scholarly journals Portable eye-tracking as a reliable assessment of oculomotor, cognitive and reaction time function: Normative data for 18–45 year old

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260351
Author(s):  
Aura Kullmann ◽  
Robin C. Ashmore ◽  
Alexandr Braverman ◽  
Christian Mazur ◽  
Hillary Snapp ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Reaction Time ◽  
Eye Tracking ◽  
Cognitive Processing ◽  
Normative Data ◽  
Head Injuries ◽  
Neural Pathways ◽  
Data Set ◽  
Normative Database ◽  
Tracking Technology

Eye movements measured by high precision eye-tracking technology represent a sensitive, objective, and non-invasive method to probe functional neural pathways. Oculomotor tests (e.g., saccades and smooth pursuit), tests that involve cognitive processing (e.g., antisaccade and predictive saccade), and reaction time tests have increasingly been showing utility in the diagnosis and monitoring of mild traumatic brain injury (mTBI) in research settings. Currently, the adoption of these tests into clinical practice is hampered by a lack of a normative data set. The goal of this study was to construct a normative database to be used as a reference for comparing patients’ results. Oculomotor, cognitive, and reaction time tests were administered to male and female volunteers, aged 18–45, who were free of any neurological, vestibular disorders, or other head injuries. Tests were delivered using either a rotatory chair equipped with video-oculography goggles (VOG) or a portable virtual reality-like VOG goggle device with incorporated infrared eye-tracking technology. Statistical analysis revealed no effects of age on test metrics when participant data were divided into pediatric (i.e.,18–21 years, following FDA criteria) and adult (i.e., 21–45 years) groups. Gender (self-reported) had an effect on auditory reaction time, with males being faster than females. Pooled data were used to construct a normative database using 95% reference intervals (RI) with 90% confidence intervals on the upper and lower limits of the RI. The availability of these RIs readily allows clinicians to identify specific metrics that are deficient, therefore aiding in rapid triage, informing and monitoring treatment and/or rehabilitation protocols, and aiding in the return to duty/activity decision. This database is FDA cleared for use in clinical practice (K192186).

Oculomotor, vestibular, reaction time and cognitive eye-tracking mild traumatic brain injury assessment

Neurology ◽  
2020 ◽  
Vol 95 (20 Supplement 1) ◽  
pp. S2.1-S2
Author(s):  
Alex Kiderman ◽  
Michael Hoffer ◽  
Mikhaylo Szczupak ◽  
Hillary Snapp ◽  
Sara Murphy ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Reaction Time ◽  
Eye Tracking ◽  
Regression Model ◽  
Mild Traumatic Brain Injury ◽  
Data Set ◽  
Retest Reliability ◽  
Test Retest Reliability ◽  
Tracking Technology

ObjectiveCan oculomotor, vestibular, reaction time and cognitive eye-tracking tests (OVRT-C) assess mild traumatic brain injury?BackgroundOVRT-C tests using eye tracking technology have been employed in our previous studies for assessing mild traumatic brain injury (mTBI). Here we present a composite Concussion Assessment algorithm that incorporates these findings.Design/MethodsConcussion Assessment algorithm was based on a data analysis from 406 males and females 18–45 years old. The subjects included 106 patients diagnosed with mTBI and 300 healthy controls. Diagnosis of mTBI was made using accepted medical practice. The participants were tested with a battery of OVRT-C tests delivered on the I-Portal Neuro Otologic Test Center (Dx NOTC) device (Neurolign Technology). A logistic regression model was used to derive the algorithm using a random sample of 70% of the data-set and validated on the remaining 30% of the data-set. Device test-retest reliability and inter-rater variability were assessed in a separate study in healthy control volunteers, ages 19–43 (n = 30). Subjects were tested with OVRT-C tests using the Dx100 which is equivalent to the NOTC. Test-retest reliability was assessed using Intraclass Correlation Coefficient (ICC) and Cronbach's alpha; testers and devices influence were assessed using a random effect regression model.ResultsTest-retest reliability of OVRT-C tests using eye tracking technology was acceptable (ICC >0.6 for all variables). The Concussion assessment algorithm was based on six OVRT-C tests. In the validation data Concussion Assessment algorithm was able to separate concussed versus controls with a sensitivity of 78.6% and specificity of 72.3%.ConclusionsOVRT-C tests delivered on I-Portal devices are repeatable and reliable. The assessment can identify mTBI subjects within an acute time post-injury with high sensitivity and specificity. The results support the use of this eye tracking device as well as the assessment to aid in the diagnosis of mTBI for patients 18–45 year old.

scholarly journals Quantitative Electroencephalogram Standardization: A Sex- and Age-Differentiated Normative Database

2021 ◽  
Vol 15 ◽  
Author(s):  
Juhee Ko ◽  
Ukeob Park ◽  
Daekeun Kim ◽  
Seung Wan Kang
Keyword(s):  
Resting State ◽  
Normative Data ◽  
Quantitative Eeg ◽  
Z Score ◽  
Data Set ◽  
Normative Database ◽  
Confounding Variables ◽  
Z Scores ◽  
Quantitative Electroencephalogram ◽  
Standardized Index

We describe the utility of a standardized index (Z-score) in quantitative EEG (QEEG) capable of when referenced to a resting-state, sex- and age-differentiated QEEG normative database (ISB-NormDB). Our ISB-NormDB comprises data for 1,289 subjects (553 males, 736 females) ages 4.5 to 81 years that met strict normative data criteria. A de-noising process allowed stratification based on QEEG variability between normal healthy men and women at various age ranges. The ISB-NormDB data set that is stratified by sex provides a unique, highly accurate ISB-NormDB model (ISB-NormDB: ISB-NormDB-Male, ISB-NormDB-Female). To evaluate the trends and accuracy of the ISB-NormDB, we used actual data to compare Z-scores obtained through the ISB-NormDB with those obtained through a traditional QEEG normative database to confirm that basic trends are maintained in most bands and are sensitive to abnormal test data. Finally, we demonstrate the value of our standardized index of QEEG, and highlight it’s capacity to minimize the confounding variables of sex and age in any analysis.

The Opposition of Surprisal and Semantic Similarity in the Prediction of Language Processing: Evidence from Eye-tracking Data

2020 ◽  
Author(s):  
Kun Sun
Keyword(s):  
Eye Tracking ◽  
Semantic Similarity ◽  
Cognitive Processing ◽  
Language Processing ◽  
Language Comprehension ◽  
Word Processing ◽  
Reading Time ◽  
Computational Models ◽  
Tracking Data ◽  
Dynamic Approach

Expectations or predictions about upcoming content play an important role during language comprehension and processing. One important aspect of recent studies of language comprehension and processing concerns the estimation of the upcoming words in a sentence or discourse. Many studies have used eye-tracking data to explore computational and cognitive models for contextual word predictions and word processing. Eye-tracking data has previously been widely explored with a view to investigating the factors that influence word prediction. However, these studies are problematic on several levels, including the stimuli, corpora, statistical tools they applied. Although various computational models have been proposed for simulating contextual word predictions, past studies usually preferred to use a single computational model. The disadvantage of this is that it often cannot give an adequate account of cognitive processing in language comprehension. To avoid these problems, this study draws upon a massive natural and coherent discourse as stimuli in collecting the data on reading time. This study trains two state-of-art computational models (surprisal and semantic (dis)similarity from word vectors by linear discriminative learning (LDL)), measuring knowledge of both the syntagmatic and paradigmatic structure of language. We develop a `dynamic approach' to compute semantic (dis)similarity. It is the first time that these two computational models have been merged. Models are evaluated using advanced statistical methods. Meanwhile, in order to test the efficiency of our approach, one recently developed cosine method of computing semantic (dis)similarity based on word vectors data adopted is used to compare with our `dynamic' approach. The two computational and fixed-effect statistical models can be used to cross-verify the findings, thus ensuring that the result is reliable. All results support that surprisal and semantic similarity are opposed in the prediction of the reading time of words although both can make good predictions. Additionally, our `dynamic' approach performs better than the popular cosine method. The findings of this study are therefore of significance with regard to acquiring a better understanding how humans process words in a real-world context and how they make predictions in language cognition and processing.

scholarly journals Normative data for ages 18‐45 for ocular motor and vestibular testing using eye tracking

2021 ◽  
Author(s):  
Aura Kullmann ◽  
Robin C. Ashmore ◽  
Alexandr Braverman ◽  
Christian Mazur ◽  
Hillary Snapp ◽  
...  
Keyword(s):  
Eye Tracking ◽  
Normative Data ◽  
Ocular Motor ◽  
Vestibular Testing

scholarly journals Effects of age on memory for pragmatic implications in advertising

2021 ◽  
Vol 15 ◽  
pp. 183449092110004
Author(s):  
Jing Yu ◽  
Xue-Rui Peng ◽  
Ming Yan
Keyword(s):  
Older Adults ◽  
Eye Tracking ◽  
Cognitive Processes ◽  
Time Processing ◽  
Movement Data ◽  
Processing Strategies ◽  
Health Related ◽  
Advertising Content ◽  
Inferential Processing ◽  
Tracking Technology

People employ automatic inferential processing when confronting pragmatically implied claims in advertising. However, whether comprehension and memorization of pragmatic implications differ between young and older adults is unclear. In the present study, we used eye-tracking technology to investigate online cognitive processes during reading of misleading advertisements. We found an interaction between age and advertising content, manifested as our older participants generated higher misleading rates in health-related than in health-irrelevant products, whereas this content-bias did not appear in their younger counterparts. Eye movement data further showed that the older adults spent more time processing critical claims for the health-related products than for the health-irrelevant products. Moreover, the correlations between fixation duration on pragmatic implications and misleading rates showed opposite trends in the two groups. The eye-tracking evidence novelly suggests that young and older adults may adopt different information processing strategies to comprehend pragmatic implications in advertising: More reading possibly enhances young adults’ gist memory whereas it facilitates older adults’ verbatim memory instead.

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