Eye movement control in Turkish sentence reading

Reading requires the assembly of cognitive processes across a wide spectrum from low-level visual perception to high-level discourse comprehension. One approach of unravelling the dynamics associated with these processes is to determine how eye movements are influenced by the characteristics of the text, in particular which features of the words within the perceptual span maximise the information intake due to foveal, spillover, parafoveal, and predictive processing. One way to test the generalisability of current proposals of such distributed processing is to examine them across different languages. For Turkish, an agglutinative language with a shallow orthography–phonology mapping, we replicate the well-known canonical main effects of frequency and predictability of the fixated word as well as effects of incoming saccade amplitude and fixation location within the word on single-fixation durations with data from 35 adults reading 120 nine-word sentences. Evidence for previously reported effects of the characteristics of neighbouring words and interactions was mixed. There was no evidence for the expected Turkish-specific morphological effect of the number of inflectional suffixes on single-fixation durations. To control for word-selection bias associated with single-fixation durations, we also tested effects on word skipping, single-fixation, and multiple-fixation cases with a base-line category logit model, assuming an increase of difficulty for an increase in the number of fixations. With this model, significant effects of word characteristics and number of inflectional suffixes of foveal word on probabilities of the number of fixations were observed, while the effects of the characteristics of neighbouring words and interactions were mixed.

Language models explain word reading times better than empirical predictability

While word predictability from sentence context is typically investigated by cloze completion probabilities (CCP), it can be more deeply understood by relying on language models (LMs), allowing to define the three key components of memory: Memory starts with experience as implemented by a text corpus, here defined by Wikipedia capturing general knowledge and (movie) subtitles approximating social interactions. LMs then consolidate a long-term memory structure from experience, as addressed by n-gram, topics and recurrent neural network (RNN) models. Retrieval was investigated by predicting fixation durations from an English and a German reading sample. Item-level regressions showed greater correlations of LMs with single-fixation duration (SFD), gaze duration (GD) and total viewing time (TVT) than CCP. When predicting each fixation case separately using generalized additive models, three LMs together always performed better than CCP. When testing single LMs against the typically-sized English CCP sample (N = 30), LMs usually performed better than CCP (8 vs. 3). The larger German CCP sample (N = 272), however, often performed better than single LMs (4 vs. 2). Subtitles-trained n-gram probabilities of present (and last) words allowed for reliable predictions of all fixation durations. Wikipedia-trained topic probabilities of the last and present word allow for reliable predictions of late GD and TVT effects. The present word predictions of RNNs were less sensitive to training-corpus choice and are recommendable if a single LM is used. Moreover, its reliable next word probability effects make it most suitable to address parafoveal preview and top-down predictions.

Single-stage clipping with bifrontal and bilateral frontotemporal craniotomies for subarachnoid hemorrhage with multiple cerebral aneurysms using Sugita head holding system: A case report

Background: Subarachnoid hemorrhage with multiple aneurysms is very challenging because it is difficult to identify the ruptured aneurysm. We could not identify the ruptured aneurysm preoperatively, so we decided to treat all of the aneurysms as a single-stage surgery. Case Description: A 79-year-old woman was diagnosed with subarachnoid hemorrhage with multiple cerebral aneurysms at the right distal anterior cerebral artery, left middle cerebral artery, and right internal carotid artery- posterior communicating artery bifurcation. We could not identify the ruptured aneurysm preoperatively. We fixed her head using the Sugita head holding system (Mizuho Co., Ltd., Tokyo) and performed clipping for each aneurysm with bifrontal craniotomy and bilateral frontotemporal craniotomy as a single-stage operation. The last aneurysm seemed ruptured, and clipping for all the aneurysms was successful. She was discharged with a good postoperative course. The Sugita head holding system allowed turning the head of the patient toward the right and left with single fixation, leading to this single-stage operation. Conclusion: Several methods for identifying a ruptured aneurysm from multiple aneurysms have been reported, but under limited medical resources, this procedure would be one of the treatment strategies.

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Human scene categorization is characterized by its remarkable speed. While many visual and conceptual features have been linked to this ability, significant correlations exist between feature spaces, impeding our ability to determine their relative contributions to scene categorization. Here, we employed a whitening transformation to decorrelate a variety of visual and conceptual features and assess the time course of their unique contributions to scene categorization. Participants (both sexes) viewed 2,250 full-color scene images drawn from 30 different scene categories while having their brain activity measured through 256-channel EEG. We examined the variance explained at each electrode and time point of visual event-related potential (vERP) data from nine different whitened encoding models. These ranged from low-level features obtained from filter outputs to high-level conceptual features requiring human annotation. The amount of category information in the vERPs was assessed through multivariate decoding methods. Behavioral similarity measures were obtained in separate crowdsourced experiments. We found that all nine models together contributed 78% of the variance of human scene similarity assessments and was within the noise ceiling of the vERP data. Low-level models explained earlier vERP variability (88 ms post-image onset), while high-level models explained later variance (169 ms). Critically, only high-level models shared vERP variability with behavior. Taken together, these results suggest that scene categorization is primarily a high-level process, but reliant on previously extracted low-level features.Significance StatementIn a single fixation, we glean enough information to describe a general scene category. Many types of features are associated with scene categories, ranging from low-level properties such as colors and contours, to high-level properties such as objects and attributes. Because these properties are correlated, it is difficult to understand each property’s unique contributions to scene categorization. This work uses a whitening transformation to remove the correlations between features and examines the extent to which each feature contributes to visual event-related potentials (vERPs) over time. We found that low-level visual features contributed first, but were not correlated with categorization behavior. High-level features followed 80 ms later, providing key insights into how the brain makes sense of a complex visual world.

Unveiling the Secrets of Escher’s Lithographs

An impossible structure gives us the impression of looking at a three-dimensional object, even though this object cannot exist, since it possesses parts that are spatially non-connectable, and are characterized by misleading geometrical properties not instantly evident. Therefore, impossible artworks appeal to our intellect and challenge our perceptive capacities. We analyzed lithographs containing impossible structures (e.g., the Necker cube), created by the famous Dutch painter Maurits Cornelis Escher (1898–1972), and used one of them (The Belvedere, 1958) to unveil the artist’s hidden secrets by means of a discrete model of the human retina based on a non-uniform distribution of receptive fields. We demonstrated that the ability of Escher in composing his lithographs by connecting spatial coherent details into an impossible whole lies in drawing these incoherent fragments just outside the zone in which 3D coherence can be perceived during a single fixation pause. The main aspects of our paper from the point of view of image processing and image understanding are the following: (1) the peculiar and original digital filter to process the image, which simulates the human vision process, by producing a space-variant sampling of the image; (2) the software for the filter, which is homemade and created for our purposes. The filtered images resulting from the processing are used to understand impossible figures. As an example, we demonstrate how the impossible figures hidden in Escher’s paintings can be understood.

Exploring website gist through rapid serial visual presentation

Background Users can make judgments about web pages in a glance. Little research has explored what semantic information can be extracted from a web page within a single fixation or what mental representations users have of web pages, but the scene perception literature provides a framework for understanding how viewers can extract and represent diverse semantic information from scenes in a glance. The purpose of this research was (1) to explore whether semantic information about a web page could be extracted within a single fixation and (2) to explore the effects of size and resolution on extracting this information. Using a rapid serial visual presentation (RSVP) paradigm, Experiment 1 explored whether certain semantic categories of websites (i.e., news, search, shopping, and social networks/blogs) could be detected within a RSVP stream of web page stimuli. Natural scenes, which have been shown to be detectable within a single fixation in the literature, served as a baseline for comparison. Experiment 2 examined the effects of stimulus size and resolution on observers’ ability to detect the presence of website categories using similar methods. Results Findings from this research demonstrate that users have conceptual models of websites that allow detection of web pages from a fixation’s worth of stimulus exposure, when provided additional time for processing. For website categories other than search, detection performance decreased significantly when web elements were no longer discernible due to decreases in size and/or resolution. The implications of this research are that website conceptual models rely more on page elements and less on the spatial relationship between these elements. Conclusions Participants can detect websites accurately when they were displayed for less than a fixation and when the participants were allowed additional processing time. Subjective comments and stimulus onset asynchrony data suggested that participants likely relied on local features for the detection of website targets for several website categories. This notion was supported when the size and/or resolution of stimuli were decreased to the extent that web elements were indistinguishable. This demonstrates that schemas or conceptualizations of websites provided information sufficient to detect websites from approximately 140 ms of stimulus exposure.

How radiographers visually perceive X-ray images with the task of accepting or rejecting them – a pilot study

Introduction: Radiographer´s usual role in the medical imaging chain is to acquire relevant and qualitatively good images that help the radiologist or physician to diagnose most accurately. After the image acquisition, the radiographer does a quality evaluation based on established imaging criteria to decide if the image is satisfactory, or otherwise reject it and subsequently take a new one. Contrary to expectations that the number of image rejects should decrease substantially with the introduction of digital imaging, a number of studies have shown that it has not, although the reasons for rejects has changed from exposure errors to positioning and centring errors. Very little research has been on examining how radiographers visually perceive and evaluate the X-ray images in this acceptance/rejection process.Purpose: Investigate how radiographers and radiography students visually perceives X-ray images in the process of accepting or rejecting them on basis of radiographic imaging criteria, and see if there are differences in strategies across experience levels.Materials and methods: Three radiography students and five radiographers with varying years of experience were given the task of accepting or rejecting shoulder and knee projection images based on positioning criteria. Using eye tracking, we measured the participants’ number and duration of gaze fixations within 1) the field of view defined by the monitor display, 2) the part of the monitor displaying the X-ray image only, and 3) the region within the X-ray images considered to be most relevant given the imaging criteria task. The quantitative eye-tracking measurements were followed-up by four qualitative questions.Results: Some differences in fixation patterns between the groups were found; the medium experienced radiographers spent statistically significant lesser number of fixations and lesser average single fixation durations than both the radiography students and the most experienced radiographers did, whereas the two latter groups scored almost equally. Conclusion: The study revealed that work experience might have some influence on how radiographers and radiography students assess X-ray images, but in subtler ways than expected. The study also revealed, however, quite large individual differences across experience.