Predictive coding of the statistical parameters of uncertain rewards by orbitofrontal neurons

Brain-correlates of processing local dependencies within a statistical learning paradigm

Statistical learning refers to the implicit mechanism of extracting regularities in our environment. Numerous studies have investigated the neural basis of statistical learning. However, how the brain responds to violations of auditory regularities based on prior (implicit) learning requires further investigation. Here, we used functional magnetic resonance imaging (fMRI) to investigate the neural correlates of processing events that are irregular based on learned local dependencies. A stream of consecutive sound triplets was presented. Unbeknown to the subjects, triplets were either (a) standard, namely triplets ending with a high probability sound or, (b) statistical deviants, namely triplets ending with a low probability sound. Participants (n = 33) underwent a learning phase outside the scanner followed by an fMRI session. Processing of statistical deviants activated a set of regions encompassing the superior temporal gyrus bilaterally, the right deep frontal operculum including lateral orbitofrontal cortex, and the right premotor cortex. Our results demonstrate that the violation of local dependencies within a statistical learning paradigm does not only engage sensory processes, but is instead reminiscent of the activation pattern during the processing of local syntactic structures in music and language, reflecting the online adaptations required for predictive coding in the context of statistical learning.

The hippocampus, ventromedial prefrontal cortex, and episodic and semantic memory

The human ventromedial prefrontal cortex (vmPFC)/anterior cingulate cortex is implicated in reward and emotion, but also in memory. It is shown how the human orbitofrontal cortex connecting with the vmPFC and anterior cingulate cortex provide a route to the hippocampus for reward and emotional value to be incorporated into episodic memory, enabling memory of where a reward was seen. It is proposed that this value component results in primarily episodic memories with some value component to be repeatedly recalled from the hippocampus so that they are more likely to become incorporated into neocortical semantic and autobiographical memories. The same orbitofrontal and anterior cingulate regions also connect in humans to the septal and basal forebrain cholinergic nuclei, thereby helping to consolidate memory, and helping to account for why damage to the vMPFC impairs memory. The human hippocampus and vmPFC thus contribute in complementary ways to forming episodic and semantic memories.

Strategic decision making and prediction differences in autism

Background

Several theories in autism posit that common aspects of the autism phenotype may be manifestations of an underlying differentiation in predictive abilities. The present study investigates this hypothesis in the context of strategic decision making in autistic participants compared to a control group.

Method

Autistic individuals (43 adults, 35 male) and a comparison group (42 adults, 35 male) of age and gender matched individuals, played a modified version of the prisoner's dilemma (PD) task where they were asked, if capable, to predict their opponents' move. The predictive performance of the two groups was assessed.

Results

Overall, participants in the autism group had a significantly lower number of correct predictions. Moreover, autistic participants stated, significantly more frequently than the comparison group, that they were unable to make a prediction. When attempting a prediction however, the success ratio did not differ between the two groups.

Conclusions

These findings indicate that there is a difference in prediction performance between the two groups. Although our task design does not allow us to identify whether this difference is due to difficulty to form a prediction or a reluctance in registering one, these findings could justify a role for prediction in strategic decision making during the PD task.

Shared and unique neural circuitry underlying temporally unpredictable threat and reward processing

Temporally unpredictable stimuli influence behavior across species, as previously demonstrated for sequences of simple threats and rewards with fixed or variable onset. Neuroimaging studies have identified a specific frontolimbic circuit that may become engaged during the anticipation of temporally unpredictable threat (U-threat). However, the neural mechanisms underlying processing of temporally unpredictable reward (U-reward) are incompletely understood. It is also unclear whether these processes are mediated by overlapping or distinct neural systems. These knowledge gaps are noteworthy given that disruptions within these neural systems may lead to maladaptive response to uncertainty. Here, using functional magnetic resonance imaging data from a sample of 159 young adults, we showed that anticipation of both U-threat and U-reward elicited activation in the right anterior insula, right ventral anterior nucleus of the thalamus and right inferior frontal gyrus. U-threat also activated the right posterior insula and dorsal anterior cingulate cortex, relative to U-reward. In contrast, U-reward elicited activation in the right fusiform and left middle occipital gyrus, relative to U-threat. Although there is some overlap in the neural circuitry underlying anticipation of U-threat and U-reward, these processes appear to be largely mediated by distinct circuits. Future studies are needed to corroborate and extend these preliminary findings.

Advances in understanding meso-cortico-limbic-striatal systems mediating risky reward seeking

The risk of an aversive consequence occurring as the result of a reward-seeking action can have a profound effect on subsequent behavior. Such aversive events can be described as punishers, as they decrease the probability that the same action will be produced again in the future and increase the exploration of less risky alternatives. Punishment can involve the omission of an expected rewarding event ("negative" punishment) or the addition of an unpleasant event ("positive" punishment). Although many individuals adaptively navigate situations associated with the risk of negative or positive punishment, those suffering from substance use disorders or behavioral addictions tend to be less able to curtail addictive behaviors despite the aversive consequences associated with them. Here, we discuss the psychological processes underpinning reward seeking despite the risk of negative and positive punishment and consider how behavioral assays in animals have been employed to provide insights into the neural mechanisms underlying addictive disorders. We then review the critical contributions of dopamine signaling to punishment learning and risky reward seeking, and address the roles of interconnected ventral striatal, cortical, and amygdala regions to these processes. We conclude by discussing the ample opportunities for future study to clarify critical gaps in the literature, particularly as related to delineating neural contributions to distinct phases of the risky decision-making process.

Partial integration of the components of value in anterior cingulate cortex

Evaluation often involves integrating multiple determinants of value, such as the different possible outcomes in risky choice. A brain region can be placed either before or after a presumed evaluation stage by measuring how responses of its neurons depend on multiple determinants of value. A brain region could also, in principle, show partial integration, which would indicate that it occupies a middle position between (preevaluative) nonintegration and (postevaluative) full integration. Existing mathematical techniques cannot distinguish full from partial integration and therefore risk misidentifying regional function. Here we use a new Bayesian regression-based approach to analyze responses of neurons in dorsal anterior cingulate cortex (dACC) to risky offers. We find that dACC neurons only partially integrate across outcome dimensions, indicating that dACC cannot be assigned to either a pre- or postevaluative position. Neurons in dACC also show putative signatures of value comparison, thereby demonstrating that comparison does not require complete evaluation before proceeding. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice

We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; but we lack a rigorous biophysical description of how basic circuit properties, such as excitatory-inhibitory (E/I) tone and cascading nonlinearities, shape attribute processing and choice behavior. Furthermore, how such properties govern choice performance under varying levels of environmental uncertainty is unknown. We investigated two-attribute, two-alternative decision-making in a dynamical, cascading nonlinear neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a final layer producing the decision. Depending on intermediate layer E/I tone, the network displays distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option's attribute information is additively integrated. In regime III, time-varying nonlinear operations amplify the separation between offer distributions by selectively attending to the attribute with the larger differences in input values. At low environmental uncertainty, a linear combination most consistently selects higher valued alternatives. However, at high environmental uncertainty, regime III is more likely than a linear operation to select alternatives with higher value. Furthermore, there are conditions where readout from the intermediate layer could be experimentally indistinguishable from the final layer. Finally, these principles are used to examine multi-attribute decisions in systems with reduced inhibitory tone, leading to predictions of different choice patterns and overall performance between those with restrictions on inhibitory tone and neurotypicals.

Neural Correlates of Strategy Switching in the Macaque Orbital Prefrontal Cortex

We can adapt flexibly to environment changes and search for the most appropriate rule to a context. The orbital prefrontal cortex (PFo) has been associated with decision making, rule generation and maintenance, and more generally has been considered important for behavioral flexibility. To better understand the neural mechanisms underlying the flexible behavior, we studied the ability to generate a switching signal in monkey PFo when a strategy is changed. In the strategy task, we used a visual cue to instruct two male rhesus monkeys either to repeat their most recent choice (i.e., stay strategy) or to change it (i.e., shift strategy). To identify the strategy switching-related signal, we compared nonswitch and switch trials, which cued the same or a different strategy from the previous trial, respectively. We found that the switching-related signal emerged during the cue presentation and it was combined with the strategy signal in a subpopulation of cells. Moreover, the error analysis showed that the activity of the switch-related cells reflected whether the monkeys erroneously switched or not the strategy, rather than what was required for that trial. The function of the switching signal could be to prompt the use of different strategies when older strategies are no longer appropriate, conferring the ability to adapt flexibly to environmental changes. In our task, the switching signal might contribute to the implementation of the strategy cued, overcoming potential interference effects from the strategy previously cued. Our results support the idea that ascribes to PFo an important role for behavioral flexibility.SIGNIFICANCE STATEMENT We can flexibly adapt our behavior to a changing environment. One of the prefrontal areas traditionally associated with the ability to adapt to new contingencies is the orbital prefrontal cortex (PFo). We analyzed the switching related activity using a strategy task in which two rhesus monkeys were instructed by a visual cue either to repeat or change their most recent choice, respectively using a stay or a shift strategy. We found that PFo neurons were modulated by the strategy switching signal, pointing to the importance of PFo in behavioral flexibility by generating control over the switching of strategies.

Neural Mechanisms of Reward Prediction Error in Autism Spectrum Disorder

Few studies have explored neural mechanisms of reward learning in ASD despite evidence of behavioral impairments of predictive abilities in ASD. To investigate the neural correlates of reward prediction errors in ASD, 16 adults with ASD and 14 typically developing controls performed a prediction error task during fMRI scanning. Results revealed greater activation in the ASD group in the left paracingulate gyrus during signed prediction errors and the left insula and right frontal pole during thresholded unsigned prediction errors. Findings support atypical neural processing of reward prediction errors in ASD in frontostriatal regions critical for prediction coding and reward learning. Results provide a neural basis for impairments in reward learning that may contribute to traits common in ASD (e.g., intolerance of unpredictability).