Sight Research Articles

Peak Alpha Frequency, Visual Perception, and Cognition in Schizophrenia

Peak Alpha Frequency, Visual Perception, and Cognition in Schizophrenia

A novel infrared and visible image fusion network based on cross-modality reinforcement and multi-attention fusion strategy

Infrared and visible image fusion focuses on the integration of complementary information, whose fused results with abundant texture details and salient targets can cater for human visual observation well. However, the loss of some important details is still a challenge in the image fusion process. In this paper, a novel method based on cross-modality reinforcement module and multi-attention fusion strategy is proposed to boost the end-to-end CNN backbone. Specifically, a cross-modality architecture is applied to compensate the spectral differences from heterogeneous images; and the multi-scale strip pooling is utilized as a further feature representation tool to model long-rang independencies precisely; then, a detail injection block is devised to fulfill the enhancement requirements of texture-contrast and target intensity; sequentially, a multi-attention fusion module is proposed to integrate features progressively. Extensive comparative experiments are conducted on several datasets to demonstrate the superiority of the proposed method in both quantitative metrics and visual perception, such as the average of visual information fidelity metric based on all the experiment samples reach to 0.964.

Eye-movement-prompted large image captioning model

Pretrained large vision-language models have shown outstanding performance on the task of image captioning. However, owing to the insufficient decoding of image features, existing large models sometimes lose important information, such as objects, scenes, and their relationships. In addition, the complex ”black-box” nature of these models makes their mechanisms difficult to explain. Research shows that humans learn richer representations than machines do, which inspires us to improve the accuracy and interpretability of large image captioning models by combining human observation patterns. We built a new dataset, called saliency in image captioning (SIC), to explore relationships between human vision and language representation. One thousand images with rich context information were selected as image data of SIC. Each image was annotated with five caption labels and five eye-movement labels. Through analysis of the eye-movement data, we found that humans efficiently captured comprehensive information for image captioning during their observations. Therefore, we propose an eye-movement-prompted large image captioning model, which is embedded with two carefully designed modules: the eye-movement simulation module (EMS) and the eye-movement analyzing module (EMA). EMS combines the human observation pattern to simulate eye-movement features, including the positions and scan paths of eye fixations. EMA is a graph neural network (GNN) based module, which decodes graphical eye-movement data and abstracts image features as a directed graph. More accurate descriptions can be predicted by decoding the generated graph. Extensive experiments were conducted on the MS-COCO and NoCaps datasets to validate our model. The experimental results showed that our network was interpretable, and could achieve superior results compared with state-of-the-art methods, i.e., 84.2% BLEU-4 and 145.1% CIDEr-D on MS-COCO Karpathy test split, indicating its strong potential for use in image captioning.

Phototherapy as the tool of emotional identification development of adolescents

The results of the empirical stage statistically proved that phototherapy is one of the effective tools of psycho-pedagogical assistance to adolescents who experience difficulties associated with emotional identification. We diagnosed the level of formation of this phenomenon within the sample of 240 respondents who are university and school students aged 17 to 20 years female and male. A number of psycho-diagnostic methods were used in the study: the method 'Toron to alexithymia scale (TAS-26)” and the questionnaire “self-attitude.” Summarizing the results, we state that most of the studied sample is in a state of emotional well-being but emotional discomfort occurs among some respondents with certain levels of propensity for alexithymia (22.5%). The research proves the positive impact of phototherapy on adolescents' emotional identification development through photographing and creating visual pictures or direct perception and interpretation of images.

Discussion on effect of observation circumstances for image in digital radiography

The discriminability of the IQI in the film radiography is affected by the observation circumstance and the luminance of film viewer. ISO17636-2 states that the images of digital radiograph shall be examined in a dimmed room. However, it does not describe requirements for the observation environment in digital radiography, despite the fact that the environment is similar to that of a normal professional PC and the display of the images can be easily adjusted. In this report, the influence of the observation environment in digital radiography was compared as the parameters the wire diameter and the WL value of a display adjustment value when the minimum wire diameter of the image quality indicator (IQI) was percepted, using images of welded steel at t25mm and t50mm. For welded steel of t25mm, differences due to SNRN values and differences due to the observation environment of light and dark room were compared. For t50mm, differences due to the presence or absence of the observation mask for the single wire of wire IQI which is places in front of the display, differences due to the resolution and brightness of the PC monitor, and differences when the WL was adjusted arbitrarily or fixed were compared. For the Digital Radiographic testing (RT-D), the basic spatial resolutions (SRb) were obtained by measuring the profile and applying of visual observation with the duplex wire type IQI. On the other hand, when observing the image of wire type IQI, the observation ways that one was obtain the perceptible image for all wires and another was to get the perceptible single wire image by using the observation mask for watching each wire were applied. Moreover, the influence of window width (WW) and window level (WL) adjustment on the discrimination of wire-type IQI was examined by quantifying it as WW/WL. As a result, it was confirmed that the discriminality in the dimmed room and the adjustment of WW and WL were effective. In addition, using the observation a mask showed that the perception of the adjacent wire image affected observer cognition in IQI discrimination during image observation. When using viewer software profiling, SRb measurements were not affected by the observation environment, but the visual observation was affected by the environment, and when observing images in the dimmed room with RT-D, it was found that adjusting WW and WL had a greater effect on discrimination for images with low SNRN and low contrast.

Corporal Filler HD, a Minimally Invasive Technique for Male Body Contouring: A Pilot Study

Background: The perception of body image is highly influenced by culture and society. Lean, more muscular, and strong bodies are usually pursued by men. Body aesthetics procedures have become popular, and minimally invasive procedures have been used to achieve body image satisfaction. Methods: This article describes a technique that utilizes hyaluronic acid filler to enhance muscular contours in the abdominal and pectoral regions. The procedure involves injecting hyaluronic acid filler at a level anterior to the pectoralis major and rectus abdominis muscles through marked entry points, creating an illusion of light and shadow that accentuates muscle definition. Additionally, the iliac region can be addressed to enhance the oblique muscles. Results: The results are illustrated with pre- and postprocedure images, demonstrating a significant aesthetic improvement, high patient satisfaction, and absence of serious adverse events. Conclusions: This minimally invasive technique is suitable for patients with a low body fat percentage and a desire to enhance muscle definition, providing immediate results with no downtime. Although the scientific literature on filler applications in the thoracoabdominal region is limited, this study demonstrates that precision in minimally invasive procedures can yield highly satisfactory outcomes.

Visual quality following FS-LASIK with Q-value-guided optimized monovision in patients with myopia and presbyopia: Custom-Q in treating myopia and presbyopia

PurposeTo evaluate the objective and subjective visual quality 3 months after femtosecond laser‐assisted laser in situ keratomileusis (FS-LASIK) performed with Q-value–guided optimized monovision scheme (Custom-Q) for correction of myopia with or without astigmatism and compensate for age-related accommodation deficiency. DesignProspective before-and-after study. MethodsPatients who had Custom-Q FS-LASIK for myopia with age-related accommodation deficiency were included in this prospective study. Distance, intermediate, and near visual acuities; refraction; Q value; corneal higher-order aberrations (HOAs); accommodative and binocular function measurements; defocus curve; contrast sensitivity and a subjective questionnaire assessing near visual ability and visual discomforts were evaluated before and after surgery. ResultsClinical data of 48 cases were analyzed. The mean age was 42.73 ± 2.67 years (40 to 50 years). At the 3-month follow-up, there were 100% (48/48), 92% (44/48), and 56% (27/48) patients who achieved a binocular uncorrected distance, intermediate and near visual acuity (UDVA, UIVA, UNVA) not less than 20/20 separately. Defocus curves revealed better results postoperatively at – 1.00 D and – 1.50 D. The Q value in the dominant eyes was more positive postoperatively (P<0.001), and in the non-dominant eyes, the Q value and corneal spherical aberration (SA) became more negative (P<0.05). The accommodative amplitude (AA) and relative accommodation improved binocularly (P<0.001). The questionnaire demonstrated high patient satisfaction with near vision, and patients’ perceptions of visual discomforts had no significantly difference compare with preoperative. ConclusionFor myopic patients with age-related accommodation deficiency, the Custom-Q ablation could improve near vision without compromising distance vision. It also led to minimal changes in objective optical quality, coordination of accommodative and binocular functions, contrast sensitivity, and subjective visual discomforts perceptions.

Effects of Vergence Eye Movement Planning on Size Perception and Early Visual Processing

Abstract Our perception of objects depends on non-oculomotor depth cues, such as pictorial distance cues and binocular disparity, and oculomotor depth cues, such as vergence and accommodation. Although vergence eye movements are always involved in perceiving real distance, previous studies have mainly focused on the effect of oculomotor state via “proprioception” on distance and size perception. It remains unclear whether the oculomotor command of vergence eye movement would also influence visual processing. To address this question, we placed a light at 28.5 cm and a screen for stimulus presentation at 57 cm from the participants. In the NoDivergence condition, participants were asked to maintain fixation on the light regardless of stimulus presentation throughout the trial. In the WithDivergence condition, participants were instructed to initially maintain fixation on the near light and then turn their two eyes outward to look at the stimulus on the far screen. The stimulus was presented for 100 msec, entirely within the preparation stage of the divergence eye movement. We found that participants perceived the stimulus as larger but were less sensitive to stimulus sizes in the WithDivergence condition than in the NoDivergence condition. The earliest visual evoked component C1 (peak latency 80 msec), which varied with stimulus size in the NoDivergence condition, showed similar amplitudes for larger and smaller stimuli in the WithDivergence condition. These results show that vergence eye movement planning affects the earliest visual processing and size perception, and demonstrate an example of the effect of motor command on sensory processing.

Ordinal information, but not metric information, matters in binding feature with depth location in three-dimensional contexts.

A basic function of human visual perception is the ability to recognize and locate objects in the environment. It has been shown that two-dimensional (2D) location can reliably bias judgments on object identity (spatial congruency bias; Golomb et al., 2014), suggesting that 2D location information is automatically bound with object features to induce such a bias. Although the binding problem of feature and location has been vigorously studied under various 2D settings, it remains unclear how depth location can be bound with object features in a three-dimensional (3D) setting. Here we conducted five experiments in various 3D contexts using the congruency bias paradigm, and found that changes of object's depth location could influence perceptual judgments on object features differently depending on whether its relative depth order with respect to others changed or not. Experiments 1 and 2 showed that the judgments on an object's color could be affected by changes in its ordinal depth, but not by changes in its absolute metric depth. Experiment 3 showed that the bias was asymmetric-changes in an object's color did bias the judgments on metric-depth location, but not if its depth order had changed. Experiments 4 and 5 investigated whether these findings could be generalized to a peripersonal near space and a large-scale far space, respectively, using more ecological virtual environments. Our findings suggest that ordinal depth plays a special role in feature-location binding: an object may be automatically bound with its relative depth relation, but not with its absolute metric-depth location. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

SDR2Tr‐GAN: A Novel Medical Image Fusion Pipeline Based on GAN With SDR2 Module and Transformer Optimization Strategy

ABSTRACTIn clinical practice, radiologists diagnose brain tumors with the help of different magnetic resonance imaging (MRI) sequences and judge the type and grade of brain tumors. It is hard to realize the brain tumor computer‐aided diagnosis system only with a single MRI sequence. However, the existing multiple MRI sequence fusion methods have limitations in the enhancement of tumor details. To improve fusion details of multi‐modality MRI images, a novel conditional generative adversarial fusion network based on three discriminators and a Staggered Dense Residual2 (SDR2) module, named SDR2Tr‐GAN, was proposed in this paper. In the SDR2Tr‐GAN network pipeline, the generator consists of an encoder, decoder, and fusion strategy that can enhance the feature representation. SDR2 module is developed with Res2Net into the encoder to extract multi‐scale features. In addition, a Multi‐Head Spatial/Channel Attention Transformer, as a fusion strategy to strengthen the long‐range dependencies of global context information, is integrated into our pipeline. A Mask‐based constraint as a novel fusion optimization mechanism was designed, focusing on enhancing salient feature details. The Mask‐based constraint utilizes the segmentation mask obtained by the pre‐trained Unet and Ground Truth to optimize the training process. Meanwhile, MI and SSIM loss jointly improve the visual perception of images. Extensive experiments were conducted on the public BraTS2021 dataset. The visual and quantitative results demonstrate that the proposed method can simultaneously enhance both global image quality and local texture details in multi‐modality MRI images. Besides, our SDR2Tr‐GAN outperforms the other state‐of‐the‐art fusion methods regarding subjective and objective evaluation.

Visual Perceptual Confidence: Exploring Discrepancies Between Self-reported and Actual Distance Perception In Virtual Reality.

Virtual Reality (VR) systems are widely used, and it is essential to know if spatial perception in virtual environments (VEs) is similar to reality. Research indicates that users tend to underestimate distances in VR. Prior work suggests that actual distance judgments in VR may not always match the users self-reported preference of where they think they most accurately estimated distances. However, no explicit investigation evaluated whether user preferences match actual performance in a spatial judgment task. We used blind walking to explore potential dissimilarities between actual distance estimates and user-selected preferences of visual complexities, VE conditions, and targets. Our findings show a gap between user preferences and actual performance when visual complexities were varied, which has implications for better visual perception understanding, VR applications design, and research in spatial perception, indicating the need to calibrate and align user preferences and true spatial perception abilities in VR.

VPRF: Visual Perceptual Radiance Fields for Foveated Image Synthesis.

Neural radiance fields (NeRF) has achieved revolutionary breakthrough in the novel view synthesis task for complex 3D scenes. However, this new paradigm struggles to meet the requirements for real-time rendering and high perceptual quality in virtual reality. In this paper, we propose VPRF, a novel visual perceptual based radiance fields representation method, which for the first time integrates the visual acuity and contrast sensitivity models of human visual system (HVS) into the radiance field rendering framework. Initially, we encode both the appearance and visual sensitivity information of the scene into our radiance field representation. Then, we propose a visual perceptual sampling strategy, allocating computational resources according to the HVS sensitivity of different regions. Finally, we propose a sampling weight-constrained training scheme to ensure the effectiveness of our sampling strategy and improve the representation of the radiance field based on the scene content. Experimental results demonstrate that our method renders more efficiently, with higher PSNR and SSIM in the foveal and salient regions compared to the state-of-the-art FoV-NeRF. The results of the user study confirm that our rendering results exhibit high-fidelity visual perception.

A Field Study about the Effects of Asymmetric Visual Perception on Lateral Driving Behaviors on Curves

A Field Study about the Effects of Asymmetric Visual Perception on Lateral Driving Behaviors on Curves

A bio-inspired visual collision detection network integrated with dynamic temporal variance feedback regulated by scalable functional countering jitter streaming

In pursuing artificial intelligence for efficient collision avoidance in robots, researchers draw inspiration from the locust’s visual looming-sensitive neural circuit to establish an efficient neural network for collision detection. However, existing bio-inspired collision detection neural networks encounter challenges posed by jitter streaming, a phenomenon commonly experienced, for example, when a ground robot moves across uneven terrain. Visual inputs from jitter streaming induce significant fluctuations in grey values, distracting existing bio-inspired networks from extracting visually looming features. To overcome this limitation, we derive inspiration from the potential of feedback loops to enable the brain to generate a coherent visual perception. We introduce a novel dynamic temporal variance feedback loop regulated by scalable functional into the traditional bio-inspired collision detection neural network. This feedback mechanism extracts dynamic temporal variance information from the output of higher-order neurons in the conventional network to assess the fluctuation level of local neural responses and regulate it by a scalable functional to differentiate variance induced by incoherent visual input. Then the regulated signal is reintegrated into the input through negative feedback loop to reduce the incoherence of the signal within the network. Numerical experiments substantiate the effectiveness of the proposed feedback loop in promoting collision detection against jitter streaming. This study extends the capabilities of bio-inspired collision detection neural networks to address jitter streaming challenges, offering a novel insight into the potential of feedback mechanisms in enhancing visual neural abilities.

Multiple independent components contribute to event-related potential correlates of conscious vision

Research has revealed two major event-related potential (ERP) markers of visual awareness: the earlier Visual Awareness Negativity (VAN, around 150–250 ms after stimulus onset), and the following Late Positivity (LP, around 300–500 ms after stimulus onset). Understanding the neural sources that give rise to VAN and LP is important in order to understand what kind of neural processes underlie conscious visual perception. Although the ERPs afford high temporal resolution, their spatial resolution is limited because multiple separate neural sources sum up at the scalp level. In the present study, we sought to characterize the locations and time-courses of independent neural sources underlying the ERP correlates of visual awareness by means of Independent Component Analysis (ICA). ICA allows identifying and localizing the temporal dynamics of different neural sources that contribute to the ERP correlates of conscious perception. The present results show that the cortical sources of VAN are localized to posterior areas including occipital and temporal cortex, while LP reflects a combination of multiple sources distributed among frontal, parietal and occipito-temporal cortex., Our findings suggest that conscious vision correlates with dynamically changing neural sources, developing in part in “accumulative fashion”: consciousness-related activity initially arises in few early sources and, subsequently, additional sources are engaged as a function of time.The results further suggest that even early latency neural sources that correlate with conscious perception may also associate with action-related processes.

AFDFusion: An adaptive frequency decoupling fusion network for multi-modality image

The multi-modality image fusion goal is to create a single image that provides a comprehensive scene description and conforms to visual perception by integrating complementary information about the merits of the different modalities, e.g., salient intensities of infrared images and detail textures of visible images. Although some works explore decoupled representations of multi-modality images, they struggle with complex nonlinear relationships, fine modal decoupling, and noise handling. To cope with this issue, we propose an adaptive frequency decoupling module to perceive the associative invariant and inherent specific among cross-modality by dynamically adjusting the learnable low frequency weight of the kernel. Specifically, we utilize a contrastive learning loss for restricting the solution space of feature decoupling to learn representations of both the invariant and specific in the multi-modality images. The underlying idea is that: in decoupling, low frequency features, which are similar in the representation space, should be pulled closer to each other, signifying the associative invariant, while high frequencies are pushed farther away, also indicating the intrinsic specific. Additionally, a multi-stage training manner is introduced into our framework to achieve decoupling and fusion. Stage I, MixEncoder and MixDecoder with the same architecture but different parameters are trained to perform decoupling and reconstruction supervised by the contrastive self-supervised mechanism. Stage II, two feature fusion modules are added to integrate the invariant and specific features and output the fused image. Extensive experiments demonstrated the proposed method superiority over the state-of-the-art methods in both qualitative and quantitative evaluation on two multi-modal image fusion tasks.

A new method for judging thermal image quality with applications

Infrared thermal imaging, a non-destructive testing technology, measures the surface temperature of objects. Assessing thermal image quality is crucial for image monitoring, system design, algorithm optimization, and benchmarking. However, developing objective metrics that align with human perception is challenging due to the distinct structure of thermal images, which often feature high background temperatures and minimal variance between objects and the background. Existing methods typically target specific local features or overall image contrast, but new measures are needed to bridge the gap between objective performance and the unique characteristics of thermal images.We propose a novel image quality assessment (IQA) method inspired by the human vision system, specifically designed for thermal images, harmonizing local and global data. The primary contributions include (1) innovative local, global, and hybrid thermal quality assessment methods that deliver precise image quality predictions without needing reference images, (2) an experimental analysis evaluating the developed blind thermal IQA measure’s applicability to various thermal images, and (3) a comprehensive analysis of traditional IQA measure-based methods applied to publicly accessible thermal databases. Extensive simulations demonstrate our method’s competitive performance and strong alignment with human perception of image quality.

Pulsed artificial light at night alters moth flight behaviour

Vehicle headlights create pulsed artificial light at night (pALAN) that is unpredictable, intense and extends into previously dark areas. Nocturnal insects often have remarkable low-light vision, but their slow pupillary light responses may leave them vulnerable to pALAN, which has important ecological consequences. To test this, we exposed nocturnal moths—important pollinators and prey—to four pALAN treatments. These comprised ‘cool’ and ‘warm’ lights, either emitted from phosphor-coated light-emitting diodes (LEDs) or RGB (red-green-blue) LEDs, matched in colour (CCT) and intensity to human vision. We assessed the initial behavioural response, likely crucial to the survival of an organism, of 428 wild-caught moths comprising 64 species. We found that exposure to a cool phosphor-coated LED light pulse increased instances of erratic flight and flight-to-light that are likely detrimental as they increase the risks of impact with a vehicle, predation or excess energy expenditure. Our findings suggest that pALAN can cause a wide range of behavioural responses in nocturnal moths, but that the most harmful effects could be minimized by reversing the current shift towards high CCT (cool) phosphor-coated LED car headlights. Lower CCT or RGB alternatives are likely to provide benefits for road safety while reducing ecological harm.

Toward a better approach for measuring visual-search slopes.

The slope of the function relating response times to the number of stimuli in a visual-search display is commonly considered a measure of search speed and is extensively used to test theories of visual cognition. Unfortunately, this important measure is confounded in multiple ways so that many classical findings in the literature must be called into question. As a way out of this predicament, we here develop a new technique to measure search speed (data collected in 2022 and 2023): Instead of manipulating the number of stimuli that need to be searched via a set-size manipulation, we achieve the intended purpose by placing the search target at different spatial positions with respect to an a-priori-known search order. Reliably inducing such a search order is the main achievement of the present study, but we also report several additional data patterns that might turn out instrumental for future research on visual attention. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Exploring the effects of social media on body dysmorphic disorder among citizens of Bahrain: a cross-sectional study

BackgroundThis study assessed the relationship between social media use and body dysmorphic disorder (BDD). We calculated the prevalence of BDD in our sample and explored factors that may be associated with BDD. Various factors that we explored include sociodemographic characteristics, body image perceptions, and specific social media platforms used. The key focus of our study is understanding the impact of social media on mental health, specifically in the context of BDD.MethodsThis was a cross-sectional online survey that included the standardized Body Dysmorphic Disorder Questionnaire (BDDQ). Data on social media use were collected through self-reported usage patterns. Statistical analysis was conducted to identify associations.ResultsIncreased overall social media use was associated with BDD (p = 0.030). The prevalence of BDD in our sample was 1.8%. Age, being single and being a student were associated with BDD, with p values of 0.004, 0.023, and < 0.001, respectively. BDD was associated with comparing one’s body image with that of people on social media (p = 0.001). BDD was associated with judging other people based on their appearance (p < 0.001). Using social media in the fields of celebrities (p = 0.020), fashion (p = 0.025), music and songs (p < 0.001) were associated with BDD.ConclusionsIncreased social media use is associated with BDD, but different patterns of social media use may affect this relationship, indicating the need for further research in this field.