English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 78056/107692 (72%)
造訪人次 : 20079365      線上人數 : 212
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: http://nccur.lib.nccu.edu.tw/handle/140.119/112326

    題名: What counts in estimation? The nature of the preverbal system
    作者: Karolis, Vyacheslav R.
    Butterworth, Brian L.
    貢獻者: 心智、大腦與學習研究中心
    關鍵詞: concept formation;human;language development;Markov chain;mathematics;physiology;psychological model;verbal behavior;Concept Formation;Humans;Language Development;Mathematics;Models, Psychological;Stochastic Processes;Verbal Behavior
    日期: 2016
    上傳時間: 2017-08-31 11:22:56 (UTC+8)
    摘要: It has been proposed that the development of verbal counting is supported by a more ancient preverbal system of estimation, the most widely canvassed candidates being the accumulator originally proposed by Gibbon and colleagues and the analogue magnitude system proposed by Dehaene and colleagues. The aim of this chapter is to assess the strengths and weaknesses of these models in terms of their capacity to emulate the statistical properties of verbal counting. The emphasis is put on the emergence of exact representations, autoscaling, and commensurability of noise characteristics. We also outline the modified architectures that may help improve models' power to meet these criteria. We propose that architectures considered in this chapter can be used to generate predictions for experimental testing and provide an example where we test the hypothesis whether the visual sense of number, ie, ability to discriminate numerosity without counting, entails enumeration of objects.
    關聯: Progress in Brain Research, Volume 227, Pages 29-51
    資料類型: article
    DOI: http://dx.doi.org/10.1016/bs.pbr.2016.04.025
    顯示於類別:[心智‧大腦與學習研究中心 ] 期刊論文


    檔案 描述 大小格式瀏覽次數


    社群 sharing

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - 回饋