Characterization of field loss based on microperimetry is predictive of face recognition difficulties

Effect of low luminance on face recognition in adults with central and peripheral vision loss

PURPOSE

To investigate the effect of low luminance on face recognition, specifically facial identity discrimination (FID) and facial expression recognition (FER), in adults with central vision loss (CVL) and peripheral vision loss (PVL) and to explore the association between clinical vision measures and low luminance FID and FER.

METHODS

Participants included 33 adults with CVL, 17 with PVL and 20 controls. FID and FER were assessed under photopic and low luminance conditions. For the FID task, 12 sets of three faces with neutral expressions were presented and participants asked to indicate the odd-face-out. For FER, 12 single faces were presented and participants asked to name the expression (neutral, happy or angry). Photopic and low luminance visual acuity (VA) and contrast sensitivity (CS) were recorded for all participants and for the PVL group, Humphrey Field Analyzer (HFA) 24-2 mean deviation (MD).

RESULTS

FID accuracy in CVL, and to a lesser extent PVL, was reduced under low compared with photopic luminance (mean reduction 20% and 8% respectively; p < 0.001). FER accuracy was reduced only in CVL (mean reduction 25%; p < 0.001). For both CVL and PVL, low luminance and photopic VA and CS were moderately to strongly correlated with low luminance FID (ρ = 0.61-0.77, p < 0.05). For PVL, better eye HFA 24-2 MD was moderately correlated with low luminance FID (ρ = 0.54, p = 0.02). Results were similar for low luminance FER. Together, photopic VA and CS explained 75% of the variance in low luminance FID, and photopic VA explained 61% of the variance in low luminance FER. Low luminance vision measures explained little additional variance.

CONCLUSION

Low luminance significantly reduced face recognition, particularly for adults with CVL. Worse VA and CS were associated with reduced face recognition. Clinically, photopic VA is a good predictor of face recognition under low luminance conditions.

Luminance Contrast of Accessible Tactile Indicators for People With Visual Impairment

Australia is one of only two known countries with a safety standard specifying levels of contrast required to provide accessible environments for people with visual impairment. However, these requirements were not developed based on empirical research involving people with vision loss. We investigated whether the level of luminance contrast in Australian accessibility standards, 30%, is adequate for people with visual impairments to detect and identify discrete tactile ground surface indicators over a range of contrasts with the background flooring before contact. We found that the 30% luminance contrast is adequate for people with low vision, although they preferred higher contrast.

The Accessibility of Commercial Off-The-Shelf Virtual Reality for Low Vision Users: A Macular Degeneration Case Study

Virtual reality (VR) is demonstrating increasing potential for therapeutic benefit in elderly care, but it is still generally considered to be the domain of the visually unimpaired. Even where VR and augmented reality (AR) are being explored for use with low vision, it is generally with a focus on creating bespoke software and hardware. However, the properties of commercial off-the-shelf (COTS) headsets, such as high luminance, may render them accessible even to very low vision users. Using a case-study approach, we explored the differences in visual perception from baseline to pass-through AR and commercial VR applications for an elderly female (Mrs. M) with advanced age-related macular degeneration. We found notable improvements in object, face, and color recognition, particularly with higher display brightness. Furthermore, Mrs. M was able to engage fully and enthusiastically with a number of (unmodified) VR applications, providing detailed descriptions of both static and moving elements. We suggest that the high luminance available in COTS VR may support more stable fixation closer to the fovea, improving visual resolution. Furthermore, the improvements we noted in color perception support previous suggestions that increasing luminance may improve photosensitivity by reducing the uptake of limited oxygen by the rod cells. We conclude that low vision should not automatically preclude users from engaging in VR research or entertainment, and that they may be able to use well-illuminated VR applications without any special modifications.

On the particular vulnerability of face recognition to aging: a review of three hypotheses

Age-related face recognition deficits are characterized by high false alarms to unfamiliar faces, are not as pronounced for other complex stimuli, and are only partially related to general age-related impairments in cognition. This paper reviews some of the underlying processes likely to be implicated in theses deficits by focusing on areas where contradictions abound as a means to highlight avenues for future research. Research pertaining to the three following hypotheses is presented: (i) perceptual deterioration, (ii) encoding of configural information, and (iii) difficulties in recollecting contextual information. The evidence surveyed provides support for the idea that all three factors are likely to contribute, under certain conditions, to the deficits in face recognition seen in older adults. We discuss how these different factors might interact in the context of a generic framework of the different stages implicated in face recognition. Several suggestions for future investigations are outlined.

A framework for streamlining research workflow in neuroscience and psychology

Successful accumulation of knowledge is critically dependent on the ability to verify and replicate every part of scientific conduct. However, such principles are difficult to enact when researchers continue to resort on ad-hoc workflows and with poorly maintained code base. In this paper I examine the needs of neuroscience and psychology community, and introduce psychopy_ext, a unifying framework that seamlessly integrates popular experiment building, analysis and manuscript preparation tools by choosing reasonable defaults and implementing relatively rigid patterns of workflow. This structure allows for automation of multiple tasks, such as generated user interfaces, unit testing, control analyses of stimuli, single-command access to descriptive statistics, and publication quality plotting. Taken together, psychopy_ext opens an exciting possibility for a faster, more robust code development and collaboration for researchers.