The Curve Visible on the Campbell-Robson Chart Is Not the Contrast Sensitivity Function

NeuroCSF: an fMRI method to measure contrast sensitivity function in human visual cortex

The contrast sensitivity function (CSF) describes a range of spatial frequencies (SFs) that are detectable at a given level of contrast and is a very valuable tool both in clinical and fundamental research. However, despite its immense value, the full potential of the CSF has not been utilized in every aspect of clinical research due to time limits and patient factors. We propose neuroCSF as a new method for measuring the CSF across the visual field directly from brain activity and with minimal demand from participants. NeuroCSF is a computational model that estimates voxel-wise CSF parameters (i.e., peak contrast sensitivity, peak spatial frequency, and spatial frequency bandwidth) from functional magnetic resonance imaging (fMRI) signals under controlled visual stimulation conditions. The approach extends the population spatial frequency tuning (Aghajari S, Vinke LN, Ling S. J Neurophysiol 123: 773-785, 2020) and population receptive field (Dumoulin SO, Wandell BA. Neuroimage 39: 647-660, 2008) methods to provide the first characterization of a full CSF using neuroimaging. We observe that across early visual areas (V1, V2, and V3), the CSF peak spatial frequency and spatial frequency cutoff are significantly higher for foveal eccentricity and decrease at parafoveal eccentricities. Conversely, SF bandwidth slowly increases with eccentricity, while peak contrast sensitivity remains constant with eccentricity for all early visual areas. Thus cortical CSF estimates vary systematically with eccentricity. The neuroCSF approach opens new perspectives for the study of cortical visual functions in various disorders where the CSF is impacted, such as amblyopia, traumatic brain injury, and multiple sclerosis.NEW & NOTEWORTHY We introduce neuroCSF, a novel functional magnetic resonance imaging (fMRI)-based method for estimating contrast sensitivity function (CSF) parameters across the visual field. This approach is the first to provide voxel-wise CSF measurements directly from brain activity, offering insights into spatial frequency tuning across visual areas. NeuroCSF has potential clinical applications for disorders affecting contrast sensitivity and visual field function, such as amblyopia and traumatic brain injury.

Assessment of visual function using mobile Apps

With the advances in smartphone and tablet screens, as well as their processing power and software, mobile apps have been developed reporting to assess visual function. This review assessed those mobile apps that have been evaluated in the scientific literature to measure visual acuity, reading metrics, contrast sensitivity, stereoacuity, colour vision and visual fields; these constitute just a small percentage of the total number of mobile apps reporting to measure these metrics available for tablets and smartphones. In general, research suggests that most of the mobile apps evaluated can accurately mimic most traditionally paper-based tests of visual function, benefitting from more even illumination from the backlit screen and aspects such as multiple tests and versions (to minimise memorisation) being available on the same equipment. Some also utilise the in-built device sensors to monitor aspects such as working distance and screen tilt. As the consequences of incorrectly recording visual function and using this to inform clinical management are serious, clinicians must check on the validity of a mobile app before adopting it as part of clinical practice.

2022 Glenn A. Fry Award lecture: Enhancing clinical assessment for improved ophthalmic management

ABSTRACT

Detailed clinical assessment is critical to allow sensitive evaluation of the eye and its management. As technology advances, these assessment techniques can be adapted and refined to improve the detection of pathological changes of ocular tissue and their impact on visual function. Enhancements in optical medical devices including spectacle, contact, and intraocular lenses have allowed for a better understanding of the mechanism and amelioration of presbyopia and myopia control. Advancements in imaging technology have enabled improved quantification of the tear film and ocular surface, informing diagnosis and treatment strategies. Miniaturized electronics, large processing power, and in-built sensors in smartphones and tablets capacitate more portable assessment tools for clinicians, facilitate self-monitoring and treatment compliance, and aid communication with patients. This article gives an overview of how technology has been used in many areas of eye care to improve assessments and treatment and provides a snapshot of some of my studies validating and using technology to inform better evidence-based patient management.

Contrast discrimination in images of natural scenes

Contrast discrimination determines the threshold contrast required to distinguish between two suprathreshold visual stimuli. It is typically measured using sine-wave gratings. We first present a modification to Barten's semi-mechanistic contrast discrimination model to account for spatial frequency effects and demonstrate how the model can successfully predict visual thresholds obtained from published classical contrast discrimination studies. Contrast discrimination functions are then measured from images of natural scenes, using a psychophysical paradigm based on that employed in our previous study of contrast detection sensitivity. The proposed discrimination model modification is shown to successfully predict discrimination thresholds for structurally very different types of natural image stimuli. A comparison of results shows that, for normal contrast levels in natural scene viewing, contextual contrast detection and discrimination are approximately the same and almost independent of spatial frequency within the range of 1-20 c/deg. At higher frequencies, both sensitivities decrease in magnitude due to optical limitations of the eye. The results are discussed in relation to current image quality models.

Stable abnormalities of contrast discrimination sensitivity in subthreshold depression: A longitudinal study

Subthreshold depression (StD), as a subclinical state, is highly prevalent and increases the risk for developing major depressive disorder (MDD). Although several studies have reported deficits of contrast sensitivity in MDD patients, it is unclear whether individuals with StD could demonstrate deficits of contrast sensitivity and whether the deficits could remain stable over time. Here we used a contrast discrimination task (a suprathreshold task) and a contrast detection task (a near-threshold task) to compare contrast sensitivity of the StD group with that of matched non-depressed controls. For each task, a spatial four-alternative forced-choice method and a psychophysical QUEST procedure were used to measure contrast discrimination threshold or contrast detection threshold. Participants performed an initial assessment and a follow-up assessment 4 months later. Compared to the non-depressed controls, individuals with StD demonstrated reduced contrast discrimination sensitivity, not only at the initial assessment but also at the follow-up assessment, indicating a stable abnormality. Contrast discrimination thresholds at the initial assessment did not predict changes of depression symptom severity over time. For contrast detection sensitivity, there was no significant difference between the StD group and non-depressed controls. We concluded that contrast discrimination testing might provide a trait-dependent biomarker for depression.