Model-based influences on humans' choices and striatal prediction errors.

The mesostriatal dopamine system is prominently implicated in model-free reinforcement learning, with fMRI BOLD signals in ventral striatum notably covarying with model-free prediction errors. However, latent learning and devaluation studies show that behavior also shows hallmarks of model-based planning, and the interaction between model-based and model-free values, prediction errors, and preferences is underexplored. We designed a multistep decision task in which model-based and model-free influences on human choice behavior could be distinguished. By showing that choices reflected both influences we could then test the purity of the ventral striatal BOLD signal as a model-free report. Contrary to expectations, the signal reflected both model-free and model-based predictions in proportions matching those that best explained choice behavior. These results challenge the notion of a separate model-free learner and suggest a more integrated computational architecture for high-level human decision-making.

Europium-directed self-assembly of a luminescent supramolecular gel from a tripodal terpyridine-based ligand.

Eu(III), the last piece in the puzzle: Europium-induced self-assembly of ligands having a C(3)-symmetrical benzene-1,3,5-tricarboxamide core results in the formation of luminescent gels. Supramolecular polymers are formed through hydrogen bonding between the ligands. The polymers are then brought together into the gel assembly through the coordination of terpyridine ends by Eu(III) ions (blue dashed arrow: distance between two ligands in the strand direction).