Number feature distortion modulates cue-based retrieval in reading

Sentences with doubly center-embedded relative clauses in which a verb phrase (VP) is missing are sometimes perceived as grammatical, thus giving rise to an illusion of grammaticality. In this paper, we provide a new account of why missing-VP sentences, which are both complex and ungrammatical, lead to an illusion of grammaticality, the so-called missing-VP effect. We propose that the missing-VP effect in particular, and processing difficulties with multiply center-embedded clauses more generally, are best understood as resulting from interference during cue-based retrieval. When processing a sentence with double center-embedding, a retrieval error due to interference can cause the verb of an embedded clause to be erroneously attached into a higher clause. This can lead to an illusion of grammaticality in the case of missing-VP sentences and to processing complexity in the case of complete sentences with double center-embedding. Evidence for an interference account of the missing-VP effect comes from experiments that have investigated the missing-VP effect in German using a speeded grammaticality judgments procedure. We review this evidence and then present two new experiments that show that the missing-VP effect can be found in German also with less restricting procedures. One experiment was a questionnaire study which required grammaticality judgments from participants without imposing any time constraints. The second experiment used a self-paced reading procedure and did not require any judgments. Both experiments confirm the prior findings of missing-VP effects in German and also show that the missing-VP effect is subject to a primacy effect as known from the memory literature. Based on this evidence, we argue that an account of missing-VP effects in terms of interference during cue-based retrieval is superior to accounts in terms of limited memory resources or in terms of experience with embedded structures.

The target article makes a strong case that L2 comprehenders recover linguistic representations that are qualitatively similar to those recovered by L1 comprehenders. Moreover as they attempt to link non-adjacent elements, they do so using the same basic mechanism: cue-based retrieval in a content-addressable memory (Van Dyke & Lewis, 2003). In this commentary, I will not address the empirical adequacy of the argument, but instead consider some interesting theoretical challenges it poses for our understanding of working memory in sentence processing.

A preliminary investigation of dispositional affect, the P300, and sentence processing

The scrambling complexity hypothesis based on working memory or locality accounts as well as syntactic accounts have proposed that processing a scrambled structure is difficult. However, the locus of this difficulty in sentence processing remains debatable. Several studies on multiple languages have explored the effect of scrambling on sentence processing and not all languages have shown an advantage for the canonical word order. Using a self-paced reading paradigm, we studied the effect of scrambling on semantic anomaly detection in Hindi sentence comprehension employing three word order types. Reading times on critical verbs, judgment latency, and error rates showed significant effect of word order type. The results further revealed significant interactions between word order and anomaly type. The patterns of results suggest that the canonical word order does not necessarily have a processing advantage in terms of speed and accuracy over non-canonical orders and do not provide support to sentence processing accounts that assume an advantage for canonical structures. The results indicate that processing speed depends on the distance between the subject and the verb, thus supporting a locality dependent working memory based model of sentence processing. The results provide evidence for the role of specific cognitive processes in Hindi sentence processing with further implications for language and literacy acquisition in Hindi.

Set-shifting and the on-line processing of relative clauses in Parkinson's disease: Results from a novel eye-tracking method

This chapter presents psycholinguistic evidence for “default correspondences” – canonical mappings between semantic roles and constituent ordering – in the comprehension of two types of noun phrase mismatch: possessive free relatives and quantificational nouns. Experiments showed that possessive free relatives were processed more slowly and comprehended less accurately than normal possessive relatives, whereas quantificational nouns were processed more quickly and understood more accurately than normal binominal noun phrases. Following Townsend & Bever (2001), possessive free relatives cause processing difficulty because the position of the head violates the default, leading to confusion in semantic role assignment. Quantificational nouns do not violate the default in this way. One implication is that default correspondences may help limit mismatch in languages through their role in sentence comprehension.

Hybrid computational models for the characterization of oil and gas reservoirs

Contents: C. Clifton, Jr., L. Frazier, K. Rayner, Introduction. Part I:Sentence Processing and the Brain. L. Osterhout, Event-Related Brain Potentials as Tools for Comprehending Language Comprehension. P. Hagoort, C. Brown, Brain Responses to Lexical Ambiguity Resolution and Parsing. Part II:Phonological Processing. P. Zwitserlood, Access to Phonological-Form Representations in Language Comprehension and Production. C.M. Connine, Vertical and Horizontal Similarity in Spoken-Word Recognition. Part III:Syntactic Processing: Information Flow and Decision Making. M.C. MacDonald, N.J. Pearlmutter, M.S. Seidenberg, Syntactic Ambiguity Resolution as Lexical Ambiguity Resolution. J.C. Trueswell, M.K. Tanenhaus, Toward a Lexicalist Framework of Constraint-Based Syntactic Ambiguity Resolution. E. Gibson, N.J. Pearlmutter, A Corpus-Based Analysis of Psycholinguistic Constraints on Prepositional-Phrase Attachment. M. Pickering, S. Barton, R. Shillcock, Unbounded Dependencies, Island Constraints, and Processing Complexity. M. Bader, I. Lasser, German Verb-Final Clauses and Sentence Processing: Evidence for Immediate Attachment. Part IV:Syntactic Processing and Computational Models. M.W. Crocker, On the Nature of the Principle-Based Sentence Processor. O. Rambow, A.K. Joshi, A Processing Model for Free Word-Order Languages. E.P. Stabler, The Finite Connectivity of Linguistic Structure. Part V:Referential Processing. S. Garrod, Resolving Pronouns and Other Anaphoric Devices: The Case for Diversity in Discourse Processing. W.S. Murray, S.P. Liversedge, Referential Context Effects on Syntactic Processing. J. Sedivy, M. Spivey-Knowlton, The Use of Structural, Lexical, and Pragmatic Information in Parsing Attachment Ambiguities. M. Spivey-Knowlton, M.K. Tanenhaus, Referential Context and Syntactic Ambiguity Resolution. Part VI:Sentence Processing and Language Acquisition. S. Crain, W. Ni, L. Conway, Learning, Parsing and Modularity.

A Distributed Denial of Service (DDoS) attack occurs when large amounts of traffic from hundreds, thousands, or even millions of other computers are routed to a network or server to crash the system and disrupt its function. These attacks are commonly used to shut down websites or applications temporarily. Such problems often need to be addressed with models that can manage the time information contained in network traffic flows. In this work, we apply a Hybrid Deep Learning method to detect malicious web traffic in the form of DDoS attacks, controlling the web flow of information reaching a server, using any dependencies between the different elements of a data stream. An original and cutting-edge Hierarchical Temporal Memory (HTM) hybrid model has been proposed. The operation of this model is predicated primarily on the portion of the cerebral cortex known as the neocortex. The neocortex is in charge of various fundamental brain functions, including the perception of senses, the comprehension of language, and the control of movement. For the hybrid implementation to be capable of encoding time sequences that incorporate incoming data, a Long Short-Term Memory (LSTM) shell is added.

This study investigated the nature of the underlying working memory system supporting sentence processing through examining individual differences in sensitivity to retrieval interference effects during sentence comprehension. Interference effects occur when readers incorrectly retrieve sentence constituents which are similar to those required during integrative processes. We examined interference arising from a partial match between distracting constituents and syntactic and semantic cues, and related these interference effects to performance on working memory, short-term memory (STM), vocabulary, and executive function tasks. For online sentence comprehension, as measured by self-paced reading, the magnitude of individuals' syntactic interference effects was predicted by general WM capacity and the relation remained significant when partialling out vocabulary, indicating that the effects were not due to verbal knowledge. For offline sentence comprehension, as measured by responses to comprehension questions, both general WM capacity and vocabulary knowledge interacted with semantic interference for comprehension accuracy, suggesting that both general WM capacity and the quality of semantic representations played a role in determining how well interference was resolved offline. For comprehension question reaction times, a measure of semantic STM capacity interacted with semantic but not syntactic interference. However, a measure of phonological capacity (digit span) and a general measure of resistance to response interference (Stroop effect) did not predict individuals' interference resolution abilities in either online or offline sentence comprehension. The results are discussed in relation to the multiple capacities account of working memory (e.g., Martin and Romani, 1994; Martin and He, 2004), and the cue-based retrieval parsing approach (e.g., Lewis et al., 2006; Van Dyke et al., 2014). While neither approach was fully supported, a possible means of reconciling the two approaches and directions for future research are proposed.

Time Course of fMRI-Activation in Language and Spatial Networks during Sentence Comprehension

Modern integrative systems biology defines itself by the complexity of the problems it takes on through computational modeling and simulation. However in integrative systems biology computers do not solve problems alone. Problem solving depends as ever on human cognitive resources. Current philosophical accounts hint at their importance, but it remains to be understood what roles human cognition plays in computational modeling. In this paper we focus on practices through which modelers in systems biology use computational simulation and other tools to handle the cognitive complexity of their modeling problems so as to be able to make significant contributions to understanding, intervening in, and controlling complex biological systems. We thus show how cognition, especially processes of simulative mental modeling, is implicated centrally in processes of model-building. At the same time we suggest how the representational choices of what to model in systems biology are limited or constrained as a result. Such constraints help us both understand and rationalize the restricted form that problem solving takes in the field and why its results do not always measure up to expectations.

Determiner phrases (DPs), an overarching term, can be classified into two determiner types: referential determiner phrases (RDPs, e.g., the boy) and quantificational determiner phrases (QDPs, e.g., each boy). Using the event-related potential (ERP) technique, this study explored the modulation of RDP vs. QDP in the online processing of English subject-verb agreement with omission errors by Chinese learners of English, addressing the question of whether singular quantification increases or decreases Chinese learners' sensitivity to agreement violations. The experiment manipulated the determiner type, specifically RDP vs. QDP, and grammaticality (grammatical vs. ungrammatical). The results indicated that similar to previous studies, a P600 effect was elicited in response to subject-verb agreement violations with omission errors, demonstrating that Chinese L2 learners are sensitive to such agreement violations. Additionally, the ERP patterns exhibited variations due to D-linking and number specification of RDP and QDP. Regarding D-linking, subject-verb agreement violations in the QDP conditions, necessitating integration of discourse-related knowledge, elicited laterally and frontally distributed P600 effects associated with integration complexity at the discourse level; however, non-D-linked referential determiners elicited the posteriorly-distributed P600 effects. Differences in number specification resulted in the distinctive P600 latencies and whether P600 was preceded by N400 or not. While both the RDP and QDP conditions exhibited the P600 effects, the onset latency of this effect in the number-unspecified RDP condition was 300 ms later compared to the number-specified QDP condition. Furthermore, an additional N400 component observed in the RDP condition suggests that L2 learners acquire morphologically complex subject-verb agreements by rote, treating them as unanalyzed chunks. This N400 component was absent in the QDP condition. From these results, the conclusion can be drawn that L2 learners are sensitive to the subject-verb agreement violations with omission errors, and L2 processing patterns of subject-verb agreement vary with different features of determiners, providing further evidence for the cue-based retrieval model during comprehension of grammatical sentences. Pedagogical implications are provided, and the future research direction is suggested.

This study investigated the role of prosody and word order in identifying the focus of sentences in Japanese. Native Japanese speakers listened to sentences with different types of word order (subject–object–verb (SOV) vs. object–subject–verb (OSV)), prosody (whether the first noun phrase is stressed or not) and preceding contexts (object- vs. subject-wh questions), while processing costs were measured using pupillometry. Although syntactically non-basic OSV was more difficult to process than basic SOV, this processing difficulty was considerably reduced when the supportive context (the subject-wh question) required S to be focused. The time–course analysis of pupillometry revealed that the Japanese speakers immediately used prosodic cues to determine the focus of sentences, but the effect of word order cues for focus was delayed until the sentence-final verb was encountered. This study advances our understanding of the temporal dynamics of focus processing and the interplay between syntactic and information structures in sentence comprehension.

This paper presents a computational framework for modeling hybrid systems in discrete-time. We introduce the class of discrete hybrid automata (DHA) and show its relation with several other existing model paradigms: piecewise affine systems, mixed logical dynamical systems, (extended) linear complementarity systems, min-max-plus-scaling systems. We present HYSDEL (hybrid systems description language), a high-level modeling language for DHA, and a set of tools for translating DHA into any of the former hybrid models. Such a multimodeling capability of HYSDEL is particularly appealing for exploiting a large number of available analysis and synthesis techniques, each one developed for a particular class of hybrid models. An automotive example shows the modeling capabilities of HYSDEL and how the different models allow to use several computational tools.