Fuzzy-trace theory

Fuzzy-trace theory (FTT) is a theory of cognition originally proposed by Valerie F. Reyna and Charles Brainerd that draws upon dual-trace conceptions to predict and explain cognitive phenomena, particularly in memory and reasoning. The theory has been used in areas such as cognitive psychology, human development, and social psychology to explain, for instance, false memory and its development, probability judgments, medical decision making, risk perception and estimation, and biases and fallacies in decision making. FTT was initially proposed in the 1990s as an attempt to unify findings from the memory and reasoning domains that could not be predicted or explained by earlier approaches to cognition and its development (e.g., constructivism and information processing). One of such challenges was the statistical independence between memory and reasoning, that is, memory for background facts of problem situations is often unrelated to accuracy in reasoning tasks. Such findings called for a rethinking of the memory-reasoning relation, which in FTT took the form of a dual-process theory linking basic concepts from psycholinguistic and Gestalt theory to memory and reasoning. More specifically, FTT posits that people form two types of mental representations about a past event, called verbatim and gist traces. Gist traces are fuzzy representations of a past event (e.g., its bottom-line meaning), hence the name fuzzy-trace theory, whereas verbatim traces are detailed representations of a past event. Although people are capable of processing both verbatim and gist information, they prefer to reason with gist traces rather than verbatim. This implies, for example, that even if people are capable of understanding ratio concepts like probabilities and prevalence rates, which are the standard for the presentation of health- and risk-related data, their choice in decision situations will usually be governed by the bottom-line meaning of it (e.g., "the risk is high" or "the risk is low"; "the outcome is bad" or "the outcome is good") rather than the actual numbers.