The response of eye-movement and pupil size to audio instruction while viewing a moving target

2000 ◽  
Author(s):  
Koji Takahashi ◽  
Minoru Nakayama ◽  
Yasutaka Shimizu
Keyword(s):  
Eye Movement ◽  
Pupil Size ◽  
Moving Target

scholarly journals Pursuit disorder and saccade dysmetria after caudal fastigial inactivation in the monkey

2018 ◽  
Vol 120 (4) ◽  
pp. 1640-1654 ◽  
Author(s):  
Clara Bourrelly ◽  
Julie Quinet ◽  
Laurent Goffart
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Visual Target ◽  
Fastigial Nucleus ◽  
Gaze Direction ◽  
Moving Target ◽  
Horizontal Meridian ◽  
Pursuit Eye Movements ◽  
Neural Processes ◽  
Slow Eye Movements

The caudal fastigial nuclei (cFN) are the output nuclei by which the medio-posterior cerebellum influences the production of saccadic and pursuit eye movements. We investigated the consequences of unilateral inactivation on the pursuit eye movement made immediately after an interceptive saccade toward a centrifugal target. We describe here the effects when the target moved along the horizontal meridian with a 10 or 20°/s speed. After muscimol injection, the monkeys were unable to track the present location of the moving target. During contralesional tracking, the velocity of postsaccadic pursuit was reduced. This slowing was associated with a hypometria of interceptive saccades such that gaze direction always lagged behind the moving target. No correlation was found between the sizes of saccade undershoot and the decreases in pursuit speed. During ipsilesional tracking, the effects on postsaccadic pursuit were variable across the injection sessions, whereas the interceptive saccades were consistently hypermetric. Here also, the ipsilesional pursuit disorder was not correlated with the saccade hypermetria either. The lack of correlation between the sizes of saccade dysmetria and changes of postsaccadic pursuit speed suggests that cFN activity exerts independent influences on the neural processes generating the saccadic and slow eye movements. It also suggests that the cFN is one locus where the synergy between the two motor categories develops in the context of tracking a moving visual target. We explain how the different fastigial output channels can account for these oculomotor tracking disorders. NEW & NOTEWORTHY Inactivation of the caudal fastigial nucleus impairs the ability to track a moving target. The accuracy of interceptive saccades and the velocity of postsaccadic pursuit movements are both altered, but these changes are not correlated. This absence of correlation is not compatible with an impaired common command feeding the circuits producing saccadic and pursuit eye movements. However, it suggests an involvement of caudal fastigial nuclei in their synergy to accurately track a moving target.

scholarly journals The study of pupil size and eye movement during deception using eye tracker

2016 ◽  
Vol 30 (2) ◽  
pp. 63-76
Author(s):  
Yeonsil Lee ◽  
LeeJangHan ◽  
Hoon Choi ◽  
Seok Chan Kim ◽  
Sang Hyun Lee ◽  
...  
Keyword(s):  
Eye Movement ◽  
Pupil Size ◽  
Eye Tracker

scholarly journals Eye Movement and Pupil Size Constriction Under Discomfort Glare

2015 ◽  
Vol 56 (3) ◽  
pp. 1649-1656 ◽  
Author(s):  
Y. Lin ◽  
S. Fotios ◽  
M. Wei ◽  
Y. Liu ◽  
W. Guo ◽  
...  
Keyword(s):  
Eye Movement ◽  
Pupil Size ◽  
Discomfort Glare

Spatial but Not Temporal Cueing Influences the Mislocalisation of a Target Flashed during Smooth Pursuit

Perception ◽  
10.1068/p3411 ◽  
2002 ◽  
Vol 31 (10) ◽  
pp. 1195-1203 ◽  
Author(s):  
Gerben Rotman ◽  
Eli Brenner ◽  
Jeroen B J Smeets
Keyword(s):  
Eye Movements ◽  
Eye Movement ◽  
Normal Condition ◽  
Smooth Pursuit ◽  
Human Subjects ◽  
The Other ◽  
Moving Target ◽  
Pursuit Eye Movements

Human subjects misjudge the position of a target that is flashed during a pursuit eye movement. Their judgments are biased in the direction in which the eyes are moving. We investigated whether this bias can be reduced by making the appearance of the flash more predictable. In the normal condition, subjects pursued a moving target that flashed somewhere along its trajectory. After the presentation, they indicated where they had seen the flash. The mislocalisations in this condition were compared to mislocalisations in conditions in which the subjects were given information about when or where the flash would come. This information consisted of giving two warning flashes spaced at equal intervals before the target flash, of giving two warning beeps spaced at equal intervals before the target flash, or of showing the same stimulus twice. Showing the same stimulus twice significantly reduced the mislocalisation. The other conditions did not. We interpret this as indicating that it is not predictability as such that influences the performance, but the fact that the target appears at a spatially cued position. This was supported by a second experiment, in which we examined whether subjects make smaller mis-judgments when they have to determine the distance between a target flashed during pursuit and a reference seen previously, than when they have to determine the distance between the flashed target and a reference seen afterwards. This was indeed the case, presumably because the reference provided a spatial cue for the flash when it was presented first. We conclude that a spatial cue reduces the mislocalisation of targets that are flashed during pursuit eye movements. The cue does not have to be exactly at the same position as the flash.

scholarly journals The World (of Warcraft) through the eyes of an expert

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3783 ◽  
Author(s):  
Yousri Marzouki ◽  
Valériane Dusaucy ◽  
Myriam Chanceaux ◽  
Sebastiaan Mathôt
Keyword(s):  
Eye Movement ◽  
Negative Correlation ◽  
Pupil Size ◽  
Visual Complexity ◽  
Mental Effort ◽  
Role Playing ◽  
World Of Warcraft ◽  
Movement Behavior ◽  
Standard Tool ◽  
Role Playing Game

Negative correlations between pupil size and the tendency to look at salient locations were found in recent studies (e.g., Mathôt et al., 2015). It is hypothesized that this negative correlation might be explained by the mental effort put by participants in the task that leads in return to pupil dilation. Here we present an exploratory study on the effect of expertise on eye-movement behavior. Because there is no available standard tool to evaluate WoW players’ expertise, we built an off-game questionnaire testing players’ knowledge about WoW and acquired skills through completed raids, highest rated battlegrounds, Skill Points, etc. Experts (N = 4) and novices (N = 4) in the massively multiplayer online role-playing game World of Warcraft (WoW) viewed 24 designed video segments from the game that differ in regards with their content (i.e, informative locations) and visual complexity (i.e, salient locations). Consistent with previous studies, we found a negative correlation between pupil size and the tendency to look at salient locations (experts, r =  − .17, p < .0001, and novices, r =  − .09, p < .0001). This correlation has been interpreted in terms of mental effort: People are inherently biased to look at salient locations (sharp corners, bright lights, etc.), but are able (i.e., experts) to overcome this bias if they invest sufficient mental effort. Crucially, we observed that this correlation was stronger for expert WoW players than novice players (Z =  − 3.3, p = .0011). This suggests that experts learned to improve control over eye-movement behavior by guiding their eyes towards informative, but potentially low-salient areas of the screen. These findings may contribute to our understanding of what makes an expert an expert.

scholarly journals Hubungan Penggunaan Smartphone terhadap Ketajaman Penglihatan

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Yonathan S. A. Angmalisang ◽  
Maya E. W. Moningka ◽  
Jimmy F. Rumampuk
Keyword(s):  
Visual Acuity ◽  
Light Intensity ◽  
Literature Review ◽  
Everyday Life ◽  
Eye Movement ◽  
Health Problem ◽  
Pupil Size ◽  
Blurred Vision ◽  
Retinal Stimulation ◽  
Smartphone Use

Abstract: Visual acuity is the ability of a person's eyes to distinguish the shapes and details of objects at a certain distance. Decreased visual acuity is still a health problem in society. A person's visual acuity is influenced by refraction, pupil size, light intensity, exposure time, retinal stimulation area, eye adaptation, and eye movement. The use of smartphones has become a necessity of everyday life in society. Several studies have shown that smartphone use can lead to decreased visual acuity. This study aimed to determine whether there is a relationship between smartphone use and visual acuity and the factors that can affect visual acuity due to smartphone use. The research design used was a literature review with journals that can be accessed free full text through PubMed and ClinicalKey. As a result, the smartphone use can lead to DED, myopia, dan blurred vision. In conclusion, there is a relationship between smartphone use and visual acuityKeywords: smartphone, visual acuity  Abstrak: Ketajaman penglihatan adalah kemampuan mata seseorang untuk membedakan bentuk dan detail objek pada jarak tertentu. Penurunan ketajaman penglihatan masih menjadi masalah kesehatan dalam masyarakat. Ketajaman penglihatan seseorang dipengaruhi oleh refraksi, ukuran pupil, intensitas cahaya, waktu pemaparan, area stimulasi retina, adaptasi mata, dan gerakan mata. Penggunaan smartphone sudah menjadi kebutuhan kehidupan sehari-hari dalam masyarakat. Beberapa penelitian menunjukkan bahwa penggunaan smartphone dapat menyebabkan penurunan ketajaman penglihatan. Tujuan penelitian untuk mengetahui apakah terdapat hubungan penggunaan smartphone terhadap ketajaman penglihatan dan faktor-faktor yang dapat mempengaruhi ketajaman penglihatan karena penggunaan smartphone. Desain penelitian yang dipakai adalah literature review dengan jurnal-jurnal yang dapat diakses secara gratis melalui PubMed dan ClinicalKey. Hasilnya menunjukkan bahwa penggunaan smartphone dapat mengakibatkan DED, miopia dan penglihatan kabur. Sebagai simpulan, terdapat hubungan penggunaan smartphone terhadap ketajaman penglihatanKata Kunci: smartphone, ketajaman penglihatan

scholarly journals Convolutional neural networks can decode eye movement data: A black box approach to predicting task from eye movements

2020 ◽  
Author(s):  
Zachary Jay Cole ◽  
Karl Kuntzelman ◽  
Michael D. Dodd ◽  
Matthew Johnson
Keyword(s):  
Neural Networks ◽  
Eye Movement ◽  
Convolutional Neural Networks ◽  
Pupil Size ◽  
General Pattern ◽  
Image Data ◽  
Black Box ◽  
Minimally Processed ◽  
Movement Data

Previous attempts to classify task from eye movement data have relied on model architectures designed to emulate theoretically defined cognitive processes, and/or data that has been processed into aggregate (e.g., fixations, saccades) or statistical (e.g., fixation density) features. _Black box_ convolutional neural networks (CNNs) are capable of identifying relevant features in raw and minimally processed data and images, but difficulty interpreting these model architectures has contributed to challenges in generalizing lab-trained CNNs to applied contexts. In the current study, a CNN classifier was used to classify task from two eye movement datasets (Exploratory and Confirmatory) in which participants searched, memorized, or rated indoor and outdoor scene images. The Exploratory dataset was used to tune the hyperparameters of the model, and the resulting model architecture was re-trained, validated, and tested on the Confirmatory dataset. The data were formatted into timelines (i.e., x-coordinate, y-coordinate, pupil size) and minimally processed images. To further understand the informational value of each component of the eye movement data, the timeline and image datasets were broken down into subsets with one or more components systematically removed. Classification of the timeline data consistently outperformed the image data. The Memorize condition was most often confused with Search and Rate. Pupil size was the least uniquely informative component when compared with the x- and y-coordinates. The general pattern of results for the Exploratory dataset was replicated in the Confirmatory dataset. Overall, the present study provides a practical and reliable black box solution to classifying task from eye movement data.

scholarly journals Experimental Analysis of Eye Movement during Tracking a Moving Target

1995 ◽  
Vol 31 (Supplement) ◽  
pp. 432-433
Author(s):  
Ryoko Fukuda ◽  
Etsuo Nakamura ◽  
Minoru Sakuma ◽  
Tadahiko Fukuda
Keyword(s):  
Eye Movement ◽  
Experimental Analysis ◽  
Moving Target
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