A Neuropsychological and Computational Investigation of Past Tense Verb Processing

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。

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.