DeepBrain: Decision Mechanisms in Deep Brain Networks

The human brain consists of densely connected networks of interacting areas and nuclei, and while the cerebral cortex has been mapped with great precision, research on the human subcortex has been relatively side-lined. The subcortex contains hundreds of small grey matter nuclei, which take up approximately 25% of the entire human brain volume. However, only 7% of these nuclei are currently accessible in standard human brain magnetic resonance imaging (MRI) atlases.

Prof. Birte Forstmann (University of Amsterdam): “My dream is to chart terra incognita: the human subcortex.” 

Impact
With DeepBrain, Prof. Forstmann aims to tackle this knowledge gap by studying the mechanisms of different decision-making domains implemented in deep brain networks. Major ongoing efforts in Prof. Forstmann’s group have focused on structural imaging of the subcortex, thereby removing an important technical barrier to advancing our knowledge. These efforts have paved the way for these first-of-their-kind functional studies on the role of the deep brain in decision-making.

In DeepBrain, Prof. Forstmann will use Ultra-high-field (UHF) 7Tesla (T) MRI and one of the three world-wide available Connectom MRI to investigate decision mechanisms in deep brain networks. The project involves a strong theory-driven and statistically high-powered model-based approach to combine beyond the-state-of-the-art techniques from cognitive neuroscience, experimental psychology, to quantitative modeling. Ultimately, this proposal will yield a unified deep-brain network model of one of the most fundamentally important human activities: decision making.

Horizon 2020 - Excellent Science: ERC Consolidator Grant