A Neuropsychological and Computational Investigation of Past Tense Verb Processing
过去时态动词处理的神经心理学和计算研究
基本信息
- 批准号:0079044
- 负责人:
- 金额:$ 25.41万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2000
- 资助国家:美国
- 起止时间:2000-08-15 至 2005-07-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The simple process of transforming the present tense of an English verb into its past-tense form has dominated the debate between two fundamentally different views of language knowledge and processing. According to traditional, symbolic theories, language knowledge takes the form of explicit rules operating over discrete, symbolic representations. By contrast, according to connectionist or neural-network theories, language processing involves the massively parallel interaction of large numbers of neuron-like processing units. The principal objective of the proposed work is to implement aconnectionist-style computational model that demonstrates the differentialinfluence of semantic and phonological factors on past-tense production and inturn, derives novel predictions that could be assessed by futureneuropsychological testing. The computational simulations will extend preliminary work byJoanisse and Seidenberg in which verb processing involved the parallelinteraction of representations of phonology (both in comprehension andproduction) and their meanings. The proposed simulations will incorporate morerealistic representations and temporal dynamics. An initial stage of modelingwill employ fixed-length phonological representations of monosyllabic verbstems, but a second stage will employ continuous-time trajectories forphonological input and output capable of handling multisyllabic items. Semanticrepresentations will be derived from a number of analyses of large textcorpora, including Lund and Burgess' Hyperspace Analogue to Language (HAL),which will be replicated if necessary in order to make the resulting semanticrepresentations publicly available for unrestricted use by other researchers. The development of a strongly theoretically motivated connectionist computational model of selective impairments in English past-tense formation will not only provide important insights into the role of semantic and phonological representations in lexical processing, but also more generally about the fundamental character of the principal components, and their interactions, in the language system.
英语动词的现在时态转化为过去时态的简单过程一直是语言知识和处理两种根本不同观点之间的争论焦点。根据传统的符号理论,语言知识采取的形式是在离散的符号表征上运行的明确规则。相比之下,根据连接主义或神经网络理论,语言处理涉及大量类似神经元的处理单元的大规模并行交互。本研究的主要目的是实现一个连接主义风格的计算模型,该模型展示了语义和语音因素对过去时态产生的不同影响,并进而得出新的预测,这些预测可以通过未来的神经心理测试进行评估。计算模拟将扩展Joanisse和Seidenberg的初步工作,其中动词处理涉及语音表征(包括理解和产生)及其意义的平行互动。拟议的模拟将纳入更现实的表示和时间动态。建模的初始阶段将采用单音节动词的固定长度的语音表示,但第二阶段将采用连续时间轨迹的语音输入和输出能够处理多音节项目。Semanticrepresentations将来自大量的大型文本语料库的分析,包括隆德和伯吉斯的超空间语言(HAL),这将是复制,如果有必要,以使所产生的semanticrepresentations公开提供给其他研究人员不受限制的使用。 发展一个具有强烈理论动机的英语过去时态形成的选择性损伤的联结主义计算模型,不仅将提供重要的见解,语义和语音表征在词汇加工中的作用,而且更普遍的是关于语言系统中主要成分的基本特征及其相互作用。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
数据更新时间:{{ journalArticles.updateTime }}
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
David Plaut其他文献
Hereditary hemochromatosis.
- DOI:
10.1007/978-1-59259-963-9_54 - 发表时间:
1993 - 期刊:
- 影响因子:0
- 作者:
David Plaut - 通讯作者:
David Plaut
David Plaut的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ truncateString('David Plaut', 18)}}的其他基金
Hemispheric and topographic neural organization of high-level visual representations
高级视觉表征的半球和地形神经组织
- 批准号:
2123069 - 财政年份:2021
- 资助金额:
$ 25.41万 - 项目类别:
Standard Grant
相似国自然基金
Computational Methods for Analyzing Toponome Data
- 批准号:60601030
- 批准年份:2006
- 资助金额:17.0 万元
- 项目类别:青年科学基金项目
相似海外基金
Integrated Computational and Mechanistic Investigation on New Reactivity and Selectivity in Emerging Enzymatic Reactions
新兴酶反应中新反应性和选择性的综合计算和机理研究
- 批准号:
2400087 - 财政年份:2024
- 资助金额:
$ 25.41万 - 项目类别:
Standard Grant
CAREER: Computational and Theoretical Investigation of Actomyosin Contraction Systems
职业:肌动球蛋白收缩系统的计算和理论研究
- 批准号:
2340865 - 财政年份:2024
- 资助金额:
$ 25.41万 - 项目类别:
Continuing Grant
Multi-Scale Experimental and Computational Investigation of Microscale Origins of Ductile Failure
延性破坏微观起源的多尺度实验和计算研究
- 批准号:
2334678 - 财政年份:2024
- 资助金额:
$ 25.41万 - 项目类别:
Standard Grant
Doctoral Dissertation Research: Computational Investigation of Extralinguistic Cognition in Developmental Parsing
博士论文研究:发展句法中语言外认知的计算研究
- 批准号:
2314618 - 财政年份:2023
- 资助金额:
$ 25.41万 - 项目类别:
Standard Grant
Computational investigation of wood combustion in timber buildings
木结构建筑中木材燃烧的计算研究
- 批准号:
2902452 - 财政年份:2023
- 资助金额:
$ 25.41万 - 项目类别:
Studentship
ERI: Computational Investigation of High-Pressure Turbulent Premixed Flames - Physical Insights and Two-Scale Predictive Modeling
ERI:高压湍流预混火焰的计算研究 - 物理见解和两尺度预测建模
- 批准号:
2301829 - 财政年份:2023
- 资助金额:
$ 25.41万 - 项目类别:
Standard Grant
Computational and Experimental Investigation and Design of Protein Interaction Specificity
蛋白质相互作用特异性的计算和实验研究与设计
- 批准号:
10621973 - 财政年份:2023
- 资助金额:
$ 25.41万 - 项目类别:
Experimental and Computational Investigation of Mechanisms Governing Soft Tissue Interfaces
软组织界面控制机制的实验和计算研究
- 批准号:
2225174 - 财政年份:2022
- 资助金额:
$ 25.41万 - 项目类别:
Standard Grant
Computational Chemistry Supported Investigation of Sustainable Organic Coatings
计算化学支持可持续有机涂料的研究
- 批准号:
2748240 - 财政年份:2022
- 资助金额:
$ 25.41万 - 项目类别:
Studentship
Investigation of Continuous-Flow Mixing of Non-Newtonian Fluids with Energy-Efficient Coaxial Mixers through Advanced Flow Visualization Techniques and Computational Fluid Dynamics
通过先进的流动可视化技术和计算流体动力学研究使用节能同轴混合器的非牛顿流体的连续流动混合
- 批准号:
RGPIN-2019-04644 - 财政年份:2022
- 资助金额:
$ 25.41万 - 项目类别:
Discovery Grants Program - Individual