future oriented topics our scientific development was enormous and very innovative this year. One of the most important topics is the use of machine-learning approaches to train predictive models for inference on phenotypical characteristics of new, individual subjects from brain imaging data. For example, Susanne Weis has found that the gender of subjects can be predicted by applying machine learning approaches to resting state data. Additionally, Ji Chen observed a new way of describing schizophrenia by the application of machine learning approaches. He identified a four-factor structure representing negative, positive, affective, and cognitive symptoms as the most stable and generalizable representation of psychopathology. In the next year we would like to investigate the application of machine learning and artificial intelligence even more to improve diagnosis and prognosis of psychiatric diseases.

A special highlight this year was the “Tag der Neugier” tat the Forschungszentrum, which gave more than 28,000 visitors the chance to take a look behind the scenes of research. At our institute, the guests were invited to perform several neuropsychological tests and personality questionnaires and compare their performance to those of others to find out what it feels like to be in such a neuropsychological testing situation. Moreover, from young to old, all visitors were fascinated by our inflatable brain, in which we gave talk and explained our research topics with posters. The absolute highlight, however, was the station where the visitors had to balance on a balance board while their movement parameters were measured using an app programmed by Jürgen Dukart’s group. Doing so, we wanted to show that smartphones and wearables record movements very sensitively and that this information can in turn be used as an objective tool for symptom evaluation and as a measure for disease progression. Below you can find a video that gives you an overview what happened at the Tag der Neugier at our institute.

I am very satisfied with the past year and hope that 2020 will be just as exciting, eventful and successful. Now I just want to wish you a Merry Christmas and a Happy New Year!