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  • 标题:Adaptive Spontaneous Transitions between Two Mechanisms of Numerical Averaging
  • 本地全文:下载
  • 作者:Noam Brezis ; Zohar Z. Bronfman ; Marius Usher
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2015
  • 卷号:5
  • 期号:1
  • DOI:10.1038/srep10415
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:We investigated the mechanism with which humans estimate numerical averages. Participants were presented with 4, 8 or 16 (two-digit) numbers, serially and rapidly (2 numerals/second) and were instructed to convey the sequence average. As predicted by a dual, but not a single-component account, we found a non-monotonic influence of set-size on accuracy. Moreover, we observed a marked decrease in RT as set-size increases and RT-accuracy tradeoff in the 4-, but not in the 16-number condition. These results indicate that in accordance with the normative directive, participants spontaneously employ analytic/sequential thinking in the 4-number condition and intuitive/holistic thinking in the 16-number condition. When the presentation rate is extreme (10 items/sec) we find that, while performance still remains high, the estimations are now based on intuitive processing. The results are accounted for by a computational model postulating population-coding underlying intuitive-averaging and working-memory-mediated symbolic procedures underlying analytical-averaging, with flexible allocation between the two.
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