Formalizing the Function of Anterior Insula in Rapid Adaptation

Abstract

Anterior insula (aIns) is thought to play a crucial role in rapid adaptation in an ever-changing environment. Mathematically, it is known to track risk and surprise. Modern theories of learning, however, assign a dominant role to signed prediction errors (PEs), not to risk and surprise. Risk and surprise only enter to the extent that they modulate the learning rate, in an attempt to approximate Bayesian learning. Even without such modulation, adaptation is still possible, albeit slow. Here, I propose a new theory of learning, reference-model based learning (RMBL), where risk and surprise are central, and PEs play a secondary, though still crucial, role. The primary goal is to bring outcomes in line with expectations in the reference model (RM). Learning is modulated by how large the PEs are relative to model anticipation, i.e., to surprise as defined by the RM. In a target location prediction task where participants were continuously required to adapt, choices appeared to be closer with to RMBL predictions than to Bayesian learning. aIns reaction to surprise was more acute in the more difficult treatment, consistent with its hypothesized role in metacognition. I discuss links with related theories, such as Active Inference, Actor-Critic Models and Reference-Model Based Adaptive Control.

The neural dynamics associated with computational complexity

“…Therefore, we expected regions that have been linked to monitoring of uncertainty to be more active during a trial with an unsatisfiable instance compared to a satisfiable one. In particular, we conjectured higher activation of the CON, on unsatisfiable instances, during late stages of the trial (Neta et al, 2017(Neta et al, , 2014Bossaerts, 2018;Fouragnan et al, 2018).…”

“…The two properties are complexity and proof hardness. Complexity captures in regions that have been previously shown to encode uncertainty, specifically in CON (Neta et al, 2017(Neta et al, , 2014Bossaerts, 2018;Fouragnan et al, 2018).…”

Continuous decisions

“…in RL [23,24,[46][47][48][49]. This also links to theoretical work on freeenergy-inspired models [50,51] that incorporate information seeking, inference and reward into a single framework. However, this rapidly growing body of work is beyond the scope of this review.…”

Epilepsy and Ecstatic Experiences: The Role of the Insula

“…In more recent versions of the theory of predictive coding [ 17 , 18 , 19 ], the opposite happens as well: in the case of surprise, the decision-maker (“agent”) attempts to bring reality in line with the reference model. The agent actively searches for environments that better reflect the reference model.…”

“…Evidence has been mounting over the last two decades that the dorsal anterior insula plays a crucial role in tracking surprise and uncertainty, in the form of a signal that compares how far outcomes are from predictions. This role emerges in a variety of settings, from complex social situations [ 19 , 20 ] down to simple probabilistic [ 21 , 22 ] and perceptual tasks [ 23 ]. Besides these functional MRI studies linking surprise and the anterior insula, there are human pathologies which also support this association.…”