Journal Article10.1037/xlm0001261
Time sharing in working memory processing.
Pierre Barrouillet,Valérie Camos,Takehiro Minamoto,Satoru Nishiyama,Weng-Tink Chooi,Aiko Morita,Robert H. Logie,Satoru Saito +7 more
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TL;DR: This paper investigated WM functioning without focusing exclusively on short-term memory performance by presenting participants with an n-back task on letters, n varying from 0 to 2, each letter being followed by a tone discrimination task involving from one to three tones.
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Abstract: Although working memory (WM) is usually defined as a cognitive system coordinating processing and storage in the short term, in most WM models, memory aspects have been developed more fully than processing systems, and many studies of WM tasks have tended to focus on memory performance. The present study investigated WM functioning without focusing exclusively on short-term memory performance by presenting participants with an n-back task on letters, n varying from 0 to 2, each letter being followed by a tone discrimination task involving from one to three tones. Predictions regarding the reciprocal effects of these tasks on each other were motivated by the time-based resource-sharing (TBRS) theoretical framework for WM that assumes the temporal sharing of attention between processing and memory. Although, as predicted, increasing the n value had a detrimental effect on tone discrimination in terms of accuracy and response times, and increasing the number of tones disrupted speed and accuracy on n-back performance, the overall pattern of results did not perfectly fit the TBRS predictions. Nonetheless, the main alternative models of WM do not seem to offer a complete account. The present findings point toward the need to use a larger range of tasks and situations in designing and testing models of WM. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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Citations
Time sharing in working memory processing.
Pierre Barrouillet,Valérie Camos,Takehiro Minamoto,Satoru Nishiyama,Weng-Tink Chooi,Aiko Morita,Robert H. Logie,Satoru Saito +7 more
TL;DR: This paper investigated WM functioning without focusing exclusively on short-term memory performance by presenting participants with an n-back task on letters, n varying from 0 to 2, each letter being followed by a tone discrimination task involving from one to three tones.
2
Accounting Resource Sharing Management Risk Assessment Model of Artificial Intelligence Algorithm
Li Wang
- 01 Mar 2024
TL;DR: The AI algorithm for risk assessment of accounting resource sharing can accurately assess the risk of accounting information resources and is superior to traditional assessment methods.
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