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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 31-八月-2017 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
dc.contributor 心智、大腦與學習研究中心zh_TW
dc.creator (作者) Karolis, Vyacheslav R.en_US
dc.creator (作者) Butterworth, Brian L.en_US
dc.date (日期) 2016
dc.date.accessioned 31-八月-2017 11:22:56 (UTC+8)-
dc.date.available 31-八月-2017 11:22:56 (UTC+8)-
dc.date.issued (上傳時間) 31-八月-2017 11:22:56 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112326-
dc.description.abstract (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.en_US
dc.format.extent 210 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Progress in Brain Research, Volume 227, Pages 29-51en_US
dc.subject (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 Behavioren_US
dc.title (題名) What counts in estimation? The nature of the preverbal systemen_US
dc.type (資料類型) article
dc.identifier.doi (DOI) 10.1016/bs.pbr.2016.04.025
dc.doi.uri (DOI) http://dx.doi.org/10.1016/bs.pbr.2016.04.025