Association of Visual Tracking Metrics With Post-concussion Symptomatology.

Attention impairment may provide a cohesive neurobiological explanation for clusters of clinical symptoms that occur after a concussion; therefore, objective quantification of attention is needed. Visually tracking a moving target is an attention-dependent sensorimotor function, and eye movement can be recorded easily and objectively to quantify performance. Our previous work suggested the utility of gaze-target synchronization metrics of a predictive visual tracking task in concussion screening and recovery monitoring. Another objectively quantifiable performance measure frequently suggested for concussion screening is simple visuo-manual reaction time (simple reaction time, SRT). Here, we used visual tracking and SRT tasks to assess changes between pre- and within-2-week post-concussion performances and explore their relationships to post-concussion symptomatology. Athletes participating in organized competitive sports were recruited. Visual tracking and SRT records were collected from the recruited athlete pool as baseline measures over a 4-year period. When athletes experienced a concussion, they were re-assessed within 2 weeks of their injury. We present the data from a total of 29 concussed athletes. Post-concussion symptom burden was assessed with the Rivermead Post-Concussion Symptoms Questionnaire and subscales of the Brain Injury Screening Questionnaire. Post-concussion changes in visual tracking and SRT performance were examined using a paired t-test. Correlations of changes in visual tracking and SRT performance to symptom burden were examined using Pearson's coefficients. Post-concussion changes in visual tracking performance were not consistent among the athletes. However, changes in several visual tracking metrics had moderate to strong correlations to symptom scales (r up to 0.68). On the other hand, while post-concussion SRT performance was reduced (p < 0.01), the changes in the performance metrics were not meaningfully correlated to symptomatology (r ≤ 0.33). Results suggest that visual tracking performance metrics reflect clinical symptoms when assessed within 2 weeks of concussion. Evaluation of concussion requires assessments in multiple domains because the clinical profiles are heterogeneous. While most individuals show recovery within a week of injury, others experience prolonged recovery periods. Visual tracking performance metrics may serve as a biomarker of debilitating symptoms of concussion implicating attention as a root cause of such pathologies.

Visual Tracking in Development and Aging.

A moving target is visually tracked with a combination of smooth pursuit and saccades. Human visual tracking eye movement develops through early childhood and adolescence, and declines in senescence. However, the knowledge regarding performance changes over the life course is based on data from distinct age groups in isolation using different procedures, and thus is fragmented. We sought to describe the age-dependence of visual tracking performance across a wide age range and compare it to that of simple visuo-manual reaction time. We studied a cross-sectional sample of 143 subjects aged 7-82 years old (37% male). Eye movements were recorded using video-oculography, while subjects viewed a computer screen and tracked a small target moving along a circular trajectory at a constant speed. For simple reaction time (SRT) measures, series of key presses that subjects made in reaction to cue presentation on a computer monitor were recorded using a standard software. The positional precision and smooth pursuit velocity gain of visual tracking followed a U-shaped trend over age, with best performances achieved between the ages of 20 and 50 years old. A U-shaped trend was also found for mean reaction time in agreement with the existing literature. Inter-individual variability was evident at any age in both visual tracking and reaction time metrics. Despite the similarity in the overall developmental and aging trend, correlations were not found between visual tracking and reaction time performances after subtracting the effects of age. Furthermore, while a statistically significant difference between the sexes was found for mean SRT in the sample, a similar difference was not found for any of the visual tracking metrics. Therefore, the cognitive constructs and their neural substrates supporting visual tracking and reaction time performances appear largely independent. In summary, age is an important covariate for visual tracking performance, especially for a pediatric population. Since visual tracking performance metrics may provide signatures of abnormal neurological or cognitive states independent of reaction time-based metrics, further understanding of age-dependent variations in normal visual tracking behavior is necessary.

Frequency Responses to Visual Tracking Stimuli May Be Affected by Concussion.

Human visual tracking performance is known to be reduced with an increase of the target's speed and oscillation frequency, but changes in brain states following a concussion may alter these frequency responses. The goal of this study was to characterize and compare frequency-dependent smooth pursuit velocity degradation in normal subjects and patients who had chronic postconcussion symptoms, and also examine cases of acutely concussed patients. Eye movements were recorded while subjects tracked a target that moved along a circular trajectory of 10° radius at 0.33, 0.40, or 0.67 Hz. Performance was characterized by the gain of smooth pursuit velocity, with reduced gain indicating reduced performance. The difference between normal and chronic patient groups in the pattern of decrease in the gain of horizontal smooth pursuit velocity as a function of the stimulus frequency reflected patients performing more poorly than normal subjects at 0.4 Hz while both groups performing similarly at 0.33 or 0.67 Hz. The performance of acute patients may represent yet another type of frequency response. The findings suggest that there may be ranges of stimulus frequencies that differentiate the effects of concussion from normal individuals.

Degradation of Binocular Coordination during Sleep Deprivation.

To aid a clear and unified visual perception while tracking a moving target, both eyes must be coordinated, so the image of the target falls on approximately corresponding areas of the fovea of each eye. The movements of the two eyes are decoupled during sleep, suggesting a role of arousal in regulating binocular coordination. While the absence of visual input during sleep may also contribute to binocular decoupling, sleepiness is a state of reduced arousal that still allows for visual input, providing a context within which the role of arousal in binocular coordination can be studied. We examined the effects of sleep deprivation on binocular coordination using a test paradigm that we previously showed to be sensitive to sleep deprivation. We quantified binocular coordination with the SD of the distance between left and right gaze positions on the screen. We also quantified the stability of conjugate gaze on the target, i.e., gaze-target synchronization, with the SD of the distance between the binocular average gaze and the target. Sleep deprivation degraded the stability of both binocular coordination and gaze-target synchronization, but between these two forms of gaze control the horizontal and vertical components were affected differently, suggesting that disconjugate and conjugate eye movements are under different regulation of attentional arousal. The prominent association found between sleep deprivation and degradation of binocular coordination in the horizontal direction may be used for a fit-for-duty assessment.

Visual memory for fixated regions of natural images dissociates attraction and recognition.

Recognition memory for fixated regions from briefly viewed full-screen natural images is examined. Low-level image statistics reveal that observers fixated, on average (pooled across images and observers), image regions that possessed greater visual saliency than non-fixated regions, a finding that is robust across multiple fixation indices. Recognition-memory performance indicates that, of the fixation loci tested, observers were adept at recognising those with a particular profile of image statistics; visual saliency was found to be attenuated for unrecognised loci, despite that all regions were freely fixated. Furthermore, although elevated luminance was the local image statistic found to discriminate least between human and random image locations, it was the greatest predictor of recognition-memory performance, demonstrating a dissociation between image features that draw fixations and those that support visual memory. An analysis of corresponding eye movements indicates that image regions fixated via short-distance saccades enjoyed better recognition-memory performance, alluding to a focal rather than ambient mode of processing. Recognised image regions were more likely to have originated from areas evaluated (a posteriori) to have higher fixation density, a numerical metric of local interest. Surprisingly, memory for image regions fixated later in the viewing period exhibited no recency advantage, despite (typically) also being longer in duration, a finding for which a number of explanations are posited.

DOVES: a database of visual eye movements.

DOVES, a database of visual eye movements, is a set of eye movements collected from 29 human observers as they viewed 101 natural calibrated images. Recorded using a high-precision dual-Purkinje eye tracker, the database consists of around 30 000 fixation points, and is believed to be the first large-scale database of eye movements to be made available to the vision research community. The database, along with MATLAB functions for its use, may be downloaded freely from http://live.ece.utexas.edu/research/doves, and used without restriction for educational and research purposes, providing that this paper is cited in any published work. This paper documents the acquisition procedure, summarises common eye movement statistics, and highlights numerous research topics for which DOVES may be used.

Foveated analysis of image features at fixations.

Analysis of the statistics of image features at observers' gaze can provide insights into the mechanisms of fixation selection in humans. Using a foveated analysis framework, in which image patches were analyzed at the resolution corresponding to their eccentricity from the prior fixation, we studied the statistics of four low-level local image features: luminance, RMS contrast, and bandpass outputs of both luminance and contrast, and discovered that the image patches around human fixations had, on average, higher values of each of these features at all eccentricities than the image patches selected at random. Bandpass contrast showed the greatest difference between human and random fixations, followed by bandpass luminance, RMS contrast, and luminance. An eccentricity-based analysis showed that shorter saccades were more likely to land on patches with higher values of these features. Compared to a full-resolution analysis, foveation produced an increased difference between human and random patch ensembles for contrast and its higher-order statistics.

Visual search in noise: revealing the influence of structural cues by gaze-contingent classification image analysis.

Visual search experiments have usually involved the detection of a salient target in the presence of distracters against a blank background. In such high signal-to-noise scenarios, observers have been shown to use visual cues such as color, size, and shape of the target to program their saccades during visual search. The degree to which these features affect search performance is usually measured using reaction times and detection accuracy. We asked whether human observers are able to use target features to succeed in visual search tasks in stimuli with very low signal-to-noise ratios. Using the classification image analysis technique, we investigated whether observers used structural cues to direct their fixations as they searched for simple geometric targets embedded at very low signal-to-noise ratios in noise stimuli that had the spectral characteristics of natural images. By analyzing properties of the noise stimulus at observers' fixations, we were able to reveal idiosyncratic, target-dependent features used by observers in our visual search task. We demonstrate that even in very noisy displays, observers do not search randomly, but in many cases they deploy their fixations to regions in the stimulus that resemble some aspect of the target in their local image features.