Methods for assessing optokinetic reflex and systems for same

Abstract

Methods for assessing optokinetic reflex of a subject are provided. Aspects of the present invention include methods comprising presenting optokinetic reflex (OKR) stimuli to a subject, tracking eye movement of the subject in response to the OKR stimuli and assessing the OKR of the subject based on the tracked eye movements. Also provided are systems for assessing optokinetic reflex of a subject, and non-transitory computer readable storage media.

Description

[0001] METHODS FOR ASSESSING OPTOKINETIC REFLEX AND SYSTEMS FOR SAME

[0002] CROSS-REFERENCE TO RELATED APPLICATION

[0003] This application claims the benefit of United States Provisional Patent Application Serial No. 63 / 706,262, filed October 11 , 2024, the disclosure of which is incorporated herein by reference in its entirety.

[0004] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH

[0005] This invention was made with government support under grant number R01 EY029772 and R21 EY036209 awarded by the National Institutes of Health. The government has certain rights in the invention.

[0006] INTRODUCTION

[0007] Current clinical diagnoses of retinal health use visual acuity and sensitivity tests, which are measurements that rely on conscious perception. For example, a standardized chart such as a Snellen chart may be used to detect visual acuity. However, such tests that rely on conscious perception are unable to detect retinal disease until at least half of the millions of light-sensitive neurons in the eye (“cones”) have already degenerated. As such, early detection and treatment of retinopathies using current visual acuity and sensitivity tests is challenging.

[0008] SUMMARY

[0009] Methods and systems for assessing optokinetic reflex are provided herein. Inventors of the present invention have identified that optokinetic reflex (OKR) is a more sensitive measure of retinal health and unlike traditional visual acuity tests (see, e.g., FIGS. 2 and 3), can reveal degeneration before 50% cone loss (FIG. 4). As shown in FIG. 5, a decrease in reflexive eye movement (e.g., OKR) 510 occurs prior to a decrease in conscious vision 505. Therefore, assessing OKR may help to identify retinal degeneration even before a subject can tell perceptually that their vision is changing. Early detection is critical because it enables patients to begin preparing for their vision loss before they have gone completely blind, which can improve subsequent quality of life. Moreover, early detection will also likely increase patients’ opportunities to seek earlier treatments (e.g., gene therapy treatments) that are currently being developed for cone degeneration and / or make lifestyle changes that prevent further degeneration and vision loss (e.g., in the case of diabetic retinopathy).

[0010] Methods for assessing optokinetic reflex of a subject are provided. Aspects of the present invention include methods comprising presenting optokinetic reflex (OKR) stimuli to a subject, tracking eye movement of the subject in response to the OKR stimuli and assessing the OKR of the subject based on the tracked eye movements. Also provided are systems for assessing optokinetic reflex of a subject, and non-transitory computer readable storage media.

[0011] BRIEF DESCRIPTION OF THE FIGURES

[0012] The invention may be best understood from the following detailed description when read in conjunction with the accompanying drawings. Included in the drawings are the following figures:

[0013] FIG. 1 illustrates a flow diagram for assessing optokinetic reflex of a subject according to embodiments of the present invention.

[0014] FIG. 2 depicts an example of a grating visual acuity test.

[0015] FIG. 3 depicts an example of a Snellen chart that can be used to measure visual acuity. The blur in the chart depicts the loss in acuity associated with 50% cone loss.

[0016] FIG. 4 depicts a graph illustrating how standard visual tests generally only detect decreases in visual acuity and / or visual sensitivity after >50% of cone loss has occurred.

[0017] FIG. 5 depicts a graph comparing metrics for reflexive eye movement vs conscious vision. FIG. 6 depicts a schematic of a setup to elicit optokinetic reflex (OKR) in mice.

[0018] FIG. 7 depicts example images showing the eye at superior, neutral and inferior positions. Arrows mark the infrared corneal reflection.

[0019] FIG. 8 depicts a graph showing stimulus positions of vertical oscillations.

[0020] FIG. 9 depicts a graph showing absolute eye position plotted with corresponding stimulus positions of vertical oscillations.

[0021] FIG. 10 depicts the graph shown in FIG. 9 with saccades marked with tick marks.

[0022] FIG. 11 depicts a graph showing relative eye position after saccades have been removed.

[0023] FIG. 12 depicts a graph showing mean oscillation of the eye position compared to the mean stimulus position.

[0024] FIG. 13 depicts a graph showing distance traveled by slow eye movements.

[0025] FIG. 14 depicts a schematic illustrating perturbation of the retina by ablating cones.

[0026] FIG. 15 depicts a timeline following ablation of cones (top) and images comparing control cones (“control”) and ablated cones (“cone-DTR”) (bottom).

[0027] FIG. 16 shows a graph quantifying cone density in control vs ablated cones.

[0028] FIGS. 17A-17B depict mean cone densities (FIG. 17A) and mean OKR gains per animal (FIG. 17B) for both the control and the cone loss condition (“DTR”).

[0029] FIG. 18 depicts a schematic showing that superior and inferior ON direction ganglion cells can be identified by injecting a retrograde tracer into their central target: the medial terminal nucleus (MTN).

[0030] FIG. 19 depicts two example ON direction selective ganglion cell spike responses in response to bars moving in 8 cardinal directions. The top cell prefers downward motion on the retina and upward motion in visual space (“Superior”); the bottom cell prefers upward motion on the retina and downward motion in visual space (“Inferior”).

[0031] FIGS. 20A-20B show direction selective ganglion cell spike responses after partial cone loss. FIG. 20A shows direction selective ganglion cell tuning curves, pooled across Superior and Inferior cells, under control conditions (“Control”) and following 25% cone loss (“DTR”) using the diphtheria toxin receptor system (DTR) targeted under the promoter for the middle wavelength sensitive opsin. Cone loss causes a decrease in spike responses across all directions. FIG. 20B shows direction selective index, determined by the vector sum divided by the scalar sum of responses across all directions, for control (“Control”) and 25% cone loss conditions (“DTR"). The tuning curves become narrower with cone loss.

[0032] FIGS. 21A-21 B depict ON direction-selective retinal ganglion cell (oDSGC) responses predict the optokinetic reflex (OKR) across stimulus types, directions, and contrasts. FIG. 21 A shows cellular data and linear prediction. FIG. 21 B shows nonlinearity and behavioral data.

[0033] FIG. 22 depicts an example image from a video showing a drifting sinusoidal grating masked by occluding scotomas.

[0034] FIG. 23 depicts the average gain across scotomas in control mice.

[0035] FIGS. 24A-24B depict four orientations of an optotype letter “E” (FIG. 24A) and two examples of the optotype letter “E” randomly obscured by scotomas (FIG. 24B).

[0036] FIG. 25 depicts objects (left panel) obscured by scotomas (right panel).

[0037] FIGS. 26A-26D depict graphs showing that simulated scotomas diminish OKR gain before conscious perception in four healthy human subjects, respectively. Each of FIGS. 26A-26D represent a different subject. The top panels show that eye movement velocity drops to 80% of control levels (0% obscured) when the moving dots are obscured by 10% or less. The bottom panels show that for the same corresponding subjects, the percent correct of optotype orientation discrimination falls to 80% correct with the optotype obscured by 79% or more. FIG. 27 depicts a set up of virtual reality headset stabilized on posts. The subject rests their head on chin rest and looks into the headset. The display of the headset shows the stimuli. Built-in cameras track the subject’s eye movements in response to these stimuli.

[0038] FIG. 28 illustrates a flow diagram showing an OKR screening decision tree for diabetic retinopathy.

[0039] FIG. 29 illustrates a flow diagram showing an OKR screening decision tree for retinopathy.

[0040] FIGS. 30A-30G illustrate that reflexive eye movements are more sensitive to simulated scotomas than conscious visual perception in humans. FIG. 30A depicts a schematic of the virtual reality headset used to display visual stimuli and measure eye movements. A custom chin rest was attached for head stabilization. Schematics of stimuli shown in the headset include (1 ) Unidirectional motion: dots drifting upwards, (2) Tumbling E: an optotype shown in 4 orientations, and (3) Glass patterns: pairs of dots that create orientation information. Each of these stimuli were obscured by varying degrees of scotoma. The unidirectional motion required the subject to passively look at the stimuli, but not make any conscious decisions, while eye movements were tracked. The tumbling E required a forced choice by the subject in the 4 cardinal directions. The Glass patterns required a continuous orientation response by matching the orientation of a black line with that of the pair of white dots. FIG. 30B depicts eye movements measured in response to the Unidirectional Motion. Eye movements reach 80% of the unobscured condition with 2% scotoma coverage. FIG. 30C depicts average area under the receiver operating characteristic (ROC AUG) as a function of scotoma coverage for the Unidirectional Motion stimulus. Perfect discrimination reached for scotoma levels of >10%. FIG. 30D depicts percent correct for control subjects performing the Tumbling E stimulus. Performance drops to 80% with 81 % scotoma coverage. FIG. 30E depicts average area under the receiver operating characteristic (ROC AUC) as a function of scotoma coverage for the Tumbling E stimulus. Perfect discrimination reached for scotoma levels of >70%. FIG. 30F depicts performance for the Glass patterns as a function of scotoma coverage. Optimal performance is normalized to 100% and chance, i.e., 90 deg off from the correct orientation, is normalized to 0%. Perfect discrimination reached for scotoma levels of >90% (not shown). FIG. 30G depicts normalized gain of eye movements in response to the Unidirectional Motion stimulus vs. Percent correct for the Tumbling E stimulus matched to the degree of scotoma. (FIGS. 30B, 30D, 30F) Individual subjects are shown in gray and the mean across the population is shown in black.

[0041] FIGS. 31A-31 K illustrate that diminished reflexive eye movements are associated with USH2A-related photoreceptor loss, but not changes in visual acuity in humans. FIG. 31 A depicts a schematic of the virtual reality headset used to display visual stimuli and measure eye movements. Schematic of the USH2A mutation which leads to primary rod loss, followed by secondary late and slow cone loss in peripheral retina. FIG. 31 B depicts net displacement of eyes during slow phase of the optokinetic reflex over a 40 sec duration of unidirectionally drifting dots for control and USH2A patients. Significant difference as determined by the rank sum test. FIG. 31 C depicts receiver operating characteristic for distinguishing between control subjects with correction for visual acuity and USH2A patients with correction for visual acuity. Line of slope unity represents chance. FIG. 31 D depicts a confusion matrix in distinguishing between control subjects with correction for visual acuity and USH2A patients with correction for visual acuity in the following categories of classification: true positive (TP), false positive (FP), true negative (TN), and false negative (FN). FIG. 31 E depicts net displacement of eyes during slow phase of the optokinetic reflex over a 40 sec duration for each USH2A patient as a function of their cone photoreceptor spacing z-score where 0 represents the control cone spacing. Significant correlation as determined by linear regression. FIG. 31 F depicts net displacement of eyes during slow phase of the optokinetic reflex over a 40 sec duration as a function of ETDRS scores for USH2A patients with visual correction (free dots), control patients with visual correction (right vertices of dashed lines), and same control patients without visual correction (left vertices of dashed lines). Same control subjects connected by a dotted line. Linear regression across all points (solid line) reveals no significant correlation. FIG. 31 G depicts net displacement of eyes during slow phase of the optokinetic reflex over a 40 sec duration for control subjects without visual correction (left), control subjects with visual correction (middle), and Ush2A patients (right). Each subject’s ETDRS score is indicated by the dot (gradient scale). FIG. 31 H depicts ETDRS scores for control subjects either with or without correction of visual acuity. Significant difference as determined by the rank sum test. FIG. 311 depicts net displacement of eyes during slow phase of the optokinetic reflex over a 40 sec duration for control subjects either with or without correction for visual acuity. No significant difference as determined by the rank sum test. FIG. 31 J depicts receiver operating characteristic for distinguishing between control subjects with and without correction for visual acuity. Line of slope unity represents chance. FIG. 31 K depicts mean difference in net displacement between control subjects with and without correction (left) and between control subjects and LISH2A subjects (right). (FIGS. 31 B, 31 G, 31 H, 311) In boxplots, horizontal line represents median, box boundaries represent interquartile range (IQR), and whiskers represent the most extreme observation within 1 .5x IQR. *p<0.05, **p<0.01 , ***p<0.001 .

[0042] FIGS. 32A-32G illustrate adaptive optics scanning laser ophthalmoscopy (AOSLO) imaging of cones in humans. FIGS. 32A and 32E depict fundus photographs with overlaid macular integrity assessment (MAIA) sensitivity levels in decibels for an USH2A patient (FIG. 32A) and control subject (FIG. 32E). The outline shows the region imaged with AOSLO. Horizontal line in (FIG. 32A) shows the horizontal spectral domain optical coherence tomography B-scan acquired through the fovea. FIG. 32B depicts horizontal spectral domain optical coherence tomography B-scan of the USH2A patient shown in (FIG. 32A). FIGS. 32C and 32F depict a montage of magnified AOSLO images of the USH2A patient (FIG. 32C) and control subject (FIG. 32F). Boxes outline regions of interest that were quantified for cones. Box marked with * outlines the image magnified in (FIGS. 32D, 32G). FIGS. 32D and 32G depicts cone mosaics of the regions of interest marked with a box from (FIGS, 32C, 32F) for the USH2A patient (FIG. 32D) and control subject (FIG. 32F). Dots demarcate locations where cones were identified by a trained grader.

[0043] FIGS. 33A-33F: FIG. 33A depicts a schematic of the expression of the simian diphtheria toxin receptor in cones and timeline of inducing cone death at postnatal day (P) >30. Schematic of behavioral setup for measuring the optokinetic reflex in mice involves the projection of gratings on a hemisphere. One eye of a headfixed mouse is centered within the hemisphere. FIG. 33B depicts en face images of cone pedicles as labeled by antibody staining of cone arrestin from a wild type (left) and cone-DTR (right) mouse with approximately 30% cone loss. FIG. 33C depicts quantification of cone densities across the entire retina for each mouse, averaged over 3 images taken in each quadrant 1 -2 mm from the center of the retina. Mice are either from the wildtype or cone-DTR conditions with varying DT concentrations. Mice with cone loss of 30% or less to 1 .5 standard deviations were chosen for subsequent analysis (orange band). FIG. 33D depicts average eye position after removal of saccades of the wildtype (WT) and cone-DTR mice with less than 30% cone loss (< 30% cone loss) in response to a sinusoidally oscillating grating along the vertical axis (*). FIG. 33E depicts average gain of slow nystagmus during the superior and inferior phases for each mouse. FIG. 33F depicts gain of eye movements relative to stimulus movements as a function of degree of cone loss for each mouse for superior motion (magenta x’s), inferior motion (black x’s), and averaged across both directions (circles). Cone loss of 0 represents the median of the control cone density. Fraction of cone loss presents the [(cone density - median control cone density) / median control cone density]. (FIGS. 33C, 33E) For box plots, horizontal line represents median, box boundaries are IQR, and whiskers represent the most extreme observation within 1 .5x IQR. Significant differences determined by rank sum test with *p<0.05, **p<0.01 , ***p<0.001 . (FIGS. 33C-33F) N denotes the number of mice used for each experiment. DETAILED DESCRIPTION

[0044] Methods for assessing optokinetic reflex of a subject are provided. Aspects of the present invention include methods comprising presenting optokinetic reflex (OKR) stimuli to a subject, tracking eye movement of the subject in response to the OKR stimuli and assessing the OKR of the subject based on the tracked eye movements. Also provided are systems for assessing optokinetic reflex of a subject, and non-transitory computer readable storage media.

[0045] Before the present invention is described in greater detail, it is to be understood that this invention is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

[0046] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limit of that range and any other stated or intervening value in that stated range, is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included in the smaller ranges and are also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.

[0047] Certain ranges are presented herein with numerical values being preceded by the term “about.” The term “about” is used herein to provide literal support for the exact number that it precedes, as well as a number that is near to or approximately the number that the term precedes. In determining whether a number is near to or approximately a specifically recited number, the near or approximating unrecited number may be a number which, in the context in which it is presented, provides the substantial equivalent of the specifically recited number.

[0048] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can also be used in the practice or testing of the present invention, representative illustrative methods and materials are now described.

[0049] All publications and patents cited in this specification are herein incorporated by reference as if each individual publication or patent were specifically and individually indicated to be incorporated by reference and are incorporated herein by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. The citation of any publication is for its disclosure prior to the filing date and should not be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.

[0050] It is noted that, as used herein and in the appended claims, the singular forms “a”, “an”, and “the” include plural referents unless the context clearly dictates otherwise. It is further noted that the claims may be drafted to exclude any optional element. As such, this statement is intended to serve as antecedent basis for use of such exclusive terminology as “solely,” “only” and the like in connection with the recitation of claim elements, or use of a “negative” limitation.

[0051] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible. While the system and method may be described for the sake of grammatical fluidity with functional explanations, it is to be expressly understood that the claims, unless expressly formulated under 35 U.S.C. § 112, are not to be construed as necessarily limited in any way by the construction of “means” or “steps” limitations, but are to be accorded the full scope of the meaning and equivalents of the definition provided by the claims under the judicial doctrine of equivalents, and in the case where the claims are expressly formulated under 35 U.S.C. § 112 are to be accorded full statutory equivalents under 35 U.S.C. § 1 12.

[0052] METHODS FOR ASSESSING OPTOKINETIC REFLEX

[0053] As discussed above, aspects of the present disclosure include methods for assessing optokinetic reflex. In particular, the present disclosure includes methods for assessing optokinetic reflex of a subject, wherein the method comprises: presenting optokinetic reflex (OKR) stimuli to a subject, tracking eye movement of the subject in response to the OKR stimuli, and assessing the OKR of the subject based on the tracked eye movements.

[0054] Methods of embodiments of the invention find use in assessing a variety of different types of subjects. The terms “subject,” “individual,” and “patient” are used interchangeably to refer to the subject being assessed. Subjects may be any mammal, including, but not limited to, humans, primates, mice, rats, etc. In some embodiments, the subject is a human. Subjects include mammals (e.g., humans) of any age, including adolescents and adults. In some embodiments, the subject is a human, wherein the human is an adult human. The subject may be of any body type or body size. The subject may have any uncorrected or corrected eyesight. In some embodiments, the subject’s uncorrected or corrected eyesight is 20 / 20. In some embodiments, the subject’s uncorrected or corrected eyesight is 20 / 20 or better. In some embodiments, the subject’s uncorrected or corrected eyesight is 20 / 20 or worse.

[0055] In some embodiments, the subject has an ocular pathology. In some embodiments, the subject has been diagnosed with a retinopathy. In some embodiments, the subject has not been previously diagnosed with a retinopathy. In some embodiments, the subject is a candidate for developing a retinopathy. Such retinopathies include any disease that damages the retina including, but not limited to, diabetic retinopathy, hypertensive retinopathy, solar retinopathy, retinopathy of prematurity, branch retinal vein occlusion, central retinal vein occlusion, hemoglobinopathy retinopathy, retinal microaneurysm, macular edema, ocular ischemia, sickle cell disease, Terson syndrome, Valsalva retinopathy, toxic retinopathy, viral retinopathy (e.g., CMV or HIV retinopathy), peripheral vitreoretinopathy, glaucoma, retinopathy due to trauma or penetrating lesions of the eye or inherited retinal degeneration. In some embodiments, the subject has been diagnosed with diabetes. In some embodiments, the subject is prediabetic and / or at an increased risk of developing diabetes. In some embodiments, the subject has not been previously diagnosed with diabetes and / or a diabetic retinopathy.

[0056] FIG. 1 illustrates a flow diagram for assessing optokinetic reflex of a subject according to some aspects of the present disclosure. At box 100, optokinetic reflex (OKR) stimuli is presented to a subject. By OKR stimuli it is meant stimuli which can induce an OKR in a subject. In embodiments, OKR stimuli induce an unconscious visual perception in the subject and / or reflexive ocular movement. In some cases, the OKR stimuli evokes OKR in a subject that is not reflective of (i.e., not correlated with) visual acuity. In some cases, the OKR stimuli evokes OKR in a subject that is reflective of (i.e., is correlated with) visual acuity.

[0057] In certain aspects, the OKR stimuli comprise images of a plurality of objects. In certain aspects, the OKR stimuli comprise images of a plurality of objects, wherein the images are configured to prevent the subject from being able to consciously track the motion of any single object. In some embodiments, the plurality of objects comprise objects with discontinuous local spatiotemporal correlations of motion. In other words, the plurality of objects comprise objects without continuous local spatiotemporal correlations of motion, but still a global perception of motion. A lack of continuous local spatiotemporal correlations of motion prevent the subject from being able to consciously track the motion of any single object, while the global perception of motion retains reflexive (i.e., unconscious) eye movement.

[0058] In some embodiments, the plurality of objects are non-overlapping. In some embodiments, the plurality of objects are rendered at a random location, e.g., within a subject’s field of view. In some embodiments, the plurality of objects are rendered at a random location in a designated area of the display (e.g., in the center of the display). In some embodiments, each object of the plurality of objects persists transiently. In other words, each object of the plurality of objects is rendered on, for example, a screen or display, and then is removed from the screen or display. In some embodiments, each object of the plurality of objects has an average lifespan in the range of 30 to 2000 ms (e.g., 30, 40, 50, 75, 100, 1 10, 120, 125, 130, 135, 140, 145, 150, 155, 160, 165, 170, 175, 180, 190, 200, 225, 250, 500, 750, 1250, 1500, 1750, 2000 ms), including, e.g., 30 to 1500 ms, 30 to 1000 ms, 30 to 500 ms, 30 to 200 ms, 30 to 150 ms, 50 to 1500 ms, 50 to 1000 ms, 50 to 500 ms, 50 to 200 ms, 50 to 200 ms, 50 to 175 ms, 50 to 150 ms, 75 to 1500 ms, 75 to 1000 ms, 75 to 500 ms, 75 to 250 ms, 75 to 225 ms, 75 to 200 ms, 75 to 175 ms, 75 to 150 ms, 100 to 1500 ms, 100 to 1000 ms, 100 to 500 ms, 100 to 250 ms, 100 to 225 ms, 100 to 200 ms, 100 to 175 ms, 100 to 150 ms, 125 to 1500 ms, 125 to 1000 ms, 125 to 500 ms, 125 to 250 ms, 125 to 225 ms, 125 to 200 ms, 125 to 175 ms, 125 to 150 ms, 150 to 1500 ms, 150 to 1000 ms, 150 to 500 ms, 150 to 250 ms, 150 to 225 ms, 150 to 200 ms and 150 to 175 ms. In some embodiments, each object of the plurality of objects has an average lifespan of 150 ms.

[0059] In some embodiments, the plurality of objects move with constant linear motion. In some embodiments, the plurality of objects move with a constant linear motion of 0.5 to 100 degrees per second (e.g., 0.5, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 1 1 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90 or 100 degrees per second), including, e.g., 1 -100, 1 -50, 1 -20, 5-100, 5-50, 5-30, 5-25, 10-25, 10-20, 10-18, 10-16, 10-15, 12-20, 12-18, 12-16, 12-15, 14-20, 14-18, or 14-16 degrees per second. In some embodiments, the plurality of objects move with a constant linear motion of 10-20 degrees per second.

[0060] In some embodiments, the plurality of objects move according to functions (e.g., periodic functions) or velocity time series. In some embodiments, the plurality of objects move according to periodic functions. (Different functions or time series may be utilized because, in embodiments, what is needed to obtain relevant measurements is a correlation between an arbitrary stimulus movement pattern and the eye movements.) By periodic functions, it is meant functions that have periodicity. For example, the plurality of objects may have oscillatory movement. In some embodiments, the periodic functions are a sum, or other combination, of trigonometric functions (e.g., the sum of 2, 3, 4 or 5 or more trigonometric functions). In some embodiments, the periodic functions have periods of 0.5 to 100 seconds (e.g., 0.5, 1 , 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90 or 100 seconds), including, e.g., 1 -100, 1 -50, 1 -20, 5- 100, 5-50, 5-30, 5-25, 10-25, 10-20, 10-18, 10-16, 10-15, 12-20, 12-18, 12-16, 12-15, 14-20, 14-18, 14-16, 1 -20, 1 -15, 2-15, 5-15 and 5-10 seconds. In some embodiments, the plurality of objects move according to periodic functions, wherein the periodic functions have periods of 1 -15 seconds.

[0061] In some embodiments, the plurality of objects comprise positive contrast objects. By positive contrast, it is meant light objects on a darker background. For example, positive contrast objects include white objects on a black background. In some embodiments, positive contrast objects have a positive contrast in the range of about 10% to about 200% (e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 1 10%, 120%, 130%, 140%, 150%, 160%, 170%, 180%, 190% or 200%), including, e.g., 20% to 200%, 20% to 150%, 50% to 150% and 50% to 100%. In some embodiments, positive contrast objects have a positive contrast in the range of about 20% to about 200%.

[0062] In some embodiments, the plurality of objects comprise negative contrast objects. By negative contrast, it is meant dark objects on a lighter background. For example, negative contrast objects include black objects on a white background. In some embodiments, negative contrast objects have a negative contrast in the range of about 10% to about 200% (e.g., 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 1 10%, 120%, 130%, 140%, 150%, 160%, 170%, 180%, 190% or 200%), including, e.g., 20% to 200%, 20% to 150%, 50% to 150% and 50% to 100%. In some embodiments, negative contrast objects have a negative contrast in the range of about 20% to about 200%.

[0063] In some embodiments, the plurality of objects comprise gaze-contingent occluding stimuli overlaid on top of the plurality of objects. For example, gazecontingent occluding stimuli include, but are not limited to, blank circles overlaid on top of the plurality of objects.

[0064] In some aspects, the OKR stimuli are configured for detecting a specific condition of the subject. In some aspects, the OKR stimuli are configured for detecting retinopathy in the subject. Such retinopathies that may be detected include any disease that damages the retina including, but not limited to, diabetic retinopathy, hypertensive retinopathy, solar retinopathy, retinopathy of prematurity, branch retinal vein occlusion, central retinal vein occlusion, hemoglobinopathy retinopathy, retinal microaneurysm, macular edema, ocular ischemia, sickle cell disease, Terson syndrome, Valsalva retinopathy, toxic retinopathy, viral retinopathy (e.g., CMV or HIV retinopathy), peripheral vitreoretinopathy, glaucoma, retinopathy due to trauma or penetrating lesions of the eye or inherited retinal degeneration.

[0065] OKR stimuli as disclosed herein may be presented to the subject on a two-dimensional (2D) or three-dimensional (3D) display. In some embodiments, the OKR stimuli are presented on a 2D display. A 2D display is a display that conveys a flat image to a subject (e.g., an image in x and y directions). In some embodiments, the OKR stimuli are presented on a 3D display. A 3D display is a display that conveys an image in x, y and z directions to a subject. In other words, the 3D display is capable of conveying depth, or the illusion of depth, to a subject. 3D displays include actual 3D displays, simulated 3D displays and combinations thereof. In some embodiments, OKR stimuli as disclosed herein are presented on a stereoscopic display. Stereoscopic displays present offset images that are displayed separately to the left eye and the right eye. Stereoscopic display may be 2D or 3D. In 3D stereoscopic displays, the separately-displayed offset images may be presented such that they are combined by the subject’s brain to convey the perception and / or illusion of depth. Stereoscopic displays (e.g., 2D stereoscopic displays, 3D stereoscopic displays) include, but are not limited to, near-eye stereoscopic displays and stereoscopic displays located at any distance away from the eye.

[0066] In some embodiments, the OKR stimuli are presented on an immersive environment display. In some embodiments, the OKR stimuli are presented on a 2D monitor including, but not limited to, a computer monitor, a television, a smartphone display and a tablet. In some embodiments, the OKR stimuli are presented in virtual reality (VR). In some embodiments, the OKR stimuli are presented using a virtual reality (VR) headset. VR headsets are near-eye displays. The VR headset may be any convenient VR headset including commercially sold VR headsets and non-commercially sold VR headsets. In some embodiments, the VR headset is custom-made. In some embodiments, the VR headset is a commercially available headset. Examples of commercially available VR headsets include but are not limited to, HTC Vive (e.g., HTC Vive, HTC Vive Pro, HTC Vive Pro 2, HTC Vive Pro Eye, HTC Vive Cosmos, HTC Vive Focus, HTC Vive Focus 2, HTC Vive Focus 3, HTC Vive Flow, HTC Vive XR Elite), Razer OSVR (e.g., Razer OSVR HDK 1 .4, Razer OSVR HDK 2), Oculus Rift (e.g., Oculus Rift CV1 , Oculus Rift S), StarBreeze StarVR, PlayStation VR (e.g., PlayStation VR, PlayStation VR2), Fove 0, Pimax 4K, Pimax 5K Plus, Pimax 8K, VRgineers VRHero (e.g., VRgineers VRHero 5K, VRgineers VRHero 5K Plus), VRgineers XTAL, Deepoon VR E3, Dell Visor, Acer AH101 , HP WMR headset, Lenovo Explorer, Samsung Odyssey (e.g., Samsung Odyssey, Samsung Odyssey+), Asus HC102, StarVR One, Varjo VR-1 , Varjo VR-2, Varjo VR-3, Varjo Aero, Valve Index, HP Reverb (e.g., HP Reverb, HP Reverb G2, HP Reverb G2 Omnicept), Oculus Quest (e.g., Oculus Quest, Oculus Quest 2), Modal VR, Samsung Gear VR, Avegant Glyph, Pico VR Goblin, Qualcomm Snapdragon (e.g., Qualcomm Snapdragon VR820, Qualcomm Snapdragon 835 VRDK), Alcatel Vision, Microsoft Hololens, Helmet Vision, Pico Neo GV, Woxter Neo VR100, Oculus Go, Lenovo Mirage Solo, GFL Developer Kit, Google Daydream View, Pico G2 4K, Pico Neo 3 Pro, Lenovo ThinkReality VRX, PICO 4, Meta Quest Pro, Bigscreen Beyond, Meta Quest 3, Varjo XR4 and Apple Vision Pro. In some embodiments, the VR headset is an HTC Vive Pro VR headset.

[0067] In some embodiments, the VR headset includes a built-in eye tracker. In some embodiments, the VR headset does not include a built-in eye tracker. Examples of VR headsets that include a built-in eye tracker include, but are not limited to, HTC Vive Pro Eye, Pimax Crystal, PlayStation VR2, HP Reverb G2 Omnicept, Pico Neo 3 Pro Eye, Meta Quest Pro, Pico 4 Enterprise, Varjo Aero and Apple Vision Pro.

[0068] Box 100 of FIG. 1 is then followed by box 105. At box 105, eye movement of the subject is tracked in response to the OKR stimuli. Such eye movement may be tracked using any eye tracker. In some embodiments, eye movement is tracked using an eye tracker that is built into a VR headset. In some embodiments, eye movement is tracked using an eye tracker that is not built into a VR headset.

[0069] In some embodiments, tracking eye movement of the subject in response to the OKR stimuli comprises illuminating the eyes of the subject with infrared light and capturing a plurality of images of the eyes of the subject using a camera. In some embodiments, the plurality of images are captured at a rate of 50 Hz or faster (e.g., 50 Hz, 60 Hz, 70 Hz, 80 Hz, 90 Hz, 100 Hz, 110 Hz, 120 Hz, 130 Hz, 140 Hz, 150 Hz, 200 Hz, 250 Hz), including 60 Hz or faster, 70 Hz or faster, 80 Hz or faster, 90 Hz or faster, 100 Hz or faster, 150 Hz or faster and 250 Hz or faster. In some embodiments, the plurality of images are captured at a rate of 60 Hz or faster. In some embodiments, the plurality of images are captured at a rate of 90 Hz or faster. In some embodiments, tracking eye movement of the subject in response to the OKR stimuli further comprises detecting a plurality of gaze points in the plurality of images. A gaze point may be recorded as an x-y coordinate with a time stamp such that the direction of a subject’s gaze can be determined at a specific point in time.

[0070] Further details regarding eye trackers that can be employed in the embodiments described herein can be found in, e.g., US Patent No. 9,179,838, US Patent No. 9,779,299, US Patent No. 9,179,833, US Patent No. 9,330,302,

[0071] US Patent No. 9,355,315, US Patent No. 9,345,402, US Patent No. 9,355,315,

[0072] US Patent No. 9,361 ,833, US Patent No. 9,386,921 , US Patent No. 9,430,040,

[0073] US Patent No. 9,468,373, US Patent No. 9,480,397, US Patent No. 9,646,207,

[0074] US Patent No. 9,619,707, US Patent No. 9,503,713, US Patent No. 10,307,054 and US Patent No. 9,665,172, the disclosures of which are incorporated herein.

[0075] In some embodiments, the camera used for tracking eye movement is built into a VR headset. Such VR headsets include, but are not limited to, the VR headsets including a built-in eye-tracker discussed above.

[0076] Box 105 of FIG. 1 is then followed by box 110. At box 110, OKR of the subject is assessed based on the tracked eye movements. In certain aspects, assessing the OKR of the subject based on the tracked eye movements comprises quantitatively assessing the OKR.

[0077] In some embodiments, assessing the OKR of a subject comprises calculating a gain between the stimulus movement and eye movement. The gain between the stimulus movement and eye movement is the total distance traveled by the eye in the direction defined by the stimulus motion divided by the total distance that the stimulus traveled. In some embodiments, calculating the gain includes calculating a correlation between eye velocity and stimulus velocity. In some embodiments, the total distance traveled by the eye is the total distance traveled by the eye after removing saccades, blinks, etc. In some embodiments, the gain is an average gain. In some embodiments, the gain is an average gain over the duration of presenting OKR stimuli to the subject. In some embodiments, assessing the OKR of a subject comprises identifying periods of blink and data loss. In certain cases, if the periods of blink and / or data loss are greater than 10%, the assessment must be repeated. In certain cases, if the periods of blink and / or data loss are less than 10%, the velocity of the eye can be set equal to the mean velocity during the 100 ms period prior to the period of blink and / or data loss. In some embodiments, assessing the OKR of a subject comprises identifying saccades. A saccade is a rapid movement of the eye that abruptly changes the point of fixation. In some embodiments, a saccade is identified if it exceeds predetermined velocity and / or acceleration thresholds. In some cases, the velocity threshold is between the range of 20 to 100 degrees per second. In some cases, the acceleration threshold is about 10 degrees per second2. In some embodiments, a saccade is identified if it exceeds a velocity threshold that is greater than 1 .5x the speed of the OKR stimulus. In some embodiments, assessing the OKR of a subject comprises computing a time shift for which the cross correlation between the OKR stimulus and the eye movement is maximized. The time shift represents the phase shift of the eye movement with respect to the stimulus movement.

[0078] In some embodiments, assessing the OKR of the subject comprises generating a reflexive vision score. In certain cases, the reflexive vision score is computed from the gain, the time shift (e.g., phase shift) and / or velocity. In some embodiments, the reflexive vision score is an age-adjusted reflexive vision score. By age-adjusted reflexive vision score, it is meant a vision score that is adjusted by multiplying the score or a component of the score with a known value that reflects age-related changes to performance. In some embodiments, assessing the OKR of the subject further comprises quantifying whether the age-adjusted reflexive vision score is below an age-adjusted mean. In some embodiments, assessing the OKR of the subject further comprises quantifying whether the age- adjusted reflexive vision score is below an age-adjusted mean, wherein the age- adjusted reflexive vision score is two standard deviations or more below an age- adjusted mean. In some cases, an age-adjusted reflexive vision score that is two standard deviations or more below an age-adjusted mean is used to determine if the patient is a suspect for a retinopathy. See, e.g., FIGS. 28 and 29.

[0079] Further Evaluation

[0080] In certain aspects, the methods described herein may be combined with further evaluations. For example, in some embodiments, the methods described herein further comprise comparing the OKR of the subject to a conscious visual perception task of the subject. Such conscious visual perception tasks include, but are not limited to forced choice tasks.

[0081] In some embodiments, the methods described herein further comprise comparing the OKR of the subject to imaging results of the subject. In some embodiments, the imaging results are retinal imaging results. In some embodiments, the imaging results (e.g., retinal imaging results) of the subject are adaptive optics imaging results. In some embodiments, the imaging results of the subject are able to detect a retinopathy (i.e., determine the presence or absence of a retinopathy in the subject).

[0082] In some embodiments, the method is a method of measuring retinal health in a subject comprising assessing OKR of a subject and determining potential clinical interpretations of retinal health based on the OKR. The OKR of a subject may be assessed according to any of the methods disclosed herein.

[0083] In some embodiments, the method is a method of measuring retinal degeneration in a subject comprising assessing OKR of a subject and determining potential clinical interpretations of retinal degeneration based on the OKR. The OKR of a subject may be assessed according to any of the methods disclosed herein.

[0084] In some embodiments, the method is a method of screening for the presence of a condition in the subject. In some embodiments, the method is a method of screening for the presence of a disease in the subject. In some embodiments, the method is a method of screening for retinopathy in the subject. In some embodiments, the method is a method of screening for diabetic retinopathy in the subject. In some embodiments, the method is a method of diagnosing a condition in the subject. In some embodiments, the method is a method of diagnosing a disease in the subject.

[0085] In some embodiments, the method comprises monitoring a disease progression (e.g., a retinopathy) by assessing the OKR of the subject at a plurality of discrete times to monitor, such as, e.g., over the course of a plurality of weeks, a plurality of months or a plurality of years. In some embodiments, the method comprises monitoring effects of treatment of a subject. In some embodiments, the method comprises monitoring the effects of gene therapy treatment of a subject.

[0086] Computer-Implemented Embodiments

[0087] The various method and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system applying a method according to the present disclosure. The described functionality can be implemented in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosure.

[0088] The various illustrative steps, components, and computing systems (such as devices, databases, interfaces, and engines) described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a general purpose processor, a graphics processor unit, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor can be a microprocessor, but in the alternative, the processor can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Although described herein primarily with respect to digital technology, a processor can also include primarily analog components. A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a graphics processor unit, a mainframe computer, a digital signal processor, a portable computing device, a personal organizer, a device controller, and a computational engine within an appliance, to name a few.

[0089] The steps of a method, process, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module, engine, and associated databases can reside in memory resources such as in RAM memory, FRAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of non-transitory computer-readable storage medium, media, or physical computer storage known in the art. An exemplary storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium can reside as discrete components in a user terminal.

[0090] As described in detail above, embodiments of the present invention relate to a computer-implemented method for assessing optokinetic reflex of a subject, the method comprising: presenting optokinetic reflex (OKR) stimuli to a subject, tracking eye movement of the subject in response to the OKR stimuli, and assessing the OKR of the subject based on the tracked eye movements. Aspects of the present disclosure further include non-transitory computer readable storage media for assessing optokinetic reflex of a subject. The non- transitory computer readable storage media according to certain embodiments comprise one or more algorithms corresponding to the subject methods described herein.

[0091] SYSTEMS FOR ASSESSING OPTOKINETIC REFLEX

[0092] As summarized above, aspects of the present disclosure include systems for assessing optokinetic reflex. Systems according to certain embodiments comprise a display, wherein the display is configured to present optokinetic reflex (OKR) stimuli to a subject and an eye-tracking unit, wherein the eye-tracking unit is configured to track eye movement of the subject in response to the OKR stimuli. In some embodiments of systems according to the present disclosure, the system further comprises a virtual reality (VR) system comprising the display and the eye-tracking unit. VR systems suitable for systems of the present disclosure include those discussed in detail above. In some embodiments, the VR system comprises a VR headset.

[0093] In some embodiments of systems according to the present disclosure, the system further comprises a processor comprising memory operably coupled to the processor wherein the memory comprises instructions stored thereon, which when executed by the processor, cause the processor to receive data representing the tracked eye movement and assess the OKR of the subject based on the tracked eye movement data. Systems according to certain embodiments comprise a processor comprising memory operably coupled to the processor, wherein the memory comprises instructions stored thereon, which, when executed by the processor, cause the processor to execute steps corresponding to the subject methods described herein.

[0094] UTILITY

[0095] The subject methods and systems find use in a variety of applications where it is desirable to assess optokinetic reflex. The subject methods and systems find use in assessing the health of ocular tissue in a subject. In some embodiments, the methods and systems described herein find use in clinical settings such as any clinical setting where traditional testing for retinopathy may be applied. In some embodiments, the methods and systems described herein find use in diagnosing disease, monitoring disease progression, determining treatment options for a disease, monitoring treatment progression for a disease or in connection with administering gene therapy. In other embodiments, the methods and systems described herein find use in settings outside of the clinic. For example, the methods and systems described herein find use in remote medicine settings, where assessment of optokinetic reflex may be newly enabled by application of the present methods and systems, such as in telemedicine contexts or at-home tests.

[0096] In addition, the subject methods and systems find use in improving the effectiveness and accuracy of assessing optokinetic reflex of a subject, particularly in cases where current clinical tests (e.g., tests that rely on conscious perception) are not able to detect retinopathies until significant degeneration has already occurred. Accordingly, the subject methods and systems find use in allowing for earlier detection of retinopathies. In some cases, earlier detection of retinopathies allows for earlier treatment to reverse, prevent, stop and / or ameliorate retinopathies or symptoms of retinopathies that would otherwise not be possible with traditional methods to detect retinopathies. In some cases, the subject methods and systems find use in improving user friendliness of a system for assessing optokinetic reflex by including additional interactive and intuitive functionality. Further, the subject methods and systems allow for painless, non- invasive optokinetic reflex assessment. In some cases, the subject methods and systems find use in improving diagnosis of a retinopathy.

[0097] The following is offered by way of illustration and not by way of limitation.

[0098] EXPERIMENTAL EXAMPLE 1;

[0099] To measure OKR in mice, mice were situated such that one eye was centered in a hemisphere (FIG. 6). Stimuli were projected onto the hemisphere’s concave surface via reflection off of a convex mirror. The mouse’s eye movements were tracked using an infrared-sensitive camera and a corneal reflection. Eye movements were measured in response to vertically drifting, fullfield gratings. The stimulus positions 800 of the vertical oscillations of the full-field gratings are shown in FIG. 8. In response to vertically drifting sinusoidal gratings, the eye traverses between superior, neutral and inferior positions (FIG. 7). FIG. 9 shows eye position 905 plotted across time relative to the stimulus positions 900 of the vertically-oscillating full-field grating.

[0100] Across all adult mice, superior- and inferior-drifting gratings generated distinct, but reproducible eye movements: while superior gratings elicited repetitive slow, upward-drifting eye movements (‘slow eye movements’) interleaved with frequent resetting saccades in the opposite direction (‘fast nystagmus’), inferior gratings tended to reliably drive only an initial slow eye movement immediately following stimulus onset, after which fast nystagmuses were infrequent and eye position changed minimally. FIG. 10 shows the same graph as FIG. 9, except that tick marks 1000 indicate superior fast nystagmuses and tick marks 1005 indicate inferior fast nystagmuses. In FIG. 11 , such saccades (i.e., fast nystagmuses), have been removed to reveal the asymmetry between superior and inferior OKR.

[0101] As shown in FIG. 13, the total distance traveled during slow eye movements was greater for superior stimuli. FIG. 13 shows cumulative vertical distance traveled during slow eye movements in response to superior 1300 and inferior 1305 drifting gratings (mean ± SEM). An average offset of vertical eye position in the superior direction is shown over the course of a single stimulus oscillation (FIG. 12). FIG. 12 shows eye position 1200 and stimulus position 1205 averaged across all oscillations and all animals (mean ± SEM). Starting eye position is normalized to 0° at cycle onset. These results demonstrate that superior motion drives a more robust OKR than inferior motion. EXAMPLE 2;

[0102] To induce partial cone loss, diphtheria toxin (DT) was injected into mice expressing diphtheria toxin receptor (DTR) in cones (FIG. 14). As shown in the timeline at the top of FIG. 15, the mice were injected with DT at postnatal day 30 (P30) and 1 week thereafter. 50% of the cones are dead after DT injection (FIG. 15, bottom panels). FIG. 16 shows histograms of cones / mm2in the control 1605 vs cone-DTR 1600. Partial cone loss results in a decrease in mean cone density (FIG. 17A) and a decrease in mean OKR gain (FIG. 17B).

[0103] Ganglion cells that detect vertical motion are selectively targeted by retrograde tracers injected in the medial terminal nucleus (FIG. 18 and FIG. 19). Further data regarding ON-direction selective ganglion cell spike responses after partial cone loss is shown in FIGS. 20. As shown in FIGS. 21A-21 B, ganglion cell responses predict behavior with partial cone loss with minimal changes in post- retinal processing. Cone loss causes a decrease in spike responses across all directions and tuning curves become narrower with cone loss.

[0104] Ganglion cell responses are shown to predict behavior with partial cone loss (FIGS. 21A-21 B). Boxes 2105 and 2110 in FIG. 21A and boxes 2115 and 2120 in FIG. 21 B show a schematic of the putative computation between oDSGCs and OKR, consisting of a subtraction between Superior and Inferior oDSGC spikes and a nonlinearity. Boxes 2125 and 2145 show two separate implementations of the subtraction model described in boxes 2105, 2110, 2115 and 2120. Boxes 2125, 2130, 2135 and 2140 and show the control condition and boxes 2145, 2150, 2155 and 2140 show a 25% cone loss condition. In box 2140, 2141 denotes the stimulus, 2142 denotes high contrast, 2143 denotes low contrast and 2144 denotes cone loss.

[0105] Boxes 2125 and 2145 show distributions of Superior and Inferior oDSGC spike responses across high-contrast (2125, left) and low-contrast (2125, right, 20% relative) superior (2125 and 2145, top) and inferior (2125 and 2145, bottom) drifting bars. The brackets (2126, 2127, 2128, 2129, 2146, 2147) denote the difference between the medians of the Superior and Inferior oDSGC response distributions in each condition. Boxes 2130 and 2150 show linear predictions of OKR are made for the average eye velocity over the course of each half oscillation cycle based on the difference in firing rate between Superior and Inferior oDSGCs (i.e. brackets in boxes 2125 and 2145) to high- and low-contrast bars drifting in the corresponding stimulus direction. The shape of the curves as sinusoids is inferred from the stimulus position over time. In box 2130, 2131 denotes the stimulus, 2132 denotes high contrast, and 2133 denotes low contrast. In box 2150, 2151 denotes the stimulus, 2152 denotes high contrast in control, 2153 denotes low contrast in control and 2154 denotes high contrast in cone loss.

[0106] Boxes 2135 and 2155 show the empirically computed nonlinearity of the relationship between linear behavioral predictions (as in boxes 2130 and 2150) from the drifting bar stimulus and the corresponding average eye velocities measured during behavioral OKR experiments for superior and inferior stimuli at high and low contrast. The points indicate univariate medians for each condition and whiskers are 95% confidence intervals computed via bootstrapping (vertical error bars are too small to see). The solid line (2136 or 2156) is a fitted sigmoid function of the form described in Equation 6 and has parameters Vmin=-1 .69, Vmin=-1 .69, Vmax=1 .82, Vmax=1 .82, r50=4.93, r50=4.93, m=0.022, m=0.022.

[0107] Equation 6:

[0108] EXAMPLE 3:

[0109] Control mice were shown drifting sinusoidal grating masked by occluding scotomas (FIG. 22). Gain was calculated by dividing eye velocity by stimulus velocity. As the occluded fraction increased, the average OKR gain decreased (FIG. 23). EXAMPLE 4;

[0110] The following test was designed to test unconscious visual perception. OKR stimuli consist of a field of positive contrast moving objects (e.g., bright spots moving on a darker background). Each individual object is rendered at a random location on the screen so as to avoid overlap between objects and, for some stimuli, control the density of objects at different eccentricities and screen locations. After rendering, each object persists on the screen only transiently, with an average lifespan of 150 ms. During this time, the object moves according to a common global motion trajectory (i.e., all objects that are currently rendered on the screen move according to the same velocity function). At the end of the object’s lifespan, it is removed from the screen. This brief life cycle occurs out of sync for every object, meaning that at every point in time there are some objects being removed and other ones just being initially rendered to replace them. The result is that there are no continuous local spatiotemporal correlations of motion but still a global perception of motion. This design is critical because it prohibits the patient from being able to consciously track the motion of any single object, while retaining the global motion perception that drives the reflexive eye movements that are being measured.

[0111] There are several different versions of OKR stimuli that are all based around this common design, but use different global velocity functions to control the object motion. For detecting retinopathies, the following were used: (1 ) constant linear motion with a speed of 10-20 degrees per second, (2) periodic functions that are the sum of 4 trigonometric functions (with periods ranging from 1 to 15 seconds), (3) objects with positive contrast between 20% and 200%, (4) gaze-contingent occluding stimuli (such as blank circles) overlaid on top of the objects so as to isolate reflexive eye movements driven by a specific retinal locus.

[0112] Eye movements are measured in response to the particular set of stimuli that are appropriate for a given disease. For stimuli with linear motion, the following steps were used to calculate the gain: 1 . Isolate the time series for binocular gaze angle. This consists of one time series each for elevation and azimuth.

[0113] 2. Identify periods of blink and data loss. If the percentage of the time series with data loss is greater than 10%, the results are invalid and the test must be repeated.

[0114] 3. Set the velocity of the eye equal to the mean velocity during the previous 100 ms during blinks and data loss.

[0115] 4. Identify saccades: This can be done using a velocity and acceleration threshold. The precise thresholds depend on the stimulus speed, but typically the velocity threshold should be between 20 and 100 deg / s, and the acceleration threshold should be ~10 deg / s2. A saccade is counted only when the total eye velocity / acceleration [sqrt(elevation2+ azimuth2)] exceeds the thresholds. Moreover, acceleration thresholds must be immediately followed by data that exceeds the velocity threshold. Note, that in calculating slow phase gain, it is acceptable to over classify eye movements as “saccades” so long as the velocity threshold is greater than 1 ,5x the stimulus speed (for stimulus speeds >5 deg / s). The assumption is that slow phase gain is typically not greater than 1 .

[0116] 5. Set the elevation and azimuth velocity to the mean value from the 100 ms immediately preceding each saccade. Then take the cumulative sum of the eye velocity time series to compute a new time series of eye position that has no saccades.

[0117] 6. Compute the average gain over the trial. This is done by finding the total distance traveled by the eye (after removing saccades, blinks, etc.) in the direction defined by the stimulus motion, and dividing that number by the total distance that the stimulus traveled. For periodic stimuli, a very similar analysis procedure is used, but instead of calculating gain on step 6 above, the time shift for which the cross correlation between the stimulus and the eye movement [in the direction(s) defined by the stimulus] is maximized is found. This time shift represents the phase shift of the eye movement with respect to the stimulus movement. A gain analogue can be computed as the ratio of the maximum cross correlation between the eye movement and the stimulus to the autocorrelation of the stimulus.

[0118] If a timeseries is used to define stimulus motion, a similar analysis procedure is used where the cross correlation between eye movement and stimulus is found, which can then be divided by the autocorrelation. In other words, the dot product of two vectors or timeseries is found. The dot product between the two timeseries and / or the projection of one timeseries onto the other timeseries can be used to calculate gain.

[0119] The gain (linear motion stimuli) and phase shift (oscillating motion stimuli) can be used to compute a reflexive vision score. This can be done in any number of ways depending on the precise number and type of stimuli used. The simplest computation is to define a weighted population vector, where the components are the mean gain and / or phase shift values for healthy individuals on a particular stimulus set. A corresponding vector of equal dimensionality is then computed for each patient based on their test results. The projection of the patient’s vector on the population mean is the “reflexive vision score” (normalized between 0 and 1 , where 1 is the projection of the mean vector onto itself). The reflexive vision score can be age-adjusted by multiplying each component by a known value that reflects age-related changes to performance (gain or phase-shift on a particular stimulus). If the age-adjusted reflexive vision score is lower than an empirically defined threshold, then the patient is a suspect for a particular retinopathy.

[0120] To immerse the subject in a virtual scene, a virtual reality (VR) headset, the HTC Vive Pro Eye, is used to display custom scenes developed within the Unity game engine. The headset is fixed to a chinrest to reduce yaw rotation, allowing the subject to freely enter and exit the virtual scene. This headset has a built-in Tobii eye tracker that encircles both eye pieces. The headset is connected to a computer running Windows 11 with an Intel Xeon processor and an NVIDIA RTX 2080 Ti GDDR6 graphics card. From the software side, spatial tracking, hardware interfacing, and frame delivery are possible through the hardware-agnostic SteamVR runtime, which bridges the Unity-developed scene with the headset. Within Unity, the OpenXR plugin is used to develop the scene, and the Vive SRanipal SDK interfaces with the built-in eye tracker, synchronizing tracking acquisition with frame delivery at a rate of 90Hz.

[0121] Traditional optokinetic reflex (OKR)-eliciting stimuli are ineffective in preventing conscious interference of an unconscious task in humans due to movement prediction and inadvertent fixation. A stimulus has been designed that reduces conscious interference in OKR behavior through unpredictable global motion and transient local visibility. Using the Unity Particle System, 300, 2D particles are spawned in random initial positions on a coplanar disc. Particles are scaled and placed a relative number of units in front of the subject, such that each particle spans approximately 195’. Each visible particle in the collection is given a lifetime of 150-200 ms, after which it will be made invisible for another 150-200 ms. It will then be spawned in a new location within the coplanar disc, and made visible. This cycle of transient visibility repeats asynchronously for each particle for the duration of the stimulus, mitigating inadvertent fixation on local features of the stimulus. To achieve the effect of global motion, particles are assigned a velocity vector in every frame - during the transiently visible period of each particle’s life, it will follow its assigned velocity trajectory until it disappears. The Gestalt percept is of global motion matching the assigned velocity vector.

[0122] This motion is either unidirectional or oscillatory. Unidirectional motion can flow at any angle offset. Oscillatory motion is useful in analysis to determine phase shift and power spectra of OKR response. However, harmonic sinusoidal motion is too easily predicted by humans. To impede this prediction, a nonharmonic velocity function was utilized, described as the sum of sines, with randomly generated frequency and phase parameters. The period of this oscillatory motion is 15 sec. The amplitude is variable. Besides motion, the contrast of the particles was modulated, which can remain static or cycle between negative and positive contrast for the duration of the stimulus.

[0123] In addition to the base OKR stimulus described above, a mask to simulate visual defects of varying sizes can be overlaid (see, e.g., right panel of FIG. 25). Static masks can occlude the visual field centrally or peripherally. Dynamic masks progressively tile visual defects (40’ size) randomly across the visual field, cycling between zero occlusion to >99% occlusion for the duration of the stimulus. Separate from this OKR-eliciting stimulus, an OKR suppression task has been built. The stimulus for this task is a sinusoidal grating, with a fixed spatial frequency. This grating will move unidirectionally, either up or down. A sphere that is the average color of the grating is placed centrally in the subject’s visual field, between the subject and the grating. This sphere diminishes in size at a constant rate as the grating behind it continues to move unidirectionally. The task requires the subject to fixate on this sphere and prevent the subject’s eyes from moving as the sphere shrinks over the duration of the task.

[0124] The Tobii eye tracker can be interfaced using the Tobii XR SDK or through the Vive SRanipal SDK. Data can be acquired at 90Hz, such that it is synced with every frame update. The embedded calibration software is used to calibrate the eye tracker to each subject. On each frame, the SDK provides a vector that lies within a unit sphere which describes the direction of eye gaze. Data points deemed invalid by the tracker are filtered out.

[0125] An OKR screening decision tree for diabetic retinopathy is shown in FIG. 28. As described in FIG. 28, if patients are diagnosed with the conditions listed in Table 1 , the change in the age-adjusted reflexive vision score over time may be used to detect diabetic retinopathy. An OKR screening decision tree for retinopathy is shown in FIG. 29.

[0126] Table 1 . List of baseline conditions.

[0127] EXAMPLE 5;

[0128] To compare an unconscious visual perception test with a conscious visual perception test, a forced choice task was designed. The subject must discern between four orientations of an optotype letter “E” (FIG. 24A). The optotype is obscured by an array of scotomas simulated in the stimulus (FIG. 24B). These scotomas randomly obscure the letter and collectively move in a rapid, Brownian motion pattern around a central fixation. (In embodiments, this is a random, small translation that occurs every frame based on a random number generator instead of translations based on previously recorded eye movements. This way, there is more randomness in the scotomas’ movements, instead of a predictable movements that are repeated every forced choice.) The scotomas obscure the stimulus to varying degrees from 0-100%. In each trial the subject uses a button to report the orientation of the optotype under a specific degree of scotoma. For analysis of the optotype stimulus, the percent correct is calculated as a function of degree of scotoma.

[0129] To compare the sensitivity of the novel OKR assessment with current visual acuity tests, such as the Tumbling E eye chart, a modified version of this task was built in virtual reality. This stimulus presents a white letter 'E' on a gray background, spanning approximately 195 arcminutes, using the Opticians Sans font, which is based on the Snellen and Sloan optotypes commonly used in visual acuity tests. At the start of each trial, the 'E' is randomly oriented in one of the four cardinal directions (up, down, left, right). Overlaid on the 'E' is a dynamic mask consisting of randomly positioned visual defects, each measuring 40 arcminutes. The mask can obscure the optotype to varying degrees, with 16 different states of occlusion ranging from 0% to over 99% coverage. These defects move collectively in a rapid, Brownian motion pattern, simulating the small, involuntary fixational eye movements that occur during visual perception. The task requires the subject to determine the orientation of the 'E' and respond using the arrow keys in a 4-alternative forced choice test. After each response, the process repeats with a new random orientation of the 'E' and a newly generated mask. In this stimulus, eye-tracking data is collected alongside response latency, subject choices, accuracy, and, for each frame, the fraction of the optotype visible through the mask.

[0130] EXAMPLE 6;

[0131] As shown in FIGS. 26A-26D, simulated scotomas diminish OKR gain before conscious perception in humans. FIGS. 26A-26D show results from four healthy human subjects, respectively. In the top panels of FIGS. 26A-26D, eye movement velocity drops to 80% of control levels (0% obscured) when the moving dots are obscured by 10% or less. In the bottom panels of FIGS. 26A- 26D, for the same corresponding subjects, the percent correct of optotype orientation discrimination falls to 80% correct with the optotype obscured by 79% or more.

[0132] EXAMPLE 7:

[0133] FIG. 27 depicts an example of a subject 2700 utilizing a system 2750 according to the present disclosure to assess the optokinetic reflex (OKR) of the subject 2700. As shown in FIG. 27, a virtual reality (VR) headset 2705 is stabilized on posts 2715. The subject 2700 rests their chin 2725 on the chin rest 2710, such that the subject’s 2700 head is stably associated with the VR headset 2705. The subject 2700 looks into the VR headset 2705. The VR headset 2705 comprises a display 2720 which presents OKR stimuli to the subject and eyetracking unit 2730 which tracks the eye movement of the subject in response to the OKR stimuli. EXAMPLE 8:

[0134] Reflexive eve movements are more sensitive to simulated scotomas than conscious visual perception in humans

[0135] It was investigated whether reflexive eye movements could be used to detect simulated retinal degeneration in healthy control subjects. Using a virtual reality (VR) headset, a drifting dot pattern consisting of a collection of upward- moving white spots with transient lifespans was presented to subjects (FIG. 30A). This pattern causes involuntary activation of OKR. OKR gain (ratio of eye velocity to stimulus velocity) evoked by this stimulus was used as the outcome measure for this study.

[0136] To test the relationship between OKR gain and simulated retinal degeneration, the white dot pattern was progressively obscured with gray “scotomas” (same color as the background). With as little as 2% of the visual field covered by these scotomas, OKR gain dropped below 80% of baseline (FIG. 30B). This result shows that OKR gain is a reliable readout of mild forms of retinal degeneration. Higher degrees of scotoma also led to progressively lower OKR gains. Calculating the area under the curve of the receiver operating characteristic (ROC AUG) for each level of scotoma revealed that scotoma conditions could be perfectly distinguished from baseline by 10% simulated degeneration and beyond (FIG. 30C).

[0137] It was next investigated how this result compares to the corresponding relationship between subjective vision tasks and simulated retinal degeneration. The same control subjects viewed a tumbling “E” optotype in the VR headset. In each trial, the orientation of the “E” was randomized (up, down, left, right), and the subjects used a keyboard to report the direction that they thought the “E” was facing. Performance on this task was tested while progressively obscuring the “E” with the same gray scotomas described above. Performance dropped below 80% of baseline only after 81 % of the visual field was covered with scotomas (FIG. 30D), and the ROC AUG remained at 0.5 (indistinguishable from baseline) until above 70% simulated degeneration (FIG. 30E). This result suggests that unlike OKR gain, performance on subjective visual tasks such as optotype identification is unaffected by small amounts of simulated degeneration. To confirm this finding, the subjects’ performance was measured on another subjective vision task involving identifying the orientation of Glass pattern dots (Glass, L., 1969. Moire Effect from Random Dots. Nature 223, 578-580). Unlike the tumbling “E” task, this Glass pattern task incorporates dots with similar spatial frequency components to the OKR stimulus, and allows for orientation detection along a continuous metric (as opposed to the 4 discrete orientations that the E can assume). Performance on this task did not drop below 80% until 96% of the visual field was covered by scotomas (FIG. 30F). Together, these results show that OKR gain is a sensitive metric for identifying mild forms of degeneration, whereas subjective visual tasks may be better for detecting severe degeneration. In a direct comparison of OKR gain and performance of optotype orientation matched for the degree of scotoma, the OKR gain is dependent, whereas orientation discrimination is independent, of mild degrees of scotoma (FIG. 30G). In contrast, the orientation discrimination is dependent, whereas OKR is independent, of severe degrees of scotoma (FIG. 30G). These findings suggest that OKR, an unconscious and reflexive eye movement, may more sensitively reflect mild visual input loss compared to measurements derived from subjective vision.

[0138] Diminished reflexive eve movements are associated with USH2A-related photoreceptor loss, but not changes in visual acuity in humans

[0139] In this experiment, the OKR gain of patients with retinal degeneration associated with mutations in the USH2A gene and the OKR gain of healthy control subjects were directly compared. Patients with USH2A variants experience retinal degeneration in the form of primary rod loss and secondary cone loss (FIG. 31 A). Using the same VR headset and stimulus described for FIG. 30, the net displacement of the eye was measured during a 40 second upward moving OKR stimulus (net displacement is linearly proportional to gain, it is simply not normalized by the stimulus velocity). It was found that USH2A patients have lower OKR gains than control subjects (FIG. 31 B). The area under the curve of the receiver operating characteristic was 0.846 (where 1 is perfect discrimination). At a threshold of 301 .32 degrees, the sensitivity was 90% and the specificity of 77% (FIGS. 31C-31 D). In the LISH2A patients only, the OKR gain was measured as a function of retinal degeneration as quantified by the z- score between nearest neighbor cone photoreceptors (cone photoreceptors imaged using AOSLO as described in FIG. 32 below). Here, a higher z-score indicates more degeneration. If control subjects were plotted on this graph, they would have an average z-score of 0. It was found that OKR gain reliably decreased with cone z-score (FIG. 31 E), indicating that it is not only useful as a binary diagnostic (i.e., to indicate which patients have retinal degeneration and which do not), but also as a continuous measure of degeneration, including for longitudinal measurement of disease progression. While the above experiment was performed at best corrected visual acuity (BOVA) for all subjects, the LISH2A population had a slightly lower BCVA than the control population (i.e., they had some uncorrectable acuity loss). To test whether this difference in acuity, rather than degeneration of the retina, could explain the OKR gain difference between control subjects and USH2A patients, a second set of experiments was performed in which OKR gain was measured in control subjects with and without corrective lenses. Visual acuity was quantified using the Early Treatment Diabetic Retinopathy Study (ETDRS), and all subjects in this experiment achieved an ETDRS score greater than or equal to 85 (equivalent to Snellen acuity of 20 / 20) while wearing corrective lenses. Without correction, however, these control subjects had significantly lower ETDRS scores, including lower than the LISH2A population from the previous experiment (FIG. 31 H). Measuring OKR gain in this control population with and without correction revealed no significant effect (FIG. 311), and if anything, caused a non-significant gain change in the opposite direction compared to LISH2A subjects (FIG. 31 K). In this example, OKR gain differences between Control and LISH2A populations cannot be attributed to effects from acuity and, distinctly, the stimulus used in this example does not evoke reflexive eye movements that are reflective of visual acuity differences (FIGS. 31J-31 K). Some embodiments of the invention may be utilized in the context of a disease that affects visual acuity, i.e., for detecting and / or analyzing visual acuity changes. Other embodiments of the invention may be utilized in the context of a disease that affects degeneration, i.e., for detecting and / or analyzing degeneration changes.

[0140] Adaptive optics scanning laser ophthalmoscopy (AOSLO) imaging of cones in humans

[0141] Adaptive optics scanning laser ophthalmoscopy (AOSLO) is a gold- standard technique used to image individual cone photoreceptors in the retina. It requires expensive, custom-made equipment, trained technicians to operate, and dozens of hours of labor per patient. It is not a scalable approach for identifying retinal degeneration, but here it is used as a gold-standard benchmark for comparison in this study. LISH2A and control patients underwent AOSLO imaging after performing the VR experiments described above (FIGS. 32A, 32E). Regions of interest (ROIs) were identified near the macula in which to quantify the number of cone photoreceptors (FIGS. 32C, 32F). Cone spacing z-scores were used as the measure of degeneration: cones were identified in the AOSLO images (FIGS. 32D, 32G) and the average distance between cones was quantified. This distance was then compared to a control dataset to calculate each subject’s z-score. A higher z-score indicates cones spaced further apart, which is suggestive of degeneration (e.g., there are missing cones, so the existing ones are spaced further apart). The average z-score of control subjects is 0.

[0142] Reflexive eve movements sensitive to cone loss <30% in mice

[0143] To understand more thoroughly the effect of photoreceptor loss on reflexive eye movements, OKR was measured in a mouse model of retinal degeneration. Partial cone loss was acutely induced in mature mice expressing the diphtheria toxin receptor in cones expressing the middle wavelength opsin (“cone-DTR” mice) (FIG. 33A, top). Only cone-DTR mice that had cone ablation that was >1 .5 standard deviation, but less than 30% cone loss compared to a control population, were included in this study (determined post-hoc) (FIGS. 33B- 33C). OKR was measured in headfixed mice by placing them in a virtual reality hemisphere and using infrared video oculography (FIG. 33A, bottom). A sinusoidally-drifting grating pattern was projected onto the hemisphere using a 405nm digital light projector and a spherical mirror. It was found that cone-DTR mice had lower OKR gains compared to wild type animals (FIGS. 33D-33E). Moreover, comparing OKR gain directly to the number of cones remaining in each animal’s retina revealed a negative correlation (FIG. 33F). This experiment demonstrates that (1 ) the relationship between OKR gain and retinal degeneration is robust across species, and (2) that mice may be a valuable experimental model for further developing diagnostic tests that leverage OKR across a variety of diseases.

[0144] Mouse Methods

[0145] Animal Subjects: All experiments were performed in accordance with protocols approved by the University of California, San Francisco Institutional Animal Care and Use Program. Mice of both sexes were used. Control mice were C57BI / 6 mice from Jackson Laboratory. Cone loss mice were on the background of C57BI / 6 with HRGPCre x DTR to selectively express the simian diphtheria toxin in cones containing middle wavelength sensitive opsin.

[0146] Induction of cone loss: Cone loss in mice was induced by expression of the simian diphtheria toxin receptor under the promoter for the middle wavelength sensitive (M) opsin. Mice were injected at postnatal day (P)30 or later to allow for normal development of the retina. Cones remained intact and healthy until 3 days following intramuscular injection of diphtheria toxin (0.025-0.1 mg / kg). At the lower dosages, approximately 30% of cones were ablated. At the higher dosages, >60% of cones were ablated. The dorsal retina endured the majority of cone death. Following diphtheria toxin injection, mice were used at P60-120 for either behavior or retinal physiology. Mice used in both types of experiments had their cones quantified by immunohistochemistry. Cone quantification: Following behavioral experiments, the left retina, which was the eye used for eye tracking, was harvested and mounted flat, preserving the dorsal-ventral and nasal-temporal axes. The retina was fixed in 2% paraformaldehyde for 20min, rinsed in PBS, and immunoprocessing for staining against cone arrestin. The cone arrestin was imaged on a Leica SP8 (40x objective, NA 1 .3; resolution 0.38 x 0.38 x 0.3 pm). Three images of the cone pedicles were taken in each of the four quadrants at 1 -2mm from the center of the retina. Images were median filtered in FIJI, then the cone pedicles were quantified in Imaris. Cones crossing two of the four boundaries of the image were eliminated from the count to prevent double counting of cones. The right eye was harvested as a whole and immersed in glutaraldehyde for Hemotoxylin and Eosin sections. The number of cell bodies in the outer nuclear layer were quantified to determine if rods were affected by the cone DTR manipulation.

[0147] Surgeries: Mice >P60 were anesthetized under ketamine / xylazine and isoflurane. The mice were placed in a stereotaxic surgery apparatus. Hair was removed from the head. After a local injection of lidocaine, a small incision was made to expose Bregma. An area of the skin was removed and the skull was exposed. Dental cement was placed to cover the hole. Three nuts were set into the dental cement to align with Bregma. The area around the headplate was treated with antibiotics and the mouse recovered on a heating pad. After one week of acclimating to the headplate, the mice were secured to the behavioral rig with the nuts. While the mouse’s head was fixed, the rest of its body was free to move around and walk on a wheel.

[0148] Stimulus: The stimulus was projected on a dome as previously described (Harris, S.C., Dunn, F.A., 2023. Asymmetric retinal direction tuning predicts optokinetic eye movements across stimulus conditions. eLife 12, e81780). The image was projected by a LightCrafter projector with a custom 405nm LED. The stimulus included a sinusoidal grating oscillating vertically. Stimuli were generated using psychopy (Pierce, J., et al. (2019). PsychoPy2: Experiments in behavior made easy. Behavior research methods, 51 (1 ), 195-203.) and Bassoon (Scott Harris, & John, J. (2024). ScottHarris17 / Bassoon: Bassoon (1.3.0). Zenodo. https: / / doi.org / 10.5281 / zenodo.13132451 ). Eye tracking: The eye position was tracked by using an infrared reflection (880nm) on the cornea. Two corneal reflections at the meridian and equator of the eye were used for calibration. The methods and equipment are identical to those previously described (Harris and Dunn, 2023). A calibration was done for each mouse in which the camera is moved ±6 deg horizontally about the eye and the image of the corneal reflection is taken at each position. The calibration was done for 5 luminance levels to determine the relationship between the pupil size and angular eye position (Harris and Dunn, 2023). Analysis: Movies of the eyes were first annotated by a neural network trained by DeepLabCut (www.deeplabcut.org) in which the corneal reflection and the pupil were identified on each frame of the movie. Data were analyzed on custom Matlab and python software. The calibration was used to translate the pupil location into angular degrees of eye movements. To isolate the slow eye movements associated with the optokinetic reflex and to remove the saccades that reset eye position, velocities >80 deg / sec were thresholded out. Slow eye movements were then analyzed for gain (eye velocity / stimulus velocity).

[0149] Human Methods Research procedures were performed in accordance with the Declaration of Helsinki. The study protocol was approved by the University of California, San Francisco institutional review board. Informed consent was obtained from all subjects. Control subjects with normal eye examinations were used in this study. Both eyes were used in the eye tracking. A standard eye chart was used to measure best corrected visual acuity according to the ETDRS protocol. All control subjects had an ETDRS of 85 or better and BCVA of 20 / 20 or better.

[0150] VR Headset: Stimulus display and eye tracking were accomplished with the HTC Vive Pro Eye with Tobii eye tracking. To prevent head movements, the device was mounted on a chin and forehead rest, securely clamped to a table. The subjects placed their head in the goggles by resting their chin on a rest. This apparatus allowed the subject’s head to remain still, thus controlling eye movement contributions from the vestibulo-ocular reflex. Subjects could abort any session by removing their head from the device.

[0151] Human psychophysics OKR stimulus: A stimulus was designed that reduces conscious interference in OKR behavior through global motion and transient local visibility. Using the Unity Particle System, 300, 2D particles are spawned in random initial positions on a coplanar disc. Particles are scaled and placed a relative number of units in front of the user, such that each particle spans approximately 195 min. Each visible particle in the collection is given a lifetime of 150-200 ms, after which it will be made invisible for another 150-200 ms. It will then be spawned in a new location within the coplanar disc, and made visible. This cycle of transient visibility repeats for the duration of the stimulus, mitigating inadvertent fixation on local features of the stimulus. To achieve the effect of global motion, particles are assigned a velocity vector in every frame. During the transiently visible period of each particle’s life, it will follow its assigned velocity trajectory till it disappears from view. The Gestalt percept is of global motion matching the assigned velocity vector.

[0152] The random dots move unidirectionally upward at 10-20 deg / sec. In addition to the base OKR stimulus described above, a mask is overlaid to simulate visual defects of varying sizes. These dynamic masks progressively tile visual defects (40 min arc diameter) randomly across the visual field, cycling between zero occlusion to >99% occlusion for the duration of the stimulus.

[0153] Human psychophysics tumbling E: This stimulus presents a white letter 'E' on a gray background, spanning approximately 195 arc min, using the Opticians Sans font, which is based on the Snellen and Sloan optotypes commonly used in visual acuity tests. At the start of each trial, the 'E' is randomly oriented in one of the four cardinal directions (up, down, left, right). Overlaid on the 'E' is a dynamic mask consisting of randomly positioned visual defects, each measuring 40 arc min. The mask can obscure the optotype to varying degrees, with 16 different states of occlusion ranging from 0% to over 99% coverage. These defects move collectively in a rapid, Brownian motion pattern, simulating the small, involuntary fixational eye movements that occur during visual perception. The task requires the user to determine the orientation of the 'E' and respond using the arrow keys in a 4-alternative forced choice test. After each response, the process repeats with a new random orientation of the 'E' and a newly generated mask. In this stimulus, eye-tracking data is collected alongside response latency, user choices, accuracy, and, for each frame, the fraction of the optotype visible through the mask.

[0154] Human psychophysics Glass patterns: An array of dots in pairs with stereotyped orientation were displayed on a monitor. On top of the dots were random scotomas covering the dots from 0-100%. The subject’s task was to use the arrow keys on a standard keyboard to orient a line that matched the orientation of the pairs of dots. This experiment was done using a standard computer monitor instead of the VR headset.

[0155] Eve tracking: The Vive Pro Eye’s built in eye infrared ocular eye tracking system (Tobii) was used with the SRanipal SDK to extract and align oculometric data during experiments. Data was acquired at 90 Hz and transformed to a polar coordinate system with the subject’s eye at the origin to measure gaze angles over time. Each user performed a 4-point calibration procedure prior to the start of the experiment.

[0156] Analysis of human psychophysics OKR stimulus: The following approach was used to calculate OKR gain: (1 ) Isolate the time series for binocular gaze angle. This consists of one time series each for elevation and azimuth. (2) Identify periods of blink and data loss. If the percentage of the time series with data loss is greater than 10%, the results are invalid and the test must be repeated. (3) Remove saccades using low pass filter and velocity and acceleration thresholds, (4) Compute the average gain over the trial by measuring the net displacement of the eye across the complete stimulus duration.

[0157] Analysis of human psychophysics tumbling E: For the analysis of the optotype stimulus, the percent of correct responses was calculated for each of 16 levels of scotoma density. Human psychophysics Glass patterns: For the analysis of the orientation matching of the Glass patterns, the difference in angle between the dot pairs and the line oriented by the subject was taken as the error. Errors of 90 deg were equated to 0% optimal and errors of 0 deg were equated to 100% optimal.

[0158] Further detail regarding certain aspects of embodiments of the present disclosure are found in the following, each of which are incorporated herein by reference in their entirety:

[0159] Bensinger, E., Rinella, N., Saud, A., Loumou, P., Ratnam, K., Griffin, S., Qin, J., Porco, T.C., Roorda, A., Duncan, J.L., 2019. Loss of Foveal Cone Structure Precedes Loss of Visual Acuity in Patients With Rod-Cone Degeneration. Invest. Ophthalmol. Vis. Sci. 60, 3187-3196. https: / / doi.Org / 10.1167 / iovs.18-26245

[0160] Care, R.A., Anastassov, LA., Kastner, D.B., Kuo, Y.-M., Santina, L.D., Dunn, F.A., 2020. Mature Retina Compensates Functionally for Partial Loss of Rod Photoreceptors. Cell Rep. 31. https: / / doi.Org / 10.1016 / j.celrep.2020.107730

[0161] Care, R.A., Kastner, D.B., De la Huerta, I., Pan, S., Khoche, A., Della Santina, L., Gamlin, C., Santo Tomas, C., Ngo, J., Chen, A., Kuo, Y.-M., Ou, Y., Dunn, F.A., 2019. Partial Cone Loss Triggers Synapse-Specific Remodeling and Spatial Receptive Field Rearrangements in a Mature Retinal Circuit. Cell Rep. 27, 2171 -2183.e5. https: / / doi.Org / 10.1016 / j.celrep.2019.04.065

[0162] Dhande, O.S., Stafford, B.K., Lim, J.-H.A., Huberman, A.D., 2015. Contributions of Retinal Ganglion Cells to Subcortical Visual Processing and Behaviors. Annu. Rev. Vis. Sci. 1 , 291-328. https: / / d0i.0rg / l 0.1146 / annurevvision-0821 14-035502

[0163] Foote, K.G., Loumou, P., Griffin, S., Qin, J., Ratnam, K., Porco, T.C., Roorda, A., Duncan, J.L., 2018. Relationship Between Foveal Cone Structure and Visual Acuity Measured With Adaptive Optics Scanning Laser Ophthalmoscopy in Retinal Degeneration. Invest. Ophthalmol. Vis. Sci. 59, 3385-3393. https: / / doi.Org / 10.1 167 / iovs.17-23708 Geller, A.M., Sieving, P.A., Green, D.G., 1992. Effect on grating identification of sampling with degenerate arrays. JOSA A 9, 472-477. https: / / doi.Org / 10.1364 / JGSAA.9.000472

[0164] Giolli, R.A., Blanks, R.H.I., Lui, F., 2006. The accessory optic system: basic organization with an update on connectivity, neurochemistry, and function, in: Buttner-Ennever, J.A. (Ed.), Progress in Brain Research, Neuroanatomy of the Oculomotor System. Elsevier, pp. 407-440. https: / / doi.org / 10.1016 / S0079- 6123(05)51013-6

[0165] Glass, L., 1969. Moire Effect from Random Dots. Nature 223, 578-580. https: / / doi.Org / 10.1038 / 223578a0

[0166] Harris, S.C., Dunn, F.A., 2023. Asymmetric retinal direction tuning predicts optokinetic eye movements across stimulus conditions. eLife 12, e81780. https: / / d0i.0rg / l 0.7554 / eLife.81780

[0167] Scott Harris, & John, J. (2024). ScottHarris17 / Bassoon: Bassoon (1 .3.0). Zenodo. https: / / doi.org / 10.5281 / zenodo.13132451

[0168] Kiebel, S., 2009. Cortical circuits for perceptual inference. Neural Netw., Cortical Microcircuits 22, 1093-1 104. https: / / d0i.0rg / l 0.1016 / j.neunet.2009.07.023

[0169] Lee, J.Y., Care, R.A., Kastner, D.B., Della Santina, L., Dunn, F.A., 2022. Inhibition, but not excitation, recovers from partial cone loss with greater spatiotemporal integration, synapse density, and frequency. Cell Rep. 38, 1 10317. https: / / d0i.0rg / l 0.1016 / j.celrep.2022.110317

[0170] Naoi, M., Maruyama, W., 1999. Cell death of dopamine neurons in aging and Parkinson’s disease. Meeh. Ageing Dev. 111 , 175-188. https: / / doi.Org / 10.1016 / 50047-6374(99)00064-0

[0171] Peirce, J., Gray, J. R., Simpson, S., MacAskill, M., Hochenberger, R., Sogo, H., ... & Lindelov, J. K. (2019).

[0172] PsychoPy2: Experiments in behavior made easy. Behavior research methods, 51 (1 ), 195-203.

[0173] Ratnam, K., Carroll, J., Porco, T.C., Duncan, J.L., Roorda, A., 2013. Relationship Between Foveal Cone Structure and Clinical Measures of Visual Function in Patients With Inherited Retinal Degenerations. Invest. Ophthalmol. Vis. Sci. 54, 5836-5847. https: / / doi.org / 10.1167 / iovs.13-12557

[0174] Santina, L.D., Yu, A.K., Harris, S.C., Solino, M., Ruiz, T.G., Most, J., Kuo, Y.-M., Dunn, F.A., Ou, Y., 2021 . Disassembly and rewiring of a mature converging excitatory circuit following injury. Cell Rep. 36. https: / / doi.Org / 10.1016 / j.celrep.2O21 .109463

[0175] Shannon, C.E., 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379-423. https: / / doi.Org / 10.1002 / j.1538-7305.1948.tb01338.x

[0176] Shen, N., Wang, B., Soto, F., Kerschensteiner, D., 2020. Homeostatic Plasticity Shapes the Retinal Response to Photoreceptor Degeneration. Curr. Biol. S0960982220303717. https: / / doi.Org / 10.1016 / j.cub.2020.03.033

[0177] Simpson, J.L, 1984. The Accessory Optic System. Annu. Rev. Neurosci. 7, 13-41. https: / / doi.org / 10.1146 / annurev.ne.07.030184.000305

[0178] The below items disclose various aspects of the invention. Each of the aspects described below can be combined with other aspects and embodiments disclosed elsewhere herein, including the claims, where the combinations are clearly compatible. Certain aspects include:

[0179] Aspect 1 . A method for assessing optokinetic reflex of a subject, the method comprising: presenting optokinetic reflex (OKR) stimuli to a subject; tracking eye movement of the subject in response to the OKR stimuli; and assessing the OKR of the subject based on the tracked eye movements.

[0180] Aspect 2. The method according to Aspect 1 , wherein the OKR stimuli comprise images of a plurality of objects.

[0181] Aspect 3. The method according to Aspect 2, wherein the images are configured to prevent the subject from being able to consciously track the motion of any single object.

[0182] Aspect 4. The method according to Aspects 2 or 3, wherein the plurality of objects comprise objects with discontinuous local spatiotemporal correlations of motion. Aspect 5. The method according to Aspect 4, wherein the plurality of objects are non-overlapping.

[0183] Aspect 6. The method according to Aspects 4 or 5, wherein the plurality of objects are rendered at random locations.

[0184] Aspect 7. The method according to any one of Aspects 4-6, wherein each object of the plurality of objects persists transiently.

[0185] Aspect 8. The method according to Aspect 7, wherein each object has an average lifespan in the range of 30 ms to 2000 ms.

[0186] Aspect 9. The method according to any one of Aspects 4-8, wherein the plurality of objects move with constant linear motion.

[0187] Aspect 10. The method according to Aspect 9, wherein the constant linear motion has a speed of 0.5 to 100 degrees per second.

[0188] Aspect 11 . The method according to any one of Aspects 4-10, wherein the plurality of objects move according to periodic functions.

[0189] Aspect 12. The method according to Aspect 11 , wherein the periodic functions have periods of 0.5 to 100 seconds.

[0190] Aspect 13. The method according to any one of Aspects 2-12, wherein plurality of objects comprise positive contrast objects.

[0191] Aspect 14. The method according to Aspect 13, wherein the positive contrast objects have a positive contrast in the range of about 20% to about 200%.

[0192] Aspect 15. The method according to any one of Aspects 2-12, wherein plurality of objects comprise negative contrast objects.

[0193] Aspect 16. The method according to Aspect 15, wherein the negative contrast objects have a negative contrast in the range of about 20% to about 200%.

[0194] Aspect 17. The method according to any one of Aspects 2-16, wherein plurality of objects comprise gaze-contingent occluding stimuli overlaid on top of the plurality of objects. Aspect 18. The method according to any of the previous Aspects, wherein the OKR stimuli are configured for detecting a specific condition of the subject.

[0195] Aspect 19. The method according to any of the previous Aspects, wherein the OKR stimuli are configured for detecting retinopathy in the subject.

[0196] Aspect 20. The method according to any one of the previous Aspects, wherein the OKR stimuli are presented on a stereoscopic display.

[0197] Aspect 21 . The method according to any of the previous Aspects, wherein the OKR stimuli are presented on an immersive environment display.

[0198] Aspect 22. The method according to any of the previous Aspects, wherein the OKR stimuli are presented in virtual reality (VR).

[0199] Aspect 23. The method according to Aspect 22, wherein the OKR stimuli are presented using a virtual reality (VR) headset.

[0200] Aspect 24. The method according to of any of the previous Aspects, wherein tracking eye movement of the subject comprises: illuminating eyes of the subject with infrared light; and capturing a plurality of images of the eyes of the subject using a camera.

[0201] Aspect 25. The method according to Aspect 24, wherein the capturing comprises capturing images at a rate of 50 Hz or faster.

[0202] Aspect 26. The method according to Aspects 24 or 25, wherein the tracking further comprises detecting a plurality of gaze points in the plurality of images.

[0203] Aspect 27. The method according to any one of Aspects 24-26, wherein the camera is built into a VR headset.

[0204] Aspect 28. The method according to any of the previous Aspects, wherein the assessing comprises quantitatively assessing the OKR.

[0205] Aspect 29. The method according to any of the previous Aspects, wherein the assessing comprises calculating a gain between the stimulus movement and eye movement.

[0206] Aspect 30. The method according to any of the previous Aspects, wherein the assessing comprises identifying periods of blink and data loss. Aspect 31 . The method according to any of the previous Aspects, wherein the assessing comprises identifying saccades.

[0207] Aspect 32. The method according to any of the previous Aspects, wherein the assessing comprises generating a reflexive vision score.

[0208] Aspect 33. The method according to Aspect 32, wherein the reflexive vision score is an age-adjusted reflexive vision score.

[0209] Aspect 34. The method according to Aspect 33, wherein the assessing further comprises quantifying whether the age-adjusted reflexive vision score is below an age-adjusted mean.

[0210] Aspect 35. The method according to Aspect 34, wherein the age- adjusted reflexive vision score is two standard deviations or more below an age- adjusted mean.

[0211] Aspect 36. The method according to any of the previous Aspects, further comprising comparing the OKR of the subject to a conscious visual perception task of the subject.

[0212] Aspect 37. The method according to any of the previous Aspects, further comprising comparing the OKR of the subject to retinal imaging results of the subject.

[0213] Aspect 38. The method according to Aspect 37, wherein the retinal imaging results are adaptive optics imaging results.

[0214] Aspect 39. A method for measuring retinal health of a subject, the method comprising: assessing OKR of a subject according to Aspect 1 ; and determining potential clinical interpretations of retinal health based on the OKR.

[0215] Aspect 40. A method for measuring retinal degeneration of a subject, the method comprising: assessing OKR of a subject according to Aspect 1 ; and determining potential clinical interpretations of retinal degeneration based on the OKR. Aspect 41 . The method according to any of the previous Aspects, wherein the method is a method of screening for the presence of a condition in the subject.

[0216] Aspect 42. The method according to any of the previous Aspects, wherein the method is a method of screening for the presence of a disease in the subject.

[0217] Aspect 43. The method according to any of the previous Aspects, wherein the method is a method of screening for retinopathy in the subject.

[0218] Aspect 44. The method according to any of the previous Aspects, wherein the method is a method of screening for diabetic retinopathy in the subject.

[0219] Aspect 45. The method according to any of the previous Aspects, wherein the method is a method of diagnosing a condition in the subject.

[0220] Aspect 46. The method according to any of the previous Aspects, wherein the method is a method of diagnosing a disease in the subject.

[0221] Aspect 47. The method according to any of the previous Aspects, further comprising: monitoring a disease progression by assessing the OKR of the subject at a plurality of discrete times to monitor.

[0222] Aspect 48. The method according to any of the previous Aspects, wherein the method is a computer-implemented method.

[0223] Aspect 49. A non-transitory computer readable storage medium comprising instructions stored thereon, the instructions comprising: algorithm for presenting optokinetic reflex (OKR) stimuli to a subject; algorithm for tracking eye movement of the subject in response to the OKR stimuli; and algorithm for assessing the OKR of the subject based on the tracked eye movements.

[0224] Aspect 50. The non-transitory computer readable storage medium according to Aspect 49, wherein the OKR stimuli comprise images of a plurality of objects. Aspect 51 . The non-transitory computer readable storage medium according to Aspect 50, wherein the images are configured to prevent the subject from being able to consciously track the motion of any single object.

[0225] Aspect 52. The non-transitory computer readable storage medium according to Aspects 50 or 51 , wherein the plurality of objects comprise objects with discontinuous local spatiotemporal correlations of motion.

[0226] Aspect 53. The non-transitory computer readable storage medium according to Aspect 52, wherein the plurality of objects are non-overlapping.

[0227] Aspect 54. The non-transitory computer readable storage medium according to Aspects 52 or 53, wherein the plurality of objects are rendered at random locations.

[0228] Aspect 55. The non-transitory computer readable storage medium according to any one of Aspects 50-54, wherein each object of the plurality of objects persists transiently.

[0229] Aspect 56. The non-transitory computer readable storage medium according to Aspect 55, wherein each object has an average lifespan is in the range of 30 ms to 2000 ms.

[0230] Aspect 57. The non-transitory computer readable storage medium according to any one of Aspects 50-56, wherein the plurality of objects move with constant linear motion.

[0231] Aspect 58. The non-transitory computer readable storage medium according to Aspect 57, wherein the constant linear motion has a speed of 0.5 to 100 degrees per second.

[0232] Aspect 59. The non-transitory computer readable storage medium according to any one of Aspects 50-58, wherein the plurality of objects move according to periodic functions.

[0233] Aspect 60. The non-transitory computer readable storage medium according to Aspect 59, wherein the periodic functions have periods of 0.5 to 100 seconds. Aspect 61 . The non-transitory computer readable storage medium according to any one of Aspects 50-60, wherein plurality of objects comprise positive contrast objects.

[0234] Aspect 62. The non-transitory computer readable storage medium according to Aspect 61 , wherein the positive contrast objects have a positive contrast in the range of about 20% to about 200%.

[0235] Aspect 63. The non-transitory computer readable storage medium according to any one of Aspects 50-60, wherein plurality of objects comprise negative contrast objects.

[0236] Aspect 64. The non-transitory computer readable storage medium according to Aspect 61 , wherein the negative contrast objects have a negative contrast in the range of about 20% to about 200%.

[0237] Aspect 65. The non-transitory computer readable storage medium according to any one of Aspects 50-64, wherein plurality of objects comprise gaze-contingent occluding stimuli overlaid on top of the plurality of objects.

[0238] Aspect 66. The non-transitory computer readable storage medium according to any one of Aspects 49-65, wherein the OKR stimuli are presented on a stereoscopic display.

[0239] Aspect 67. The non-transitory computer readable storage medium of any one of Aspects 49-66, wherein the OKR stimuli are presented on an immersive environment display.

[0240] Aspect 68. The non-transitory computer readable storage medium according to any one of Aspects 49-67, wherein the OKR stimuli are presented in virtual reality (VR).

[0241] Aspect 69. The non-transitory computer readable storage medium according to Aspect 68, wherein the OKR stimuli are presented using a virtual reality (VR) headset.

[0242] Aspect 70. The non-transitory computer readable storage medium according to of any one of Aspects 49-69, wherein algorithm for tracking eye movement of the subject comprises: algorithm for illuminating eyes of the subject with infrared light; and algorithm for capturing a plurality of images of the eyes of the subject using a camera.

[0243] Aspect 71 . The non-transitory computer readable storage medium according to Aspect 70, wherein the algorithm for capturing comprises algorithm for capturing images at a rate of 50 Hz or faster.

[0244] Aspect 72. The non-transitory computer readable storage medium according to Aspects 70 or 71 , wherein the algorithm for tracking further comprises algorithm for detecting a gaze point in the plurality of images.

[0245] Aspect 73. The non-transitory computer readable storage medium according to any one of Aspects 70-72, wherein the camera is built into a VR headset.

[0246] Aspect 74. The non-transitory computer readable storage medium according to any one of Aspects 49-73, the instructions stored thereon further comprising: algorithm for quantitatively assessing the OKR.

[0247] Aspect 75. The non-transitory computer readable storage medium according to any one of Aspects 49-74, the instructions stored thereon further comprising: algorithm for calculating a gain between the stimulus movement and eye movement.

[0248] Aspect 76. The non-transitory computer readable storage medium according to any one of Aspects 49-75, the instructions stored thereon further comprising: algorithm for identifying periods of blink and data loss.

[0249] Aspect 77. The non-transitory computer readable storage medium according to any one of Aspects 49-76, the instructions stored thereon further comprising: algorithm for identifying saccades.

[0250] Aspect 78. The non-transitory computer readable storage medium according to any one of Aspects 49-77, the instructions stored thereon further comprising: algorithm for generating a reflexive vision score.

[0251] Aspect 79. The non-transitory computer readable storage medium according to Aspect 78, wherein the reflexive vision score is an age-adjusted reflexive vision score.

[0252] Aspect 80. The non-transitory computer readable storage medium according to Aspect 79, the instructions stored thereon further comprising: algorithm for quantifying whether the age-adjusted reflexive vision score is below an age-adjusted mean.

[0253] Aspect 81 . The non-transitory computer readable storage medium according to Aspect 80, wherein the age-adjusted reflexive vision score is two standard deviations or more below an age-adjusted mean.

[0254] Aspect 82. The non-transitory computer readable storage medium according to any one of Aspects 49-81 , the instructions stored thereon further comprising: algorithm for comparing the OKR of the subject to a conscious visual perception task of the subject.

[0255] Aspect 83. The non-transitory computer readable storage medium according to any one of Aspects 49-82, the instructions stored thereon further comprising: algorithm for comparing the OKR of the subject to retinal imaging results of the subject.

[0256] Aspect 84. The non-transitory computer readable storage medium according to Aspect 83, wherein the retinal imaging results are adaptive optics imaging results.

[0257] Aspect 85. The non-transitory computer readable storage medium according to Aspect 49, the instructions stored thereon further comprising: algorithm for determining potential clinical interpretations of retinal health based on the OKR.

[0258] Aspect 86. The non-transitory computer readable storage medium according to Aspect 49, the instructions stored thereon further comprising: algorithm for determining potential clinical interpretations of retinal degeneration based on the OKR.

[0259] Aspect 87. A system for assessing optokinetic reflex of a subject, the system comprising: a display, wherein the display is configured to: present optokinetic reflex (OKR) stimuli to a subject; and an eye-tracking unit, wherein the eye-tracking unit is configured to: track eye movement of the subject in response to the OKR stimuli.

[0260] Aspect 88. The system according to Aspect 87, further comprising a virtual reality (VR) system comprising: the display; and the eye-tracking unit.

[0261] Aspect 89. The system according to Aspect 88, wherein the virtual reality (VR) system comprises a virtual reality (VR) headset.

[0262] Aspect 90. The system according to any one of Aspects 87-89, the system further comprising: a processor comprising memory operably coupled to the processor wherein the memory comprises instructions stored thereon, which when executed by the processor, cause the processor to: receive data representing the tracked eye movement; and assess the OKR of the subject based on the tracked eye movement data.

[0263] Although the foregoing invention has been described in some detail by way of illustration and example for purposes of clarity of understanding, it is readily apparent to those of ordinary skill in the art in light of the teachings of this invention that certain changes and modifications may be made thereto without departing from the spirit or scope of the appended claims.

[0264] Accordingly, the preceding merely illustrates the principles of the invention. It will be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the invention and are included within its spirit and scope. Furthermore, all examples and conditional language recited herein are principally intended to aid the reader in understanding the principles of the invention and the concepts contributed by the inventors to furthering the art and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents and equivalents developed in the future, i.e., any elements developed that perform the same function, regardless of structure. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims.

[0265] The scope of the present invention, therefore, is not intended to be limited to the exemplary embodiments shown and described herein. Rather, the scope and spirit of present invention is embodied by the appended claims. In the claims, 35 U.S.C. § 1 12(f) or 35 U.S.C. § 1 12(6) is expressly defined as being invoked for a limitation in the claim only when the exact phrase “means for” or the exact phrase “step for” is recited at the beginning of such limitation in the claim; if such exact phrase is not used in a limitation in the claim, then 35 U.S.C. § 1 12(f) or 35 U.S.C. § 1 12(6) is not invoked.

Claims

What is claimed is:1 . A method for assessing optokinetic reflex of a subject, the method comprising: presenting optokinetic reflex (OKR) stimuli to a subject; tracking eye movement of the subject in response to the OKR stimuli; and assessing the OKR of the subject based on the tracked eye movements.

2. The method according to claim 1 , wherein the OKR stimuli comprise images of a plurality of objects.

3. The method according to claim 2, wherein the images are configured to prevent the subject from being able to consciously track the motion of any single object.

4. The method according to claims 2 or 3, wherein the plurality of objects comprise objects with discontinuous local spatiotemporal correlations of motion.

5. The method according to claim 4, wherein the plurality of objects are nonoverlapping.

6. The method according to claims 4 or 5, wherein the plurality of objects are rendered at random locations.

7. The method according to any one of claims 4-6, wherein each object of the plurality of objects persists transiently.

8. The method according to claim 7, wherein each object has an average lifespan in the range of 30 ms to 2000 ms.

9. The method according to any one of claims 4-8, wherein the plurality of objects move with constant linear motion.

10. The method according to claim 9, wherein the constant linear motion has a speed of 0.5 to 100 degrees per second.1 1 . The method according to any one of claims 4-10, wherein the plurality of objects move according to periodic functions.

12. The method according to claim 1 1 , wherein the periodic functions have periods of 0.5 to 100 seconds.

13. The method according to any one of claims 2-12, wherein plurality of objects comprise positive contrast objects.

14. The method according to claim 13, wherein the positive contrast objects have a positive contrast in the range of about 20% to about 200%.

15. The method according to any one of claims 2-12, wherein plurality of objects comprise negative contrast objects.

16. The method according to claim 15, wherein the negative contrast objects have a negative contrast in the range of about 20% to about 200%.

17. The method according to any one of claims 2-16, wherein plurality of objects comprise gaze-contingent occluding stimuli overlaid on top of the plurality of objects.

18. The method according to any of the previous claims, wherein the OKR stimuli are configured for detecting a specific condition of the subject.

19. The method according to any of the previous claims, wherein the OKR stimuli are configured for detecting retinopathy in the subject.

20. The method according to any one of the previous claims, wherein the OKR stimuli are presented on a stereoscopic display.21 . The method according to any of the previous claims, wherein the OKR stimuli are presented on an immersive environment display.

22. The method according to any of the previous claims, wherein the OKR stimuli are presented in virtual reality (VR).

23. The method according to claim 22, wherein the OKR stimuli are presented using a virtual reality (VR) headset.

24. The method according to of any of the previous claims, wherein tracking eye movement of the subject comprises: illuminating eyes of the subject with infrared light; and capturing a plurality of images of the eyes of the subject using a camera.

25. The method according to claim 24, wherein the capturing comprises capturing images at a rate of 50 Hz or faster.

26. The method according to claims 24 or 25, wherein the tracking further comprises detecting a plurality of gaze points in the plurality of images.

27. The method according to any one of claims 24-26, wherein the camera is built into a VR headset.

28. The method according to any of the previous claims, wherein the assessing comprises quantitatively assessing the OKR.

29. The method according to any of the previous claims, wherein the assessing comprises calculating a gain between the stimulus movement and eye movement.

30. The method according to any of the previous claims, wherein the assessing comprises identifying periods of blink and data loss.31 . The method according to any of the previous claims, wherein the assessing comprises identifying saccades.

32. The method according to any of the previous claims, wherein the assessing comprises generating a reflexive vision score.

33. The method according to claim 32, wherein the reflexive vision score is an age-adjusted reflexive vision score.

34. The method according to claim 33, wherein the assessing further comprises quantifying whether the age-adjusted reflexive vision score is below an age-adjusted mean.

35. The method according to claim 34, wherein the age-adjusted reflexive vision score is two standard deviations or more below an age-adjusted mean.

36. The method according to any of the previous claims, further comprising comparing the OKR of the subject to a conscious visual perception task of the subject.

37. The method according to any of the previous claims, further comprising comparing the OKR of the subject to retinal imaging results of the subject.

38. The method according to claim 37, wherein the retinal imaging results are adaptive optics imaging results.

39. A method for measuring retinal health of a subject, the method comprising: assessing OKR of a subject according to claim 1 ; and determining potential clinical interpretations of retinal health based on the OKR.

40. A method for measuring retinal degeneration of a subject, the method comprising: assessing OKR of a subject according to claim 1 ; and determining potential clinical interpretations of retinal degeneration based on the OKR.41 . The method according to any of the previous claims, wherein the method is a method of screening for the presence of a condition in the subject.

42. The method according to any of the previous claims, wherein the method is a method of screening for the presence of a disease in the subject.

43. The method according to any of the previous claims, wherein the method is a method of screening for retinopathy in the subject.

44. The method according to any of the previous claims, wherein the method is a method of screening for diabetic retinopathy in the subject.

45. The method according to any of the previous claims, wherein the method is a method of diagnosing a condition in the subject.

46. The method according to any of the previous claims, wherein the method is a method of diagnosing a disease in the subject.

47. The method according to any of the previous claims, further comprising: monitoring a disease progression by assessing the OKR of the subject at a plurality of discrete times to monitor.

48. The method according to any of the previous claims, wherein the method is a computer-implemented method.

49. A non-transitory computer readable storage medium comprising instructions stored thereon, the instructions comprising: algorithm for presenting optokinetic reflex (OKR) stimuli to a subject; algorithm for tracking eye movement of the subject in response to the OKR stimuli; and algorithm for assessing the OKR of the subject based on the tracked eye movements.

50. The non-transitory computer readable storage medium according to claim49, wherein the OKR stimuli comprise images of a plurality of objects.51 . The non-transitory computer readable storage medium according to claim50, wherein the images are configured to prevent the subject from being able to consciously track the motion of any single object.

52. The non-transitory computer readable storage medium according to claims 50 or 51 , wherein the plurality of objects comprise objects with discontinuous local spatiotemporal correlations of motion.

53. The non-transitory computer readable storage medium according to claim 52, wherein the plurality of objects are non-overlapping.

54. The non-transitory computer readable storage medium according to claims 52 or 53, wherein the plurality of objects are rendered at random locations.

55. The non-transitory computer readable storage medium according to any one of claims 50-54, wherein each object of the plurality of objects persists transiently.

56. The non-transitory computer readable storage medium according to claim 55, wherein each object has an average lifespan is in the range of 30 ms to 2000 ms.

57. The non-transitory computer readable storage medium according to any one of claims 50-56, wherein the plurality of objects move with constant linear motion.

58. The non-transitory computer readable storage medium according to claim 57, wherein the constant linear motion has a speed of 0.5 to 100 degrees per second.

59. The non-transitory computer readable storage medium according to any one of claims 50-58, wherein the plurality of objects move according to periodic functions.

60. The non-transitory computer readable storage medium according to claim 59, wherein the periodic functions have periods of 0.5 to 100 seconds.61 . The non-transitory computer readable storage medium according to any one of claims 50-60, wherein plurality of objects comprise positive contrast objects.

62. The non-transitory computer readable storage medium according to claim 61 , wherein the positive contrast objects have a positive contrast in the range of about 20% to about 200%.

63. The non-transitory computer readable storage medium according to any one of claims 50-60, wherein plurality of objects comprise negative contrast objects.

64. The non-transitory computer readable storage medium according to claim 61 , wherein the negative contrast objects have a negative contrast in the range of about 20% to about 200%.

65. The non-transitory computer readable storage medium according to any one of claims 50-64, wherein plurality of objects comprise gaze-contingent occluding stimuli overlaid on top of the plurality of objects.

66. The non-transitory computer readable storage medium according to any one of claims 49-65, wherein the OKR stimuli are presented on a stereoscopic display.

67. The non-transitory computer readable storage medium of any one of claims 49-66, wherein the OKR stimuli are presented on an immersive environment display.

68. The non-transitory computer readable storage medium according to any one of claims 49-67, wherein the OKR stimuli are presented in virtual reality (VR).

69. The non-transitory computer readable storage medium according to claim 68, wherein the OKR stimuli are presented using a virtual reality (VR) headset.

70. The non-transitory computer readable storage medium according to of any one of claims 49-69, wherein algorithm for tracking eye movement of the subject comprises: algorithm for illuminating eyes of the subject with infrared light; and algorithm for capturing a plurality of images of the eyes of the subject using a camera.71 . The non-transitory computer readable storage medium according to claim 70, wherein the algorithm for capturing comprises algorithm for capturing images at a rate of 50 Hz or faster.

72. The non-transitory computer readable storage medium according to claims 70 or 71 , wherein the algorithm for tracking further comprises algorithm for detecting a gaze point in the plurality of images.

73. The non-transitory computer readable storage medium according to any one of claims 70-72, wherein the camera is built into a VR headset.

74. The non-transitory computer readable storage medium according to any one of claims 49-73, the instructions stored thereon further comprising: algorithm for quantitatively assessing the OKR.

75. The non-transitory computer readable storage medium according to any one of claims 49-74, the instructions stored thereon further comprising: algorithm for calculating a gain between the stimulus movement and eye movement.

76. The non-transitory computer readable storage medium according to any one of claims 49-75, the instructions stored thereon further comprising: algorithm for identifying periods of blink and data loss.

77. The non-transitory computer readable storage medium according to any one of claims 49-76, the instructions stored thereon further comprising: algorithm for identifying saccades.

78. The non-transitory computer readable storage medium according to any one of claims 49-77, the instructions stored thereon further comprising: algorithm for generating a reflexive vision score.

79. The non-transitory computer readable storage medium according to claim78, wherein the reflexive vision score is an age-adjusted reflexive vision score.

80. The non-transitory computer readable storage medium according to claim79, the instructions stored thereon further comprising: algorithm for quantifying whether the age-adjusted reflexive vision score is below an age-adjusted mean.81 . The non-transitory computer readable storage medium according to claim80, wherein the age-adjusted reflexive vision score is two standard deviations or more below an age-adjusted mean.

82. The non-transitory computer readable storage medium according to any one of claims 49-81 , the instructions stored thereon further comprising: algorithm for comparing the OKR of the subject to a conscious visual perception task of the subject.

83. The non-transitory computer readable storage medium according to any one of claims 49-82, the instructions stored thereon further comprising: algorithm for comparing the OKR of the subject to retinal imaging results of the subject.

84. The non-transitory computer readable storage medium according to claim83, wherein the retinal imaging results are adaptive optics imaging results.

85. The non-transitory computer readable storage medium according to claim49, the instructions stored thereon further comprising: algorithm for determining potential clinical interpretations of retinal health based on the OKR.

86. The non-transitory computer readable storage medium according to claim49, the instructions stored thereon further comprising: algorithm for determining potential clinical interpretations of retinal degeneration based on the OKR.

87. A system for assessing optokinetic reflex of a subject, the system comprising: a display, wherein the display is configured to: present optokinetic reflex (OKR) stimuli to a subject; and an eye-tracking unit, wherein the eye-tracking unit is configured to: track eye movement of the subject in response to the OKR stimuli.

88. The system according to claim 87, further comprising a virtual reality (VR) system comprising: the display; and the eye-tracking unit.

89. The system according to claim 88, wherein the virtual reality (VR) system comprises a virtual reality (VR) headset.

90. The system according to any one of claims 87-89, the system further comprising:a processor comprising memory operably coupled to the processor wherein the memory comprises instructions stored thereon, which when executed by the processor, cause the processor to: receive data representing the tracked eye movement; and assess the OKR of the subject based on the tracked eye movement data.

Images