↓Skip to main content
  1. Research projects/

Q02: Data management for computational modelling

Data management and training platform. A decentralized data management infrastructure will help focus on developmental and therapeutic longitudinal data, training all participating researchers in the necessary skills for future use. This strategy will lay the foundations for further data-driven computational modelling projects in the next funding period.

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.

Contributors

Christine Ecker

C05: The neuroanatomical underpinnings of clinical aggression and their relationship with the negative valence and cognitive control systems Q02: Data management for computational modelling Principal investigator Research data committee member Goethe University Frankfurt
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.

Gabriele Ende

A03: Modulation of aggression by acute threat A08: The metabolic lung-brain axis in aggressive behavior in patients with AMD Q02: Data management for computational modelling Principal investigator Research data committee member Quality control group member Heidelberg University Central Institute of Mental Health
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.

Klaus Mathiak

B03: A process-based brain-computer interface to modulate aggressive behavior – a real-time fMRI neurofeedback study C02: Aggressive decisions in social conflicts: Neuro-cognitive models for healthy individuals and psychiatric patients with high scores of aggression Q02: Data management for computational modelling Principal investigator Research data committee member Equal opportunity committee member RWTH Aachen
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.

Events

News

Distribits 2025

Q02: Data management for computational modelling Research data management
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.

Publications

Basic stimulus processing alterations from top-down cognitive control in depression drive independent temporal components of multi-echo naturalistic fMRI data

Klaus Mathiak Jana Zweerings Q02: Data management for computational modelling
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.