Two main findings emerged from the current study. First, behavioral data indicated that patients were less able to learn to speed up to maximize rewards, which is consistent with a Go learning deficit. The model simulations suggest this deficit may at least in part be due to lower αG parameter, as a regression analysis revealed that individual differences in the tendency to speed up to maximize rewards in the DEV condition is predicted by αG, such that higher parameters were associated with increased speeding. Given that SZ showed a deficit in both αG and the DEV, but not αN or IEV, we feel that the results of the computational model provide further confidence that the deficits specific to Go learning in schizophrenia are reliable. Furthermore, symptom sub-group analyses revealed that, in terms of DEV performance, Go learning deficits are most severe in patients exhibiting greater severity of negative symptoms.
These findings are consistent with our previous probabilistic selection study indicating that SZ is associated with impaired Go learning and intact No Go learning (19
). When viewed in conjunction with neurocomputational models of corticostriatal circuitry in reinforcement learning (7
), the current behavioral and modeling findings are suggestive of potential dysfunction in the direct D1 driven BG pathway leading to abnormalities in using positive feedback to guide behavior, with relatively intact function in the D2 driven, indirect pathway leading to normal use of probabilistic negative feedback in decision making. This BG-based account is supported by other evidence indicating that BG dopamine acts to speed responding toward rewarding cues (42
), as well as pharmacological and animal studies showing that this process likely relies on D1-driven activation and Go learning (44
). However, this interpretation is of course speculative, and cannot be confirmed without conducting a study on unmedicated 1st
episode patients to see if No Go learning improves when patients are treated with D2 blocking antipsychotics.
A second major finding was that SZ patients exhibited a large and reliable reduction in the tendency to make exploratory behavioral adjustments toward responses that could potentially yield larger expected values than those obtained by staying with the status quo. Additionally, given that there was no association between anhedonia and overall RT variability or consecutive variance, anhedonia appears to be selectively associated with the failure to initiate the proactive
strategy of adjusting responses to gather more information in order to reduce uncertainty about potential benefits of alternative behaviors. These findings demonstrate the usefulness of computational modeling approaches to psychiatry (25
We posit that these effects are related to degradations in prefrontal cortical dopaminergic function, often attributed as a source of negative symptoms (28
). This interpretation is supported by our recently reported gene-dose effect of the val/met polymorphism of the COMT gene in healthy individuals performing this same task (36
), which indicated that the val/val genotype was characterized by the lowest degree of uncertainty-driven exploration and the met/met genotype with the greatest degree of exploration. Variations in COMT affect prefrontal, and particularly orbitofrontal, dopamine levels (22
), and a recent study reported a COMT gene dose effect on orbitofrontal activity during reward receipt (54
). Thus together, these studies support the assertion that the val/val genotype shares features of cognitive dysfunction observed in SZ (55
). Finally, ongoing imaging work in healthy individuals (56
), together with other related studies (35
), suggest that relative uncertainty computations associated with exploration are represented in prefrontal cortical activation patterns. Finally, even if the computations of expected reward values are relatively intact in SZ, it is possible that patients with anhedonia explicitly assign a negative expected value to uncertain outcomes, due to their prior expectations (see (51
) for a related model of depression). Regardless of the neural mechanism, our findings suggest that anhedonia may result from an inability to determine when to explore actions that might improve one's ability to obtain rewards.
Of particular interest was that reduced uncertainty-driven exploration correlated with the Avolition-Anhedonia domain on the SANS, but not the Restricted Affect factor. Additionally, the effect was more highly related to anhedonia than avolition. This result is potentially informative about differences in the pathology of these symptom domains. As rated by the SANS, anhedonia reflects a behavioral component of reward seeking (e.g., initiating social activities, sexual interest/and or activity, pursuing recreational activities, number of close relationships), rather than the capacity to experience pleasure, which is often inferred from behavior. Avolition items on the SANS are less related to reward seeking behavior, and more broadly related to the frequency with which patients initiate and persist in many kinds of tasks which is likely to be influenced by a number of factors, such as disorganization, generalized cognitive impairment, and sedation. The significant correlation with anhedonia, but not avolition may therefore reflect that reduced reward seeking behavior in schizophrenia is critically related to the extent to which patients make exploratory choices when they are uncertain about the value of alternative actions and whether they might produce better outcomes than the status quo.
Results should be viewed with certain limitations in mind. First, analyses regarding the role of medication on task performance should be viewed with caution, as CPZ equivalents for atypical medications may not be appropriate and D2 potency classifications provide only a gross estimate of the effects of different antipsychotics. A more definitive test of antipsychotic effects should be conducted in first episode patients tested on and off medications. Second, we did not collect DNA in this study and it is unclear whether the COMT genetic effect observed in healthy individuals on exploration may partially contribute to the effects of anhedonia and SZ reported here. Finally, although the SANS is still the gold standard negative symptom assessment in the field, it has recently been suggested that newer measures being developed in response to the NIMH MATRICS (e.g., (60
)) initiative may provide a more comprehensive and current assessment of negative symptom dimensions. As such, it is unclear whether the relationship reported between SANS anhedonia and exploration may actually reflect some other component of negative symptoms on these newer scales.
In summary, the current findings have important implications for understanding the etiology of schizophrenia. Results from the computational model and behavioral data indicate that patients have deficits in Go learning, which appear to be due to reduced sensitivity to positive prediction errors. Thus patients show a reduced sensitivity to the impact of rewarding outcomes on future behavioral choices. Furthermore, patients display reduced uncertainty-driven exploration, which was specifically associated with greater severity of anhedonia. Thus, patients are less likely to explore, and therefore less likely to discover, that an alternative response might yield more rewarding outcomes. While these deficits are independent of one another in the model, at a clinical level it is easy to imagine how these impairments might amplify one another and result in a narrow behavioral repertoire and a lack of goal-directed, reward-seeking behavior.