The differentiation between positive and negative valence is central to psychiatry. A seemingly categorical distinction between the drive toward rewards vs. the effort to avoid punishment appears central to many symptoms of psychiatric dysfunction and is evident in both how diagnostic categories are delineated and in the definition of cross-diagnostic constructs in RDoC. However, while there has been major progress in understanding how reward drives learning and actions and the underlying neural mechanisms, there has been much less progress in understanding the mechanisms by which loss and punishment affect behavior. Indeed, there has been continued controversy about whether the neural mechanisms of reward and loss are dissociable at all. Studies of the neural bases of reward seeking vs. loss avoidance have yielded mixed results, manifested both in inconsistent findings about shared vs. separate neural circuitry, and in surprising results in psychiatric populations, for instance showing reward processing abnormalities in psychiatric conditions that appear at face value to be driven by avoidance (e.g. OCD and anxiety). This has made it virtually impossible to address the critical question of defining valid measurements for reward seeking vs. loss avoidance separately, let alone for understanding the balance between them and their relation to other dimensional constructs and psychopathology. Here we address this challenge. We build on a computational framework that resolves the inconsistency in existing results by formalizing how avoiding a loss can ? in certain circumstances and in some people ? be reframed as a reward. Here we advance the hypothesis that using computational methods for quantifying and isolating this subjective reframing will allow us better to disentangle the relative, covert contributions of reward seeking vs. loss avoidance, and clarify their neural underpinnings. We propose to test this hypothesis by rigorously assessing the validity of the resulting measures (compared to simpler measures of overt reward and loss behavior) across tasks, measures, and test-retest replications. In particular, we address two specific aims. First, we seek to compare neural and behavioral measures of reward seeking and loss avoidance across tasks and participants using computational models and functional MRI in a large sample of participants. Second, we seek to examine individual differences in reward seeking and loss avoidance learning and their relationship to dimensions of psychiatric symptomatology using a large online sample.
Both aims make use of two parallel and complementary experimental tasks which each test reward seeking, loss avoidance, and the extent to which the balance between the two is affected by differences in baseline expectations of reward or loss. Together, these studies offer an integrative computational framework to test the construct validity of measures of reward seeking and loss avoidance, the relationship between them, the new construct of their relative reframing, and how individual differences in these constructs are manifest across the population in brain and behavior.
The RDoCS framework offers a compelling new organization of behaviorally relevant dimensions for mental health into separate and testable constructs, central among them a differentiation between seeking rewards and avoiding losses. Yet many open questions remain about each of these constructs, their validity across individuals and across measurements, and the extent to which they are really separate vs. overlapping and interacting in both healthy and disordered behavior and brain function. We address these questions with a computational framework that takes into account how, and when, losses can be reframed as rewards, allowing a detailed evaluation of the neural and behavioral substrates of each construct (as well as the new construct of the reframing process itself), their validity across tasks and across time.
