Background: Understanding factors that contribute to posterior capsular opacification (PCO) development is a significant public concern as treatment can lead to complications. In order to prevent PCO, a better understanding of intraocular lens (IOL) characteristics, including design and material, and patient interaction is required. Herein, we performed a retrospective multivariable analysis to determine which factors (IOL and patient based) were least likely to result in PCO.
Methods: One hundred eighty post-mortem eyes with implanted IOLs were collected from the Minnesota Eye Bank, along with clinical history, including date of cataract surgery and IOL model number. The capsular bag (CB) with the IOL implant was removed from all eyes to obtain digital images. PCO outcome was quantified on CB images using an objective, automated custom image analyzer (Medical Parachute Automated Detector Opacification Software). The software measured intensity and area of the opacification within the IOL optic edge, intra-optic edge (IOE = intensity/area), and in Soemmering’s ring (SR = intensity/area). Epidemiologic analysis assessed which IOL characteristics and patient-related factors correlated with PCO. IOL factors included material, edge design, lens filter, company, IOL model, decentration and time from cataract surgery to death. Patient factors included sex, age and diabetes, among others.
Results: Multivariate analyses showed non-diabetic patients had less PCO (P=0.05). Individuals 50–80 years old compared to 80+ had lower SR PCO (P=0.04). Non-blue light filter IOLs had lower SR and IOE PCO compared to filter IOLs (P=0.03, 0.001). Square and frosted optic edge design had lower SR and IOE PCO rates compared to OptiEdge and round optic edge design (P=0.002, 0.02). The IOL model that had the least PCO was the ZA9003 model, but this was only significant for SR and not IOE PCO (P=0.04). Adjusting for patient-factors, IOL lens model was no longer a confounding factor for PCO. Patients with an IOL implanted for <7 years had lower SR PCO, whereas lower IOE PCO was only seen in implants <4 years old (P=0.0001, 0.04).
Conclusions: In order to generate a lens that does not develop PCO, it is critical to understand the IOL- and patient-related factors that lead to PCO development. Based on our data, the most susceptible patients are elderly and diabetic, and it may be preferable to implant a square and frosted edge lens without blue-light filtering in this cohort.
Background: The guiding principle of functional brain mapping is that the cortex exhibits a spatial pattern of response reflecting its underlying functional organization. We know that large-scale patterns are common across individuals—everyone roughly has the same visual areas for example, but we do not know about small patterns, like the distribution of ocular dominance and orientation columns. Studies investigating the temporal aspect of brain-to-brain similarity have shown that a large portion of the brain is temporally synchronized across subjects (Hasson et al., 2004), but spatial pattern similarity has been scarcely studied, let alone at a fine scale. In the current study, we investigated fine-scale spatial pattern similarity between subjects during movie viewing and generated a map of prototypical patterns spanning the visual system. Characteristics of the map, such as spatial pattern size and distribution, reveal properties of the underlying structure and organisation of the visual cortex. These results will guide future brain mapping studies in decoding the informative spatial patterns of the visual cortex and increasing the resolution of current brain maps.
Methods: We had 56 subjects watch two movie clips from “Under the Sea 3D:IMAX” during an fMRI scan. Each clip was 5 minutes in length and was presented in 2D and 3D, in random order. We calculated the intersubject correlation of the spatial pattern inside predefined searchlights of diameter 3, 5, 7, 9 and 11 mm, covering the entire brain. A single threshold permutations test was used to test for significance: we generated 1,000 permutations made from scrambling the spatial patterns inside each searchlight of every subject, pooled these permutations together to generate a large distribution and used the 95th percentile to threshold the actual measurements. We compared these spatial pattern correlations to convexity variance between subjects to determine whether spatial pattern correlation could be explained by differing degrees of alignment across the cortex. We also compared spatial pattern correlation during 2D and 3D movie presentation.
Results: We found significant correlations in spatial pattern between subjects in the majority of early visual cortex, as well as higher visual areas. We found that mean spatial pattern similarity in a visual area tended to decrease as we move up the visual hierarchy. Spatial pattern correlation showed significant positive correlation with convexity variance for most visual areas, meaning that as anatomical misalignment increased, patterns became more similar. Spatial pattern correlation therefore cannot be explained by anatomical misalignment. Lastly, spatial pattern correlations tended to be higher for 3D movie presentation compared to 2D.
Conclusions: Our results suggest that many processes in early visual areas and even higher visual areas process visual information the same way in different individuals. Our results expand past studies by exploring spatial patterns instead of temporal patterns and studying at a fine-scale. This is the first study, to our knowledge, exploring fine-scale spatial patterns across the visual system. Our results show that fine-scale structures underlying activation patterns may be highly similar across subjects, pointing to a more ingrained organisation of the visual system than previously believed. This map we termed the “protoSPACE map”, may one day result in the detection of more subtle abnormalities that arise only during realistic vision in situations such as schizophrenia or mild traumatic brain injury, where traditional anatomical MRI scans report no changes.
Background: Stereoscopic Vision uses the disparity between the two images received by the two eyes in order to create a tridimensional representation. With this study, we aimed at providing an estimate of binocular vision at a level prior to disparity processing. In particular, we wanted to assess the spatial properties of the visual system for detecting interocular correlations (IOC).
Methods: We developed dichoptic stimuli, made of textures which IOC is sinusoidally modulated at various correlation spatial frequencies. Then, we compared the sensitivity to these stimuli to the sensitivity to analogous stimuli with disparity modulation.
Results: We observed that IOC sensitivity presents a low-pass/band-pass profile and increases as a function of presentation duration and contrast, in a similar way as disparity sensitivity.
Conclusions: IOC sensitivity is weakly—though significantly—correlated with disparity sensitivity in the general population, which suggests that it could provide a marker for binocular vision, prior to disparity processing.
Background: Cognitive control is defined as the ability to act flexibly in the environment by either behaving automatically or inhibiting said automatic behaviour and it can be measured using an interleaved pro/anti-saccade task. Decline in cognitive control has been attributed to normal aging and neurological illnesses such as Parkinson’s disease (PD) as well as decline in other cognitive abilities. This parallel might highlight the role played by cognitive control in information processing and working memory. However, little is known about the relationship between cognitive control and other cognitive processes such as visual memory, decision making, and visual search. We thus propose to correlate the incidence of impaired cognitive control with deficits in visual memory, decision making and visual search in three groups: younger adults, older adults and patients with idiopathic PD.
Methods: Seventy-one participants, namely 34 adults (M =22.75, SD =3.8), 22 older adults (M =67.4, SD =8.3), and 20 PD patients (M =65.59, SD =8.2) performed four tasks: interleaved pro/anti-saccade, visual memory, decision making, and serial and pop-out visual search.
Results: Results show that within each group, anti-saccade error rate (ER) were significantly and negatively correlated with visual memory ER (ryounger =?0.378, P=0.036; rolder =?0.440, Polder =0.046; rPD =?0.609, P=0.016). On the other hand, correct decision-making reaction times (RT) were significantly correlated with anti-saccade ER, and RTs only in older adults (rER =0.529, P=0.014; rRT =0.512, P=0.018) and PD patients (rER =0.727, P=0.012; rRT =0.769, P=0.001). For visual search, PD patients showed a significant relationship between RTs for correct pro-saccades and pop-out (r=0.665, P=0.007), and serial (r=0.641, P=0.010) search RTs. Furthermore, there was a significant correlation between MoCA scores and anti-saccade RTs (r=?0.559, P=0.030) and ER (r=?0.562, P=0.029) in PD patients. Taken together, these results support the hypothesis of PD patients’ reliance on bottom-up processes as top-down processes decline. For younger adults, there was a significant correlation between serial search performance and both anti-saccade ER (r=0.488, P=0.005), and correct pro-saccade ER (r=0.413, P=0.021). In older adults, this relationship was absent, but anti-saccade ER significantly correlated with pop-out search times (r=0.473, P=0.030).
Conclusions: We found significant relationships between cognitive tasks and cognitive control as measured through the interleaved pro/anti-saccade task across and within participant groups, providing evidence of the appropriateness of the use of the interleaved pro/anti-saccade task as a measure of overall cognitive control.
Background: Understanding how individuals with autism spectrum disorder (ASD) learn is important for developing and implementing effective educational and behavioral interventions. Evidence suggests that individuals with ASD are relatively stronger in certain areas of perception (Simmons et al., 2009; Dakin and Frith, 2005); it therefore cannot be assumed that individuals with ASD learn using the same rules and strategies as neurotypicals (NT). Of particular interest, perceptual learning (PL) is a class of learning that is based upon changes induced by the repeated exposure and response to specific types of perceptual information. Such learning often includes feedback, indicating whether or not a response was correct during a trial within a PL task. The objectives of this study were to perform a pilot investigation of; (I) perceptual learning in adults with and without ASD using a low-level orientation discrimination task; and (II) the influence of feedback on accuracy in this task.
Methods: Eleven adults with ASD and fifteen NT adults, matched on Wechsler full-scale IQ and age (18–31 years), performed a low-level PL task. They were asked to indicate whether a grating was tilted to the left (i.e., counter-clockwise) or to the right (i.e., clockwise) relative to an oblique 45-degree reference orientation. Thresholds, defined by the minimal deviation in degrees needed to discriminate tilt orientation, were measured for each participant every 15 minutes, with each block consisting of 420 trials. To assess baseline performance, all participants completed a first block with no feedback. Participants were then randomly assigned to either feedback (NASD =6, NTD =8) or no feedback groups (NASD =5, NTD =7) and completed six subsequent testing blocks.
Results: PL was defined as the percent change in orientation discrimination threshold in each of the six testing blocks relative to baseline performance. No significant increase was found in performance as a function of testing block for any group; PL was therefore not evidenced under the conditions tested. ASD performance remained equal to that of baseline across testing blocks, whether or not trial-by-trial feedback was present. In contrast, NT performance was significantly increased when feedback was present.
Conclusions: NT individuals significantly benefited from feedback, while individuals with ASD did not. These results provide preliminary evidence for a divergent learning style in ASD and NT individuals. These pilot findings raise important questions regarding the impact of feedback during interventions, and at a more basic level, the atypical underlying perceptual and cognitive processes in individuals with ASD.
Background: Perceptual profiles, or the performance on visual-perceptual tasks that reflect early visual information processing, have been used to suggest condition-specific visuo-perceptual abilities across neurodevelopmental conditions (NDCs). The complexity-specific hypothesis (Bertone et al., 2010) was based on perceptual profiles defined by a selective decrease in sensitivity to more complex, texture-defined information in adults with autism and fragile-x syndrome, suggesting the atypical development of neural networks underlying early perception in NDCs. The aim of this study was to evaluate whether the complexity-specific hypothesis is applicable to children and adolescents with different NDCs by defining and comparing their perceptual profiles.
Methods: A single interval, two alternative forced-choice identification paradigm was used to measure the perceptual profiles of 64 participants with a NDC (MIQ =78) and 43 typically developing (TD) participants (MIQ =103), aged 5 to 17 years. Participants with a NDC were diagnosed with either: autism spectrum disorder (ASD, n=32), attention deficit/hyperactivity disorder (ADHD, n=9), or intellectual disability (ID, n=12). Perceptual profiles were defined by measuring participants’ sensitivity to static (orientation identification task) and dynamic (direction identification task) gratings (1 cpd) defined by either luminance (simple) or texture (complex) information. The Weschler Abbreviated Scale of Intelligence 2 (WASI-2) was used as a measure of cognitive ability.
Results: When performance was averaged across NDC and TD participants, no between-group difference in sensitivity was found for any of the conditions assessed. However, when assessed as a function of diagnosis, we found that the ID group was less sensitive to both the luminance (P=0.04) and texture-defined (P=0.01) dynamic information when compared to the TD group. Notably, although the perceptual profile of the ASD group was similar of that of the TD group, a significant positive relationship between mental age and sensitivity to both texture-defined static (r=?0.5) and dynamic (r=?0.4) information was found.
Conclusions: The ?ndings demonstrate that different conditions-specific perceptual profiles exist across children and adolescents with different types of NDCs, exemplified by differences found in this study for the ID group. In addition, the positive relationship between perceptual performance and mental age within the ASD group suggests that these perceptual abilities may still be undergoing maturation during the age-range assessed, and provides support for the complexity-specific hypothesis specific to the ASD profile during development. These results exemplify the importance of defining perceptual profiles at different periods of development across NDCs, since the tenets of most perceptually-relevant cognitive theories are based primarily on adult data.
Background: It has been suggested that adaptation to texture density only ever reduces, i.e., never increases, perceived density, implying that density adaptation is ‘uni-directional’ and that texture density is coded as a scalar attribute (Durgin & Huk, 1997). However, we have recently shown that simultaneous density contrast, which describes the effect of a surround texture on the perceived density of a centre region, is ‘bi-directional’—that is, not only do denser surrounds reduce perceived density of the center but sparser surrounds enhance it (Sun, Baker, & Kingdom, 2016). Therefore, we decided to re-examine the directionality of density adaptation.
Methods: We measured the density aftereffect in random dot patterns using a 2AFC matching procedure that established a point-of-subjective-equality (PSE) between an adapted test patch and an unadapted match patch. The adaptors and test were presented at the same position, either at top left or bottom right of the fixation. The match was presented at bottom left or top right correspondingly. These positions were fixed within a block and switched between blocks. Then, using sequential presentation, we measured the density aftereffect for a wide range of adaptor and test densities.
Results: In the first experiment, we observed a unidirectional density aftereffect when test and match were presented simultaneously as in previous studies. However, when they were presented sequentially, bidirectionality was obtained. This bidirectional aftereffect remained when the presentation order of test and match was reversed (second experiment). In the third experiment, we used sequential presentation to measure the density aftereffect for a wide range of adaptor densities (0–73 dots/deg2) and test densities (1.6, 6.4, and 25.6 dots/deg2). We found bidirectionality for all combinations of adaptor and test densities, consistent with our previous SDC results.
Conclusions: In three experiments, we found that density adaptation is bidirectional when the test and match stimuli are presented sequentially. The unidirectional density adaptation reported in previous studies might have been due to effects arising from simultaneous presentation of test and match stimuli. Our evidence again supports the idea that there are density-selective channels in the visual system in line with our previous finding in SDC.
Background: Short-term monocular deprivation has been recently shown to temporarily increase the sensitivity of the patched eye. Many studies have patched subjects for an arbitrary period of 2.5 hours, but for no principled reason. Our goal is to show a relationship, if any, between the length of patching duration and the strength of its effect.
Methods: We tested nine subjects with three different patching durations: 1-, 2-, 3-hour. Four of the nine subjects were patched for 5-hour. Monocular deprivation was achieved by the use of a translucent eyepatch. A session included two rounds of baseline testing of interocular eye balance, patching, and post-patching tests. Each post-patching test occurred at 0, 3, 6, 12, 24, 48, 60 and 96 minutes after patching to track the patching effect over time. Every subject performed two sessions per condition.
Results: One-hour patching produced a small shift in ocular dominance. A larger shift occurred from 2-hour patching, but 3-hour patching produced a comparable effect to the one measured after 2-hour patching.
Conclusions: These results show a saturation of the patching effect beyond 2-hour patching. Hence, we believe that 2-hour patching duration is the optimal duration for eye dominance changes induced by monocular deprivation.
Background: Visual salience computed using algorithmic procedures have been shown to predict eye-movements in a number of contexts. However, despite calls to incorporate computationally-defined visual salience metrics as a means of assessing the effectiveness of advertisements, few studies have incorporated these techniques in a marketing context. The present study sought to determine the impact of visual salience and knowledge of a brand on eye-movement patterns and buying preferences.
Methods: Participants (N=38) were presented with 54 pairs of products presented on the left and right sides of a blank white screen. For each pair, one product was a known North American product, such as Fresca?, and one was an unknown British product of the same category, such as Irn Bru?. Participants were asked to select which product they would prefer to buy while their eye movements were recorded. Salience was computed using Itti & Koch’s [2001] computational model of bottom-up salience. Products were defined as highly salient if the majority of the first five predicted fixations were in the region of the product.
Results: Results showed that participants were much more likely to prefer to buy known products, and tentative evidence suggests that participants had longer total dwell times when looking at unknown products. Salience appears to have had little or no effect on preference for a product, nor did it predict total dwell time or time to first fixation. There also appears to be no interaction between knowledge of a product and visual salience on any of the measures analyzed.
Conclusions: The results indicate that product salience may not be a useful predictor of attention under the constraints of the present experiment. Future studies could use a different operational definition of visual salience which might be more predictive of visual attention. Furthermore, a more fine-grained analysis of product familiarity based on survey data may reveal patterns obscured by the definitional constraints of the present study.
