Predicting psychosis across diagnostic boundaries: Behavioral and computational modeling evidence for impaired reinforcement learning in schizophrenia and bipolar disorder with a history of psychosis.

Abstract

There is increasing evidence that schizophrenia (SZ) and bipolar disorder (BD) share a number of cognitive, neurobiological, and genetic markers. Shared features may be most prevalent among SZ and BD with a history of psychosis. This study extended this literature by examining reinforcement learning (RL) performance in individuals with SZ (n = 29), BD with a history of psychosis (BD+; n = 24), BD without a history of psychosis (BD-; n = 23), and healthy controls (HC; n = 24). RL was assessed through a probabilistic stimulus selection task with acquisition and test phases. Computational modeling evaluated competing accounts of the data. Each participant's trial-by-trial decision-making behavior was fit to 3 computational models of RL: (a) a standard actor-critic model simulating pure basal ganglia-dependent learning, (b) a pure Q-learning model simulating action selection as a function of learned expected reward value, and (c) a hybrid model where an actor-critic is "augmented" by a Q-learning component, meant to capture the top-down influence of orbitofrontal cortex value representations on the striatum. The SZ group demonstrated greater reinforcement learning impairments at acquisition and test phases than the BD+, BD-, and HC groups. The BD+ and BD- groups displayed comparable performance at acquisition and test phases. Collapsing across diagnostic categories, greater severity of current psychosis was associated with poorer acquisition of the most rewarding stimuli as well as poor go/no-go learning at test. Model fits revealed that reinforcement learning in SZ was best characterized by a pure actor-critic model where learning is driven by prediction error signaling alone. In contrast, BD-, BD+, and HC were best fit by a hybrid model where prediction errors are influenced by top-down expected value representations that guide decision making. These findings suggest that abnormalities in the reward system are more prominent in SZ than BD; however, current psychotic symptoms may be associated with reinforcement learning deficits regardless of a Diagnostic and Statistical Manual of Mental Disorders (5th Edition; American Psychiatric Association, 2013) diagnosis.

Reduced model-based decision-making in schizophrenia.

“…Further, several recent reports examining reward-learning in SZ which also used paradigms that might engage cognitive control relatively more strongly have also failed to show correlations between task performance and negative symptoms. This is consistent with the hypothesis that the role of higher order cognitive processes in decision-making deficits may be somewhat independent of negative symptoms (Collins, et al, 2014; Culbreth, et al, 2015; Strauss, et al, 2015). …”

The effect of limited cognitive resources on communication disturbances in serious mental illness

“…Second, we examined language dysfunction and cognitive resources in SMI in a manner is that consistent with an RDoC approach (Insel et al, 2010). Our results of similar cognitive abilities and performance on the dual-task across our patient groups is consistent with previous findings (Barch, 2009; Barch and Sheffield, 2014; Simonsen et al, 2011; Strauss et al, 2015). While it is somewhat surprising that patients with schizophrenia did not differ in communication disturbances than patients without, it may be the case that patients with bipolar disorder and major depressive disorder who meet federal criteria for SMI–as in our study–exhibit similar communication disturbances as those with schizophrenia.…”

“…First, a broad array of deficits in attention, working memory, concentration and other “on-line” abilities is exhibited in individuals with SMI, and these deficits appear to be similar across SMI boundaries (Mackin and Areán, 2009; Simonsen et al, 2011; Strauss et al, 2015). Second, a number of correlational studies have observed that cognitive deficits are associated with more language impairment in schizophrenia, depression, and mania using behavioral-based procedures/technologies (Becker et al, 2012; Docherty, 2005; Radanovic et al, 2013; Rosenstein et al, 2014).…”

Deficits in reinforcement learning but no link to apathy in patients with schizophrenia

“…In further contrast to some previous studies161920, we found no association of apathy symptoms with a relative preference for loss-avoidance learning or other learning parameters. However, other recent studies have also reported no relation of learning parameters with apathy symptom severity343738.…”