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Parsing costs as predictors of reading difficulty: An evaluation using the Potsdam Sentence Corpus
(2008)
The surprisal of a word on a probabilistic grammar constitutes a promising complexity metric for human sentence comprehension difficulty. Using two different grammar types, surprisal is shown to have an effect on fixation durations and regression probabilities in a sample of German readers’ eye movements, the Potsdam Sentence Corpus. A linear mixed-effects model was used to quantify the effect of surprisal while taking into account unigram and bigram frequency, word length, and empirically-derived word predictability; the so-called “early” and “late” measures of processing difficulty both showed an effect of surprisal. Surprisal is also shown to have a small but statistically non-significant effect on empirically-derived predictability itself. This work thus demonstrates the importance of including parsing costs as a predictor of comprehension difficulty in models of reading, and suggests that a simple identification of syntactic parsing costs with early measures and late measures with durations of post-syntactic events may be difficult to uphold.
Eye fixation durations during normal reading correlate with processing difficulty but the specific cognitive mechanisms reflected in these measures are not well understood. This study finds support in German readers’ eyefixations for two distinct difficulty metrics: surprisal, which reflects the change in probabilities across syntactic analyses as new words are integrated, and retrieval, which quantifies comprehension difficulty in terms of working memory constraints. We examine the predictions of both metrics using a family of dependency parsers indexed by an upper limit on the number of candidate syntactic analyses they retain at successive words. Surprisal models all fixation measures and regression probability. By contrast, retrieval does not model any measure in serial processing. As more candidate analyses are considered in parallel at each word, retrieval can account for the same measures as surprisal. This pattern suggests an important role for ranked parallelism in theories of sentence comprehension.
We examined relations between eye movements (single-fixation durations) and RSVP-based event-related potentials (ERPs; N400’s) recorded during reading the same sentences in two independent experiments. Longer fixation durations correlated with larger N400 amplitudes. Word frequency and predictability of the fixated word as well as the predictability of the upcoming word accounted for this covariance in a path-analytic model. Moreover, larger N400 amplitudes entailed longer fixation durations on the next word, a relation accounted for by word frequency. This pattern offers a neurophysiological correlate for the lag-word frequency effect on fixation durations: Word processing is reliably expressed not only in fixation durations on currently fixated words, but also in those on subsequently fixated words.
Human information processing depends critically on continuous predictions about upcoming events, but the temporal convergence of expectancy-based top-down and input-driven bottom-up streams is poorly understood. We show that, during reading, event-related potentials differ between exposure to highly predictable and unpredictable words no later than 90 ms after visual input. This result suggests an extremely rapid comparison of expected and incoming visual information and gives an upper temporal bound for theories of top-down and bottom-up interactions in object recognition.
Microsaccades are very small, involuntary flicks in eye position that occur on average once or twice per second during attempted visual fixation. Microsaccades give rise to EMG eye muscle spikes that can distort the spectrum of the scalp EEG and mimic increases in gamma band power. Here we demonstrate that microsaccades are also accompanied by genuine and sizeable cortical activity, manifested in the EEG. In three experiments, high-resolution eye movements were corecorded with the EEG: during sustained fixation of checkerboard and face stimuli and in a standard visual oddball task that required the counting of target stimuli. Results show that microsaccades as small as 0.15° generate a field potential over occipital cortex and midcentral scalp sites 100 –140 ms after movement onset, which resembles the visual lambda response evoked by larger voluntary saccades. This challenges the standard assumption of human brain imaging studies that saccade-related brain activity is precluded by fixation, even when fully complied with. Instead, additional cortical potentials from microsaccades were present in 86% of the oddball task trials and of similar amplitude as the visual response to stimulus onset. Furthermore, microsaccade probability varied systematically according to the proportion of target stimuli in the oddball task, causing modulations of late stimulus-locked event-related potential (ERP) components. Microsaccades present an unrecognized source of visual brain signal that is of interest for vision research and may have influenced the data of many ERP and neuroimaging studies.
Elderly adults (N = 116; average age = 73 years) were randomly assigned to one of four treatment groups varying in the amount of training and testing on fluid intelligence tests. They were compared before and after treatment on self-efficacy and utility beliefs for intelligence tests and everyday competence. Although both ability training and extended retest practice resulted in significant gains in objective test performance (Baltes, Kliegl, & Dittmann-Kohli, 1988), only ability training resulted in positive changes in self-efficacy. However, these changes were restricted to testrelated self-efficacy. Training had no impact on perceived utility or on everyday self-efficacy beliefs. Implications of the results are discussed with regard to interventions to increase intellectual self-efficacy in elderly persons.
Computational models such as E-Z Reader and SWIFT are ideal theoretical tools to test quantitatively our current understanding of eye-movement control in reading. Here we present a mathematical analysis of word skipping in the E-Z Reader model by semianalytic methods, to highlight the differences in current modeling approaches. In E-Z Reader, the word identification system must outperform the oculomotor system to induce word skipping. In SWIFT, there is competition among words to be selected as a saccade target. We conclude that it is the question of competitors in the “game” of word skipping that must be solved in eye movement research.
Mathematical models have become an important tool for understanding the control of eye movements during reading. Main goals of the development of the SWIFT model (Engbert, Longtin, & Kliegl, 2002)were to investigate the possibility of spatially distributed processing and to implement a general mechanism for all types of eye movements we observe in reading experiments. Here, we present an advanced version of SWIFT which integrates properties of the oculomotor system and effects of word recognition to explain many of the experimental phenomena faced in reading research. We propose new procedures for the estimation of model parameters and for the test of the model’s performance. A mathematical analysis of the dynamics of the SWIFT model is presented. Finally, within this framework, we present an analysis of the transition from parallel to serial processing.
We investigate the cognitive control in polyrhythmic hand movements as a model paradigm for bimanual coordination. Using a symbolic coding of the recorded time series, we demonstrate the existence of qualitative transitions induced by experimental manipulation of the tempo. A nonlinear model with delayed feedback control is proposed, which accounts for these dynamical transitions in terms of bifurcations resulting from variation of the external control parameter. Furthermore, it is shown that transitions can also be observed due to fluctuations in the timing control level. We conclude that the complexity of coordinated bimanual movements results from interactions between nonlinear control mechanisms with delayed feedback and stochastic timing components.