The authors have no acknowledgments.

The Institutional Review Boards of Kent State University and Stetson University have approved all methods described here.
1. Eligible Participants
NOTE: The purpose of this research is to understand reading processes in skilled adult readers. Thus, certain eligibility requirements must be met. Such controls ensure that results are directly applicable to a population of skilled adult readers with typical cognitive processes.
<ol>
	<li>Recruit participants that meet the following eligibility requirements: must be at least 18 years old, have no reading disabilities (dyslexia, alexia, dysgraphia, etc.), have normal or corrected vision (glasses or contacts are acceptable), and speak English as their native language.</li>
</ol>
2. Experimental Stimuli
NOTE:&#160;Stimuli construction involves the selection of individual target words as well as the creation of sentence contexts in which those target words are embedded.
<ol>
	<li>Prepare stimuli for oculomotor corrective regressions.
	<ol>
		<li>Select a set of at least 30 target words to be embedded into sentences. The target word (wordn) is the word on which word skipping and regressive eye movements will be measured. Select words from an English language corpus, such as CELEX14, which provides word frequencies. Select words that are low frequency, with frequencies lower than 30 counts per million. Choose a three-letter content word to facilitate word skipping.</li>
		<li>Select the pre-target words (wordn-1) so that the reader is likely to fixate it before skipping or fixating wordn. Again, using an English language corpus, select words that are high frequency, with at least 30 counts per million. Choose a five to seven letter content word to increase the likelihood that it will be fixated and not skipped.</li>
		<li>Select the post-target word (wordn+1) so that the reader is likely to fixate it after skipping or fixating wordn. Using the same English language corpus from the previous two steps, select a high frequency preposition that is at least four letters long.</li>
		<li>Using the words selected in the previous three steps, create sentence contexts in which these three words will be embedded. Place wordsn-1, wordn, and wordn+1 in the middle of the sentence. See step 2.2.6 for some example stimuli. 
		&#8203;NOTE: Sentences should be neutral in context without any emotionally charged language. The sentence frames need to be written so that that the overall sentence is grammatical and that wordsn-1, wordn, and wordn+1 fit smoothly into the sentence frame. The target wordn should not be predictable from the context that precedes it (see step 2.2.5 for information about norming to ensure that target words are not predictable).</li>
		<li>After sentence frames are created, norm the stimuli using a cloze task to ensure that the target wordn is not predictable from the sentence context.
		<ol>
			<li>In this task, recruit a separate set of participants.</li>
			<li>Have these participants view each sentence context up until the target word, without including the target, and produce a word that they think best fits the sentence.</li>
			<li>Let the participants complete this task using pen and paper or enter words on a computer using a program or any other software package for behavioral research. 
			NOTE: If the target word is produced by more than 20% of participants, then it is considered predictable from the sentence context and must be replaced with a less predictable word and normed again. In the original experiment11, 100 participants completed the cloze task, and no target word was predicted from the preceding context.</li>
		</ol>
		</li>
		<li>See an example sentence below. In this sentence, green is wordn-1, gem is the three-letter low-frequency unpredictable wordn, and around is wordn+1. In this experiment, the target word was controlled to be low frequency (mean = 10.54 counts per million, standard deviation = 6.97)14. 
		The actress wore a green gem around her neck at the awards show. 
		Another set of 10 experimental stimuli are presented below from the original experiment14. 
		He stared at the large urn across the room. 
		She was afraid of the black fox until it wagged its tail. 
		He tried to grab the small eel from the pond. 
		She wanted to see the great zoo inside of the new theme park. 
		They walked around the whole gym after their workout. 
		The child asked the young elf about working in Santa&#39;s shop. 
		There was always a short cot under the bed at her cousin&#39;s house. 
		There was really heavy fog along the coastline this morning. 
		He placed his right ski above his left one when he performed the trick. 
		She performed her first gig since she wrote some new songs.</li>
	</ol>
	</li>
	<li>Prepare stimuli for comprehension-based regressions.
	<ol>
		<li>Obtain sentence contexts for this experiment by adapting from a previous study that already has normed sentence frames with ambiguous homophones12. Download this article and view Appendix A, which provides neutral sentence frames that end with an ambiguous homophone.</li>
		<li>Using these sentence frames, write the second half of the sentence that disambiguates the homophone to its subordinate meaning. Determine the subordinate meaning of the target word using the University of South Florida homograph norms15. For example, the subordinate meaning of the homophone grade is &#34;hill incline&#34; while the dominant meaning is &#34;evaluation scale.&#34; Thus, for the sentence &#34;Mike didn&#39;t like the grade&#8230;&#34; add &#34;&#8230;of the hill that they were driving down.&#34; This ending makes it so that the ambiguous homophone &#34;grade&#34; is disambiguated to its subordinate meaning by the word &#34;hill.&#34; Each sentence should have two short function words between the ambiguous homophone and the words that disambiguates it. Another set of 10 example sentences are presented below14 
		Barbara examined the corn on her foot after it became painful. 
		Ben finally noticed the bluff when the trail suddenly ended. 
		Betty searched for the file for her nails since they were torn. 
		Debbie liked the case that the lawyer decided to take on. 
		Everyone noticed the crab when he whined about everything. 
		Fred closely examined the table and the chart in the report. 
		Harry didn&#39;t like the suit that was filed against him. 
		He was happy about the press when the wrinkle was removed from his pants. 
		Helen looked at the cardinal in the church on Sunday. 
		It was a very bad sentence that the judge delivered to the defendant. 
		Jen easily saw the ruler and the queen at the palace.</li>
	</ol>
	</li>
</ol>
3. Comprehension Check
<ol>
	<li>Verify that all participants are reading for comprehension throughout the experiment. Thus, randomly present a series of comprehension questions throughout the experiment. Use simple statements that are followed by a yes or no question to ensure that the participant was comprehending each sentence. Present the comprehension questions separately from the sentence. Eye movement patterns may be different when a participant is not paying close attention to the text. Remove data from any participant who scores less than 80% accuracy on the comprehension questions from data analysis. There should be comprehension questions on at least 10% of trials. Comprehension questions should follow filler sentences, not experimental sentences. An example of four comprehension questions are presented below: 
	Sentence:&#160; &#160; &#160; Christina went to California with her parents last year. 
	Question:&#160; &#160; &#160; &#160;Did Christina go to Vermont last year? 
	Sentence:&#160; &#160; &#160; After Mark graduated from college he found a job immediately. 
	Question:&#160; &#160; &#160; &#160;Did Mark fail to find a job? 
	Sentence:&#160; &#160; &#160; The telephone rang just as Samantha crawled into bed. 
	Question:&#160; &#160; &#160; &#160;Did someone call Samantha last night? 
	Sentence:&#160; &#160; &#160; The tourists regretted not being able to stay longer in Florida. 
	Question:&#160; &#160; &#160; &#160;Did the tourists want to stay longer?</li>
</ol>
4. Eye Tracking Procedure
<ol>
	<li>Recruit at least 50 participants for each experiment (oculomotor control and comprehension-based regressions) to ensure sufficient data for analyses; drop trials without regressions. Prepare at least 40 experimental stimuli for each experiment, with at least 10 comprehension questions, and at least 20 filler sentences for each experiment. Each experiment should take approximately 30 minutes to complete.</li>
	<li>Use an eye-tracker with a sampling rate of 1,000 Hz, which means that eye positions are measured 1,000 times per second. Measure the eye movements from the right eye. 
	NOTE: This sampling rate is important as eye movement behavior is extremely fast, and a sample rate of less than 1,000 Hz might not be sensitive enough to capture all cognitive processing.</li>
	<li>Have the participants seated about 60 cm (24 in.) away from a computer screen. Use a 21 in. screen or other screens for the original experiment14.
	<ol>
		<li>To stabilize head movements, have participants rest their chin on a chin rest. Allow participants to adjust the height of the chin rest and chair until they are comfortable.</li>
		<li>Instruct the participants to rest their fingers on a &#34;yes&#34; button and a &#34;no&#34; button that they will use to answer comprehension questions.</li>
	</ol>
	</li>
	<li>To calibrate participants&#39; eye positions, use a nine-dot calibration. Instruct the participants to gaze at a white circle in the center of a black screen. Participants will move their eyes to the white circle as it moves around to eight other positions on the screen. Have the participants keep their eyes on the circle until it moves to a new position.
	<ol>
		<li>After calibration, validate eye positions. If participants&#39; eye positions are corrected within one degree of visual angle, then ask the participants move on to the reading portion of the study.</li>
	</ol>
	</li>
	<li>Have each sentence appear one at a time in random order in the center of the screen. Use any monospaced font such as Courier so that all characters take up the same amount of space on the participant&#39;s retina. Intermix filler sentences and comprehension sentences (followed by questions) with experimental sentences.</li>
	<li>Prior to each sentence, have the participant gaze at a white circle on the left side of the screen that corresponds to the position of the first letter of the first word. When participants are looking at this position, have the experimenter press a button that controls the onset for reading. 
	NOTE: This experiment uses self-paced reading, so the participant will press the &#34;yes&#34; button when they have finished reading the sentence. After reading each sentence, the white circle will appear on the screen again and the process will repeat with the next sentence.</li>
	<li>Perform a drift correct prior to each sentence to ensure that calibration remains accurate. If the eye position is off by more than one degree of visual angle, recalibrate the participant&#39;s eye positions.</li>
</ol>
5. Quantitative Analysis of Data
<ol>
	<li>After all data have been collected, open the program DataViewer, and load in all data files in .edf format if using EyeLink software. Delete fixation durations that are fewer than 100 ms or longer than 1,000 ms as these do not reflect linguistic processing.</li>
	<li>Next, run an Interest Area Report to gather the desired eye movement behavior measures from each word of interest: wordn, and wordn+1. Set interest areas around these items using a delimiter and the default settings for interest area size in Experiment Builder. Select several variables in order to determine the type of regressive eye movement and the presence or absence of an IOR effect: 
	IA_SKIP: This variable indicates whether wordn was skipped. This is important to determine whether the regression to wordn is a return or non-return regression. 
	IA_REGRESSION_IN: This variable indicates whether a regression was made into wordn. Only analyze trials in which this value is 1, otherwise it is not relevant for IOR analyses because no return eye movement was made to this target. 
	IA_REGRESSION_OUT: This variable indicates whether a regression was made out of wordn+1. Only analyze cases in which this variable is 1, which indicates that a return eye movement was made. 
	IA_FIRST_RUN_DWELL_TIME: This variable is a measure of how long the reader spent on wordn+1 on the first pass through the sentence. This duration indicates the amount of processing it took before a regressive eye movement was made. This duration will include any potential inhibition time before a regressive eye movement.</li>
	<li>Now that each trial has been categorized, have the researcher inspect each trial individually to determine whether it counts as an oculomotor- or comprehension-based regressive eye movement. Only inspect trials where IA_REGRESSION OUT of wordn+1 is 1 and where IA_REGRESSION_IN to wordn is 1.
	<ol>
		<li>In DataViewer, select the participant&#39;s data, and open each trial. Click through each fixation to inspect whether the regression out of wordn+1 was made directly into wordn after it has been fixated or skipped. If so, mark this trial to be included in analyses in the data file. Do not include trials where a regression was made to an earlier part of the sentence or when a regression was made out of wordn+1 after processing other parts of the sentence.</li>
	</ol>
	</li>
	<li>After all trials have been marked, analyze data using linear mixed effects models with the languageR and lme4 packages in R Studio16. Specify random slopes and intercepts for both participants and items. Fixed effects should include skipping of the target word and regressions into the target word.</li>
</ol>

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	<li>Rayner, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Eye+movements+in+reading+and+information+processing:+20+years+of+research.">Eye movements in reading and information processing: 20 years of research.</a> Psychological Bulletin. 124 (3), 372-422 (1998).</li><li>Posner, M. I., Cohen, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Components+of+visual+orienting.">Components of visual orienting.</a> Attention and Performance X: Control Language Processes. (32), 531-556 (1984).</li><li>Klein, R. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Inhibition+of+return.">Inhibition of return.</a> Trends in Cognitive Sciences. 4 (4), 138-147 (2000).</li><li>Henderson, J. M., Luke, S. 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The authors have nothing to disclose.

The current research provides a method for distinguishing between two different types of regressive eye movements during reading - those that are based on comprehension difficulty and those that are based on oculomotor error. The data provide evidence that a low-level attentional process, IOR, may depend on the type of regression. It was found that IOR only occurs for oculomotor-based regressions, but not for comprehension based regressions14. Thus, it is important...

The method described in this paper was designed to investigate the role of inhibition of return (IOR) in regressive eye movements during reading, focusing on regressions triggered as a result of comprehension difficulty versus those triggered as a result of oculomotor error. Specifically, we investigated whether regressions launched as a result of comprehension difficulty and those launched as a result of oculomotor error are subject to IOR effects.
Regressive eye movements, or regressions, are eye movements that move backwards through the text. Depending on reader and text characteristics, 10-25% of eye movements move backwards1. This has led researchers to investigate whether IOR effects affect regressive eye movements during natural reading. IOR is an oculomotor effect that results in increased latency to return attention to a target that had been previously attended compared to a target that had not been previously attended2. While much of the work done to establish IOR effects has involved non-reading visual attention tasks3, the effect has been extended to reading4,5.
The work examining regressions and IOR in reading has focused on whether an oculomotor effect such as IOR can influence eye movement control in reading. One study5 found evidence of IOR in a reading task. They found that readers spent approximately 30 ms longer on the fixation preceding a regression. This was interpreted as the IOR &#34;cost&#34; - the delay before returning to a previously fixated position. This was supported in regular reading and mindless reading conditions6.
Despite evidence that IOR can be found in regular reading situations, it is clear that regressive eye movements do not all have the same underlying cause. Regressions resulting from comprehension difficulty have been well documented7,8,9,10.&#160;Despite the evidence that eye movements during reading are generally guided by cognitive and linguistic factors1, it is also assumed that sometimes regressions occur in response to low-level oculomotor factors, such as target overshoot1. It is assumed that on some trials, readers mis-program a saccade and land beyond their intended target word (an overshoot). In this case, a short, corrective regressive saccade may occur so that the unintentionally skipped word can be fixated. Given that two underlying mechanisms - linguistic and oculomotor - have been posited for regressive eye movements, it is not clear whether IOR occurs for both. The current method allows for the measurement of IOR effects when regressive eye movements have been launched as a result of comprehension difficulties and as a result of oculomotor overshoot. Thus, the method allows researchers to distinguish the underlying mechanisms of regressive eye movements, allowing for the evaluation of IOR effects.
The current method takes advantage of the two identified mechanisms triggering regressive eye movements. By designing the materials so that re-reading is likely to be triggered by comprehension difficulty or overshoot, researchers are able to examine the circumstances under which IOR might occur in reading. To encourage re-reading as a result of oculomotor error, we embedded short target words that show high skipping rates of about 50% (adapted from previous research11). Skipped words are often followed by a corrective regressive saccade when the skipping is a result of oculomotor error11. The other set of materials was comprised of sentences that contained semantically ambiguous homographic homophones (e.g., grade: school/incline). The sentences were adapted from an ambiguity study12 and contained information as to the intended meaning of the homophone that followed the word. Thus, this would increase the chances that readers would re-read for comprehension. The context was consistent with the less-likely meaning of the homophone, making it likely that readers would have to re-read after having initially selected the more frequent, dominant meaning on their first encounter with the target word. The combination of eye-movement monitoring and materials designed to increase regressions makes this method unique in allowing for the examination of regressive eye movements with differing underlying causes.
Understanding the mechanisms underlying regressive saccades and the role that oculomotor factors such as IOR play in them is important to models of eye movement control as well as for understanding the relationship between oculomotor and cognitive control of eye movements. For example, a recent version of the E-Z Reader model of eye movement control employs a 30 ms cost for all regressive eye movements13. However, our methodology demonstrated that such a cost only applies to regressions resulting from oculomotor error.
Eye movement measures allow researchers to track the moment-to-moment cognitive processing during reading1. Recently, models of eye movement control have begun to try to explain the mechanisms underlying regressive eye movements. Since regressions are often launched in relation to comprehension difficulties, any researcher interested in understanding the comprehension processes during reading should attempt to differentiate regressions resulting from oculomotor error versus comprehension processes. This methodology indicates that a cost for regressions is a result only of oculomotor error, serving as a launching point for differentiating between types of regressions. The combination of eye movement measures (regressions, fixation times before regressions) and carefully controlled materials allow for this differentiation.

<table><tbody><tr><td>Eyelink 1000 Plus</td><td>SR Research</td><td></td><td>Video-based eye tracker</td></tr><tr><td>Experiment Builder Software</td><td>SR Research</td><td></td><td>Software to build eye tracking experiments</td></tr><tr><td>Data Viewer</td><td>SR Research</td><td></td><td>Software to retireve eye tracking measures</td></tr></tbody></table>

eye-tracking to distinguish comprehension-based and oculomotor-based regressive eye movements during reading

Regressive eye movements are eye movements that move backwards through the text and comprise approximately 10-25% of eye movements during reading. As such, understanding the causes and mechanisms of regressions plays an important role in understanding eye movement behavior. Inhibition of return (IOR) is an oculomotor effect that results in increased latency to return attention to a previously attended target versus a target that was not previously attended. Thus, IOR may affect regressions. This paper describes how to design materials to distinguish between regressions caused by comprehension-related and oculomotor processes; the latter is subject to IOR. The method allows researchers to identify IOR and control the causes of regressions. While the method requires tightly controlled materials and large numbers of participants and materials, it allows researchers to distinguish and control the types of regressions that occur in their reading studies.

The results of our previous work using this paradigm14 resulted in a 17% regression rate in the oculomotor error condition and a 29% regression rate in the comprehension difficulty condition14. In the oculomotor error condition, 32% of the regressions were to previously fixated words and 68% of regressions were to previously skipped words. The reverse pattern occurred in the comprehension difficulty condition. Of the 29% of regressions, 61% were to previously fixated words ...

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Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading

The method was designed to investigate the role of inhibition of return (IOR) in regressive eye movements during reading. The focus is on differentiating between regressions triggered as a result of comprehension difficulty versus those triggered from oculomotor error, including the role of IOR in the two types of regressions.

Regressive eye movements are eye movements that move backwards through the text and comprise approximately 10-25% of eye movements during reading. As ...

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6.1K Views.  Kent State University. The method was designed to investigate the role of inhibition of return (IOR) in regressive eye movements during reading. The focus is on differentiating between regressions triggered as a result of comprehension difficulty versus those triggered from oculomotor error, including the role of IOR in the two types of regressions.

Video: Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading

Using Eye Movements to Evaluate the Cognitive Processes Involved in Text Comprehension

The present article describes how to use eye tracking methodologies to study the cognitive processes involved in text comprehension. Measuring eye movements during reading is one of the most precise methods for measuring moment-by-moment (online) processing demands during text comprehension. Cognitive processing demands are reflected by several aspects of eye movement behavior, such as fixation duration, number of fixations, and number of regressions (returning to prior parts of a text). Important properties of eye tracking equipment that researchers need to consider are described, including how frequently the eye position is measured (sampling rate), accuracy of determining eye position, how much head movement is allowed, and ease of use. Also described are properties of stimuli that influence eye movements that need to be controlled in studies of text comprehension, such as the position, frequency, and length of target words. Procedural recommendations related to preparing the participant, setting up and calibrating the equipment, and running a study are given. Representative results are presented to illustrate how data can be evaluated. Although the methodology is described in terms of reading comprehension, much of the information presented can be applied to any study in which participants read verbal stimuli.

The present article describes how to use eye tracking methodologies to study the cognitive processes involved in text comprehension. Descriptions of eye tracking equipment, how to develop experimental stimuli, and procedural recommendations are included. The information presented can be applied to most any study using verbal stimuli.

The present article describes how to use eye  tracking methodologies to study the cognitive processes involved in text  comprehension. Measuring eye ...

Eye Movement Monitoring of Memory

Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank yesterday."), however such reports can often be unreliable or sensitive to response bias 1, and may be unobtainable in some participant populations. Furthermore, explicit reports only reveal when information has reached consciousness and cannot comment on when memories were accessed during processing, regardless of whether the information is subsequently accessed in a conscious manner. Eye movement monitoring (eye tracking) provides a tool by which memory can be probed without asking participants to comment on the contents of their memories, and access of such memories can be revealed on-line 2,3. Video-based eye trackers (either head-mounted or remote) use a system of cameras and infrared markers to examine the pupil and corneal reflection in each eye as the participant views a display monitor. For head-mounted eye trackers, infrared markers are also used to determine head position to allow for head movement and more precise localization of eye position. Here, we demonstrate the use of a head-mounted eye tracking system to investigate memory performance in neurologically-intact and neurologically-impaired adults. Eye movement monitoring procedures begin with the placement of the eye tracker on the participant, and setup of the head and eye cameras. Calibration and validation procedures are conducted to ensure accuracy of eye position recording. Real-time recordings of X,Y-coordinate positions on the display monitor are then converted and used to describe periods of time in which the eye is static (i.e. fixations) versus in motion (i.e., saccades). Fixations and saccades are time-locked with respect to the onset/offset of a visual display or another external event (e.g. button press). Experimental manipulations are constructed to examine how and when patterns of fixations and saccades are altered through different types of prior experience. The influence of memory is revealed in the extent to which scanning patterns to new images differ from scanning patterns to images that have been previously studied 2, 4-5. Memory can also be interrogated for its specificity; for instance, eye movement patterns that differ between an identical and an altered version of a previously studied image reveal the storage of the altered detail in memory 2-3, 6-8. These indices of memory can be compared across participant populations, thereby providing a powerful tool by which to examine the organization of memory in healthy individuals, and the specific changes that occur to memory with neurological insult or decline 2-3, 8-10.

Eye movement monitoring (or eye tracking) reveals where in space the eyes linger, when and for how long. Here, we demonstrate how eye tracking can be used to investigate the integrity of memory in multiple participant populations, without requiring verbal, or otherwise explicit, reports.

Explicit (often verbal) reports are typically used to investigate memory (e.g. "Tell me what you remember about the person you saw at the bank ...

Neuroscience

VisualEyes: A Modular Software System for Oculomotor Experimentation

Eye movement studies have provided a strong foundation forming an understanding of how the brain acquires visual information in both the normal and dysfunctional brain.1 However, development of a platform to stimulate and store eye movements can require substantial programming, time and costs. Many systems do not offer the flexibility to program numerous stimuli for a variety of experimental needs. However, the VisualEyes System has a flexible architecture, allowing the operator to choose any background and foreground stimulus, program one or two screens for tandem or opposing eye movements and stimulate the left and right eye independently. This system can significantly reduce the programming development time needed to conduct an oculomotor study. The VisualEyes System will be discussed in three parts: 1) the oculomotor recording device to acquire eye movement responses, 2) the VisualEyes software written in LabView, to generate an array of stimuli and store responses as text files and 3) offline data analysis. Eye movements can be recorded by several types of instrumentation such as: a limbus tracking system, a sclera search coil, or a video image system. Typical eye movement stimuli such as saccadic steps, vergent ramps and vergent steps with the corresponding responses will be shown. In this video report, we demonstrate the flexibility of a system to create numerous visual stimuli and record eye movements that can be utilized by basic scientists and clinicians to study healthy as well as clinical populations.

Neural control and cognitive processes can be studied through eye movements. The VisualEyes software allows an operator to program stimuli on two computer screens independently using a simple, custom scripting language. The system can stimulate tandem eye movements (saccades and smooth pursuit) or opposing eye movements (vergence) or any combination.

Eye movement studies have provided a strong foundation forming an understanding of how the brain acquires visual information in both the normal and ...

Eye-Tracking Control to Assess Cognitive Functions in Patients with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with pathological involvement of upper and lower motoneurons, subsequently leading to progressive loss of motor and speech abilities. In addition, cognitive functions are impaired in a subset of patients. To evaluate these potential deficits in severely physically impaired ALS patients, eye-tracking is a promising means to conduct cognitive tests. The present article focuses on how eye movements, an indirect means of communication for physically disabled patients, can be utilized to allow for detailed neuropsychological assessment. The requirements, in terms of oculomotor parameters that have to be met for sufficient eye-tracking in ALS patients are presented. The properties of stimuli, including type of neuropsychological tests and style of presentation, best suited to successfully assess cognitive functioning, are also described. Furthermore, recommendations regarding procedural requirements are provided. Overall, this methodology provides a reliable, easy to administer and fast approach for assessing cognitive deficits in patients who are unable to speak or write such as patients with severe ALS. The only confounding factor might be deficits in voluntary eye movement control in a subset of ALS patients.

Cognitive deficits are common in about one third of patients with amyotrophic lateral sclerosis, a neurological condition leading to progressive impairments in speech and movement abilities. To conduct cognitive tests in patients unable to speak or write a reliable and easy to administer eye-tracking paradigm was developed.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder with pathological involvement of upper and lower motoneurons, subsequently leading to ...

Eye Tracking During Visually Situated Language Comprehension: Flexibility and Limitations in Uncovering Visual Context Effects

The present work is a description and an assessment of a methodology designed to quantify different aspects of the interaction between language processing and the perception of the visual world. The recording of eye-gaze patterns has provided good evidence for the contribution of both the visual context and linguistic/world knowledge to language comprehension. Initial research assessed object-context effects to test&#160;theories of modularity in language processing. In the introduction, we describe how subsequent investigations have taken the role of the wider visual context in language processing as a research topic in its own right, asking questions such as how our visual perception of events and of speakers contributes to&#160;comprehension informed by&#160;comprehenders&#39; experience. Among the examined aspects of the visual context are actions, events, a speaker&#39;s gaze, and emotional facial expressions, as well as spatial object configurations. Following an overview of the eye-tracking method and its different applications, we list the key steps of the methodology in the protocol, illustrating how to successfully use it to study visually-situated language comprehension. A final section presents three sets of representative results and illustrates the benefits and limitations of eye tracking for investigating the interplay between the perception of the visual world and language comprehension.

The present article reviews an eye-tracking methodology for studies on language comprehension. To obtain reliable data, key steps of the protocol must be followed. Among these are the correct set-up of the eye tracker (e.g., ensuring good quality of the eye and head images) and accurate calibration.

The present work is a description and an assessment of a methodology designed to quantify different aspects of the interaction between language processing ...

Loneliness Assuaged: Eye-Tracking an Audience Watching Barrage Videos

Researchers usually theorize media exposure based on assumptions of legacy media. However, a new interactive video viewing format, in this case barrage video where viewers&#8217; comments are overlaid over visual content, challenges past perspectives. This study proposes an activation and match satisfaction model to study viewing behaviors of lonely people and to challenge previous claims. It presents a protocol to examine the mechanism of how loners use barrage videos by combining eye tracking and self-report measures. Eye tracking documents the audience&#39;s conscious and subconscious watching behaviors in real time and allows for inference of the amount of allocated cognitive resources in response to rational and emotional content. The self-report gauges the amount of satisfaction obtained. Overall, results from the measures supported an activation and match satisfaction model regarding loners and their barrage video viewing behaviors. Implications are discussed.

The study proposes an activation-match model to study how loneliness is mitigated when a lonely audience watches barrage videos of rational and emotional appeals. The protocol uses eye tracking to document duration and fixation, accounting for the degree of satisfaction when emotional needs are appeased by content and barrage.

Researchers usually theorize media exposure based on assumptions of legacy media. However, a new interactive video viewing format, in this case barrage ...

Eye-tracking Technology and Data-mining Techniques used for a Behavioral Analysis of Adults engaged in Learning Processes

Behavioral analysis of adults engaged in learning tasks is a major challenge in the field of adult education. Nowadays, in a world of continuous technological changes and scientific advances, there is a need for life-long learning and education within both formal and non-formal educational environments. In response to this challenge, the use of eye-tracking technology and data-mining techniques, respectively, for supervised (mainly prediction) and unsupervised (specifically cluster analysis) learning, provide methods for the detection of forms of learning among users and/or the classification of their learning styles. In this study, a protocol is proposed for the study of learning styles among adults with and without previous knowledge at different ages (18 to 69-year-old) and at different points throughout the learning process (start and end). Statistical analysis-of-variance techniques mean that differences may be detected between the participants by type of learner and previous knowledge of the task. Likewise, the use of&#160;unsupervised learning clustering techniques throws light on similar forms of learning among the participants across different groups. All these data will facilitate personalized proposals from the teacher for the presentation of each task at different points in the chain of information processing. It will likewise be easier for the teacher to adapt teaching materials to the learning needs of each student or group of students with similar characteristics.

We present a protocol for a behavioral analysis of adults (ages 18 to 70-year-old) engaged in learning processes, undertaking tasks designed for Self-Regulated Learning (SRL). The participants, university teachers and students, and adults from the University of Experience, were monitored with eye-tracking devices and the data were analyzed with data-mining techniques.

Behavioral analysis of adults engaged in learning tasks is a major challenge in the field of adult education. Nowadays, in a world of continuous ...

Investigating Oculomotor Responses in Visual Duration Perception Tasks

Eye Movements in Visual Duration Perception: Disentangling Stimulus from Time in Predecisional Processes

Eye-tracking methods may allow the online monitoring of cognitive processing during visual duration perception tasks, where participants are asked to estimate, discriminate, or compare time intervals defined by visual events like flashing circles. However, and to our knowledge, attempts to validate this possibility have remained inconclusive so far, and results remain focused on offline behavioral decisions made after stimulus appearance. This paper presents an eye-tracking protocol for exploring the cognitive processes preceding behavioral responses in an interval comparison task, where participants viewed two consecutive intervals and had to decide whether it speeded up (first interval longer than second) or slowed down (second interval longer). 
Our main concern was disentangling oculomotor responses to the visual stimulus itself from correlates of duration related to judgments. To achieve this, we defined three consecutive time windows based on critical events: baseline onset, the onset of the first interval, the onset of the second interval, and the end of the stimulus. We then extracted traditional oculomotor measures for each (number of fixations, pupil size) and focused on time-window-related changes to separate the responses to the visual stimulus from those related to interval comparison per se. As we show in the illustrative results, eye-tracking data showed significant differences that were consistent with behavioral results, raising hypotheses on the mechanisms engaged. This protocol is embryonic and will require many improvements, but it represents an important step forward in the current state of art.

Author Spotlight: Exploring the Link Between Time Perception of Visual Stimuli and Reading Skills

We present a protocol that employs eye tracking to monitor eye movements during an interval comparison (duration perception) task based on visual events. The aim is to provide a preliminary guide to separate oculomotor responses to duration perception tasks (comparison or discrimination of time intervals) from responses to the stimulus itself.

Eye-tracking methods may allow the online monitoring of cognitive processing during visual duration perception tasks, where participants are asked to ...

Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking

Cognitive impairment is a common phenomenon in Parkinson&#8217;s disease that has implications on the prognosis. A simple, noninvasive and objective proxy measurement of cognitive function in Parkinson&#8217;s disease will be helpful in detecting early cognitive decline. As a physiological metric, eye movement parameter is not confounded by the subject&#39;s attributes and intelligence and can function as a proxy marker if it correlates with cognitive functions. To this end, this study explored the relationship between the eye movement parameters and performance in cognitive tests in multiple domains. In the experiment, a visual search task with eye tracking was set up, where subjects were asked to look for a number embedded in an array of alphabets scattered randomly on a computer screen. The differentiation between the number and the alphabet is an overlearned task such that the confounding effect of cognitive ability on the eye movement parameters is minimized. The average saccadic amplitude and fixation duration were captured and calculated during the visual search task. The cognitive assessment battery covered domains of frontal-executive functions, attention, verbal and visual memory. It was found that prolonged fixation duration was associated with poorer performance in verbal fluency, visual and verbal memory, allowing further exploration on the use of eye movement parameters as proxy markers for cognitive function in Parkinson&#8217;s disease patients. The experimental paradigm has been found to be highly tolerable in our group of Parkinson&#39;s disease patients and could be applied transdiagnostically to other disease entities for similar research questions.

Here, we present a protocol to study the relationship between the eye movement parameters and cognitive functions in non-demented Parkinson&#39;s disease patients. The experiment used an eye tracker to measure the saccadic amplitude and fixation duration in a visual search task. The correlation with performance in multi-domain cognitive tasks was subsequently measured.

Cognitive impairment is a common phenomenon in Parkinson&#8217;s disease that has implications on the prognosis. A simple, noninvasive and objective proxy ...

Gaze-Contingent Framework for Studying and Training in Simulated Vision Loss

A Gaze-Contingent Display Framework for Perceptual Learning Research with Simulated Central Vision Loss

Macular degeneration (MD) is one of the leading causes of vision impairment in the Western world. Patients with MD tend to develop spontaneous eye movement strategies to compensate for their vision loss, including adopting a preferred retinal locus, or PRL, a spared peripheral region that they use more frequently to replace the damaged fovea. However, not all patients are successful in developing a PRL, and even when they do, it might take them months. Currently, no gold standard rehabilitative therapy exists, and MD research is further hindered by issues of recruitment, compliance, and comorbidity. To help address these issues, a growing body of research has used eye tracking-guided, gaze-contingent displays in a simulated central vision loss paradigm in individuals with intact vision. While simulated vision loss is qualitatively different than pathological central vision loss, our framework provides for a highly controlled model through which to study compensatory eye movements and test possible rehabilitation interventions in low vision. By developing a comprehensive framework, rather than relying on isolated and disconnected tasks, we create a cohesive environment where we can test larger-scale hypotheses, allowing us to examine interactions between tasks, assess training effects across multiple measures, and establish a consistent methodology for future research. Furthermore, participants in simulated central vision loss studies show similarities in their oculomotor compensatory behaviors compared to patients with MD. Here, we present a framework for conducting gaze-contingent studies related to simulated central vision loss. We emphasize the utilization of the framework to test behavioral and oculomotor performance of healthy individuals on a wide range of perceptual tasks encompassing different levels of visual processing. We also discuss how this framework can be adapted for training MD patients.

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

We present development of a gaze-contingent display framework designed for perceptual and oculomotor research simulating central vision loss. This framework is particularly adaptable for studying compensatory behavioral and oculomotor strategies in individuals experiencing both simulated and pathological central vision loss.