AB050.Neuronal response to visual contrast varies as function of the cortical layer

Background:For years,studies using several animal models have highlighted the predominant role of the primary visual area in visual information processing.Its six cortical layers have morphological,hodological and physiological differences,although their roles regarding the integration of visual contrast and the messages sent by the layers to other brain regions have been poorly explored.Given that cortical layers have distinct properties,this study aims to understand these differences and how they are affected by a changing visual contrast.Methods:A linear multi-channel electrode was placed in the primary visual cortex(V1)of the anesthetized mouse to record neuronal activity across the different cortical layers.The laminar position of the electrode was verified in real time by measuring the current source density(CSD)and the multi-unit activity(MUA),and confirmed post-mortem by histological analysis.Drifting gratings varying in contrast enabled the measurement of the firing rate of neurons throughout layers.We fitted this data to the Naka-Rushton equations,which generated the contrast response function(CRF)of neurons.Results:The analysis revealed that the baseline activity as well as the rate of change of neural discharges(the slope of the CRF)had a positive correlation across the cortical layers.In addition,we found a trend between the cortical position and the contrast evoking the semi-saturation of the activity.A significant difference in the maximum discharge rate was also found between layers II/III and IV,as well as between layers II/III and V.Conclusions:Since layers II/III and V process visual contrast differently,our results suggest that higher cortical visual areas,as well subcortical regions,receive different information regarding a change in visual contrast.Thus,a contrast may be processed differently throughout the different areas of the visual cortex.

AB052.A standardized quantification of the visual contrast response function

Background:All neurons of the visual system exhibit response to differences in luminance.This neural response to visual contrast,also known as the contrast response function(CRF),follows a characteristic sigmoid shape that can be fitted with the Naka-Rushton equation.Four parameters define the CRF,and they are often used in different visual research disciplines,since they describe selective variations of neural responses.As novel technologies have grown,the capacity to record thousands of neurons simultaneously brings new challenges:processing and robustly analyzing larger amounts of data to maximize the outcomes of our experimental measurements.Nevertheless,current guidelines to fit neural activity based on the Naka-Rushton equation have been poorly discussed in depth.In this study,we explore several methods of boundary-setting and least-square curve-fitting for the CRF in order to avoid the pitfalls of blind curve-fitting.Furthermore,we intend to provide recommendations for experimenters to better prepare a solid quantification of CRF parameters that also minimize the time of the data acquisition.For this purpose,we have created a simplified theoretical model of spike-response dynamics,in which the firing rate of neurons is generated by a Poisson process.The spike trains generated by the theoretical model depending on visual contrast intensities were then fitted with the Naka-Rushton equation.This allowed us to identify combinations of parameters that were more important to adjust before performing experiments,to optimize the precision and efficiency of curve fitting(e.g.,boundaries of CRF parameters,number of trials,number of contrast tested,metric of contrast used and the effect of including multi-unit spikes into a single CRF,among others).Several goodness-of-fit methods were also examined in order to achieve ideal fits.With this approach,it is possible to anticipate the minimal requirements to gather and analyze data in a more efficient way in order to build stronger functional models.Methods:Spike-trains were randomly generated following a Poisson distribution in order to draw both an underlying theoretical curve and an empirical one.Random noise was added to the fit to simulate empirical conditions.The correlation function was recreated on the simulated data and re-fit using the Naka-Rushton equation.The two curves were compared:the idea being to determine the most advantageous boundaries and conditions for the curve-fit to be optimal.Statistical analysis was performed on the data to determine those conditions for experiments.Experiments were then conducted to acquire data from mice and cats to verify the model.Results:Results were obtained successfully and a model was proposed to assess the goodness of the fit of the contrast response function.Various parametres and their influence of the model were tested.Other similar models were proposed and their performance was assessed and compared to the previous ones.The fit was optimized to give semi-strict guidelines for scientists to follow in order to maximize their efficiency while obtaining the contrast tuning of a neuron.Conclusions:The aim of the study was to assess the optimal testing parametres of the neuronal response to visual gratings with various luminance,also called the CRF.As technology gets more powerful and potent,one must make choices when experimenting.With a strong model,robust boundaries,and strong experimental conditioning,the best fit to a function can lead to more efficient analysis and stronger cognitive models.

Visual perception alterations in COVID-19:a preliminary study

AIM:To compare the visual perception(color and chromatic-achromatic contrast vision)of a small cohort of COVID-19 patients at the time of infection and after 6mo with that of a healthy population matched for sex and age.METHODS:A total of 25 patients(9 females,16 males,mean age:54±10y)with COVID-19 hospitalized in the COVID-19 Unit of the University Clinical Hospital of Valladolid were recruited for this preliminary study.Visual perception,as determined by monocular measurement of contrast sensitivity function(CSF)and color vision was assessed in each patient using the Optopad test.The results obtained were then compared with those of a sample of 16 age-and sex-matched healthy controls(5 females,11 males,mean age:50±6y)in which the same measurement procedure was repeated.Statistically significant differences between groups were assessed using the Mann-Whitney U test.Measurements were repeated after a minimum follow-up period of 6mo and statistically significant differences between the two time points in each group were assessed using the Wilcoxon signed rank test.RESULTS:Discrimination thresholds(color and chromatic-achromatic contrast vision)and their corresponding sensitivity,calculated as the inverse of the discrimination threshold,were evaluated.Analysis of the data revealed higher contrast threshold results(i.e.,worse contrast sensitivity)in the COVID-19 group than in the control group for all spatial frequencies studied in the Optopad-CSF achromatic test and most of the spatial frequencies studied in the Optopad-CSF chromatic test for the red-green and blue-yellow mechanisms.In addition,color threshold results in the COVID-19 group were also significantly higher(i.e.,worse color sensitivity)for almost all color mechanisms studied in the Optopad-Color test.At 6mo,most of the differences found between the groups were maintained despite COVID-19 recovery.CONCLUSION:The present results provide preliminary evidence that visual perception may be impaired in COVID-19,even when the infection has passed.Although further research is needed to determine the precise causes of this finding,analysis of CSF and color vision could provide valuable information on the visual impact of COVID-19.

Source Quantitative Identification by Reference-Based Cubic Blind Deconvolution Algorithm

The semi-blind deconvolution algorithm improves the separation accuracy by introducing reference information.However,the separation performance depends largely on the construction of reference signals.To improve the robustness of the semi-blind deconvolution algorithm to the reference signals and the convergence speed,the reference-based cubic blind deconvolution algorithm is proposed in this paper.The proposed algorithm can be combined with the contribution evaluation to provide trustworthy guidance for suppressing satellite micro-vibration.The normalized reference-based cubic contrast function is proposed and the validity of the new contrast function is theoretically proved.By deriving the optimal step size of gradient iteration under the new contrast function,we propose an efficient adaptive step optimization method.Furthermore,the contribution evaluation method based on vector projection is presented to implement the source contribution evaluation.Numerical simulation analysis is carried out to validate the availability and superiority of this method.Further tests given by the simulated satellite experiment and satellite ground experiment also confirm the effectiveness.The signals of control moment gyroscope and flywheel were extracted,respectively,and the contribution evaluation of vibration sources to the sensitive load area was realized.This research proposes a more accurate and robust algorithm for the source separation and provides an effective tool for the quantitative identification of the mechanical vibration sources.

Anisometropia magnitude and visual deficits in previously untreated anisometropic amblyopia

AIM:To assess the quantitative association between anisometropia magnitude(AM) and the losses of resolution and contrast sensitivity;and to exemplify how the function of fusion and stereopsis vary with AM in previously untreated anisometropic amblyopia. METHODS:A total of 57 patients with previously untreated anisometropic amblyopia without strabismus(range:8-35 years),were measured refractive error,best corrected visual acuity(BCVA),fusion and stereopsis,and 48 patients have completed contrast sensitivity function test.AM was determined by dioptric vector addition model,and the amblyopia depth was determined by the difference of BCVA in logMAR units between the amblyopic and fellow eyes.RESULTS:AM was significantly correlated with both amblyopia depth(Pearson R=0.728,P【0.001) and the inter-ocular difference of the area under the log contrast sensitivity function(AULCSF)(R=0.505,P【0.001).Depth of amblyopia and the inter-ocular difference of AULCSF was also significantly correlated(R=0.761,P【0.001).The more severity of amblyopia,the poorer levels of contrast sensitivity.Most pure anisometropes with AM was less than 3.0D retain fusion and some stereopsis,but when AM were more than 3.0D,especially for the anisometropes whose AM was more than 6.0D,fusion and stereopsis function were seriously impaired.CONCLUSION:In the patients with previously untreated anisometropic amblyopia,higher degree of anisometropia is significantly associated with deeper amblyopia,worse contrast sensitivity,fusion and stereopsis functions.

NEW VISUAL PERCEPTUAL POOLING STRATEGY FOR IMAGE QUALITY ASSESSMENT

Most of Image Quality Assessment (IQA) metrics consist of two processes. In the first process, quality map of image is measured locally. In the second process, the last quality score is converted from the quality map by using the pooling strategy. The first process had been made effective and significant progresses, while the second process was always done in simple ways. In the second process of the pooling strategy, the optimal perceptual pooling weights should be determined and computed according to Human Visual System (HVS). Thus, a reliable spatial pooling mathematical model based on HVS is an important issue worthy of study. In this paper, a new Visual Perceptual Pooling Strategy (VPPS) for IQA is presented based on contrast sensitivity and luminance sensitivity of HVS. Experimental results with the LIVE database show that the visual perceptual weights, obtained by the proposed pooling strategy, can effectively and significantly improve the performances of the IQA metrics with Mean Structural SIMilarity (MSSIM) or Phase Quantization Code (PQC). It is confirmed that the proposed VPPS demonstrates promising results for improving the performances of existing IQA metrics.

JPEG2000 COMPRESSION CODING USING HUMAN VISUAL SYSTEM MODEL

In order to apply the Human Visual System (HVS) model to JPEG2000 standard,several implementation alternatives are discussed and a new scheme of visual optimization isintroduced with modifying the slope of rate-distortion. The novelty is that the method of visual weighting is not lifting the coefficients in wavelet domain, but is complemented by code stream organization. It remains all the features of Embedded Block Coding with Optimized Truncation (EBCOT) such as resolution progressive, good robust for error bit spread and compatibility of lossless compression. Well performed than other methods, it keeps the shortest standard codestream and decompression time and owns the ability of VIsual Progressive (VIP) coding.

AB001.How to optimize the visual contrast response of cortical neurons

Background:In the visual system,one of the most explored neural behaviors is the response of cells to changes in visual contrast.This neural response to visual contrast,also known as the contrast response function(CRF),can be fitted with the Naka-Rushton equation(NRE).Assessing the CRF of many neurons at the same time is critical to establishing functional visual properties.However,maximizing the performance of neurons to fit the NRE,while minimizing their time acquisitions is a challenge.We present a method to accurately obtain reliable NRE fits from experimental data,that ensure a reasonable time of record acquisition.Methods:We simulated CRF of cortical neurons with a toy model based on the response of Poisson spike trains to varied levels of contrasts.We first tested whether mean values or the whole set of contrast responses fit better the NRE.Then,we analyzed what were the boundaries to optimize the fit of the NRE,and after we explore the consequences of fitting the NRE with single-or multi-units.With these outcomes,we varied experimental parameters such as the number of trials,number of input contrasts and length of time acquisition to calculate the errors of fitting CRFs.Those data sets that maximize the CRF fit but minimize the time of recording were selected.The selected data set was then evaluated in visual cortical neurons of anesthetized cats from areas 17,18 and 21a.Results:First,we found that is always better to fit the NRE with mean values rather than the whole set of points.Then,we noticed that either removing or imposing loose boundaries to the CRF parameters lead to an increase in the performance of the NRE fit.Afterward,we found that single units(SU)or assume multi-unit formed of several SUs(>30)adjusted considerably better the NRE fit.Finally,the experiments showed that specific sets of patterns(number of trials,number of input contrasts and length of time acquisition)satisfied our two constraints:minimize the error of the NRE fit while maximizing the acquisition time of recording.The most characteristic pattern was the one with 6 points,15 repetitions and 1 second of duration.However,cortical areas varied in the representation of the patterns.Conclusions:Theoretical simulations of many different sets of patterns and their following experimental validation suggest strongly that a particular set of patterns can satisfy the imposed constraints.With this approach,we provided a tool that allows an optimal design of stimuli to assess the CRF of large neuronal populations and guarantees the finest fit for each unit analyzed.

Comparison of ocular modulation transfer function determined by a ray-tracing aberrometer and a double-pass system in early cataract patients

Background The evaluation of retinal image quality in cataract eyes has gained importance and the clinical modulation transfer functions （MTF） can obtained by aberrometer and double pass （DP） system. This study aimed to compare MTF derived from a ray tracing aberrometer and a DP system in early cataractous and normal eyes. Methods There were 128 subjects with 61 control eyes and 67 eyes with early cataract defined according to the Lens Opacities Classification System II1. A laser ray-tracing wavefront aberrometer （iTrace） and a double pass （DP） system （OQAS） assessed ocular MTF for 6.0 mm pupil diameters following dilation. Areas under the MTF （AUMTF） and their correlations were analyzed. Stepwise multiple regression analysis assessed factors affecting the differences between iTrace- and OQAS-derived AUMTF for the early cataract group. Results For both early cataract and control groups, iTrace-derived MTFs were higher than OQAS-derived MTFs across a range of spatial frequencies （P 〈0.01）. No significant difference between the two groups occurred for iTrace-derived AUMTF, but the early cataract group had significantly smaller OQAS-derived AUMTF than did the control group （P 〈0.01）. AUMTF determined from both the techniques demonstrated significant correlations with nuclear opacities, higher-order aberrations （HOAs）, visual acuity, and contrast sensitivity functions, while the OQAS-derived AUMTF also demonstrated significant correlations with age and cortical opacity grade. The factors significantly affecting the difference between iTrace and OQAS AUMTF were root-mean-squared HOAs （standardized beta coefficient=-0.63, P 〈0.01） and age （standardized beta coefficient=0.26, P 〈0.01）. Conclusions MTFs determined from a iTrace and a DP system （OQAS） differ significantly in early cataractous and normal subjects. Correlations with visual performance were higher for the DP system. OQAS-derived MTF may be useful as an indicator of visual performance in early cataract eyes.

Blind source separation with unknown and dynamically changing number of source signals

The contrast function remains to be an open problem in blind source separation （BSS） when the number of source signals is unknown and/or dynamically changed. The paper studies this problem and proves that the mutual information is still the contrast function for BSS if the mixing matrix is of full column rank. The mutual information reaches its minimum at the separation points, where the random outputs of the BSS system are the scaled and permuted source signals, while the others are zero outputs. Using the property that the transpose of the mixing matrix and a matrix composed by m observed signals have the indentical null space with probability one, a practical method, which can detect the unknown number of source signals n, ulteriorly traces the dynamical change of the sources number with a few of data, is proposed. The effectiveness of the proposed theorey and the developed novel algorithm is verified by adaptive BSS simulations with unknown and dynamically changing number of source signals.

Measurement of the spatial resolution and the relative density resolution in an industrial cone-beam micro computed tomography system

The spatial resolution and the relative density resolution are the two most critical indicators in CT system. The method recommended in the ASTM E1695-95 and GJB 5311-2004 is only suitable to the fan-beam CT system. In this paper, for industrial cone-beam micro CT system, we will adopt the edge response function （ERF） created by the step edges of a steel ball to measure the system 3D PSF and MTF. To describe the contrast discrimination function more accurately, we will first propose to extend the two-dimensional measurement region to the three-dimensional space. Our experimental spatial resolution is （55.56＋0.56） lp/mm and the relative density resolution is 1% within 300 μm×300 μm×300 μm according to the 3σ rule.

Avian contrast sensitivity inspired contour detector for unmanned aerial vehicle landing

Runway detection is a demanding task for autonomous landing of unmanned aerial vehicles. Inspired by the attenuation effect and surround suppression mechanism, a novel biologically computational method based on the avian contrast sensitivity is proposed for runway contour detection. For the noisy stimuli, deniosed responses of the biologically inspired Gabor energy operator are generalized followed by the denoising layer and the multiresolution fusion layer. Moreover, two factors such as contour effect and texture suppression are considered in the contrast sensitivity based surround inhibition. Different from traditional detectors, which do not distinguish between contours and texture edges, the proposed method can respond strongly to contours and suppress the texture information. Applying the contrast sensitivity inspired detector to noisy runway scenes yields effective contours, while the non-meaningful texture elements are removed dramatically at the same time. Besides the superior performance over traditional detectors, the proposed method is capable to provide insight into the attenuation effect of the avian contrast sensitivity function and has potential applications in computer vision and pattern recognition.

Improved single image dehazing using dark channel prior

An improved single image dehazing method based on dark channel prior and wavelet transform is proposed. This proposed method employs wavelet transform and guided filter instead of the soft matting procedure to estimate and refine the depth map of haze images. Moreover, a contrast enhancement method based on just noticeable difference(JND) and quadratic function is adopted to enhance the contrast for the dehazed image, since the scene radiance is usually not as bright as the atmospheric light,and the dehazed image looks dim. The experimental results show that the proposed approach can effectively enhance the haze image and is well suitable for implementing on the surveillance and obstacle detection systems.