Examining recognition criterion rigidity during testing using a biased-feedback technique: evidence for adaptive criterion learning.

Recognition models often assume that subjects use specific evidence values (decision criteria) to adaptively parse continuous memory evidence into response categories (e.g., "old," "new"). Although explicit pretest instructions influence criterion placement, these criteria appear extremely resistant to change once testing begins. We tested criterion sensitivity to local feedback using a novel biased-feedback technique designed to tacitly encourage certain errors by indicating they are the correct choices. Experiment 1 demonstrated that fully correct feedback had little effect on criterion placement, whereas biased feedback during Experiments 2 and 3 yielded prominent, durable, and adaptive criterion shifts, with observers reporting that they were unaware of the manipulation in Experiment 3. These data suggest that recognition criteria can be easily modified during testing through a form of feedback learning that operates independently of stimulus characteristics and observers' awareness of the nature of the manipulation. This mechanism may be fundamentally different from criterion shifts following explicit instructions and warnings, or shifts linked to manipulations of stimulus characteristics combined with feedback highlighting those manipulations.