Context-invariant neural dynamics underlying the encoding of Bayesian uncertainty, but not confidence

Beliefs about action-outcomes contingencies are often updated in opaque environments where feedbacks might be inaccessible and agents might need to rely on other information for evidence accumulation. It remains unclear, however, whether and how the neural dynamics subserving confidence and uncertainty during belief updating might be context-dependent. Here, we applied a Bayesian model to estimate uncertainty and confidence in healthy humans (n=28) using two multi-option fMRI tasks, one with and one without feedbacks. We found that across both tasks, uncertainty was computed in the anterior insular, anterior cingulate, and dorsolateral prefrontal cortices, whereas confidence was encoded in anterior hippocampus, amygdala and medial prefrontal cortex. However, dynamic causal modelling (DCM) revealed a critical divergence between how effective connectivity in these networks was modulated by the available information. Specifically, there was directional influence from the anterior insula to other regions during uncertainty encoding, independent of outcome availability. Conversely, the network computing confidence was driven either by the anterior hippocampus when outcomes were not available, or by the medial prefrontal cortex and amygdala when feedbacks were immediately accessible. These findings indicate that confidence encoding might largely rely on evidence accumulation and therefore dynamically changes as a function of the available sensory information (i.e. symbolic sequences monitored by the hippocampus, and monetary feedbacks computed by amygdala and medial prefrontal cortex). In contrast, uncertainty could be triggered by any information that disputes existing beliefs (i.e. processed in the insula), independent of its content.Significance StatementOur choices are guided by our beliefs about action-outcome contingencies. In environments where only one action leads to a desired outcome, high estimated action-outcome probabilities result in confidence, whereas low probabilities distributed across multiple choices result in uncertainty. These estimations are continuously updated, sometimes based on feedbacks provided by the environment, but sometimes this update takes place in opaque environments where feedbacks are not readily available. Here, we show that uncertainty computations are driven by the anterior insula, independent of feedback availability. Conversely, confidence encoding dynamically adapts to the information available, as we found it was driven either by the anterior hippocampus, when feedback was absent, or by the medial prefrontal cortex and amygdala, otherwise.