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An endogenous distributed model of ordering in serial recall
Simon Farrell1, Stephan Lewandowsky
1University of Western Australia, Crawley, Australia.
Psychonomic Bulletin & Review
|May 25, 2002
Summary
We present SOB, a novel distributed memory model for serial order recall. This model accurately predicts recall patterns, error types, and the impact of list length and word frequency.
Area of Science:
- Cognitive Psychology
- Computational Neuroscience
- Memory Models
Background:
- Understanding serial order memory is crucial for cognitive science.
- Existing models face challenges in explaining complex recall phenomena.
- Distributed representations are debated for their ability to support precise recall.
Purpose of the Study:
- Introduce a new distributed model of memory for serial order, named SOB.
- Explain the mechanisms underlying ordered serial recall using endogenous processes.
- Demonstrate the model's ability to account for various empirical findings in memory research.
Main Methods:
- Developed a computational model (SOB) based on distributed representations.
- Simulated encoding and retrieval processes within the model.
- Tested the model's predictions against established data on serial recall.
Main Results:
- SOB accurately reproduces the serial position curve.
- The model explains diverse error patterns: transpositions, omissions, intrusions, and repetitions.
- SOB accounts for list length effects, recall levels, response latency, and word frequency impacts.
Conclusions:
- Distributed representations can support unambiguous serial recall.
- SOB provides a unified framework for understanding serial order memory.
- The model challenges previous assumptions about the limitations of distributed memory systems.
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