Mona M. Garvert

The paper shows that the brain encodes network structure using distinct brain regions, with hippocampus representing shortest-path distances and retrosplenial complex representing global connectivity.

The paper investigates the emergence of abstract relational representations in the human medial prefrontal cortex over time using fMRI and graph-learning paradigms.

The paper investigates neural mechanisms of credit assignment for delayed outcomes using fMRI and an adaptive learning task, identifying roles for lOFC, HC, and lFPC in tracking causal choices over time.

The study investigates how the brain generalizes abstract linguistic rules to form novel meanings, finding that a frontoparietal network, not the medial prefrontal-hippocampal network, supports this process.

This study investigates how the hippocampus supports both episodic and spatial memory, finding evidence for a common coding mechanism rather than parallel processing.

The paper shows that the entorhinal cortex represents an abstract value space during decision making with a grid-like pattern aligned to the most informative value axis.

The paper investigates how the hippocampal formation represents different types of relational information by analyzing fMRI data to show distinct semantic and statistical maps.

The paper shows how hippocampal cognitive maps adapt to guide reward generalization by shifting emphasis from temporal to spatial relationships as a task progresses.

The paper investigates how ventromedial prefrontal cortex (vmPFC) represents context and context-dependent values during decision-making, showing that both relevant and irrelevant values are encoded and influence behavior.

The paper shows that entorhinal and ventromedial prefrontal cortex representations generalize reinforcement learning problem structures across different tasks.

The paper tests if computational principles of spatial search apply to conceptual search using a Gaussian Process model and finds similar but distinct generalization patterns.