A computational neuroimaging study of reinforcement learning and goal-directed exploration in schizophrenia spectrum disorders.

BACKGROUND: Prior evidence indicates that negative symptom severity and cognitive deficits, in people with schizophrenia (PSZ), relate to measures of reward-seeking and loss-avoidance behavior (implicating the ventral striatum/VS), as well as uncertainty-driven exploration (reliant on rostrolateral prefrontal cortex/rlPFC). While neural correlates of reward-seeking and loss-avoidance have been examined in PSZ, neural correlates of uncertainty-driven exploration have not. Understanding neural correlates of uncertainty-driven exploration is an important next step that could reveal insights to how this mechanism of cognitive and negative symptoms manifest at a neural level. METHODS: We acquired fMRI data from 29 PSZ and 36 controls performing the Temporal Utility Integration decision-making task. Computational analyses estimated parameters corresponding to learning rates for both positive and negative reward prediction errors (RPEs) and the degree to which participates relied on representations of relative uncertainty. Trial-wise estimates of expected value, certainty, and RPEs were generated to model fMRI data. RESULTS: Behaviorally, PSZ demonstrated reduced reward-seeking behavior compared to controls, and negative symptoms were positively correlated with loss-avoidance behavior. This finding of a bias toward loss avoidance learning in PSZ is consistent with previous work. Surprisingly, neither behavioral measures of exploration nor neural correlates of uncertainty in the rlPFC differed significantly between groups. However, we showed that trial-wise estimates of relative uncertainty in the rlPFC distinguished participants who engaged in exploratory behavior from those who did not. rlPFC activation was positively associated with intellectual function. CONCLUSIONS: These results further elucidate the nature of reinforcement learning and decision-making in PSZ and healthy volunteers.

Motivational deficits in schizophrenia relate to abnormalities in cortical learning rate signals.

Individuals from across the psychosis spectrum display impairments in reinforcement learning. In some individuals, these deficits may result from aberrations in reward prediction error (RPE) signaling, conveyed by dopaminergic projections to the ventral striatum (VS). However, there is mounting evidence that VS RPE signals are relatively intact in medicated people with schizophrenia (PSZ). We hypothesized that, in PSZ, reinforcement learning deficits often are not related to RPE signaling per se but rather their impact on learning and behavior (i.e., learning rate modulation), due to dysfunction in anterior cingulate and dorsomedial prefrontal cortex (dmPFC). Twenty-six PSZ and 23 healthy volunteers completed a probabilistic reinforcement learning paradigm with occasional, sudden, shifts in contingencies. Using computational modeling, we found evidence of an impairment in trial-wise learning rate modulation (α) in PSZ before and after a reinforcement contingency shift, expressed most in PSZ with more severe motivational deficits. In a subsample of 22 PSZ and 22 healthy volunteers, we found little evidence for between-group differences in VS RPE and dmPFC learning rate signals, as measured with fMRI. However, a follow-up psychophysiological interaction analysis revealed decreased dmPFC-VS connectivity concurrent with learning rate modulation, most prominently in individuals with the most severe motivational deficits. These findings point to an impairment in learning rate modulation in PSZ, leading to a reduced ability to adjust task behavior in response to unexpected outcomes. At the level of the brain, learning rate modulation deficits may be associated with decreased involvement of the dmPFC within a greater RL network.

The role of working memory in analogical mapping.

The impact of a working-memory load on analogical mapping was examined in two experiments, using a dual-task paradigm. In Experiment 1, we used a phonological working-memory load; in Experiment 2, we used a phonological working-memory load and an executive working-memory load. The subjects were required to identify correspondences between visual scenes, either for single objects or for three objects simultaneously. The results indicated that the imposition of either a phonological or an executive working-memory load decreased the frequency with which the subjects identified correspondences between scenes based on relations and increased the frequency with which they identified correspondences based on object attributes. The frequency with which subjects made relational mappings was increased by the instruction to find correspondences for multiple objects in a scene simultaneously, rather than for just one. These results indicate that mapping on the basis of relations places greater demands on both modality-specific buffers and executive components of working memory than does mapping on the basis of object attributes.