About Edible Restaurants: Conflicts between Syntax and Semantics as Revealed by ERPs.

In order to investigate conflicts between semantics and syntax, we recorded ERPs, while participants read Dutch sentences. Sentences containing conflicts between syntax and semantics (Fred eats in asandwich…/Fred eats arestaurant…) elicited an N400. These results show that conflicts between syntax and semantics not necessarily lead to P600 effects and are in line with the processing competition account. According to this parallel account the syntactic and semantic processing streams are fully interactive and information from one level can influence the processing at another level. The relative strength of the cues of the processing streams determines which level is affected most strongly by the conflict. The processing competition account maintains the distinction between the N400 as index for semantic processing and the P600 as index for structural processing.

The Unification Space implemented as a localist neural net: predictions and error-tolerance in a constraint-based parser.

We introduce a novel computer implementation of the Unification-Space parser (Vosse and Kempen in Cognition 75:105-143, 2000) in the form of a localist neural network whose dynamics is based on interactive activation and inhibition. The wiring of the network is determined by Performance Grammar (Kempen and Harbusch in Verb constructions in German and Dutch. Benjamins, Amsterdam, 2003), a lexicalist formalism with feature unification as binding operation. While the network is processing input word strings incrementally, the evolving shape of parse trees is represented in the form of changing patterns of activation in nodes that code for syntactic properties of words and phrases, and for the grammatical functions they fulfill. The system is capable, at least qualitatively and rudimentarily, of simulating several important dynamic aspects of human syntactic parsing, including garden-path phenomena and reanalysis, effects of complexity (various types of clause embeddings), fault-tolerance in case of unification failures and unknown words, and predictive parsing (expectation-based analysis, surprisal effects). English is the target language of the parser described.

In defense of competition during syntactic ambiguity resolution.

In a recent series of publications (Traxler et al. J Mem Lang 39:558-592, 1998; Van Gompel et al. J Mem Lang 52:284-307, 2005; see also Van Gompel et al. (In: Kennedy, et al.(eds) Reading as a perceptual process, Oxford, Elsevier pp 621-648, 2000); Van Gompel et al. J Mem Lang 45:225-258, 2001) eye tracking data are reported showing that globally ambiguous (GA) sentences are read faster than locally ambiguous (LA) counterparts. They argue that these data rule out "constraint-based" models where syntactic and conceptual processors operate concurrently and syntactic ambiguity resolution is accomplished by competition. Such models predict the opposite pattern of reading times. However, this argument against competition is valid only in conjunction with two standard assumptions in current constraint-based models of sentence comprehension: (1) that syntactic competitions (e.g., Which is the best attachment site of the incoming constituent?) are pooled together with conceptual competitions (e.g., Which attachment site entails the most plausible meaning?), and (2) that the duration of a competition is a function of the overall (pooled) quality score obtained by each competitor. We argue that it is not necessary to abandon competition as a successful basis for explaining parsing phenomena and that the above-mentioned reading time data can be accounted for by a parallel-interactive model with conceptual and syntactic processors that do not pool their quality scores together. Within the individual linguistic modules, decision-making can very well be competition-based.

Retrieval and unification of syntactic structure in sentence comprehension: an FMRI study using word-category ambiguity.

Sentence comprehension requires the retrieval of single word information from long-term memory, and the integration of this information into multiword representations. The current functional magnetic resonance imaging study explored the hypothesis that the left posterior temporal gyrus supports the retrieval of lexical-syntactic information, whereas left inferior frontal gyrus (LIFG) contributes to syntactic unification. Twenty-eight subjects read sentences and word sequences containing word-category (noun-verb) ambiguous words at critical positions. Regions contributing to the syntactic unification process should show enhanced activation for sentences compared to words, and only within sentences display a larger signal for ambiguous than unambiguous conditions. The posterior LIFG showed exactly this predicted pattern, confirming our hypothesis that LIFG contributes to syntactic unification. The left posterior middle temporal gyrus was activated more for ambiguous than unambiguous conditions (main effect over both sentences and word sequences), as predicted for regions subserving the retrieval of lexical-syntactic information from memory. We conclude that understanding language involves the dynamic interplay between left inferior frontal and left posterior temporal regions.