Self-Consistent Estimation of Mislocated Fixations during Reading

During reading, we generate saccadic eye movements to move words into the center of the visual field for word processing. However, due to systematic and random errors in the oculomotor system, distributions of within-word landing positions are rather broad and show overlapping tails, which suggests that a fraction of fixations is mislocated and falls on words to the left or right of the selected target word. Here we propose a new procedure for the self-consistent estimation of the likelihood of mislocated fixations in normal reading. Our approach is based on iterative computation of the proportions of several types of oculomotor errors, the underlying probabilities for word-targeting, and corrected distributions of landing positions. We found that the average fraction of mislocated fixations ranges from about 10% to more than 30% depending on word length. These results show that fixation probabilities are strongly affected by oculomotor errors

Reading sentences of uniform word length II: very rapid adaptation of the preferred saccade length

In the current study we investigated whether readers adjust their preferred saccade length (PSL) during reading on a trial-by-trial basis. The PSL refers to the distance between a saccade launch site and saccade target (i.e., the word center during reading) when participants neither undershoot nor overshoot this target (McConkie, Kerr, Reddix, & Zola, 1988). The tendency for saccades longer or shorter than the PSL to under or overshoot their target is referred to as the range error. Recent research by Cutter, Drieghe, and Liversedge (2017) has shown that the PSL changes to be shorter when readers are presented with thirty consecutive sentences exclusively made of three letter words, and longer when presented with thirty consecutive sentences exclusively made of five letter words. We replicated and extended this work by this time presenting participants with these uniform sentences in an unblocked design. We found that adaptation still occurred across different sentence types despite participants only having one trial to adapt. Our analyses suggested that this effect was driven by the length of the words readers were making saccades away from, rather than the length of the words in the rest of the sentence. We propose an account of the range error in which readers use parafoveal word length information to estimate the length of a saccade between the centre of two parafoveal words (termed the Centre-Based Saccade Length) prior to landing on the first of these words

Is preview benefit from word n + 2 a common effect in reading Chinese? Evidence from eye movements

Although most studies of reading English (and other alphabetic languages) have indicated that readers do not obtain preview benefit from word n + 2, Yang, Wang, Xu, and Rayner (2009) reported evidence that Chinese readers obtain preview benefit from word n + 2. However, this effect may not be common in Chinese because the character prior to the target word in Yang et al.’s experiment was always a very high frequency function word. In the current experiment, we utilized a relatively low frequency word n + 1 to examine whether an n + 2 preview benefit effect would still exist and failed to find any preview benefit from word n + 2. These results are consistent with a recent study which indicated that foveal load modulates the perceptual span during Chinese reading (Yan, Kliegl, Shu, Pan, & Zhou, 2010). Implications of these results for models of eye movement control are discussed

Deep Eyedentification: Biometric Identification using Micro-Movements of the Eye

We study involuntary micro-movements of the eye for biometric identification. While prior studies extract lower-frequency macro-movements from the output of video-based eye-tracking systems and engineer explicit features of these macro-movements, we develop a deep convolutional architecture that processes the raw eye-tracking signal. Compared to prior work, the network attains a lower error rate by one order of magnitude and is faster by two orders of magnitude: it identifies users accurately within seconds

Seeing two faces together: preference formation in humans and rhesus macaques

Humans, great apes and old world monkeys show selective attention to faces depending on conspecificity, familiarity, and social status supporting the view that primates share similar face processing mechanisms. Although many studies have been done on face scanning strategy in monkeys and humans, the mechanisms influencing viewing preference have received little attention. To determine how face categories influence viewing preference in humans and rhesus macaques (Macaca mulatta), we performed two eye-tracking experiments using a visual preference task whereby pairs of faces from different species were presented simultaneously. The results indicated that viewing time was significantly influenced by the pairing of the face categories. Humans showed a strong bias towards an own-race face in an Asian–Caucasian condition. Rhesus macaques directed more attention towards non-human primate faces when they were paired with human faces, regardless of the species. When rhesus faces were paired with faces from Barbary macaques (Macaca sylvanus) or chimpanzees (Pan troglodytes), the novel species’ faces attracted more attention. These results indicate that monkeys’ viewing preferences, as assessed by a visual preference task, are modulated by several factors, species and dominance being the most influential

Defining eye-fixation sequences across individuals and tasks: the Binocular-Individual Threshold (BIT) algorithm

We propose a new fully automated velocity-based algorithm to identify fixations from eye-movement records of both eyes, with individual-specific thresholds. The algorithm is based on robust minimum determinant covariance estimators (MDC) and control chart procedures, and is conceptually simple and computationally attractive. To determine fixations, it uses velocity thresholds based on the natural within-fixation variability of both eyes. It improves over existing approaches by automatically identifying fixation thresholds that are specific to (a) both eyes, (b) x- and y- directions, (c) tasks, and (d) individuals. We applied the proposed Binocular-Individual Threshold (BIT) algorithm to two large datasets collected on eye-trackers with different sampling frequencies, and compute descriptive statistics of fixations for larger samples of individuals across a variety of tasks, including reading, scene viewing, and search on supermarket shelves. Our analysis shows that there are considerable differences in the characteristics of fixations not only between these tasks, but also between individuals

In Defense of Competition During Syntactic Ambiguity Resolution

In a recent series of publications (Traxler et al. J Mem Lang 39:558–92, 1998; Van Gompel et al. J Mem Lang 52:284–07, 2005; see also Van Gompel et al. (In: Kennedy, et al.(eds) Reading as a perceptual process, Oxford, Elsevier pp 621–48, 2000); Van Gompel et al. J Mem Lang 45:225–58, 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

Recurrence Plot Based Measures of Complexity and its Application to Heart Rate Variability Data

The knowledge of transitions between regular, laminar or chaotic behavior is essential to understand the underlying mechanisms behind complex systems. While several linear approaches are often insufficient to describe such processes, there are several nonlinear methods which however require rather long time observations. To overcome these difficulties, we propose measures of complexity based on vertical structures in recurrence plots and apply them to the logistic map as well as to heart rate variability data. For the logistic map these measures enable us not only to detect transitions between chaotic and periodic states, but also to identify laminar states, i.e. chaos-chaos transitions. The traditional recurrence quantification analysis fails to detect the latter transitions. Applying our new measures to the heart rate variability data, we are able to detect and quantify the laminar phases before a life-threatening cardiac arrhythmia occurs thereby facilitating a prediction of such an event. Our findings could be of importance for the therapy of malignant cardiac arrhythmias