Figure 1.

A schematic diagram of the proposed opportunity cost model. The expected costs and benefits of target and nontarget tasks are estimated (top). These computations give rise to phenomenology (e.g., qualia such as frustration, boredom, flow), which, in turn, motivates the allocation of computational processes to tasks that are expected to optimize costs and benefits. This allocation determines performance, on both the target and nontarget tasks. The experienced costs and benefits then recursively feed into another iteration of the same sequence, with continued adjustment of allocation decisions, but without depletion of any physical resource.