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中文摘要
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描述(申请人提供):该提案中概述的研究旨在使用计算建模和电生理学的方法学新颖组合来产生一个阅读模型,该模型不仅模拟文本理解发生的行为标志-例如词汇决策-而且模拟实例化理解本身的实际大脑过程-例如N400 ERP成分或前颞叶的激活。虽然已经存在许多优秀的阅读模型,但它们中没有一个能够模拟任何生理结果,第一部分是因为很难将功能神经成像数据集减少到适合于计算模拟的参数,第二部分是因为创建包含神经成像数据的模型需要计算建模和神经成像的跨学科专业知识。拟议的研究计划提供了对这两个困难的牵引力;第一个是通过概述一个程序,以便于计算模拟的方式描述丰富的电生理数据(例如,第二个是将卡内基梅隆大学在计算建模方面的卓越表现与伊利诺伊大学在心理生理学研究方面的著名实力结合起来。阅读对于流利的读者来说是一种自动的、毫不费力的技能,以至于它的复杂性以及它受损的严重后果,往往只有在功能障碍时才能被注意到。诵读困难可以通过大脑损伤获得,也可以在教育过程中发展,尽管它很普遍,但人们仍然不太了解。本研究的目的是建立一个基于阅读大脑记录的阅读模型,该模型可以作为针对性治疗发展性和获得性阅读障碍的基础。
英文摘要
DESCRIPTION (provided by applicant): The research outlined in this proposal aims to use a methodologically novel combination of computational modeling and electrophysiology to produce a model of reading that simulates not just the behavioral signifiers that comprehension of text has taken place -- such as lexical decision -- but the actual brain processes that instantiate that comprehension itself -- such as the N400 ERP component or activation of the anterior temporal lobe. While many excellent models of reading already exist, not one of them is able to simulate any physiological results, in first part because it is difficult to reduce functional neuroimaging data sets down to parameters that are appropriate for computational simulation, and in second part because creating a model which incorporates neuroimaging data requires interdisciplinary expertise in both computational modeling and neuroimaging. The proposed research plan provides traction on both of these difficulties; the first by outlining a procedure for describing rich electrophysiological data in a manner tractable for computational simulation (e.g., mean amplitude over a time window), the second by bringing together Carnegie Mellon's excellence in computational modeling with the University of Illinois' noted strength in psychophysiological research. Reading is such an automatic and effortless skill in fluent readers that its complexity, and the serious consequences of its impairment, are often only noticed in dysfunction. Dyslexia can be acquired through brain damage or developed during education, and despite its prevalence s still not well understood. This research aims at developing a model of reading based on recordings from reading brains-a model which can be used as the basis for targeted treatments of both developed and acquired dyslexia.
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Physiologically constrained computational modeling of visual word recognition
  • 批准号:
    7799562
  • 项目类别:
  • 资助金额:
    $5.01万
  • 财政年份:
    2010
  • 负责人:
    Sarah Laszlo
  • 依托单位:
海外基金