This is a distributed project, with representatives at all main TRR379 sites.
As a key software solution, this project employs DataLad. DataLad is a data management software designed to facilitate the organization, sharing, and reproducibility of scientific datasets. It integrates version control with data handling, allowing researchers to track changes, collaborate efficiently, and ensure the accessibility and integrity of their data. By leveraging tools like Git and Git-annex, DataLad provides a streamlined way to manage large datasets, making it particularly valuable in fields like neuroimaging and bioinformatics.
Christine Ecker is a professor at Goethe University Frankfurt, specializing in clinical neuroscience and psychiatry. Her research focuses on the neurobiological underpinnings of autism spectrum disorders and other neurodevelopmental conditions, utilizing advanced neuroimaging techniques. Ecker’s work aims to bridge the gap between clinical practice and neuroscience to improve diagnostic and therapeutic strategies for these disorders.
Gabriele Ende is a researcher associated with the Central Institute of Mental Health (ZI) in Mannheim, Germany. Her work primarily focuses on neuroimaging and the application of magnetic resonance spectroscopy (MRS) in psychiatric and neurological disorders. Ende’s research aims to deepen the understanding of brain chemistry and its alterations in various mental health conditions.
Michael Hanke is a professor at the Heinrich Heine University Düsseldorf, and head of the Psychoinformatics group in the Institute for Neuroscience and Medicine (INM-7) at the Forschungszentrum Jülich. He has co-created several neuroinformatics software projects, among them the NeuroDebian, PyMVPA, and DataLad.
Klaus Mathiak is a professor at RWTH Aachen University, specializing in psychiatry and psychotherapy. His research integrates neuroimaging, psychophysiology, and clinical studies to understand the neural mechanisms underlying social cognition, aggression, and media influence on behavior. Mathiak’s work aims to enhance therapeutic interventions for psychiatric disorders by elucidating the brain’s role in social and emotional processing.
This two-hour workshop provides the first opportunity to get “hands on” with the information management infrastructure of TRR379. Attendees receive a more detailed introduction to the general approach to research data management (RDM) and the employed technologies, continuing from the short presentation by Q02 on the first day of the 2025 retreat.
The Distribits 2025 conference and hackathon (23-25 October in Düsseldorf, Germany) will bring together researchers, software developers, and other data enthusiasts working on distributed data management technologies and FAIR workflows. These themes are integral to the decentralized data management infrastructure employed within the TRR 379. Namely, this year’s Distribits event will feature talks on the development and application of DataLad, git-annex, and other distributed data tools, which are core technologies enabling version control, sharing, and reproducibility of datasets across TRR 379 sites.
On September 3, 2025, the TRR 379 successfully rolled out the DFG’s (Deutsche Forschungsgemeinschaft) annual survey on coordinated programmes using the TRR 379’s integrated metadata system, reflecting the consortium’s commitment to data-driven research management.
Perceptual changes in major depressive disorder (MDD) may extend beyond emotional content and include the processing of basic stimulus features. These alterations may ultimately contribute to perceptual bias and anhedonia. To characterize blood oxygen level-dependent (BOLD) signal of perceptual processing, we investigated temporally independent fMRI signal components related to naturalistic stimulus processing in 39 patients with MDD and 36 healthy subjects. Leveraging the capability of multi-echo data to detect BOLD activity changes, we extracted physiologically meaningful group temporal components. For each component that exhibited a significant correlation with the movie content, we localized its underlying brain network and assessed MDD-associated alterations. Two components exhibited significant group differences; one was associated with auditory features (sound pressure level) and one with visual features (temporal contrast of intensity). Notably, these deficits in MDD localized primarily to higher-order processing areas, such as the dorsal prefrontal cortex and insula, rather than primary sensory cortices. For the visual feature component, additional group differences emerged in non-visual primary sensory cortices (auditory and somatosensory) as well as major hubs of the motor system. Our findings support the hypothesis that basic sensory processing deficits represent an inherent feature of MDD which may contribute to anhedonia and negative perceptual bias. These deficits are primarily confined to higher-order processing units, as well as cross-modal primary sensory cortices indicating predominant dysfunction of top-down control and multisensory integration. Therapeutic effects of interventions targeting the prefrontal cortex may be partially mediated by restoring prefrontal control not only over emotional but also sensory processing hubs.