Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning

In Bayesian brain theories, hierarchically related prediction errors (PEs) play a central role for predicting sensory inputs and inferring their underlying causes, e.g., the probabilistic structure of the environment and its volatility. Notably, PEs at different hierarchical levels may be encoded by different neuromodulatory transmitters. Here, we tested this possibility in computational fMRI studies of audio-visual learning. Using a hierarchical Bayesian model, we found that low-level PEs about visual stimulus outcome were reflected by widespread activity in visual and supramodal areas but also in the midbrain. In contrast, high-level PEs about stimulus probabilities were encoded by the basal forebrain. These findings were replicated in two groups of healthy volunteers. While our fMRI measures do not reveal the exact neuron types activated in midbrain and basal forebrain, they suggest a dichotomy between neuromodulatory systems, linking dopamine to low-level PEs about stimulus outcome and acetylcholine to more abstract PEs about stimulus probabilities. [Display omitted] •Hierarchical precision-weighted prediction errors (PEs) during audio-visual learning•PEs about sensory outcome are widely represented throughout the brain•BOLD signal in midbrain reflects PEs about stimulus outcome•BOLD signal in basal forebrain reflects PEs about stimulus probabilities Prediction errors (PEs) are crucial teaching signals for learning. Iglesias et al. show that different PEs map onto distinct neurotransmitter systems: the dopaminergic midbrain signals PEs about visual stimulus outcomes, while the cholinergic basal forebrain encodes PEs about stimulus probabilities.