Abstract
There is a wealth of evidence showing that increasing the distance between an argument and its head leads to more processing effort, namely, locality effects; these are usually associated with constraints in working memory (DLT: Gibson, 2000; activation-based model: Lewis and Vasishth, 2005). In SOV languages, however, the opposite effect has been found: antilocality (see discussion in Levy et al., 2013). Antilocality effects can be explained by the expectation-based approach as proposed by Levy (2008) or by the activation-based model of sentence processing as proposed by Lewis and Vasishth (2005). We report an eye-tracking and a self-paced reading study with sentences in Spanish together with measures of individual differences to examine the distinction between expectation- and memory-based accounts, and within memory-based accounts the further distinction between DLT and the activation-based model. The experiments show that (i) antilocality effects as predicted by the expectation account appear only for high-capacity readers; (ii) increasing dependency length by interposing material that modifies the head of the dependency (the verb) produces stronger facilitation than increasing dependency length with material that does not modify the head; this is in agreement with the activation-based model but not with the expectation account; and (iii) a possible outcome of memory load on low-capacity readers is the increase in regressive saccades (locality effects as predicted by memory-based accounts) or, surprisingly, a speedup in the self-paced reading task; the latter consistent with good-enough parsing (Ferreira et al., 2002). In sum, the study suggests that individual differences in working memory capacity play a role in dependency resolution, and that some of the aspects of dependency resolution can be best explained with the activation-based model together with a prediction component.
Highlights
Long-distance dependencies have been investigated since Fodor’s (1978) work on parsing strategies, but many questions remainworking memory capacity (WMC) differences in dependency resolution unanswered or only partially answered
This is supported by research that shows that longer dependencies produced (i) locality effects, that is, a slowdown at the region of the dependency resolution when the distance between dependent and head or subcategorizing verb is increased; (ii) Event Related Potential (ERP) measures associated with difficulty (Kluender and Kutas, 1993; Fiebach et al, 2002; but see: Phillips et al, 2005); and (iii) deterioration of response accuracy in speed-accuracy trade-off (SAT) experiments (McElree, 2000; McElree et al, 2003)
A GLMM showed that WMC was a significant predictor of accuracy; Coef = 0.21, SE = 0.10, z = 1.98, p = 0.048
Summary
Long-distance dependencies ( called non-local, filler-gap, or unbounded dependencies) have been investigated since Fodor’s (1978) work on parsing strategies, but many questions remainWMC differences in dependency resolution unanswered or only partially answered. Memory-Based Explanations There is a wealth of evidence showing that increasing the distance between an argument and its head hinders underlying memory processes in some way This is supported by research that shows that longer dependencies produced (i) locality effects, that is, a slowdown (or increase of regressive saccades) at the region of the dependency resolution when the distance between dependent and head or subcategorizing verb (or gap) is increased (either in self-paced reading, eye-tracking experiments, or both; among others: Gibson, 2000; Grodner and Gibson, 2005; Demberg and Keller, 2008; Bartek et al, 2011; Vasishth and Drenhaus, 2011); (ii) Event Related Potential (ERP) measures associated with difficulty (Kluender and Kutas, 1993; Fiebach et al, 2002; but see: Phillips et al, 2005); and (iii) deterioration of response accuracy in speed-accuracy trade-off (SAT) experiments (McElree, 2000; McElree et al, 2003). We discuss two theories that account for the memory-based locality effects: dependency locality theory (DLT; Gibson, 2000) and the activation-based model (Lewis and Vasishth, 2005)
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