Contrast is the differential luminance between one object and another. Contrast sensitivity (CS) quantifies the ability to detect this difference: estimating contrast threshold provides information about the quality of vision and helps diagnose and monitor eye diseases. High contrast visual acuity assessment is traditionally performed in the eye care practice, whereas the estimate of the discrimination of low contrast targets, an important complementary task for the perception of details, is far less employed. An example is driving when the contrast between vehicles, obstacles, pedestrians, and the background is reduced by fog. Many conditions can selectively degrade CS, while visual acuity remains intact. In addition to spatial CS, “temporal” CS is defined as the ability to discriminate luminance differences in the temporal domain, i.e., to discriminate information that reaches the visual cortex as a function of time. Likewise, temporal sensitivity of the visual system can be investigated in terms of critical fusion frequency (CFF), an indicator of the integrity of the magnocellular system that is responsible for the perception of transient stimulations. As a matter of fact, temporal resolution can be abnormal in neuro-ophthalmological clinical conditions. This paper aims at considering CS and its application to the clinical practice.
Perception is the ability to see, hear, or become aware of external stimuli through the senses. Visual stimuli are electromagnetic waves that interact with the eye and elicit a sensation. Sensations, indeed, imply the detection, resolution, and recognition of objects and images, and their accuracy depends on the integrity of the visual system. In clinical practice, evaluating the integrity of the visual system relies greatly on the assessment of visual acuity, that is to say on the capacity to identify a signal. Visual acuity, indeed, is of utmost importance for diagnosing and monitoring ophthalmological diseases. Visual acuity is a function that detects the presence of a stimulation (a signal) and resolves its detail(s). This is the case of a symbol like “E”: the stimulus is detected, then it is resolved as three horizontal bars and a vertical bar. In fact, within the clinical setting visual acuity is usually measured with alphanumeric symbols and is a three-step process that involves not only detection and resolution, but, due to the semantic content of letters and numbers, their recognition. Along with subjective (psychophysical) procedures, objective methods that do not require the active participation of the observer have been proposed to estimate visual acuity in non-collaborating subjects, malingerers, or toddlers. This paper aims to explain the psychophysical rationale underlying the measurement of visual acuity and revise the most common procedures used for its assessment.
Abstract: Program accreditation is usually a voluntary process based on published standards and performed by a governmental or non-governmental agency of peers. The accreditation process has several components: self-assessment guide completion, site visit and review of program data by the accrediting body. Program accreditation’s primary function is to facilitate self-assessment, provide standards of education and lead to program improvement. It also serves to protect the student’s education and ultimately improve patient care. The International Council of Ophthalmology has developed International Guidelines for accreditation of ophthalmology residency programs and is launching a pilot program to accredit programs on demand.
Background: With a large portion of older adults living longer, the number of individuals diagnosed with low vision is increasing. The use of optical coherence tomography/scanning laser ophthalmoscope (OCT/SLO) to diagnose retinal disease has become common place in the last 10 years, yet currently there are no OCT/SLO databases for pathological vision. Our aim is to develop a clinical database of individuals who have drusen (i.e., lipid deposits found under the retina), or have been diagnosed with age-related macular degeneration (AMD), with information as to how the structure of the diseased retina changes over time, as well as measures of visual and cognitive functional performance.
Methods: Fundus photographs and retinal scans will be taken using the same model of optos OCT/SLO located in three test sites (MAB-Mackay Rehabilitation Centre, School of Optometry Clinic at the University of Montreal, and the Lighthouse Institute, New York, USA). For each individual entry in the database, demographic and diagnosis information will be available. All OCT/SLO images will be graded according to the Age-related Eye Disease Study standard, in addition to number and size of drusen, severity of geographic atrophy, severity of pigment mottling and presence of choroidal neovascularization. Retinal topography and Raster scans from the OCT/SLO will provide a cross-sectional look at affected retinas. Fixation stability will be recorded using the SLO function, and present four different tasks that are designed to reproduce typical tasks of daily vision, with each task lasting for 10 seconds. The tasks are cross fixation, face recognition, visual search, and reading. These tasks in addition to the retinal scans will be used to determine the eccentricity of a preferred retinal locus from the anatomical fovea, and can be used as an outcome measure for clinical interventions in visually impaired patients.
Results: The database will be available to professors training eye-care practitioners and rehabilitation specialists as a teaching tool. Students will be able to familiarize themselves with the retina and a variety of AMD-related pathologies before they start working with patients. The database will also be accessible by researchers interested in studying AMD from basic science to epidemiology, to investigate how drusen and AMD impact visual and cognitive functional performance.
Conclusions: The common infrastructure is easily accessible to all VHRN members on request. The database will also be accessible online in 2018 (see http://cvl.concordia.ca for more information).
Background: Visual deficits, caused by ocular disease or trauma to the visual system, can cause lasting damage with insufficient treatment options available. However, recent research has focused on neural plasticity as a means to regain visual abilities. In order to better understand the involvement of neural plasticity and reorganization in partial vision restoration, we aim to evaluate the partial recovery of a visual deficit over time using three behavioural tests. In our study, a partial optic nerve crush (ONC) serves as an induced visual deficit, allowing for residual vision from surviving cells.
Methods: Three behavioural tests—optokinetic reflex, object recognition, and visual cliff—were conducted in 9 mice prior to a bilateral, partial ONC, then 1, 3, 7, 14, 21, and 28 days after the ONC. The optokinetic reflex test measured the tracking reflex in response to moving sinusoidal gratings. These gratings increase in spatial frequency until a reflex is no longer observed, i.e., a visual acuity threshold is reached. The object recognition test examines the animal’s exploratory behaviour in its capacity to distinguish high versus low contrast objects. The visual cliff test also evaluates exploratory behaviour, by simulating a cliff to observe the animal’s sense of depth perception. All three tests provide an estimate of the rodent’s visual abilities at different levels of the visual pathway.
Results: The partial optic nerve crush resulted in a total loss of visual acuity as measured by the optokinetic reflex. The deficit did not show improvement during the 4 following weeks. Despite the visual cliff test showing a non-significant decrease in deep end preference 1-day post ONC, though this was not the case for subsequent test occasions. The object recognition test showed no significant trends.
Conclusions: In conclusion, the optokinetic reflex test showed a significant loss of function following the visual deficit, but no recovery. However, a complimentary pilot study shows visual recovery using lighter crush intensities. The spatial visual function does not seem to be affected by the ONC, suggesting that the object recognition and visual cliff tests, in their current design, may rely on somatosensory means of exploration.
Background: The perception of visual forms is crucial for effective interactions with our environment and for the recognition of visual objects. Thus, to determine the codes underlying this function is a fundamental theoretical objective in the study of the visual forms perception. The vast majority of research in the field is based on a hypothetico-deductive approach. Thus, we first begin by formulating a theory, then we make predictions and finally we conduct experimental tests. After decades of application of this approach, the field remains far from having a consensus as to the traits underlying the representation of visual form. Our goal is to determine, without theoretical a priori or any bias whatsoever, the information underlying the discrimination and recognition of 3D visual forms in normal human adults.
Methods: To this end, the adaptive bubble technique developed by Wang et al. [2011] is applied on six 3D synthetic objects under varying views from one test to another. This technique is based on the presentation of stimuli that are partially revealed through Gaussian windows, the location of which is random and the number of which is established in such a way as to maintain an established performance criterion. Gradually, the experimental program uses participants’ performance to determine the stimulus regions that participants use to recognize objects. The synthetic objects used in this study are unfamiliar and were generated from a program produced at C. Edward Connor’s lab, Johns Hopkins University School of Medicine.
Results: The results were integrated across participants to establish regions of presented stimuli that determine the observers’ ability to recognize them—i.e., diagnostic attributes. The results will be reported in graphical form with a Z scores mapping that will be superimposed on silhouettes of the objects presented during the experiment. This mapping makes it possible to quantify the importance of the different regions on the visible surface of an object for its recognition by the participants.
Conclusions: The diagnostic attributes that have been identified are the best described in terms of surface fragments. Some of these fragments are located on or near the outer edge of the stimulus while others are relatively distant. The overlap is minimal between the effective attributes for the different points of view of the same object. This suggests that the traits underlying the recognition of objects are specific to the point of view. In other words, they do not generalize through the points of view.
