Relating control of alcohol use to functional brain connectomics: Integrating information from multiple studies (A09*)

• Subject Area: Cognitive, Systems and Behavioural Neurobiology ; Biological Psychiatry
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 402170461

In this project, we will use functional brain connectomics to predict AUD-related variables, especially measures of control over alcohol intake in time. We will employ advanced machine learning techniques and emphasize both, prediction accuracy as well as interpretability. To this end, we will (i) combine whole brain connectomics with machine learning, (ii) we will use normative modelling, and (iii) meta-matching. We will use an fMRI multiverse approach with different input data domains including static and dynamic connectomic measures from resting state fMRI as well as task-based activations and connectivities from the Stop Signal Task. Information from other data sets will be integrated towards our goals, in particular from the the IMAGEN cohort (N≈2000) and from the UK-Biobank (N≈36.000).

• DFG Programme: CRC/Transregios
• Subproject of: TRR 265: Losing and Regaining Control over Drug Intake: From Trajectories to Mechanisms to Interventions
• Applicant Institution: Ruprecht-Karls-Universität Heidelberg
• Project Heads: Michael Marxen, Ph.D.; Professor Dr. Henrik Walter