This chapter explores some of the many different ways of tending to these various, interacting aspects of prediction error minimization in order to prevent misperception. It turns out there are a number of balances, and probabilistic “knobs” that can be tweaked such as to optimize, or fail to optimize, the representation of the world. For example, there might be trade-offs that allow some amount of misperception in order to efficiently explain away sensory input elsewhere; there might also be trade-offs between accuracy and precision, between high level and low levels of the perceptual hierarchy, and, as focused on at the end of this chapter, there is a crucial balance to get right between passive perceptual inference and active inference. In particular, the workings of the brain are compared to the Bayesian workings of a courtroom. The last sections of the chapter consider how this picture of the prediction error minimization mechanism could apply to aspects of mental illness, in particular delusions in schizophrenia and perceptual disturbances in autism.
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