Observer Models
Observer Models
Observer models specify computations that are sufficient to predict the behavior of an observer for many different input stimuli with a small number of parameters. Observer models specify the transformations leading to the relevant internal representations from the stimulus, and define the decision rules for particular tasks. These models have a remarkable ability to summarize compactly the behavioral outcomes in many conditions and provide a conceptual framework within which to understand the responses of the sensory system. In this chapter, we consider both modern single-channel and multichannel observer models. Each observer in a task can be described by a small number of parameters that fully specify how the stimulus is recoded in an internal response and then subjected to a task-relevant decision. Once these parameters have been estimated from specific experimental tests, it is possible to make predictions about an observer’s responses to a wide range of stimuli and paradigms.
Keywords: Internal representations of stimuli, Perceptual template, External noise, Internal noise, Decision rules, Threshold versus contrast (TvC) functions, Double-pass consistency, Single channel model, Multichannel model, Modelfest
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