Diagnosis and repair of negative polarity constructions in the light of symbolic resonance analysis

Drenhaus, Heiner; Graben, Peter beim; Saddy, Douglas; Frisch, Stefan

doi:10.1016/j.bandl.2005.05.001

Cited by 32 publications

(44 citation statements)

References 30 publications

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“…The main finding was that, compared to the grammatical condition (2a), both the inaccessible licensor (2b) and no licensor (2c) conditions showed N400 and P600 components at the Table 1 Judgment accuracies and reaction times in the (Drenhaus, Saddy, & Frisch, 2005) NPI jemals. Because the N400 component, in general, reflects semantic integration problems and violations of selectional restrictions and implausibility (Kutas & Petten, 1994); and because the P600 component reflects syntactic reanalysis and repair (Friederici, 1995(Friederici, , 2002, increased syntactic complexity and ambiguity (Friederici, Hahne, & Saddy, 2002;Frisch, Schlesewsky, Saddy, & Alpermann, 2002;Kaan, Harris, Gibson, & Holcomb, 2000), the results suggested that an NPI occurring in an illegal environment results in both semantic and syntactic processing problems compared to their licensed counterparts (also see Drenhaus, beim Graben, Saddy, & Frisch, 2006).…”

Section: The Intrusion Effectmentioning

confidence: 99%

Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

et al. 2008

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A central question in online human sentence comprehension is, "How are linguistic relations established between different parts of a sentence?" Previous work has shown that this dependency resolution process can be computationally expensive, but the underlying reasons for this are still unclear. This article argues that dependency resolution is mediated by cue-based retrieval, constrained by independently motivated working memory principles defined in a cognitive architecture. To demonstrate this, this article investigates an unusual instance of dependency resolution, the processing of negative and positive polarity items, and confirms a surprising prediction of the cue-based retrieval model: Partialcue matches-which constitute a kind of similarity-based interference-can give rise to the intrusion of ungrammatical retrieval candidates, leading to both processing slow-downs and even errors of judgment that take the form of illusions of grammaticality in patently ungrammatical structures. A notable achievement is that good quantitative fits are achieved without adjusting the key model parameters.

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Section: The Intrusion Effectmentioning

confidence: 99%

Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

et al. 2008

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“…Late positivities which co-vary also with semantic and pragmatic contexts have been reported e.g. by Drenhaus et al (2006). For this reason, Bornkessel and Schlesewsky (2006) propose distinguishing between the P600 and late positivites in their model..3…”

Section: The P600 Component In Language Processingmentioning

confidence: 99%

“…Partitioning the observable space of ERP time series, beim Graben et al (2000, Frisch et al (2004) and Drenhaus et al (2006) were able to describe ERP components by suitable order parameters obtained from a symbolic dynamics of the time series. In this approach, each ERP epoch is represented by a string of length L of a few symbols {a i |i = 1, 2,…, I} which form an epoch ensemble E ¼ fs k ¼ ða ðkÞ i 1 ; .…”

Section: The P600 Component In Language Processingmentioning

confidence: 99%

Towards dynamical system models of language-related brain potentials

2008

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Event-related brain potentials (ERP) are important neural correlates of cognitive processes. In the domain of language processing, the N400 and P600 reflect lexicalsemantic integration and syntactic processing problems, respectively. We suggest an interpretation of these markers in terms of dynamical system theory and present two nonlinear dynamical models for syntactic computations where different processing strategies correspond to functionally different regions in the system's phase space.

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“…Also higher cognitive functions such as language processing and their neural correlates such as event-related brain potentials (ERPs) [23,8,19] might be modeled with leaky integrator networks. Kawamoto [38] used a Hopfield net with exponentially decaying activation and habituating synaptic weights to modeling lexical ambiguity resolution.…”

Section: Cognitive Modelingmentioning

confidence: 99%

Neural and Cognitive Modeling with Networks of Leaky Integrator Units

Graben

Liebscher

Kurths

Understanding Complex Systems

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Summary. After reviewing several physiological findings on oscillations in the electroencephalogram (EEG) and their possible explanations by dynamical modeling, we present neural networks consisting of leaky integrator units as an universal paradigm for neural and cognitive modeling. In contrast to standard recurrent neural networks, leaky integrator units are described by ordinary differential equations living in continuous time. We present an algorithm to train the temporal behavior of leaky integrator networks by generalized backpropagation and discuss their physiological relevance. Eventually, we show how leaky integrator units can be used to build oscillators which may serve as models of brain oscillations and cognitive processing.

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Diagnosis and repair of negative polarity constructions in the light of symbolic resonance analysis

Cited by 32 publications

References 30 publications

Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

Processing Polarity: How the Ungrammatical Intrudes on the Grammatical

Towards dynamical system models of language-related brain potentials

Neural and Cognitive Modeling with Networks of Leaky Integrator Units

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