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We used Chinese prenominal relative clauses (RCs) to test the predictions of two competing accounts of sentence comprehension difficulty: the experience-based account of Levy () and the Dependency Locality Theory (DLT; Gibson, ). Given that in Chinese RCs, a classifier and/or a passive marker BEI can be added to the sentence-initial position, we manipulated the presence/absence of classifiers and the presence/absence of BEI, such that BEI sentences were passivized subject-extracted RCs, and no-BEI sentences were standard object-extracted RCs. We conducted two self-paced reading experiments, using the same critical stimuli but somewhat different filler items. Reading time patterns from both experiments showed facilitative effects of BEI within and beyond RC regions, and delayed facilitative effects of classifiers, suggesting that cues that occur before a clear signal of an upcoming RC can help Chinese comprehenders to anticipate RC structures. The data patterns are not predicted by the DLT, but they are consistent with the predictions of experience-based theories.
What theories best characterise the parsing processes triggered upon encountering ambiguity, and what effects do these processes have on eye movement patterns in reading? The present eye-tracking study, which investigated processing of attachment ambiguities of an adjunct in Spanish, suggests that readers sometimes underspecify attachment to save memory resources, consistent with the good-enough account of parsing. Our results confirm a surprising prediction of the good-enough account: high-capacity readers commit to an attachment decision more often than low-capacity participants, leading to more errors and a greater need to reanalyse in garden-path sentences. These results emerged only when we separated functionally different types of regressive eye movements using a scanpath analysis; conventional eye-tracking measures alone would have led to different conclusions. The scanpath analysis also showed that rereading was the dominant strategy for recovering from garden-pathing. Our results may also have broader implications for models of reading processes: reanalysis effects in eye movements occurred late, which suggests that the coupling of oculo-motor control and the parser may not be as tight as assumed in current computational models of eye movement control in reading.
Which repair strategy does the language system deploy when it gets garden-pathed, and what can regressive eye movements in reading tell us about reanalysis strategies? Several influential eye-tracking studies on syntactic reanalysis (Frazier & Rayner, 1982; Meseguer, Carreiras, & Clifton, 2002; Mitchell, Shen, Green, & Hodgson, 2008) have addressed this question by examining scanpaths, i.e., sequential patterns of eye fixations. However, in the absence of a suitable method for analyzing scanpaths, these studies relied on simplified dependent measures that are arguably ambiguous and hard to interpret. We address the theoretical question of repair strategy by developing a new method that quantifies scanpath similarity. Our method reveals several distinct fixation strategies associated with reanalysis that went undetected in a previously published data set (Meseguer et al., 2002). One prevalent pattern suggests re-parsing of the sentence, a strategy that has been discussed in the literature (Frazier & Rayner, 1982); however, readers differed tremendously in how they orchestrated the various fixation strategies. Our results suggest that the human parsing system non-deterministically adopts different strategies when confronted with the disambiguating material in garden-path sentences.
Scanpaths have played an important role in classic research on reading behavior. Nevertheless, they have largely been neglected in later research perhaps due to a lack of suitable analytical tools. Recently, von der Malsburg and Vasishth (2011) proposed a new measure for quantifying differences between scanpaths and demonstrated that this measure can recover effects that were missed with the traditional eyetracking measures. However, the sentences used in that study were difficult to process and scanpath effects accordingly strong. The purpose of the present study was to test the validity, sensitivity, and scope of applicability of the scanpath measure, using simple sentences that are typically read from left to right. We derived predictions for the regularity of scanpaths from the literature on oculomotor control, sentence processing, and cognitive aging and tested these predictions using the scanpath measure and a large database of eye movements. All predictions were confirmed: Sentences with short words and syntactically more difficult sentences elicited more irregular scanpaths. Also, older readers produced more irregular scanpaths than younger readers. In addition, we found an effect that was not reported earlier: Syntax had a smaller influence on the eye movements of older readers than on those of young readers. We discuss this interaction of syntactic parsing cost with age in terms of shifts in processing strategies and a decline of executive control as readers age. Overall, our results demonstrate the validity and sensitivity of the scanpath measure and thus establish it as a productive and versatile tool for reading research.
Eye movement data have proven to be very useful for investigating human sentence processing. Eyetracking research has addressed a wide range of questions, such as recovery mechanisms following garden-pathing, the timing of processes driving comprehension, the role of anticipation and expectation in parsing, the role of semantic, pragmatic, and prosodic information, and so on. However, there are some limitations regarding the inferences that can be made on the basis of eye movements. One relates to the nontrivial interaction between parsing and the eye movement control system which complicates the interpretation of eye movement data. Detailed computational models that integrate parsing with eye movement control theories have the potential to unpack the complexity of eye movement data and can therefore aid in the interpretation of eye movements. Another limitation is the difficulty of capturing spatiotemporal patterns in eye movements using the traditional word-based eyetracking measures. Recent research has demonstrated the relevance of these patterns and has shown how they can be analyzed. In this review, we focus on reading, and present examples demonstrating how eye movement data reveal what events unfold when the parser runs into difficulty, and how the parsing system interacts with eye movement control. WIREs Cogn Sci 2013, 4:125134. doi: 10.1002/wcs.1209 For further resources related to this article, please visit the WIREs website.
Seven experiments using self-paced reading and eyetracking suggest that omitting the middle verb in a double centre embedding leads to easier processing in English but leads to greater difficulty in German. One commonly accepted explanation for the English pattern-based on data from offline acceptability ratings and due to Gibson and Thomas (1999)- is that working-memory overload leads the comprehender to forget the prediction of the upcoming verb phrase (VP), which reduces working-memory load. We show that this VP-forgetting hypothesis does an excellent job of explaining the English data, but cannot account for the German results. We argue that the English and German results can be explained by the parser's adaptation to the grammatical properties of the languages; in contrast to English, German subordinate clauses always have the verb in clause-final position, and this property of German may lead the German parser to maintain predictions of upcoming VPs more robustly compared to English. The evidence thus argues against language- independent forgetting effects in online sentence processing; working-memory constraints can be conditioned by countervailing influences deriving from grammatical properties of the language under study.
Sentence comprehension requires that the comprehender work out who did what to whom. This process has been characterized as retrieval from memory. This review summarizes the quantitative predictions and empirical coverage of the two existing computational models of retrieval and shows how the predictive performance of these two competing models can be tested against a benchmark data-set. We also show how computational modeling can help us better understand sources of variability in both unimpaired and impaired sentence comprehension.
This tutorial analyzes voice onset time (VOT) data from Dongbei (Northeastern) Mandarin Chinese and North American English to demonstrate how Bayesian linear mixed models can be fit using the programming language Stan via the R package brms. Through this case study, we demonstrate some of the advantages of the Bayesian framework: researchers can (i) flexibly define the underlying process that they believe to have generated the data; (ii) obtain direct information regarding the uncertainty about the parameter that relates the data to the theoretical question being studied; and (iii) incorporate prior knowledge into the analysis. Getting started with Bayesian modeling can be challenging, especially when one is trying to model one’s own (often unique) data. It is difficult to see how one can apply general principles described in textbooks to one’s own specific research problem. We address this barrier to using Bayesian methods by providing three detailed examples, with source code to allow easy reproducibility. The examples presented are intended to give the reader a flavor of the process of model-fitting; suggestions for further study are also provided. All data and code are available from: https://osf.io/g4zpv.
We present the fundamental ideas underlying statistical hypothesis testing using the frequentist framework. We start with a simple example that builds up the one-sample t-test from the beginning, explaining important concepts such as the sampling distribution of the sample mean, and the iid assumption. Then, we examine the meaning of the p-value in detail and discuss several important misconceptions about what a p-value does and does not tell us. This leads to a discussion of Type I, II error and power, and Type S and M error. An important conclusion from this discussion is that one should aim to carry out appropriately powered studies. Next, we discuss two common issues that we have encountered in psycholinguistics and linguistics: running experiments until significance is reached and the ‘garden-of-forking-paths’ problem discussed by Gelman and others. The best way to use frequentist methods is to run appropriately powered studies, check model assumptions, clearly separate exploratory data analysis from planned comparisons decided upon before the study was run, and always attempt to replicate results.