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A schema is a mental framework that helps individuals organize and interpret information. Schemata, formed from previous experiences, influence how we process new information: how we encode it, the inferences we make, and how we retrieve it. For instance, a schema for what a typical classroom looks like might include desks, a teacher's desk, a whiteboard, and students in such an environment. This expectation helps us quickly understand and navigate new classrooms without needing to analyze...
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Familiarity and categorization processes in memory search.

Robert M Nosofsky1, Rui Cao1, Gregory E Cox1

  • 1Indiana University, Bloomington, United States.

Cognitive Psychology
|September 21, 2014
PubMed
Summary
This summary is machine-generated.

This study tested a memory search model in varied-mapping (VM) and consistent-mapping (CM) tasks. Results show categorization-based processing in CM, where probe repetition affects false alarms and reaction times differently in VM versus CM.

Keywords:
Automatic processingCategorizationExemplar modelFamiliarityMemory searchOld–new recognitionResponse times

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Area of Science:

  • Cognitive Psychology
  • Human Memory Research
  • Computational Neuroscience

Background:

  • Memory search tasks differentiate between varied mappings (VM) and consistent mappings (CM) of items.
  • Distinct performance patterns arise from VM and CM, but quantitative memory-based models are lacking.
  • Understanding these processes is crucial for developing comprehensive models of human memory.

Purpose of the Study:

  • To evaluate a modern exemplar-retrieval model's ability to explain memory search performance in VM and CM tasks.
  • To investigate the roles of familiarity-based and categorization-based processes in memory retrieval.
  • To account for detailed response-time distributions in highly practiced subjects across different memory set sizes.

Main Methods:

  • Conducted probe-recognition experiments using both VM and CM tasks.
  • Tested an exemplar-retrieval model against detailed response-time (RT) distributions.
  • Manipulated negative probe repetition across trials to observe its effects.

Main Results:

  • The exemplar-retrieval model quantitatively accounted for performance across varied memory set sizes.
  • Negative probe repetition significantly increased false-alarm rates and correct-rejection RTs in VM.
  • No significant changes in false-alarm rates or correct-rejection RTs were observed in CM due to probe repetition.

Conclusions:

  • Evidence supports a strong form of categorization-based processing in CM tasks.
  • Observers utilize the "new" category membership of negative probes for recognition decisions in CM.
  • The model successfully captured the dissociation in performance between VM and CM tasks.