Predicting behavior from the multimodal profile of brain regions

• Applicant: Professorin Sarah Genon, Ph.D.
• Subject Area: Human Cognitive and Systems Neuroscience
• Term: since 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 519107208

Individual behavior prediction based on neuroimaging data and machine learning models have become increasingly popular. However, several challenges are present including the overall lower prediction accuracies in large samples, as well as the difficulty in interpreting the prediction models and outcomes. In this project, we address these challenges using our recently developed region-wise psychometric prediction framework with multimodal neuroimaging data. First, we aim to perform a systematic evaluation of multimodal psychometric prediction making use of multiple large datasets encompassing functional, structural and diffusion magnetic resonance imaging data. Then, we aim to improve model interpretability by specifically quantifying the contribution of neuroimaging features from each brain region and of each confounding variable. Overall, we propose to develop a multimodal psychometric prediction framework for improving predictive power beyond unimodal approaches, and for characterizing brain regions’ or confounding variables’ contribution to psychometric predictions.

• DFG Programme: Research Grants