The effect of age and gender on anti-saccade performance: Results from a large cohort of healthy aging individuals.

By 2050, the global population of people aged 65 years or older will triple. While this is accompanied with an increasing burden of age-associated diseases, it also emphasizes the need to understand the effects of healthy aging on cognitive processes. One such effect is a general slowing of processing speed, which is well documented in many domains. The execution of anti-saccades depends on a well-established brain-wide network ranging from various cortical areas and basal ganglia through the superior colliculus down to the brainstem saccade generators. To clarify the consequences of healthy aging as well as gender on the execution of reflexive and voluntary saccades, we measured a large sample of healthy, non-demented individuals (n = 731, aged 51-84 years) in the anti-saccade task. Age affected various aspects of saccade performance: The number of valid trials decreased with age. Error rate, saccadic reaction times (SRTs), and variability in saccade accuracy increased with age, whereas anti-saccade costs, accuracy, and peak velocity of anti-saccades and direction errors were not affected by age. Gender affected SRTs independent of age and saccade type with male participants having overall shorter SRTs. Our rigid and solid statistical testing using linear mixed-effect models provide evidence for a uniform slowing of processing speed independent of the actually performed eye movement. Our data do not support the assumption of a specific deterioration of frontal lobe functions with aging.

Model-Based Separation, Detection, and Classification of Eye Movements.

OBJECTIVE: We present a physiologically motivated eye movement analysis framework for model-based separation, detection, and classification (MBSDC) of eye movements. By estimating kinematic and neural controller signals for saccades, smooth pursuit, and fixational eye movements in a mechanistic model of the oculomotor system we are able to separate and analyze these eye movements independently. METHODS: We extended an established oculomotor model for horizontal eye movements by neural controller signals and by a blink artifact model. To estimate kinematic (position, velocity, acceleration, forces) and neural controller signals from eye position data, we employ Kalman smoothing and sparse input estimation techniques. The estimated signals are used for detecting saccade start and end points, and for classifying the recording into saccades, smooth pursuit, fixations, post-saccadic oscillations, and blinks. RESULTS: On simulated data, the reconstruction error of the velocity profiles is about half the error value obtained by the commonly employed approach of filtering and numerical differentiation. In experiments with smooth pursuit data from human subjects, we observe an accurate signal separation. In addition, in neural recordings from non-human primates, the estimated neural controller signals match the real recordings strikingly well. SIGNIFICANCE: The MBSDC framework enables the analysis of multi-type eye movement recordings and provides a physiologically motivated approach to study motor commands and might aid the discovery of new digital biomarkers. CONCLUSION: The proposed framework provides a model-based approach for a wide variety of eye movement analysis tasks.

Automated False Alarm Reduction in a Real-Life Intensive Care Setting Using Motion Detection.

BACKGROUND: Contemporary monitoring systems are sensitive to motion artifacts and cause an excess of false alarms. This results in alarm fatigue and hazardous alarm desensitization. To reduce the number of false alarms, we developed and validated a novel algorithm to classify alarms, based on automatic motion detection in videos. METHODS: We considered alarms generated by the following continuously measured parameters: arterial oxygen saturation, systolic blood pressure, mean blood pressure, heart rate, and mean intracranial pressure. The movements of the patient and in his/her surroundings were monitored by a camera situated at the ceiling. Using the algorithm, alarms were classified into RED (true), ORANGE (possibly false), and GREEN alarms (false, i.e., artifact). Alarms were reclassified by blinded clinicians. The performance was evaluated using confusion matrices. RESULTS: A total of 2349 alarms from 45 patients were reclassified. For RED alarms, sensitivity was high (87.0%) and specificity was low (29.6%) for all parameters. As the sensitivities and specificities for RED and GREEN alarms are interrelated, the opposite was observed for GREEN alarms, i.e., low sensitivity (30.2%) and high specificity (87.2%). As RED alarms should not be missed, even at the expense of false positives, the performance was acceptable. The low sensitivity for GREEN alarms is acceptable, as it is not harmful to tag a GREEN alarm as RED/ORANGE. It still contributes to alarm reduction. However, a 12.8% false-positive rate for GREEN alarms is critical. CONCLUSIONS: The proposed system is a step forward toward alarm reduction; however, implementation of additional layers, such as signal curve analysis, multiple parameter correlation analysis and/or more sophisticated video-based analytics are needed for improvement.

Portable Infrared Pupillometer in Patients With Subarachnoid Hemorrhage: Prognostic Value and Circadian Rhythm of the Neurological Pupil Index (NPi).

BACKGROUND: Portable automated infrared pupillometry is becoming increasingly popular. To generate an objective reference base, the Neurological Pupil index (NPi) which combines different values of the pupillary light reflex is being introduced into clinical practice. In this explorative study, we examined different aspects of the NPi in relation to clinical severity and outcome in patients with aneurysmal subarachnoid hemorrhage (aSAH). MATERIALS AND METHODS: Patients with serial assessment of the NPi (NeurOptics pupillometer NPi-200, Irvine, CA) starting no later than day 2 after aSAH onset were included in the study. Relative numbers of pathologic NPi's, absolute NPi values, and their variances were compared according to aSAH clinical severity grade, functional outcome, and case fatality. The correlation between NPi and intracranial pressure, and NPi periodicity, were also examined. RESULTS: In total, 18 patients with 4456 NPi values were eligible for inclusion in the analysis. The general trend of the NPi over time reflected the course of the neurological illness. Mean NPi tended to be lower in patients with clinically severe compared with nonsevere aSAH (3.75±0.40 vs. 4.56±0.06; P=0.171), and in patients with unfavorable compared with favorable outcomes (3.64±0.48 vs. 4.50±0.08; P=0.198). The mean variance of the NPi was higher in patients with severe compared with nonsevere aSAH (0.49±0.17 vs. 0.06±0.02; P=0.025). Pathologic NPi values were recorded more frequently in patients with severe compared with nonsevere aSAH (16.3%±8.8% vs. 0.0%±0.0%; P=0.002), and in those with unfavorable compared with favorable outcomes (19.2%±10.6% vs. 0.7%±0.6%; P=0.017). NPi was inversely correlated with intracranial pressure (Spearman r=-0.551, P<0.001). We observed a circadian pattern of NPi's which was seemingly disrupted in patients with fatal outcome. CONCLUSIONS: On the basis of this preliminary study, the assessment of NPi by pupillometry is feasible and might complement multimodal neuromonitoring in patients with aSAH.

Estimation of Neural Inputs and Detection of Saccades and Smooth Pursuit Eye Movements by Sparse Bayesian Learning.

Eye movements reveal a great wealth of information about the visual system and the brain. Therefore, eye movements can serve as diagnostic markers for various neurological disorders. For an objective analysis, it is crucial to have an automatic and robust procedure to extract relevant eye movement parameters. An essential step towards this goal is to detect and separate different types of eye movements such as fixations, saccades and smooth pursuit. We have developed a model-based approach to perform signal detection and separation on eye movement recordings, using source separation techniques from sparse Bayesian learning. The key idea is to model the oculomotor system with a state space model and to perform signal separation in the neural domain by estimating sparse inputs which trigger saccades. The algorithm was evaluated on synthetic data, neural recordings from rhesus monkeys and on manually annotated human eye movement recordings with different smooth pursuit paradigms. The developed approach shows a high noise-robustness, provides saccade and smooth pursuit parameters, as well as estimates of the position, velocity and acceleration profiles. In addition, by estimating the input to the oculomotor system, we obtain an estimate of the neural inputs to the oculomotor muscles.

The effect of sampling rate and lowpass filters on saccades - A modeling approach.

The study of eye movements has become popular in many fields of science. However, using the preprocessed output of an eye tracker without scrutiny can lead to low-quality or even erroneous data. For example, the sampling rate of the eye tracker influences saccadic peak velocity, while inadequate filters fail to suppress noise or introduce artifacts. Despite previously published guiding values, most filter choices still seem motivated by a trial-and-error approach, and a thorough analysis of filter effects is missing. Therefore, we developed a simple and easy-to-use saccade model that incorporates measured amplitude-velocity main sequences and produces saccades with a similar frequency content to real saccades. We also derived a velocity divergence measure to rate deviations between velocity profiles. In total, we simulated 155 saccades ranging from 0.5° to 60° and subjected them to different sampling rates, noise compositions, and various filter settings. The final goal was to compile a list with the best filter settings for each of these conditions. Replicating previous findings, we observed reduced peak velocities at lower sampling rates. However, this effect was highly non-linear over amplitudes and increasingly stronger for smaller saccades. Interpolating the data to a higher sampling rate significantly reduced this effect. We hope that our model and the velocity divergence measure will be used to provide a quickly accessible ground truth without the need for recording and manually labeling saccades. The comprehensive list of filters allows one to choose the correct filter for analyzing saccade data without resorting to trial-and-error methods.

Video game players show higher performance but no difference in speed of attention shifts.

Video games have become both a widespread leisure activity and a substantial field of research. In a variety of tasks, video game players (VGPs) perform better than non-video game players (NVGPs). This difference is most likely explained by an alteration of the basic mechanisms underlying visuospatial attention. More specifically, the present study hypothesizes that VGPs are able to shift attention faster than NVGPs. Such alterations in attention cannot be disentangled from changes in stimulus-response mappings in reaction time based measurements. Therefore, we used a spatial cueing task with varying cue lead times (CLTs) to investigate the speed of covert attention shifts of 98 male participants divided into 36 NVGPs and 62 VGPs based on their weekly gaming time. VGPs exhibited higher peak and mean performance than NVGPs. However, we did not find any differences in the speed of covert attention shifts as measured by the CLT needed to achieve peak performance. Thus, our results clearly rule out faster stimulus-response mappings as an explanation for the higher performance of VGPs in line with previous studies. More importantly, our data do not support the notion of faster attention shifts in VGPs as another possible explanation.

Association between vestibulo-ocular reflex suppression, balance, gait, and fall risk in ageing and neurodegenerative disease: protocol of a one-year prospective follow-up study.

BACKGROUND: Falls frequency increases with age and particularly in neurogeriatric cohorts. The interplay between eye movements and locomotion may contribute substantially to the occurrence of falls, but is hardly investigated. This paper provides an overview of current approaches to simultaneously measure eye and body movements, particularly for analyzing the association of vestibulo-ocular reflex (VOR) suppression, postural deficits and falls in neurogeriatric risk cohorts. Moreover, VOR suppression is measured during head-fixed target presentation and during gaze shifting while postural control is challenged. Using these approaches, we aim at identifying quantitative parameters of eye-head-coordination during postural balance and gait, as indicators of fall risk. METHODS/DESIGN: Patients with Progressive Supranuclear Palsy (PSP) or Parkinson's disease (PD), age- and sex-matched healthy older adults, and a cohort of young healthy adults will be recruited. Baseline assessment will include a detailed clinical assessment, covering medical history, neurological examination, disease specific clinical rating scales, falls-related self-efficacy, activities of daily living, neuro-psychological screening, assessment of mobility function and a questionnaire for retrospective falls. Moreover, participants will simultaneously perform eye and head movements (fixating a head-fixed target vs. shifting gaze to light emitting diodes in order to quantify vestibulo-ocular reflex suppression ability) under different conditions (sitting, standing, or walking). An eye/head tracker synchronized with a 3-D motion analysis system will be used to quantify parameters related to eye-head-coordination, postural balance, and gait. Established outcome parameters related to VOR suppression ability (e.g., gain, saccadic reaction time, frequency of saccades) and motor related fall risk (e.g., step-time variability, postural sway) will be calculated. Falls will be assessed prospectively over 12 months via protocols and monthly telephone interviews. DISCUSSION: This study protocol describes an experimental setup allowing the analysis of simultaneously assessed eye, head and body movements. Results will improve our understanding of the influence of the interplay between eye, head and body movements on falls in geriatric high-risk cohorts.

The effects of video game play on the characteristics of saccadic eye movements.

Video game play has become a common leisure activity all around the world. To reveal possible effects of playing video games, we measured saccades elicited by video game players (VGPs) and non-players (NVGPs) in two oculomotor tasks. First, our subjects performed a double-step task. Second, we asked our subjects to move their gaze opposite to the appearance of a visual target, i.e. to perform anti-saccades. As expected on the basis of previous studies, VGPs had significantly shorter saccadic reaction times (SRTs) than NVGPs for all saccade types. However, the error rates in the anti-saccade task did not reveal any significant differences. In fact, the error rates of VGPs were actually slightly lower compared to NVGPs (34% versus 40%, respectively). In addition, VGPs showed significantly higher saccadic peak velocities in every saccade type compared to NVGP. Our results suggest that faster SRTs in VGPs were associated with a more efficient motor drive for saccades. Taken together, our results are in excellent agreement with earlier reports of beneficial video game effects through the general reduction in SRTs. Our data clearly provides additional experimental evidence for an higher efficiency of the VGPs on the one hand and refutes the notion of a reduced impulse control in VGPs on the other.