Title |
Modeling working memory: An interference model of complex span
|
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Published in |
Psychonomic Bulletin & Review, June 2012
|
DOI | 10.3758/s13423-012-0272-4 |
Pubmed ID | |
Authors |
Klaus Oberauer, Stephan Lewandowsky, Simon Farrell, Christopher Jarrold, Martin Greaves |
Abstract |
This article introduces a new computational model for the complex-span task, the most popular task for studying working memory. SOB-CS is a two-layer neural network that associates distributed item representations with distributed, overlapping position markers. Memory capacity limits are explained by interference from a superposition of associations. Concurrent processing interferes with memory through involuntary encoding of distractors. Free time in-between distractors is used to remove irrelevant representations, thereby reducing interference. The model accounts for benchmark findings in four areas: (1) effects of processing pace, processing difficulty, and number of processing steps; (2) effects of serial position and error patterns; (3) effects of different kinds of item-distractor similarity; and (4) correlations between span tasks. The model makes several new predictions in these areas, which were confirmed experimentally. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 4 | 1% |
Japan | 2 | <1% |
Switzerland | 1 | <1% |
Russia | 1 | <1% |
United Kingdom | 1 | <1% |
United States | 1 | <1% |
Poland | 1 | <1% |
Unknown | 327 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 76 | 22% |
Researcher | 63 | 19% |
Student > Master | 44 | 13% |
Student > Bachelor | 34 | 10% |
Student > Doctoral Student | 21 | 6% |
Other | 50 | 15% |
Unknown | 50 | 15% |
Readers by discipline | Count | As % |
---|---|---|
Psychology | 182 | 54% |
Neuroscience | 24 | 7% |
Computer Science | 11 | 3% |
Social Sciences | 9 | 3% |
Agricultural and Biological Sciences | 8 | 2% |
Other | 43 | 13% |
Unknown | 61 | 18% |