Aims: To profile site of stroke/cerebrovascular accident, type and extent of field loss, treatment options, and outcome.
Methods: Prospective multicentre cohort trial. Standardised referral and investigation protocol of visual parameters.
Results: 915 patients were recruited with a mean age of 69 years (SD 14). 479 patients (52%) had visual field loss. 51 patients (10%) had no visual symptoms. Almost half of symptomatic patients (n = 226) complained only of visual field loss: almost half (n = 226) also had reading difficulty, blurred vision, diplopia, and perceptual difficulties. 31% (n = 151) had visual field loss as their only visual impairment: 69% (n = 328) had low vision, eye movement deficits, or visual perceptual difficulties. Occipital and parietal lobe strokes most commonly caused visual field loss. Treatment options included visual search training, visual awareness, typoscopes, substitutive prisms, low vision aids, refraction, and occlusive patches. At followup 15 patients (7.5%) had full recovery, 78 (39%) had improvement, and 104 (52%) had no recovery. Two patients (1%) had further decline of visual field. Patients with visual field loss had lower quality of life scores than stroke patients without visual impairment.
Conclusions: Stroke survivors with visual field loss require assessment to accurately define type and extent of loss, diagnose coexistent visual impairments, and offer targeted treatment.
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http://dx.doi.org/10.1155/2013/719096 | DOI Listing |
Vision Res
January 2025
Department of Psychology, University of Nevada, Reno, NV 89557, United States.
A neural theory of human lightness computation is described and computer-simulated. The theory proposes that lightness is derived from transient ON and OFF cell responses in the early visual pathways that have different characteristic neural gains and that are generated by fixational eye movements (FEMs) as the eyes transit luminance edges in the image. The ON and OFF responses are combined with corollary discharge signals that encode the eye movement direction to create directionally selective ON and OFF responses.
View Article and Find Full Text PDFNatl Sci Rev
January 2025
Key Laboratory of Precision and Intelligent Chemistry, University of Science and Technology of China, Hefei 230026, China.
Affordable high-resolution cameras and state-of-the-art computer vision techniques have led to the emergence of various vision-based tactile sensors. However, current vision-based tactile sensors mainly depend on geometric optics or marker tracking for tactile assessments, resulting in limited performance. To solve this dilemma, we introduce optical interference patterns as the visual representation of tactile information for flexible tactile sensors.
View Article and Find Full Text PDFVisual perception is characterized by known asymmetries in the visual field; human's visual sensitivity is higher along the horizontal than the vertical meridian, and along the lower than the upper vertical meridian. These asymmetries decrease with decreasing eccentricity from the periphery to the center of gaze, suggesting that they may be absent in the 1-deg foveola, the retinal region used to explore scenes at high-resolution. Using high-precision eyetracking and gaze-contingent display, allowing for accurate control over the stimulated foveolar location despite the continuous eye motion at fixation, we investigated fine visual discrimination at different isoeccentric locations across the foveola and parafovea.
View Article and Find Full Text PDFAdaptive optics scanning light ophthalmoscopy (AOSLO) enables high-resolution retinal imaging, eye tracking, and stimulus delivery in the living eye. AOSLO-mediated visual stimuli are created by temporally modulating the excitation light as it scans across the retina. As a result, each location within the field of view receives a brief flash of light during each scanner cycle (every 33-40 ms).
View Article and Find Full Text PDFNeuroimage
January 2025
Division of Arts and Sciences, NYU Shanghai, 567 West Yangsi Road, Pudong New District, 200124, Shanghai, China; Center for Neural Science, New York University, 4 Washington Place, NY, 10003, NY, USA; NYU-ECNU Institute of Brain and Cognitive Science, 3663 Zhongshan Road North, Putuo District, 200062, Shanghai, China. Electronic address:
BOLD response can be fitted using the population receptive field (PRF) model to reveal how visual input is represented on the cortex (Dumoulin and Wandell, 2008). Fitting the PRF model costs considerable time, often requiring days to analyze BOLD signals for a small cohort of subjects. We introduce the qPRF ("quick PRF"), a system for accelerated PRF modeling that reduced the computation time by a factor ¿1,000 without losing goodness-of-fit when compared to another widely available PRF modeling package (Kay et al.
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