Quantification of expected information gain in visual acuity and contrast sensitivity tests.

We make use of expected information gain to quantify the amount of knowledge obtained from measurements in a population. In the first application, we compared the expected information gain in the Snellen, ETDRS, and qVA visual acuity (VA) tests, as well as in the Pelli-Robson, CSV-1000, and qCSF contrast sensitivity (CS) tests. For the VA tests, ETDRS generated more expected information gain than Snellen. Additionally, the qVA test with 15 rows (or 45 optotypes) generated more expected information gain than ETDRS, whether scored with VA threshold alone or with both VA threshold and VA range. Regarding the CS tests, CSV-1000 generated more expected information gain than Pelli-Robson, and the qCSF test with 25 trials generated more expected information gain than CSV-1000, whether scored with AULCSF or with CSF at six spatial frequencies. The active learning-based qVA and qCSF tests have the potential to generate more expected information gain than traditional paper chart tests. Although we have specifically applied it to compare VA and CS tests, expected information gain is a general concept that can be used to compare measurements in any domain.

Visual function resists early neurodegeneration in the visual system in primary progressive multiple sclerosis.

BACKGROUND: Neurodegeneration in multiple sclerosis (MS) affects the visual system but dynamics and pathomechanisms over several years especially in primary progressive MS (PPMS) are not fully understood. METHODS: We assessed longitudinal changes in visual function, retinal neurodegeneration using optical coherence tomography, MRI and serum NfL (sNfL) levels in a prospective PPMS cohort and matched healthy controls. We investigated the changes over time, correlations between outcomes and with loss of visual function. RESULTS: We followed 81 patients with PPMS (mean disease duration 5.9 years) over 2.7 years on average. Retinal nerve fibre layer thickness (RNFL) was reduced in comparison with controls (90.1 vs 97.8 µm; p<0.001). Visual function quantified by the area under the log contrast sensitivity function (AULCSF) remained stable over a continuous loss of RNFL (0.46 µm/year, 95% CI 0.10 to 0.82; p=0.015) up until a mean turning point of 91 µm from which the AULCSF deteriorated. Intereye RNFL asymmetry above 6 µm, suggestive of subclinical optic neuritis, occurred in 15 patients and was related to lower AULCSF but occurred also in 5 out of 44 controls. Patients with an AULCSF progression had a faster increase in Expanded Disability Status Scale (beta=0.17/year, p=0.043). sNfL levels were elevated in patients (12.2 pg/mL vs 8.0 pg/mL, p<0.001), but remained stable during follow-up (beta=-0.14 pg/mL/year, p=0.291) and were not associated with other outcomes. CONCLUSION: Whereas neurodegeneration in the anterior visual system is already present at onset, visual function is not impaired until a certain turning point. sNfL is not correlated with structural or functional impairment in the visual system.

Collective endpoint of visual acuity and contrast sensitivity function from hierarchical Bayesian joint modeling.

Clinical trials typically analyze multiple endpoints for signals of efficacy. To improve signal detection for treatment effects using the high-dimensional data collected in trials, we developed a hierarchical Bayesian joint model (HBJM) to compute a five-dimensional collective endpoint (CE5D) of contrast sensitivity function (CSF) and visual acuity (VA). The HBJM analyzes row-by-row CSF and VA data across multiple conditions, and describes visual functions across a hierarchy of population, individuals, and tests. It generates joint posterior distributions of CE5D that combines CSF (peak gain, peak frequency, and bandwidth) and VA (threshold and range) parameters. The HBJM was applied to an existing dataset of 14 eyes, each tested with the quantitative VA and quantitative CSF procedures in four Bangerter foil conditions. The HBJM recovered strong correlations among CE5D components at all levels. With 15 qVA and 25 qCSF rows, it reduced the variance of the estimated components by 72% on average. Combining signals from VA and CSF and reducing noises, CE5D exhibited significantly higher sensitivity and accuracy in discriminating performance differences between foil conditions at both the group and test levels than the original tests. The HBJM extracts valuable information about covariance of CSF and VA parameters, improves precision of the estimated parameters, and increases the statistical power in detecting vision changes. By combining signals and reducing noise from multiple tests for detecting vision changes, the HBJM framework exhibits potential to increase statistical power for combining multi-modality data in ophthalmic trials.

Quantification of Expected Information Gain in Visual Acuity and Contrast Sensitivity Tests.

We introduce expected information gain to quantify measurements and apply it to compare visual acuity (VA) and contrast sensitivity (CS) tests. We simulated observers with parameters covered by the visual acuity and contrast sensitivity tests and observers based on distributions of normal observers tested in three luminance and four Bangerter foil conditions. We first generated the probability distributions of test scores for each individual in each population in the Snellen, ETDRS and qVA visual acuity tests and the Pelli-Robson, CSV-1000 and qCSF contrast sensitivity tests and constructed the probability distributions of all possible test scores of the entire population. We then computed expected information gain by subtracting expected residual entropy from the total entropy of the population. For acuity tests, ETDRS generated more expected information gain than Snellen; scored with VA threshold only or with both VA threshold and VA range, qVA with 15 rows (or 45 optotypes) generated more expected information gain than ETDRS. For contrast sensitivity tests, CSV-1000 generated more expected information gain than Pelli-Robson; scored with AULCSF or with CS at six spatial frequencies, qCSF with 25 trials generated more expected information gain than CSV-1000. The active learning based qVA and qCSF tests can generate more expected information than the traditional paper chart tests. Although we only applied it to compare visual acuity and contrast sensitivity tests, information gain is a general concept that can be used to compare measurements and data analytics in any domain.

Assessment of the application of cladode cactus mucilage flocculants for hot chemical degreasing electroplating wastewater treatment and reuse: process efficiency and storage stability.

Pressures related to urban growth and industrial activities exacerbated by climate change had an impact on water resources in Tunisia. The present study examines the application of cladode cactus mucilage (CCM) flocculants for hot alkaline chemical degreasing Zn-electroplating wastewater treatment and reuse (WWTR). The CCM flocculation process was selected through their environmental benefits, economic facilities, sustainable use of the natural biopolymer product, input biopolymers substitution, and on-site treated wastewater (TWW) reuse and recovery. The alum coagulation and CCM flocculation were performed by the jar test series. The suitability of treated wastewater quality (TWWQ) with alum/CCM was also assessed for reuse purpose in terms of corrosion-scaling indices (RSI, LSI, PSI, AI), oxidation-reduction potential (ORP), and microbiological community growth (Bacillus, Pseudomonas, Mesophilic bacteria and yeasts) for 28 days storage at 25 °C. The total alkalinity removal efficiency reached 95.8% with an optimum dosage of alum + CCM for hot alkaline chemical degreasing wastewater bath rinsing. The results showed that the stability of TWWQ has significantly deteriorated during storage leading to aggressive wastewater, pathogen growth, and biological malodor production which make them unsuitable for reuse. Therefore, there is a need for CCM processing alternatives that preserve the physico-chemical and microbial of TWW properties during storage.

Quantifying Uncertainty of the Estimated Visual Acuity Behavioral Function With Hierarchical Bayesian Modeling.

Purpose: The goal of this study is to develop a hierarchical Bayesian model (HBM) to better quantify uncertainty in visual acuity (VA) tests by incorporating the relationship between VA threshold and range across multiple individuals and tests. Methods: The three-level HBM consisted of multiple two-dimensional Gaussian distributions of hyperparameters and parameters of the VA behavioral function (VABF) at the population, individual, and test levels. The model was applied to a dataset of quantitative VA (qVA) assessments of 14 eyes in 4 Bangerter foil conditions. We quantified uncertainties of the estimated VABF parameters (VA threshold and range) from the HBM and compared them with those from the qVA. Results: The HBM recovered covariances between VABF parameters and provided better fits to the data than the qVA. It reduced the uncertainty of their estimates by 4.2% to 45.8%. The reduction of uncertainty, on average, resulted in 3 fewer rows needed to reach a 95% accuracy in detecting a 0.15 logMAR change of VA threshold or both parameters than the qVA. Conclusions: The HBM utilized knowledge across individuals and tests in a single model and provided better quantification of the uncertainty of the estimated VABF, especially when the number of tested rows was relatively small. Translational Relevance: The HBM can increase the accuracy in detecting VA changes. Further research is necessary to evaluate its potential in clinical populations.

Validation of Computer-Adaptive Contrast Sensitivity as a Tool to Assess Visual Impairment in Multiple Sclerosis Patients.

BACKGROUND: Impairment of visual function is one of the major symptoms of people with multiple sclerosis (pwMS). A multitude of disease effects including inflammation and neurodegeneration lead to structural impairment in the visual system. However, the gold standard of disability quantification, the expanded disability status scale (EDSS), relies on visual assessment charts. A more comprehensive assessment of visual function is the full contrast sensitivity function (CSF), but most tools are time consuming and not feasible in clinical routine. The quantitative CSF (qCSF) test is a computerized test to assess the full CSF. We have already shown a better correlation with visual quality of life (QoL) than for classical high and low contrast charts in multiple sclerosis (MS). OBJECTIVE: To study the precision, test duration, and repeatability of the qCSF in pwMS. In order to evaluate the discrimination ability, we compared the data of pwMS to healthy controls. METHODS: We recruited two independent cohorts of MS patients. Within the precision cohort (n = 54), we analyzed the benefit of running 50 instead of 25 qCSF trials. The repeatability cohort (n = 44) was assessed by high contrast vision charts and qCSF assessments twice and we computed repeatability metrics. For the discrimination ability we used the data from all pwMS without any previous optic neuritis and compared the area under the log CSF (AULCSF) to an age-matched healthy control data set. RESULTS: We identified 25 trials of the qCSF algorithm as a sufficient amount for a precise estimate of the CSF. The median test duration for one eye was 185 s (range 129-373 s). The AULCSF had better test-retest repeatability (Mean Average Precision, MAP) than visual acuity measured by standard high contrast visual acuity charts or CSF acuity measured with the qCSF (0.18 vs. 0.11 and 0.17, respectively). Even better repeatability (MAP = 0.19) was demonstrated by a CSF-derived feature that was inspired by low-contrast acuity charts, i.e., the highest spatial frequency at 25% contrast. When compared to healthy controls, the MS patients showed reduced CSF (average AULCSF 1.21 vs. 1.42, p < 0.01). CONCLUSION: High precision, usability, repeatability, and discrimination support the qCSF as a tool to assess contrast vision in pwMS.

Psychophysical Validation of a Novel Active Learning Approach for Measuring the Visual Acuity Behavioral Function.

Purpose: To evaluate the performance of the quantitative visual acuity (qVA) method in measuring the visual acuity (VA) behavioral function. Methods: We evaluated qVA performance in terms of the accuracy, precision, and efficiency of the estimated VA threshold and range in Monte Carlo simulations and a psychophysical experiment. We also compared the estimated VA threshold from the qVA method with that from the Electronic Early Treatment Diabetic Retinopathy Study (E-ETDRS) and Freiburg Visual Acuity Text (FrACT) methods. Four repeated measures with all three methods were conducted in four Bangerter foil conditions in 14 eyes. Results: In both simulations and psychophysical experiment, the qVA method quantified the full acuity behavioral function with two psychometric parameters (VA threshold and VA range) with virtually no bias and with high precision and efficiency. There was a significant correlation between qVA estimates of VA threshold and range in the psychophysical experiment. In addition, qVA threshold estimates were highly correlated with those from the E-ETDRS and FrACT methods. Conclusions: The qVA method can provide an accurate, precise, and efficient assessment of the full acuity behavioral function with both VA threshold and range. Translational Relevance: The qVA method can accurately, precisely, and efficiently assess the full VA behavioral function. Further research will evaluate the potential value of these rich measures for both clinical research and patient care.

From Gaussian blobs to naturalistic videos: Comparison of oculomotor behavior across different stimulus complexities.

Research on eye movements has primarily been performed in two distinct ways: (1) under highly controlled conditions using simple stimuli such as dots on a uniform background, or (2) under free-viewing conditions with complex images, real-world movies, or even with observers moving around in the world. Although both approaches offer important insights, the generalizability among eye movement behaviors observed under these different conditions is unclear. Here, we compared eye movement responses to video clips showing moving objects within their natural context with responses to simple Gaussian blobs on a blank screen. Importantly, for both conditions, the targets moved along the same trajectories at the same speed. We measured standard oculometric measures for both stimulus complexities, as well as the effect of the relative angle between saccades and pursuit, and compared them across conditions. In general, eye movement responses were qualitatively similar, especially with respect to pursuit gain. For both types of stimuli, the accuracy of saccades and subsequent pursuit was highest when both eye movements were collinear. We also found interesting differences; for example, latencies of initial saccades to moving Gaussian blob targets were significantly faster compared to saccades to moving objects in video scenes, whereas pursuit accuracy was significantly higher in video scenes. These findings suggest a lower processing demand for simple target conditions during saccade preparation and an advantage for tracking behavior in natural scenes due to higher predictability provided by the context information.

Following Forrest Gump: Smooth pursuit related brain activation during free movie viewing.

Most fMRI studies investigating smooth pursuit (SP) related brain activity have used simple synthetic stimuli such as a sinusoidally moving dot. However, real-life situations are much more complex and SP does not occur in isolation but within sequences of saccades and fixations. This raises the question whether the same brain networks for SP that have been identified under laboratory conditions are activated when following moving objects in a movie. Here, we used the publicly available studyforrest data set that provides eye movement recordings along with 3 â€‹T fMRI recordings from 15 subjects while watching the Hollywood movie "Forrest Gump". All three major eye movement events, namely fixations, saccades, and smooth pursuit, were detected with a state-of-the-art algorithm. In our analysis, smooth pursuit (SP) was the eye movement of interest, while saccades were acting as the steady state of viewing behaviour due to their lower variability. For the fMRI analysis we used an event-related design modelling saccades and SP as regressors initially. Because of the interdependency of SP and content motion, we then added a new low-level content motion regressor to separate brain activations from these two sources. We identified higher BOLD-responses during SP than saccades bilaterally in MT+/V5, in middle cingulate extending to precuneus, and in the right temporoparietal junction. When the motion regressor was added, SP showed higher BOLD-response relative to saccades bilaterally in the cortex lining the superior temporal sulcus, precuneus, and supplementary eye field, presumably due to a confounding effect of background motion. Only parts of V2 showed higher activation during saccades in comparison to SP. Taken together, our approach should be regarded as proof of principle for deciphering brain activity related to SP, which is one of the most prominent eye movements besides saccades, in complex dynamic naturalistic situations.

Two hours in Hollywood: A manually annotated ground truth data set of eye movements during movie clip watching.

In this short article we present our manual annotation of the eye movement events in a subset of the large-scale eye tracking data set Hollywood2. Our labels include fixations, saccades, and smooth pursuits, as well as a noise event type (the latter representing either blinks, loss of tracking, or physically implausible signals). In order to achieve more consistent annotations, the gaze samples were labelled by a novice rater based on rudimentary algorithmic suggestions, and subsequently corrected by an expert rater. Overall, we annotated eye movement events in the recordings corresponding to 50 randomly selected test set clips and 6 training set clips from Hollywood2, which were viewed by 16 observers and amount to a total of approximately 130 minutes of gaze data. In these labels, 62.4% of the samples were attributed to fixations, 9.1% - to saccades, and, notably, 24.2% - to pursuit (the remainder marked as noise). After evaluation of 15 published eye movement classification algorithms on our newly collected annotated data set, we found that the most recent algorithms perform very well on average, and even reach human-level labelling quality for fixations and saccades, but all have a much larger room for improvement when it comes to smooth pursuit classification. The data set is made available at https://gin.g-node.org/ioannis.agtzidis/hollywood2_em.

Characterizing and automatically detecting smooth pursuit in a large-scale ground-truth data set of dynamic natural scenes.

Eye movements are fundamental to our visual experience of the real world, and tracking smooth pursuit eye movements play an important role because of the dynamic nature of our environment. Static images, however, do not induce this class of eye movements, and commonly used synthetic moving stimuli lack ecological validity because of their low scene complexity compared to the real world. Traditionally, ground truth data for pursuit analyses with naturalistic stimuli are obtained via laborious hand-labelling. Therefore, previous studies typically remained small in scale. We here present the first large-scale quantitative characterization of human smooth pursuit. In order to achieve this, we first provide a methodological framework for such analyses by collecting a large set of manual annotations for eye movements in dynamic scenes and by examining the bias and variance of human annotators. To enable further research on even larger future data sets, we also describe, improve, and thoroughly analyze a novel algorithm to automatically classify eye movements. Our approach incorporates unsupervised learning techniques and thus demonstrates improved performance with the addition of unlabelled data. The code and data related to our manual and automated eye movement annotation are publicly available via https://web.gin.g-node.org/ioannis.agtzidis/gazecom_annotations/.

Visual exploration of emotional faces in schizophrenia using masks from the Japanese Noh theatre.

Studying eye movements during visual exploration is widely used to investigate visual information processing in schizophrenia. Here, we used masks from the Japanese Noh theatre to study visual exploration behavior during an emotional face recognition task and a brightness evaluation control task using the same stimuli. Eye movements were recorded in 25 patients with schizophrenia and 25 age-matched healthy controls while participants explored seven photos of Japanese Noh masks tilted to seven different angles. Additionally, participants were assessed on seven upright binary black and white pictures of these Noh masks (Mooney-like pictures), seven Upside-down pictures (180° upside-down turned Mooneys), and seven Neutral pictures. Participants either had to indicate whether they had recognized a face and its emotional expression, or they had to evaluate the brightness of the picture (total N = 56 trials). We observed a clear effect of inclination angle of Noh masks on emotional ratings (p < 0.001) and visual exploration behavior in both groups. Controls made larger saccades than patients when not being able to recognize a face in upside-down Mooney pictures (p < 0.01). Patients also made smaller saccades when exploring pictures for brightness (p < 0.05). Exploration behavior in patients was related to depressive symptom expression during emotional face recognition but not during brightness evaluation. Our findings suggest that visual exploration behavior in patients with schizophrenia is less flexible than in controls depending on the specific task requirements, specifically when exploring physical aspects of the environment.

Binocular Summation and Suppression of Contrast Sensitivity in Strabismus, Fusion and Amblyopia.

Purpose: Amblyopia and strabismus affect 2%-5% of the population and cause a broad range of visual deficits. The response to treatment is generally assessed using visual acuity, which is an insensitive measure of visual function and may, therefore, underestimate binocular vision gains in these patients. On the other hand, the contrast sensitivity function (CSF) generally takes longer to assess than visual acuity, but it is better correlated with improvement in a range of visual tasks and, notably, with improvements in binocular vision. The present study aims to assess monocular and binocular CSFs in amblyopia and strabismus patients. Methods: Both monocular CSFs and the binocular CSF were assessed for subjects with amblyopia (n = 11), strabismus without amblyopia (n = 20), and normally sighted controls (n = 24) using a tablet-based implementation of the quick CSF, which can assess a full CSF in <3 min. Binocular summation was evaluated against a baseline model of simple probability summation. Results: The CSF of amblyopic eyes was impaired at mid-to-high spatial frequencies compared to fellow eyes, strabismic eyes without amblyopia, and control eyes. Binocular contrast summation exceeded probability summation in controls, but not in subjects with amblyopia (with or without strabismus) or strabismus without amblyopia who were able to fuse at the test distance. Binocular summation was less than probability summation in strabismic subjects who were unable to fuse. Conclusions: We conclude that monocular and binocular contrast sensitivity deficits define important characteristics of amblyopia and strabismus that are not captured by visual acuity alone and can be measured efficiently using the quick CSF.

Free visual exploration of natural movies in schizophrenia.

BACKGROUND: Eye tracking dysfunction (ETD) observed with standard pursuit stimuli represents a well-established biomarker for schizophrenia. How ETD may manifest during free visual exploration of real-life movies is unclear. METHODS: Eye movements were recorded (EyeLink®1000) while 26 schizophrenia patients and 25 healthy age-matched controls freely explored nine uncut movies and nine pictures of real-life situations for 20 s each. Subsequently, participants were shown still shots of these scenes to decide whether they had explored them as movies or pictures. Participants were additionally assessed on standard eye-tracking tasks. RESULTS: Patients made smaller saccades (movies (p = 0.003), pictures (p = 0.002)) and had a stronger central bias (movies and pictures (p < 0.001)) than controls. In movies, patients' exploration behavior was less driven by image-defined, bottom-up stimulus saliency than controls (p < 0.05). Proportions of pursuit tracking on movies differed between groups depending on the individual movie (group*movie p = 0.011, movie p < 0.001). Eye velocity on standard pursuit stimuli was reduced in patients (p = 0.029) but did not correlate with pursuit behavior on movies. Additionally, patients obtained lower rates of correctly identified still shots as movies or pictures (p = 0.046). CONCLUSION: Our results suggest a restricted centrally focused visual exploration behavior in patients not only on pictures, but also on movies of real-life scenes. While ETD observed in the laboratory cannot be directly transferred to natural viewing conditions, these alterations support a model of impairments in motion information processing in patients resulting in a reduced ability to perceive moving objects and less saliency driven exploration behavior presumably contributing to alterations in the perception of the natural environment.

1D CNN with BLSTM for automated classification of fixations, saccades, and smooth pursuits.

Deep learning approaches have achieved breakthrough performance in various domains. However, the segmentation of raw eye-movement data into discrete events is still done predominantly either by hand or by algorithms that use hand-picked parameters and thresholds. We propose and make publicly available a small 1D-CNN in conjunction with a bidirectional long short-term memory network that classifies gaze samples as fixations, saccades, smooth pursuit, or noise, simultaneously assigning labels in windows of up to 1 s. In addition to unprocessed gaze coordinates, our approach uses different combinations of the speed of gaze, its direction, and acceleration, all computed at different temporal scales, as input features. Its performance was evaluated on a large-scale hand-labeled ground truth data set (GazeCom) and against 12 reference algorithms. Furthermore, we introduced a novel pipeline and metric for event detection in eye-tracking recordings, which enforce stricter criteria on the algorithmically produced events in order to consider them as potentially correct detections. Results show that our deep approach outperforms all others, including the state-of-the-art multi-observer smooth pursuit detector. We additionally test our best model on an independent set of recordings, where our approach stays highly competitive compared to literature methods.

New Precision Metrics for Contrast Sensitivity Testing.

Visual sensitivity is comprehensively described by the contrast sensitivity function (CSF), but current routine clinical care does not include its assessment because of the time-consuming need to estimate thresholds for a large number of spatial frequencies. The quick CSF method, however, dramatically reduces testing times by using a Bayesian information maximization rule. We evaluate the test-retest variability of a tablet-based quick CSF implementation in a study with 100 subjects who repeatedly assessed their vision with and without optical correction. We first discuss two commonly used measures of repeatability, intraclass correlation and the Bland-Altman Coefficient of Repeatability, and show that they are vulnerable to artifacts. Instead, we propose to formulate precision as an information retrieval task: from all repeat test scores, can we retrieve a certain individual based on their first test score? We then use rank-based analyses such as mean average precision as a better measure to compare different test metrics, and show that the highest test-retest precision is achieved using a summary statistic, the area under the log CSF (AULCSF). This demonstrates the benefit of assessment of the whole CSF compared to sensitivity at individual spatial frequencies only. AULCSF also yields best discrimination performance (99.2%) between measurements that were taken with and without glasses, respectively, even better than CSF Acuity. The tablet-based quick CSF thus enables the rapid and reliable home monitoring of visual function, which has the potential to improve early diagnosis and treatment of ophthalmic pathologies such as diabetic retinopathy or age-related macular degeneration.

Evaluation of the precision of contrast sensitivity function assessment on a tablet device.

The contrast sensitivity function (CSF) relates the visibility of a spatial pattern to both its size and contrast, and is therefore a more comprehensive assessment of visual function than acuity, which only determines the smallest resolvable pattern size. Because of the additional dimension of contrast, estimating the CSF can be more time-consuming. Here, we compare two methods for rapid assessment of the CSF that were implemented on a tablet device. For a single-trial assessment, we asked 63 myopes and 38 emmetropes to tap the peak of a "sweep grating" on the tablet's touch screen. For a more precise assessment, subjects performed 50 trials of the quick CSF method in a 10-AFC letter recognition task. Tests were performed with and without optical correction, and in monocular and binocular conditions; one condition was measured twice to assess repeatability. Results show that both methods are highly correlated; using both common and novel measures for test-retest repeatability, however, the quick CSF delivers more precision with testing times of under three minutes. Further analyses show how a population prior can improve convergence rate of the quick CSF, and how the multi-dimensional output of the quick CSF can provide greater precision than scalar outcome measures.

A novel measure to determine viewing priority and its neural correlates in the human brain.

A key property of human visual behavior is the very frequent movement of our eyes to potentially relevant information in the environment. Observers thus continuously have to prioritize information for directing their eyes to. Research in this field has been hampered by a lack of appropriate measures and tools. Here, we propose and validate a novel measure of priority that takes advantage of the variability in the natural viewing behavior of individual observers. In short, our measure assumes that priority is low when observers' gaze behavior is inconsistent and high when it is very consistent. We calculated priority for gaze data obtained during an experiment in which participants viewed dynamic natural scenes while we simultaneously recorded their gaze position and brain activity using functional magnetic resonance imaging. Our priority measure shows only limited correlation with various saliency, surprise, and motion measures, indicating it is assessing a distinct property of visual behavior. Finally, we correlated our priority measure with the BOLD signal, thereby revealing activity in a select number of human occipital and parietal areas. This suggests the presence of a cortical network involved in computing and representing viewing priority. We conclude that our new analysis method allows for empirically establishing the priority of events in near-natural vision paradigms.

Using 10AFC to further improve the efficiency of the quick CSF method.

The contrast sensitivity function (CSF) provides a fundamental characterization of spatial vision, important for basic and clinical applications, but its long testing times have prevented easy, widespread assessment. The original quick CSF method was developed using a two-alternative forced choice (2AFC) grating orientation identification task (Lesmes, Lu, Baek, & Albright, 2010), and obtained precise CSF assessments while reducing the testing burden to only 50 trials. In this study, we attempt to further improve the efficiency of the quick CSF method by exploiting the properties of psychometric functions in multiple-alternative forced choice (m-AFC) tasks. A simulation study evaluated the effect of the number of alternatives m on the efficiency of the sensitivity measurement by the quick CSF method, and a psychophysical study validated the quick CS method in a 10AFC task. We found that increasing the number of alternatives of the forced-choice task greatly improved the efficiency of CSF assessment in both simulation and psychophysical studies. The quick CSF method based on a 10-letter identification task can assess the CSF with an averaged standard deviation of 0.10 decimal log unit in less than 2 minutes.