Risk prediction error signaling: A two-component response?

Organisms use rewards to navigate and adapt to (uncertain) environments. Error-based learning about rewards is supported by the dopaminergic system, which is thought to signal reward prediction errors to make adjustments to past predictions. More recently, the phasic dopamine response was suggested to have two components: the first rapid component is thought to signal the detection of a potentially rewarding stimulus; the second, slightly later component characterizes the stimulus by its reward prediction error. Error-based learning signals have also been found for risk. However, whether the neural generators of these signals employ a two-component coding scheme like the dopaminergic system is unknown. Here, using human high density EEG, we ask whether risk learning, or more generally speaking surprise-based learning under uncertainty, is similarly comprised of two temporally dissociable components. Using a simple card game, we show that the risk prediction error is reflected in the amplitude of the P3b component. This P3b modulation is preceded by an earlier component, that is modulated by the stimulus salience. Source analyses are compatible with the idea that both the early salience signal and the later risk prediction error signal are generated in insular, frontal, and temporal cortex. The identified sources are parts of the risk processing network that receives input from noradrenergic cells in the locus coeruleus. Finally, the P3b amplitude modulation is mirrored by an analogous modulation of pupil size, which is consistent with the idea that both the P3b and pupil size indirectly reflect locus coeruleus activity.

Formalizing the Function of Anterior Insula in Rapid Adaptation.

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 possible role of the insula in the epilepsy and the gambling disorder of Fyodor Dostoyevsky.

Background The retrospective diagnosis of Fyodor Mikhailovich Dostoyevsky's (1821-1881) neurological and psychiatric disease proves to be particularly interesting. Recent neurobiological data suggest a solution to the questions regarding the writer's retrospective diagnosis, claiming the insular cortex to be the origin of the rare ecstatic seizures. Regarding Dostoyevsky's pathological gambling, this hypothesis is consistent with another finding from recent neuroscience, namely that the malfunction of the insula could be an important underlying pathology in gambling disorder. Case study Literary and scientific overview (1928-2015) on the subjects of Dostoyevsky's epilepsy and gambling disorder. Discussion and conclusion Taking Dostoyevsky's neurological (ecstatic seizures) and psychiatric (pathological gambling) disease and the crossroads into consideration, these two disciplines make regarding the underlying pathology, we would like to suggest a speculative theory that these two disorders have a common insular pathomechanism, namely, the malfunctioning of the risk prediction-risk prediction error coding system. Furthermore, based on Dostoyevsky's case, regarding gambling disorder in general, we would like to hypothesize that the three common gambling-related cognitive distortions (near-miss effect, gambler's fallacy, and the illusion of control) can be all attributed to the impairment of the anterior insular risk prediction-risk prediction error coding system.